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1. Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis

Author: Fu, Z, Brooks, MM, Irvin, S, Jordan, S, Aben, KKH, Anton-Culver, H, Bandera, E, Beckmann, MW, Berchuck, A, Brooks-Wilson, A, Chang-Claude, J, Cook, LS, Cramer, DW, Cushing-Haugen, KL, Doherty, JA, Ekici, AB, Fasching, PA, Fortner, RT, Gayther, SA, Gentry-Maharaj, A, Giles, GG, Goode, EL, Goodman, MT, Harris, HR, Hein, A, Kaaks, R, Kiemeney, LA, Koebel, M, Kotsopoulos, J, Le, ND, Lee, AW, Matsuo, K, McGuire, V, McLaughlin, JR, Menon, U, Milne, RL, Moysich, KB, Pearce, CL, Pike, MC, Qin, B, Ramus, SJ, Riggan, MJ, Rothstein, JH, Schildkraut, JM, Sieh, W, Sutphen, R, Terry, KL, Thompson, PJ, Titus, L, van Altena, AM, White, E, Whittemore, AS, Wu, AH, Zheng, W, Ziogas, A, Taylor, SE, Tang, L, Songer, T, Wentzensen, N, Webb, PM, Risch, HA, Modugno, F, Fu, Z, Brooks, MM, Irvin, S, Jordan, S, Aben, KKH, Anton-Culver, H, Bandera, E, Beckmann, MW, Berchuck, A, Brooks-Wilson, A, Chang-Claude, J, Cook, LS, Cramer, DW, Cushing-Haugen, KL, Doherty, JA, Ekici, AB, Fasching, PA, Fortner, RT, Gayther, SA, Gentry-Maharaj, A, Giles, GG, Goode, EL, Goodman, MT, Harris, HR, Hein, A, Kaaks, R, Kiemeney, LA, Koebel, M, Kotsopoulos, J, Le, ND, Lee, AW, Matsuo, K, McGuire, V, McLaughlin, JR, Menon, U, Milne, RL, Moysich, KB, Pearce, CL, Pike, MC, Qin, B, Ramus, SJ, Riggan, MJ, Rothstein, JH, Schildkraut, JM, Sieh, W, Sutphen, R, Terry, KL, Thompson, PJ, Titus, L, van Altena, AM, White, E, Whittemore, AS, Wu, AH, Zheng, W, Ziogas, A, Taylor, SE, Tang, L, Songer, T, Wentzensen, N, Webb, PM, Risch, HA, and Modugno, F
Abstract: BACKGROUND: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC. METHODS: LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source. RESULTS: LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes. CONCLUSIONS: LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC.
Published: 2023

2. p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study

Author: Kobel, M, Kang, E-Y, Weir, A, Rambau, PF, Lee, C-H, Nelson, GS, Ghatage, P, Meagher, NS, Riggan, MJ, Alsop, J, Anglesio, MS, Beckmann, MW, Bisinotto, C, Boisen, M, Boros, J, Brand, AH, Brooks-Wilson, A, Carney, ME, Coulson, P, Courtney-Brooks, M, Cushing-Haugen, KL, Cybulski, C, Deen, S, El-Bahrawy, MA, Elishaev, E, Erber, R, Fereday, S, Fischer, A, Gayther, SA, Barquin-Garcia, A, Gentry-Maharaj, A, Gilks, CB, Gronwald, H, Grube, M, Harnett, PR, Harris, HR, Hartkopf, AD, Hartmann, A, Hein, A, Hendley, J, Hernandez, BY, Huang, Y, Jakubowska, A, Jimenez-Linan, M, Jones, ME, Kennedy, CJ, Kluz, T, Koziak, JM, Lesnock, J, Lester, J, Lubinski, J, Longacre, TA, Lycke, M, Mateoiu, C, McCauley, BM, McGuire, V, Ney, B, Olawaiye, A, Orsulic, S, Osorio, A, Paz-Ares, L, Ramon Y Cajal, T, Rothstein, JH, Ruebner, M, Schoemaker, MJ, Shah, M, Sharma, R, Sherman, ME, Shvetsov, YB, Singh, N, Steed, H, Storr, SJ, Talhouk, A, Traficante, N, Wang, C, Whittemore, AS, Widschwendter, M, Wilkens, LR, Winham, SJ, Benitez, J, Berchuck, A, Bowtell, DD, Candido dos Reis, FJ, Campbell, I, Cook, LS, DeFazio, A, Doherty, JA, Fasching, PA, Fortner, RT, Garcia, MJ, Goodman, MT, Goode, EL, Gronwald, J, Huntsman, DG, Karlan, BY, Kelemen, LE, Kommoss, S, Le, ND, Martin, SG, Menon, U, Modugno, F, Pharoah, PDP, Schildkraut, JM, Sieh, W, Staebler, A, Sundfeldt, K, Swerdlow, AJ, Ramus, SJ, Brenton, JD, Kobel, M, Kang, E-Y, Weir, A, Rambau, PF, Lee, C-H, Nelson, GS, Ghatage, P, Meagher, NS, Riggan, MJ, Alsop, J, Anglesio, MS, Beckmann, MW, Bisinotto, C, Boisen, M, Boros, J, Brand, AH, Brooks-Wilson, A, Carney, ME, Coulson, P, Courtney-Brooks, M, Cushing-Haugen, KL, Cybulski, C, Deen, S, El-Bahrawy, MA, Elishaev, E, Erber, R, Fereday, S, Fischer, A, Gayther, SA, Barquin-Garcia, A, Gentry-Maharaj, A, Gilks, CB, Gronwald, H, Grube, M, Harnett, PR, Harris, HR, Hartkopf, AD, Hartmann, A, Hein, A, Hendley, J, Hernandez, BY, Huang, Y, Jakubowska, A, Jimenez-Linan, M, Jones, ME, Kennedy, CJ, Kluz, T, Koziak, JM, Lesnock, J, Lester, J, Lubinski, J, Longacre, TA, Lycke, M, Mateoiu, C, McCauley, BM, McGuire, V, Ney, B, Olawaiye, A, Orsulic, S, Osorio, A, Paz-Ares, L, Ramon Y Cajal, T, Rothstein, JH, Ruebner, M, Schoemaker, MJ, Shah, M, Sharma, R, Sherman, ME, Shvetsov, YB, Singh, N, Steed, H, Storr, SJ, Talhouk, A, Traficante, N, Wang, C, Whittemore, AS, Widschwendter, M, Wilkens, LR, Winham, SJ, Benitez, J, Berchuck, A, Bowtell, DD, Candido dos Reis, FJ, Campbell, I, Cook, LS, DeFazio, A, Doherty, JA, Fasching, PA, Fortner, RT, Garcia, MJ, Goodman, MT, Goode, EL, Gronwald, J, Huntsman, DG, Karlan, BY, Kelemen, LE, Kommoss, S, Le, ND, Martin, SG, Menon, U, Modugno, F, Pharoah, PDP, Schildkraut, JM, Sieh, W, Staebler, A, Sundfeldt, K, Swerdlow, AJ, Ramus, SJ, and Brenton, JD
Abstract: Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36-3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11-2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.
Published: 2023

3. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci

Author: Chen, H, Fan, S, Stone, J, Thompson, DJ, Douglas, J, Li, S, Scott, C, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Li, C, Peters, U, Hopper, JL, Southey, MC, Nguyen-Dumont, T, Nguyen, TL, Fasching, PA, Behrens, A, Cadby, G, Murphy, RA, Aronson, K, Howell, A, Astley, S, Couch, F, Olson, J, Milne, RL, Giles, GG, Haiman, CA, Maskarinec, G, Winham, S, John, EM, Kurian, A, Eliassen, H, Andrulis, I, Evans, DG, Newman, WG, Hall, P, Czene, K, Swerdlow, A, Jones, M, Pollan, M, Fernandez-Navarro, P, McConnell, DS, Kristensen, VN, Rothstein, JH, Wang, P, Habel, LA, Sieh, W, Dunning, AM, Pharoah, PDP, Easton, DF, Gierach, GL, Tamimi, RM, Vachon, CM, Lindstrom, S, Chen, H, Fan, S, Stone, J, Thompson, DJ, Douglas, J, Li, S, Scott, C, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Li, C, Peters, U, Hopper, JL, Southey, MC, Nguyen-Dumont, T, Nguyen, TL, Fasching, PA, Behrens, A, Cadby, G, Murphy, RA, Aronson, K, Howell, A, Astley, S, Couch, F, Olson, J, Milne, RL, Giles, GG, Haiman, CA, Maskarinec, G, Winham, S, John, EM, Kurian, A, Eliassen, H, Andrulis, I, Evans, DG, Newman, WG, Hall, P, Czene, K, Swerdlow, A, Jones, M, Pollan, M, Fernandez-Navarro, P, McConnell, DS, Kristensen, VN, Rothstein, JH, Wang, P, Habel, LA, Sieh, W, Dunning, AM, Pharoah, PDP, Easton, DF, Gierach, GL, Tamimi, RM, Vachon, CM, and Lindstrom, S
Abstract: BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
Published: 2022

4. Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium

Author: Martins, FC, Couturier, D-L, Paterson, A, Karnezis, AN, Christine, C, Nazeran, TM, Odunsi, A, Gentry-Maharaj, A, Vrvilo, A, Hein, A, Talhouk, A, Osorio, A, Hartkopf, AD, Brooks-Wilson, A, DeFazio, A, Fischer, A, Hartmann, A, Hernandez, BY, McCauley, BM, Karpinskyj, C, de Sousa, CB, Hogdall, C, Tiezzi, DG, Herpel, E, Taran, FA, Modugno, F, Keeney, G, Nelson, G, Steed, H, Song, H, Luk, H, Benitez, J, Alsop, J, Koziak, JM, Lester, J, Rothstein, JH, de Andrade, JM, Lundvall, L, Paz-Ares, L, Robles-Diaz, L, Wilkens, LR, Garcia, MJ, Intermaggio, MP, Alcaraz, M-L, Brett, MA, Beckmann, MW, Jimenez-Linan, M, Anglesio, M, Carney, ME, Schneider, M, Traficante, N, Pejovic, N, Singh, N, Le, N, Sinn, P, Ghatage, P, Erber, R, Edwards, R, Vierkant, R, Ness, RB, Leung, S, Orsulic, S, Brucker, SY, Kaufmann, SH, Fereday, S, Gayther, S, Winham, SJ, Kommoss, S, Pejovic, T, Longacre, TA, McGuire, V, Rhenius, V, Sieh, W, Shvetsov, YB, Whittemore, AS, Staebler, A, Karlan, BY, Rodriguez-Antona, C, Bowtell, DD, Goode, EL, Hogdall, E, Candido dos Reis, FJ, Gronwald, J, Chang-Claude, J, Moysich, KB, Kelemen, LE, Cook, LS, Goodman, MT, Fasching, PA, Crawford, R, Deen, S, Menon, U, Huntsman, DG, Kobel, M, Ramus, SJ, Pharoah, PDP, Brenton, JD, Martins, FC, Couturier, D-L, Paterson, A, Karnezis, AN, Christine, C, Nazeran, TM, Odunsi, A, Gentry-Maharaj, A, Vrvilo, A, Hein, A, Talhouk, A, Osorio, A, Hartkopf, AD, Brooks-Wilson, A, DeFazio, A, Fischer, A, Hartmann, A, Hernandez, BY, McCauley, BM, Karpinskyj, C, de Sousa, CB, Hogdall, C, Tiezzi, DG, Herpel, E, Taran, FA, Modugno, F, Keeney, G, Nelson, G, Steed, H, Song, H, Luk, H, Benitez, J, Alsop, J, Koziak, JM, Lester, J, Rothstein, JH, de Andrade, JM, Lundvall, L, Paz-Ares, L, Robles-Diaz, L, Wilkens, LR, Garcia, MJ, Intermaggio, MP, Alcaraz, M-L, Brett, MA, Beckmann, MW, Jimenez-Linan, M, Anglesio, M, Carney, ME, Schneider, M, Traficante, N, Pejovic, N, Singh, N, Le, N, Sinn, P, Ghatage, P, Erber, R, Edwards, R, Vierkant, R, Ness, RB, Leung, S, Orsulic, S, Brucker, SY, Kaufmann, SH, Fereday, S, Gayther, S, Winham, SJ, Kommoss, S, Pejovic, T, Longacre, TA, McGuire, V, Rhenius, V, Sieh, W, Shvetsov, YB, Whittemore, AS, Staebler, A, Karlan, BY, Rodriguez-Antona, C, Bowtell, DD, Goode, EL, Hogdall, E, Candido dos Reis, FJ, Gronwald, J, Chang-Claude, J, Moysich, KB, Kelemen, LE, Cook, LS, Goodman, MT, Fasching, PA, Crawford, R, Deen, S, Menon, U, Huntsman, DG, Kobel, M, Ramus, SJ, Pharoah, PDP, and Brenton, JD
Abstract: BACKGROUND: PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study. METHODS: Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran-Mantel-Haenszel tests. RESULTS: Downregulation of cytoplasmic PTEN expression was most frequent in ENOC (most frequently in younger patients; p value = 0.0001) and CCOC and was associated with longer overall survival in HGSOC (hazard ratio: 0.78, 95% CI: 0.65-0.94, p value = 0.022). PTEN expression was associated with ER, PR and AR expression (p values: 0.0008, 0.062 and 0.0002, respectively) in HGSOC and with lower CD8 counts in CCOC (p value < 0.0001). Heterogeneous expression of PTEN was more prevalent in advanced HGSOC (p value = 0.019) and associated with higher CD8 counts (p value = 0.0016). CONCLUSIONS: PTEN loss is a frequent driver in ovarian carcinoma associating distinctly with expression of hormonal receptors and CD8+ TIL counts in HGSOC and CCOC histotypes.
Published: 2020

5. Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Author: Schaffter, T, Buist, DSM, Lee, C, Nikulin, Y, Ribli, D, Guan, Y, Lotter, W, Jie, Z, Du, H, Wang, S, Feng, J, Feng, M, Kim, H-E, Albiol, F, Albiol, A, Morrell, S, Wojna, Z, Ahsen, ME, Asif, U, Yepes, AJ, Yohanandan, S, Rabinovici-Cohen, S, Yi, D, Hoff, B, Yu, T, Neto, EC, Rubin, DL, Lindholm, P, Margolies, LR, McBride, RB, Rothstein, JH, Sieh, W, Ben-Ari, R, Harrer, S, Trister, A, Friend, S, Norman, T, Sahiner, B, Strand, F, Guinney, J, Stolovitzky, G, Schaffter, T, Buist, DSM, Lee, C, Nikulin, Y, Ribli, D, Guan, Y, Lotter, W, Jie, Z, Du, H, Wang, S, Feng, J, Feng, M, Kim, H-E, Albiol, F, Albiol, A, Morrell, S, Wojna, Z, Ahsen, ME, Asif, U, Yepes, AJ, Yohanandan, S, Rabinovici-Cohen, S, Yi, D, Hoff, B, Yu, T, Neto, EC, Rubin, DL, Lindholm, P, Margolies, LR, McBride, RB, Rothstein, JH, Sieh, W, Ben-Ari, R, Harrer, S, Trister, A, Friend, S, Norman, T, Sahiner, B, Strand, F, Guinney, J, and Stolovitzky, G
Abstract: IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. OBJECTIVE: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. DESIGN, SETTING, AND PARTICIPANTS: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. MAIN OUTCOMES AND MEASUREMENTS: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. RESULTS: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms
Published: 2020

6. Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women

Author: Grant, DJ, Manichaikul, A, Alberg, AJ, Bandera, E, Barnholtz-Sloan, J, Bondy, M, Cote, ML, Funkhouser, E, Moorman, PG, Peres, LC, Peters, ES, Schwartz, AG, Terry, PD, Wang, X-Q, Keku, TO, Hoyo, C, Berchuck, A, Sandler, DP, Taylor, JA, O'Brien, KM, Edwards, DRV, Edwards, TL, Beeghly-Fadiel, A, Wentzensen, N, Pearce, CL, Wu, AH, Whittemore, AS, McGuire, V, Sieh, W, Rothstein, JH, Modugno, F, Ness, R, Moysich, K, Rossing, MA, Doherty, JA, Sellers, TA, Permuth-Way, JB, Monteiro, AN, Levine, DA, Setiawan, VW, Haiman, CA, LeMarchand, L, Wilkens, LR, Karlan, BY, Menon, U, Ramus, S, Gayther, S, Gentry-Maharaj, A, Terry, KL, Cramer, DW, Goode, EL, Larson, MC, Kaufmann, SH, Cannioto, R, Odunsi, K, Etter, JL, Huang, R-Y, Bernardini, MQ, Tone, AA, May, T, Goodman, MT, Thompson, PJ, Carney, ME, Tworoger, SS, Poole, EM, Lambrechts, D, Vergote, I, Vanderstichele, A, Van Nieuwenhuysen, E, Anton-Culver, H, Ziogas, A, Brenton, JD, Bjorge, L, Salvensen, HB, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Moffitt, M, Cook, L, Le, ND, Brooks-Wilson, A, Kelemen, LE, Pharoah, PDP, Song, H, Campbell, I, Eccles, D, DeFazio, A, Kennedy, CJ, Schildkraut, JM, Grant, DJ, Manichaikul, A, Alberg, AJ, Bandera, E, Barnholtz-Sloan, J, Bondy, M, Cote, ML, Funkhouser, E, Moorman, PG, Peres, LC, Peters, ES, Schwartz, AG, Terry, PD, Wang, X-Q, Keku, TO, Hoyo, C, Berchuck, A, Sandler, DP, Taylor, JA, O'Brien, KM, Edwards, DRV, Edwards, TL, Beeghly-Fadiel, A, Wentzensen, N, Pearce, CL, Wu, AH, Whittemore, AS, McGuire, V, Sieh, W, Rothstein, JH, Modugno, F, Ness, R, Moysich, K, Rossing, MA, Doherty, JA, Sellers, TA, Permuth-Way, JB, Monteiro, AN, Levine, DA, Setiawan, VW, Haiman, CA, LeMarchand, L, Wilkens, LR, Karlan, BY, Menon, U, Ramus, S, Gayther, S, Gentry-Maharaj, A, Terry, KL, Cramer, DW, Goode, EL, Larson, MC, Kaufmann, SH, Cannioto, R, Odunsi, K, Etter, JL, Huang, R-Y, Bernardini, MQ, Tone, AA, May, T, Goodman, MT, Thompson, PJ, Carney, ME, Tworoger, SS, Poole, EM, Lambrechts, D, Vergote, I, Vanderstichele, A, Van Nieuwenhuysen, E, Anton-Culver, H, Ziogas, A, Brenton, JD, Bjorge, L, Salvensen, HB, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Moffitt, M, Cook, L, Le, ND, Brooks-Wilson, A, Kelemen, LE, Pharoah, PDP, Song, H, Campbell, I, Eccles, D, DeFazio, A, Kennedy, CJ, and Schildkraut, JM
Abstract: An association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom-designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high-grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 1.2 × 10-6 , BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6-3.4, P = 1.6 × 10-5 , BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 2.3 × 10-5 , BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.
Published: 2019

7. MyD88 and TLR4 Expression in Epithelial Ovarian Cancer

Author: Block, MS, Vierkant, RA, Rambau, PF, Winham, SJ, Wagner, P, Traficante, N, Toloczko, A, Tiezzi, DG, Taran, FA, Sinn, P, Sieh, W, Sharma, R, Rothstein, JH, Ramon y Cajal, T, Paz-Ares, L, Oszurek, O, Orsulic, S, Ness, RB, Nelson, G, Modugno, F, Menkiszak, J, McGuire, V, McCauley, BM, Mack, M, Lubinski, J, Longacre, TA, Li, Z, Lester, J, Kennedy, CJ, Kalli, KR, Jung, AY, Johnatty, SE, Jimenez-Linan, M, Jensen, A, Intermaggio, MP, Hung, J, Herpel, E, Hernandez, BY, Hartkopf, AD, Harnett, PR, Ghatage, P, Garcia-Bueno, JM, Gao, B, Fereday, S, Eilber, U, Edwards, RP, de Sousa, CB, de Andrade, JM, Chudecka-Glaz, A, Chenevix-Trench, G, Cazorla, A, Brucker, SY, Alsop, J, Whittemore, AS, Steed, H, Staebler, A, Moysich, KB, Menon, U, Koziak, JM, Kommoss, S, Kjaer, SK, Kelemen, LE, Karlan, BY, Huntsman, DG, Hogdall, E, Gronwald, J, Goodman, MT, Gilks, B, Jose Garcia, M, Fasching, PA, de Fazio, A, Deen, S, Chang-Claude, J, dos Reis, FJC, Campbell, IG, Brenton, JD, Bowtell, DD, Benitez, J, Pharoah, PDP, Kobel, M, Ramus, SJ, Goode, EL, Block, MS, Vierkant, RA, Rambau, PF, Winham, SJ, Wagner, P, Traficante, N, Toloczko, A, Tiezzi, DG, Taran, FA, Sinn, P, Sieh, W, Sharma, R, Rothstein, JH, Ramon y Cajal, T, Paz-Ares, L, Oszurek, O, Orsulic, S, Ness, RB, Nelson, G, Modugno, F, Menkiszak, J, McGuire, V, McCauley, BM, Mack, M, Lubinski, J, Longacre, TA, Li, Z, Lester, J, Kennedy, CJ, Kalli, KR, Jung, AY, Johnatty, SE, Jimenez-Linan, M, Jensen, A, Intermaggio, MP, Hung, J, Herpel, E, Hernandez, BY, Hartkopf, AD, Harnett, PR, Ghatage, P, Garcia-Bueno, JM, Gao, B, Fereday, S, Eilber, U, Edwards, RP, de Sousa, CB, de Andrade, JM, Chudecka-Glaz, A, Chenevix-Trench, G, Cazorla, A, Brucker, SY, Alsop, J, Whittemore, AS, Steed, H, Staebler, A, Moysich, KB, Menon, U, Koziak, JM, Kommoss, S, Kjaer, SK, Kelemen, LE, Karlan, BY, Huntsman, DG, Hogdall, E, Gronwald, J, Goodman, MT, Gilks, B, Jose Garcia, M, Fasching, PA, de Fazio, A, Deen, S, Chang-Claude, J, dos Reis, FJC, Campbell, IG, Brenton, JD, Bowtell, DD, Benitez, J, Pharoah, PDP, Kobel, M, Ramus, SJ, and Goode, EL
Abstract: OBJECTIVE: To evaluate myeloid differentiation primary response gene 88 (MyD88) and Toll-like receptor 4 (TLR4) expression in relation to clinical features of epithelial ovarian cancer, histologic subtypes, and overall survival. PATIENTS AND METHODS: We conducted centralized immunohistochemical staining, semi-quantitative scoring, and survival analysis in 5263 patients participating in the Ovarian Tumor Tissue Analysis consortium. Patients were diagnosed between January 1, 1978, and December 31, 2014, including 2865 high-grade serous ovarian carcinomas (HGSOCs), with more than 12,000 person-years of follow-up time. Tissue microarrays were stained for MyD88 and TLR4, and staining intensity was classified using a 2-tiered system for each marker (weak vs strong). RESULTS: Expression of MyD88 and TLR4 was similar in all histotypes except clear cell ovarian cancer, which showed reduced expression compared with other histotypes (P<.001 for both). In HGSOC, strong MyD88 expression was modestly associated with shortened overall survival (hazard ratio [HR], 1.13; 95% CI, 1.01-1.26; P=.04) but was also associated with advanced stage (P<.001). The expression of TLR4 was not associated with survival. In low-grade serous ovarian cancer (LGSOC), strong expression of both MyD88 and TLR4 was associated with favorable survival (HR [95% CI], 0.49 [0.29-0.84] and 0.44 [0.21-0.89], respectively; P=.009 and P=.02, respectively). CONCLUSION: Results are consistent with an association between strong MyD88 staining and advanced stage and poorer survival in HGSOC and demonstrate correlation between strong MyD88 and TLR4 staining and improved survival in LGSOC, highlighting the biological differences between the 2 serous histotypes.
Published: 2018

8. rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology

Author: Kelemen, LE, Earp, M, Fridley, BL, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Ekici, AB, Hein, A, Lambrechts, D, Lambrechts, S, Van Nieuwenhuysen, E, Vergote, I, Rossing, MA, Doherty, JA, Chang-Claude, J, Behrens, S, Moysich, KB, Cannioto, R, Lele, S, Odunsi, K, Goodman, MT, Shvetsov, YB, Thompson, PJ, Wilkens, LR, Doerk, T, Antonenkova, N, Bogdanova, N, Hillemanns, P, Runnebaum, IB, du Bois, A, Harter, P, Heitz, F, Schwaab, I, Butzow, R, Pelttari, LM, Nevanlinna, H, Modugno, F, Edwards, RP, Kelley, JL, Ness, RB, Karlan, BY, Lester, J, Orsulic, S, Walsh, C, Kjaer, SK, Jensen, A, Cunningham, JM, Vierkant, RA, Giles, GG, Bruinsma, F, Southey, MC, Hildebrandt, MAT, Liang, D, Lu, K, Wu, X, Sellers, TA, Levine, DA, Schildkraut, JM, Iversen, ES, Terry, KL, Cramer, DW, Tworoger, SS, Poole, EM, Bandera, EV, Olson, SH, Orlow, I, Thomsen, LCV, Bjorge, L, Krakstad, C, Tangen, IL, Kiemeney, LA, Aben, KKH, Massuger, LFAG, van Altena, AM, Pejovic, T, Bean, Y, Kellar, M, Cook, LS, Le, ND, Brooks-Wilson, A, Gronwald, J, Cybulski, C, Jakubowska, A, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Hogdall, E, Engelholm, SA, Hogdall, C, Lundvall, L, Nedergaard, L, Pharoah, PDP, Dicks, E, Song, H, Tyrer, JP, McNeish, I, Siddiqui, N, Carty, K, Glasspool, R, Paul, J, Campbell, IG, Eccles, D, Whittemore, AS, McGuire, V, Rothstein, JH, Sieh, W, Narod, SA, Phelan, CM, McLaughlin, JR, Risch, HA, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Gentry-Maharaj, A, Ramus, SJ, Wu, AH, Pearce, CL, Lee, AW, Pike, MC, Kupryjanczyk, J, Podgorska, A, Plisiecka-Halasa, J, Sawicki, W, Goode, EL, Berchuck, A, Kelemen, LE, Earp, M, Fridley, BL, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Ekici, AB, Hein, A, Lambrechts, D, Lambrechts, S, Van Nieuwenhuysen, E, Vergote, I, Rossing, MA, Doherty, JA, Chang-Claude, J, Behrens, S, Moysich, KB, Cannioto, R, Lele, S, Odunsi, K, Goodman, MT, Shvetsov, YB, Thompson, PJ, Wilkens, LR, Doerk, T, Antonenkova, N, Bogdanova, N, Hillemanns, P, Runnebaum, IB, du Bois, A, Harter, P, Heitz, F, Schwaab, I, Butzow, R, Pelttari, LM, Nevanlinna, H, Modugno, F, Edwards, RP, Kelley, JL, Ness, RB, Karlan, BY, Lester, J, Orsulic, S, Walsh, C, Kjaer, SK, Jensen, A, Cunningham, JM, Vierkant, RA, Giles, GG, Bruinsma, F, Southey, MC, Hildebrandt, MAT, Liang, D, Lu, K, Wu, X, Sellers, TA, Levine, DA, Schildkraut, JM, Iversen, ES, Terry, KL, Cramer, DW, Tworoger, SS, Poole, EM, Bandera, EV, Olson, SH, Orlow, I, Thomsen, LCV, Bjorge, L, Krakstad, C, Tangen, IL, Kiemeney, LA, Aben, KKH, Massuger, LFAG, van Altena, AM, Pejovic, T, Bean, Y, Kellar, M, Cook, LS, Le, ND, Brooks-Wilson, A, Gronwald, J, Cybulski, C, Jakubowska, A, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Hogdall, E, Engelholm, SA, Hogdall, C, Lundvall, L, Nedergaard, L, Pharoah, PDP, Dicks, E, Song, H, Tyrer, JP, McNeish, I, Siddiqui, N, Carty, K, Glasspool, R, Paul, J, Campbell, IG, Eccles, D, Whittemore, AS, McGuire, V, Rothstein, JH, Sieh, W, Narod, SA, Phelan, CM, McLaughlin, JR, Risch, HA, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Gentry-Maharaj, A, Ramus, SJ, Wu, AH, Pearce, CL, Lee, AW, Pike, MC, Kupryjanczyk, J, Podgorska, A, Plisiecka-Halasa, J, Sawicki, W, Goode, EL, and Berchuck, A
Abstract: Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10-28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.
Published: 2018

9. Adult height is associated with increased risk of ovarian cancer: a Mendelian randomisation study

Author: Dixon-Suen, SC, Nagle, CM, Thrift, AP, Pharoah, PDP, Ewing, A, Pearce, CL, Zheng, W, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Jung, AY, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Doerk, T, Park-Simon, T-W, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, du Bois, A, Harter, P, Schwaab, I, Karlan, BY, Lester, J, Orsulic, S, Rimel, BJ, Kjaer, SK, Hogdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LCV, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubinski, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Hogdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Wu, AH, Pike, MC, Tseng, C-C, Kupryjanczyk, J, Dansonka-Mieszkowska, A, Budzilowska, A, Rzepecka, IK, Webb, PM, Dixon-Suen, SC, Nagle, CM, Thrift, AP, Pharoah, PDP, Ewing, A, Pearce, CL, Zheng, W, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, Wicklund, KG, Chang-Claude, J, Jung, AY, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Doerk, T, Park-Simon, T-W, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, du Bois, A, Harter, P, Schwaab, I, Karlan, BY, Lester, J, Orsulic, S, Rimel, BJ, Kjaer, SK, Hogdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LCV, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bruegl, A, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubinski, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Hogdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, Anton-Culver, H, Ziogas, A, Menon, U, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Wu, AH, Pike, MC, Tseng, C-C, Kupryjanczyk, J, Dansonka-Mieszkowska, A, Budzilowska, A, Rzepecka, IK, and Webb, PM
Abstract: BACKGROUND: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias. METHODS: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis. RESULTS: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours. CONCLUSIONS: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.
Published: 2018

10. Adult body mass index and risk of ovarian cancer by subtype: A Mendelian randomization study

Author: Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Pearce, CL, Zheng, W, Painter, JN, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, GWicklund, K, Chang-Claude, J, Rudolph, A, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Karlan, BY, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LC, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, Anton-Culver, H, Dixon-Suen, Suzanne, Nagle, CM, Thrift, AP, Pharoah, PDP, Pearce, CL, Zheng, W, Painter, JN, Chenevix-Trench, G, Fasching, PA, Beckmann, MW, Lambrechts, D, Vergote, I, Lambrechts, S, Van Nieuwenhuysen, E, Rossing, MA, Doherty, JA, GWicklund, K, Chang-Claude, J, Rudolph, A, Moysich, KB, Odunsi, K, Goodman, MT, Wilkens, LR, Thompson, PJ, Shvetsov, YB, Dörk, T, Park-Simon, TW, Hillemanns, P, Bogdanova, N, Butzow, R, Nevanlinna, H, Pelttari, LM, Leminen, A, Modugno, F, Ness, RB, Edwards, RP, Kelley, JL, Heitz, F, Karlan, BY, Kjær, SK, Høgdall, E, Jensen, A, Goode, EL, Fridley, BL, Cunningham, JM, Winham, SJ, Giles, GG, Bruinsma, F, Milne, RL, Southey, MC, Hildebrandt, MAT, Wu, X, Lu, KH, Liang, D, Levine, DA, Bisogna, M, Schildkraut, JM, Berchuck, A, Cramer, DW, Terry, KL, Bandera, EV, Olson, SH, Salvesen, HB, Thomsen, LC, Kopperud, RK, Bjorge, L, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Cook, LS, Le, ND, Swenerton, KD, Brooks-Wilson, A, Kelemen, LE, Lubiński, J, Huzarski, T, Gronwald, J, Menkiszak, J, Wentzensen, N, Brinton, L, Yang, H, Lissowska, J, Høgdall, CK, Lundvall, L, Song, H, Tyrer, JP, Campbell, I, Eccles, D, Paul, J, Glasspool, R, Siddiqui, N, Whittemore, AS, Sieh, W, McGuire, V, Rothstein, JH, Narod, SA, Phelan, C, Risch, HA, McLaughlin, JR, and Anton-Culver, H
Published: 2016

11. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

Author: Hampras, SS, Sucheston-Campbell, LE, Cannioto, R, Chang-Claude, J, Modugno, F, Doerk, T, Hillemanns, P, Preus, L, Knutson, KL, Wallace, PK, Hong, C-C, Friel, G, Davis, W, Nesline, M, Pearce, CL, Kelemen, LE, Goodman, MT, Bandera, EV, Terry, KL, Schoof, N, Eng, KH, Clay, A, Singh, PK, Joseph, JM, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Cook, LS, Cramer, DW, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Despierre, E, Dicks, E, Doherty, JA, du Bois, A, Duerst, M, Easton, D, Eccles, D, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Gronwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hogdall, C, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Klapdor, R, Kolomeyevskaya, N, Krakstad, C, Kjaer, SK, Kruszka, B, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Liu, S, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Moes-Sosnowska, J, Narod, SA, Nedergaard, L, Nevanlinna, H, Nickels, S, Olson, SH, Orlow, I, Weber, RP, Paul, J, Pejovic, T, Pelttari, LM, Perkins, B, Permuth-Wey, J, Pike, MC, Plisiecka-Halasa, J, Poole, EM, Risch, HA, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schernhammer, E, Schmitt, K, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Tangen, IL, Teo, S-H, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Tyrer, J, van Altena, AM, Vergote, I, Vierkant, RA, Walsh, C, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Gayther, SA, Ramus, SJ, Sellers, TA, Schildkraut, JM, Phelan, CM, Berchuck, A, Chenevix-Trench, G, Cunningham, JM, Pharoah, PP, Ness, RB, Odunsi, K, Goode, EL, Moysich, KB, Hampras, SS, Sucheston-Campbell, LE, Cannioto, R, Chang-Claude, J, Modugno, F, Doerk, T, Hillemanns, P, Preus, L, Knutson, KL, Wallace, PK, Hong, C-C, Friel, G, Davis, W, Nesline, M, Pearce, CL, Kelemen, LE, Goodman, MT, Bandera, EV, Terry, KL, Schoof, N, Eng, KH, Clay, A, Singh, PK, Joseph, JM, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Cook, LS, Cramer, DW, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Despierre, E, Dicks, E, Doherty, JA, du Bois, A, Duerst, M, Easton, D, Eccles, D, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Gronwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hogdall, C, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Klapdor, R, Kolomeyevskaya, N, Krakstad, C, Kjaer, SK, Kruszka, B, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Liu, S, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Moes-Sosnowska, J, Narod, SA, Nedergaard, L, Nevanlinna, H, Nickels, S, Olson, SH, Orlow, I, Weber, RP, Paul, J, Pejovic, T, Pelttari, LM, Perkins, B, Permuth-Wey, J, Pike, MC, Plisiecka-Halasa, J, Poole, EM, Risch, HA, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schernhammer, E, Schmitt, K, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Tangen, IL, Teo, S-H, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Tyrer, J, van Altena, AM, Vergote, I, Vierkant, RA, Walsh, C, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Gayther, SA, Ramus, SJ, Sellers, TA, Schildkraut, JM, Phelan, CM, Berchuck, A, Chenevix-Trench, G, Cunningham, JM, Pharoah, PP, Ness, RB, Odunsi, K, Goode, EL, and Moysich, KB
Abstract: BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.
Published: 2016

12. PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Author: Southey, MC, Goldgar, DE, Winqvist, R, Pylkas, K, Couch, F, Tischkowitz, M, Foulkes, WD, Dennis, J, Michailidou, K, van Rensburg, EJ, Heikkinen, T, Nevanlinna, H, Hopper, JL, Doerk, T, Claes, KBM, Reis-Filho, J, Teo, ZL, Radice, P, Catucci, I, Peterlongo, P, Tsimiklis, H, Odefrey, FA, Dowty, JG, Schmidt, MK, Broeks, A, Hogervorst, FB, Verhoef, S, Carpenter, J, Clarke, C, Scott, RJ, Fasching, PA, Haeberle, L, Ekici, AB, Beckmann, MW, Peto, J, dos-Santos-Silva, I, Fletcher, O, Johnson, N, Bolla, MK, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Marme, F, Burwinkel, B, Yang, R, Guenel, P, Therese, T, Menegaux, F, Sanchez, M, Bojesen, S, Nielsen, SF, Flyger, H, Benitez, J, Pilar Zamora, M, Arias Perez, JI, Menendez, P, Anton-Culver, H, Neuhausen, S, Ziogas, A, Clarke, CA, Brenner, H, Arndt, V, Stegmaier, C, Brauch, H, Bruening, T, Ko, Y-D, Muranen, TA, Aittomaki, K, Blomqvist, C, Bogdanova, NV, Antonenkova, NN, Lindblom, A, Margolin, S, Mannermaa, A, Kataja, V, Kosma, V-M, Hartikainen, JM, Spurdle, AB, Wauters, E, Smeets, D, Beuselinck, B, Floris, G, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Olson, JE, Vachon, C, Pankratz, VS, McLean, C, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Kristensen, V, Alnaes, GG, Zheng, W, Hunter, DJ, Lindstrom, S, Hankinson, SE, Kraft, P, Andrulis, I, Knight, JA, Glendon, G, Mulligan, AM, Jukkola-Vuorinen, A, Grip, M, Kauppila, S, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Hollestelle, A, Garcia-Closas, M, Figueroa, J, Chanock, SJ, Lissowska, J, Czene, K, Darabi, H, Eriksson, M, Eccles, DM, Rafiq, S, Tapper, WJ, Gerty, SM, Hooning, MJ, Martens, JWM, Collee, JM, Tilanus-Linthorst, M, Hall, P, Li, J, Brand, JS, Humphreys, K, Cox, A, Reed, MWR, Luccarini, C, Baynes, C, Dunning, AM, Hamann, U, Torres, D, Ulmer, HU, Ruediger, T, Jakubowska, A, Lubinski, J, Jaworska, K, Durda, K, Slager, S, Toland, AE, Ambrosone, CB, Yannoukakos, D, Swerdlow, A, Ashworth, A, Orr, N, Jones, M, Gonzalez-Neira, A, Pita, G, Rosario Alonso, M, Alvarez, N, Herrero, D, Tessier, DC, Vincent, D, Bacot, F, Simard, J, Dumont, M, Soucy, P, Eeles, R, Muir, K, Wiklund, F, Gronberg, H, Schleutker, J, Nordestgaard, BG, Weischer, M, Travis, RC, Neal, D, Donovan, JL, Hamdy, FC, Khaw, K-T, Stanford, JL, Blot, WJ, Thibodeau, S, Schaid, DJ, Kelley, JL, Maier, C, Kibel, AS, Cybulski, C, Cannon-Albright, L, Butterbach, K, Park, J, Kaneva, R, Batra, J, Teixeira, MR, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Renner, SP, Hartmann, A, Hein, A, Ruebner, M, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambretchs, S, Doherty, JA, Rossing, MA, Nickels, S, Eilber, U, Wang-Gohrke, S, Odunsi, K, Sucheston-Campbell, LE, Friel, G, Lurie, G, Killeen, JL, Wilkens, LR, Goodman, MT, Runnebaum, I, Hillemanns, PA, Pelttari, LM, Butzow, R, Modugno, F, Edwards, RP, Ness, RB, Moysich, KB, du Bois, A, Heitz, F, Harter, P, Kommoss, S, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, E, Peissel, B, Bonanni, B, Bernard, L, Goode, EL, Fridley, BL, Vierkant, RA, Cunningham, JM, Larson, MC, Fogarty, ZC, Kalli, KR, Liang, D, Lu, KH, Hildebrandt, MAT, Wu, X, Levine, DA, Dao, F, Bisogna, M, Berchuck, A, Iversen, ES, Marks, JR, Akushevich, L, Cramer, DW, Schildkraut, J, Terry, KL, Poole, EM, Stampfer, M, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Bjorge, L, Salvesen, HB, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, Y, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Grski, B, Gronwald, J, Menkiszak, J, Hogdall, CK, Lundvall, L, Nedergaard, L, Engelholm, SA, Dicks, E, Tyrer, J, Campbell, I, McNeish, I, Paul, J, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Cai, H, Shu, X-O, Teten, RT, Sutphen, R, McLaughlin, JR, Narod, SA, Phelan, CM, Monteiro, AN, Fenstermacher, D, Lin, H-Y, Permuth, JB, Sellers, TA, Chen, YA, Tsai, Y-Y, Chen, Z, Gentry-Maharaj, A, Gayther, SA, Ramus, SJ, Menon, U, Wu, AH, Pearce, CL, Van den Berg, D, Pike, MC, Dansonka-Mieszkowska, A, Plisiecka-Halasa, J, Moes-Sosnowska, J, Kupryjanczyk, J, Pharoah, PDP, Song, H, Winship, I, Chenevix-Trench, G, Giles, GG, Tavtigian, SV, Easton, DF, Milne, RL, Southey, MC, Goldgar, DE, Winqvist, R, Pylkas, K, Couch, F, Tischkowitz, M, Foulkes, WD, Dennis, J, Michailidou, K, van Rensburg, EJ, Heikkinen, T, Nevanlinna, H, Hopper, JL, Doerk, T, Claes, KBM, Reis-Filho, J, Teo, ZL, Radice, P, Catucci, I, Peterlongo, P, Tsimiklis, H, Odefrey, FA, Dowty, JG, Schmidt, MK, Broeks, A, Hogervorst, FB, Verhoef, S, Carpenter, J, Clarke, C, Scott, RJ, Fasching, PA, Haeberle, L, Ekici, AB, Beckmann, MW, Peto, J, dos-Santos-Silva, I, Fletcher, O, Johnson, N, Bolla, MK, Sawyer, EJ, Tomlinson, I, Kerin, MJ, Miller, N, Marme, F, Burwinkel, B, Yang, R, Guenel, P, Therese, T, Menegaux, F, Sanchez, M, Bojesen, S, Nielsen, SF, Flyger, H, Benitez, J, Pilar Zamora, M, Arias Perez, JI, Menendez, P, Anton-Culver, H, Neuhausen, S, Ziogas, A, Clarke, CA, Brenner, H, Arndt, V, Stegmaier, C, Brauch, H, Bruening, T, Ko, Y-D, Muranen, TA, Aittomaki, K, Blomqvist, C, Bogdanova, NV, Antonenkova, NN, Lindblom, A, Margolin, S, Mannermaa, A, Kataja, V, Kosma, V-M, Hartikainen, JM, Spurdle, AB, Wauters, E, Smeets, D, Beuselinck, B, Floris, G, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Olson, JE, Vachon, C, Pankratz, VS, McLean, C, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Kristensen, V, Alnaes, GG, Zheng, W, Hunter, DJ, Lindstrom, S, Hankinson, SE, Kraft, P, Andrulis, I, Knight, JA, Glendon, G, Mulligan, AM, Jukkola-Vuorinen, A, Grip, M, Kauppila, S, Devilee, P, Tollenaar, RAEM, Seynaeve, C, Hollestelle, A, Garcia-Closas, M, Figueroa, J, Chanock, SJ, Lissowska, J, Czene, K, Darabi, H, Eriksson, M, Eccles, DM, Rafiq, S, Tapper, WJ, Gerty, SM, Hooning, MJ, Martens, JWM, Collee, JM, Tilanus-Linthorst, M, Hall, P, Li, J, Brand, JS, Humphreys, K, Cox, A, Reed, MWR, Luccarini, C, Baynes, C, Dunning, AM, Hamann, U, Torres, D, Ulmer, HU, Ruediger, T, Jakubowska, A, Lubinski, J, Jaworska, K, Durda, K, Slager, S, Toland, AE, Ambrosone, CB, Yannoukakos, D, Swerdlow, A, Ashworth, A, Orr, N, Jones, M, Gonzalez-Neira, A, Pita, G, Rosario Alonso, M, Alvarez, N, Herrero, D, Tessier, DC, Vincent, D, Bacot, F, Simard, J, Dumont, M, Soucy, P, Eeles, R, Muir, K, Wiklund, F, Gronberg, H, Schleutker, J, Nordestgaard, BG, Weischer, M, Travis, RC, Neal, D, Donovan, JL, Hamdy, FC, Khaw, K-T, Stanford, JL, Blot, WJ, Thibodeau, S, Schaid, DJ, Kelley, JL, Maier, C, Kibel, AS, Cybulski, C, Cannon-Albright, L, Butterbach, K, Park, J, Kaneva, R, Batra, J, Teixeira, MR, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Renner, SP, Hartmann, A, Hein, A, Ruebner, M, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambretchs, S, Doherty, JA, Rossing, MA, Nickels, S, Eilber, U, Wang-Gohrke, S, Odunsi, K, Sucheston-Campbell, LE, Friel, G, Lurie, G, Killeen, JL, Wilkens, LR, Goodman, MT, Runnebaum, I, Hillemanns, PA, Pelttari, LM, Butzow, R, Modugno, F, Edwards, RP, Ness, RB, Moysich, KB, du Bois, A, Heitz, F, Harter, P, Kommoss, S, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, E, Peissel, B, Bonanni, B, Bernard, L, Goode, EL, Fridley, BL, Vierkant, RA, Cunningham, JM, Larson, MC, Fogarty, ZC, Kalli, KR, Liang, D, Lu, KH, Hildebrandt, MAT, Wu, X, Levine, DA, Dao, F, Bisogna, M, Berchuck, A, Iversen, ES, Marks, JR, Akushevich, L, Cramer, DW, Schildkraut, J, Terry, KL, Poole, EM, Stampfer, M, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Bjorge, L, Salvesen, HB, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, Y, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Grski, B, Gronwald, J, Menkiszak, J, Hogdall, CK, Lundvall, L, Nedergaard, L, Engelholm, SA, Dicks, E, Tyrer, J, Campbell, I, McNeish, I, Paul, J, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Cai, H, Shu, X-O, Teten, RT, Sutphen, R, McLaughlin, JR, Narod, SA, Phelan, CM, Monteiro, AN, Fenstermacher, D, Lin, H-Y, Permuth, JB, Sellers, TA, Chen, YA, Tsai, Y-Y, Chen, Z, Gentry-Maharaj, A, Gayther, SA, Ramus, SJ, Menon, U, Wu, AH, Pearce, CL, Van den Berg, D, Pike, MC, Dansonka-Mieszkowska, A, Plisiecka-Halasa, J, Moes-Sosnowska, J, Kupryjanczyk, J, Pharoah, PDP, Song, H, Winship, I, Chenevix-Trench, G, Giles, GG, Tavtigian, SV, Easton, DF, and Milne, RL
Abstract: BACKGROUND: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. METHODS: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. RESULTS: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. CONCLUSIONS: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.
Published: 2016

13. Variation in NF-κB signaling pathways and survival in invasive epithelial ovarian cancer

Author: Block, MS, Charbonneau, B, Vierkant, RA, Fogarty, Z, Bamlet, WR, Pharoah, PDP, Chenevix-Trench, G, Rossing, MA, Cramer, D, Pearce, CL, Schildkraut, J, Menon, U, Kjaer, SK, Levine, DA, Gronwald, J, Culver, HA, Whittemore, AS, Karlan, BY, Lambrechts, D, Wentzensen, N, Kupryjanczyk, J, Chang-Claude, J, Bandera, EV, Hogdall, E, Heitz, F, Kaye, SB, Fasching, PA, Campbell, I, Goodman, MT, Pejovic, T, Bean, YT, Hays, LE, Lurie, G, Eccles, D, Hein, A, Beckmann, MW, Ekici, AB, Paul, J, Brown, R, Flanagan, JM, Harter, P, Du Bois, A, Schwaab, I, Hogdall, CK, Lundvall, L, Olson, SH, Orlow, I, Paddock, LE, Rudolph, A, Eilber, U, Dansonka-Mieszkowska, A, Rzepecka, IK, Ziolkowska-Seta, I, Brinton, LA, Yang, H, Garcia-Closas, M, Despierre, E, Lambrechts, S, Vergote, I, Walsh, CS, Lester, J, Sieh, W, McGuire, V, Rothstein, JH, Ziogas, A, Lubinski, J, Cybulski, C, Menkiszak, J, Jensen, A, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Berchuck, A, Wu, AH, Pike, MC, Van Den Berg, D, Terry, KL, Vitonis, AF, Ramirez, SM, Rider, DN, Knutson, KL, and Sellers, TA
Subjects: endocrine system diseases, female genital diseases and pregnancy complications
Abstract: Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-kB (NF-kB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-kB family in 10,084 patients with invasive EOC (5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance, P < 2.5 × 10-5). Results were statistically significant when assessed for patients of a single histology. Key associations were with caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41-2.35; P = 4.13 × 10-6] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) rs7501462 in patients with endometrioid EOC (HR, 0.68; 95% CI, 0.56-0.82; P = 2.33 × 10-5). Other associations of note included TNF receptor-associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77-0.92; P = 6.49 ± 10-5) and phospholipase C, gamma 1 (PLCG1) rs11696662 in patients with clear cell EOC (HR, 0.43; 95% CI, 0.26-0.73; P = 4.56 × 10-4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies. © 2014 American Association for Cancer Research.
Published: 2014

14. Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk

Author: Agoulnik, IU, Chornokur, G, Lin, H-Y, Tyrer, JP, Lawrenson, K, Dennis, J, Amankwah, EK, Qu, X, Tsai, Y-Y, Jim, HSL, Chen, Z, Chen, AY, Permuth-Wey, J, Aben, KKH, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, du Bois, A, Despierre, E, Dicks, E, Doherty, JA, Dork, T, Durst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harrington, P, Harter, P, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kelemen, LE, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lim, BK, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Milne, RL, Modugno, F, Moysich, KB, Ness, RB, Nevanlinna, H, Eilber, U, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Pike, MC, Poole, EM, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schernhammer, E, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Spiewankiewicz, B, Sucheston, L, Teo, S-H, Terry, KL, Thompson, PJ, Thomsen, L, Tangen, IL, Tworoger, SS, van Altena, AM, Vierkant, RA, Vergote, I, Walsh, CS, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Hasmad, HN, Berchuck, A, Iversen, ES, Schildkraut, JM, Ramus, SJ, Goode, EL, Monteiro, ANA, Gayther, SA, Narod, SA, Pharoah, PP, Sellers, TA, Phelan, CM, Agoulnik, IU, Chornokur, G, Lin, H-Y, Tyrer, JP, Lawrenson, K, Dennis, J, Amankwah, EK, Qu, X, Tsai, Y-Y, Jim, HSL, Chen, Z, Chen, AY, Permuth-Wey, J, Aben, KKH, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, du Bois, A, Despierre, E, Dicks, E, Doherty, JA, Dork, T, Durst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harrington, P, Harter, P, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kelemen, LE, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lim, BK, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Milne, RL, Modugno, F, Moysich, KB, Ness, RB, Nevanlinna, H, Eilber, U, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Pike, MC, Poole, EM, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schernhammer, E, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Spiewankiewicz, B, Sucheston, L, Teo, S-H, Terry, KL, Thompson, PJ, Thomsen, L, Tangen, IL, Tworoger, SS, van Altena, AM, Vierkant, RA, Vergote, I, Walsh, CS, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Hasmad, HN, Berchuck, A, Iversen, ES, Schildkraut, JM, Ramus, SJ, Goode, EL, Monteiro, ANA, Gayther, SA, Narod, SA, Pharoah, PP, Sellers, TA, and Phelan, CM
Abstract: BACKGROUND: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons. RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4). CONCLUSION: These results, generated on a large cohort of women, revealed associatio
Published: 2015

15. Common Genetic Variation in Circadian Rhythm Genes and Risk of Epithelial Ovarian Cancer (EOC).

Author: Jim, HSL, Lin, H-Y, Tyrer, JP, Lawrenson, K, Dennis, J, Chornokur, G, Chen, Z, Chen, AY, Permuth-Wey, J, Aben, KK, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, du Bois, A, Despierre, E, Sieh, W, Doherty, JA, Dörk, T, Dürst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Vierkant, RA, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lim, BK, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Milne, RL, Modugno, F, Thomsen, L, Moysich, KB, Ness, RB, Nevanlinna, H, Eilber, U, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Palmieri Weber, R, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Pike, MC, Poole, EM, Schernhammer, E, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Song, H, Southey, MC, Spiewankiewicz, B, Sucheston-Campbell, L, Teo, S-H, Terry, KL, Thompson, PJ, Tangen, IL, Tworoger, SS, van Altena, AM, Vergote, I, Walsh, CS, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Amankwah, E, Berchuck, A, Georgia Chenevix-Trench on behalf of the AOCS management group 95,96, Schildkraut, JM, Kelemen, LE, Ramus, SJ, Monteiro, ANA, Goode, EL, Narod, SA, Gayther, SA, Pharoah, PDP, Sellers, TA, Phelan, CM, Jim, HSL, Lin, H-Y, Tyrer, JP, Lawrenson, K, Dennis, J, Chornokur, G, Chen, Z, Chen, AY, Permuth-Wey, J, Aben, KK, Anton-Culver, H, Antonenkova, N, Bruinsma, F, Bandera, EV, Bean, YT, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bunker, CH, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, du Bois, A, Despierre, E, Sieh, W, Doherty, JA, Dörk, T, Dürst, M, Easton, DF, Eccles, DM, Edwards, RP, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goodman, MT, Gronwald, J, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, CK, Hogdall, E, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Vierkant, RA, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lim, BK, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Milne, RL, Modugno, F, Thomsen, L, Moysich, KB, Ness, RB, Nevanlinna, H, Eilber, U, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Palmieri Weber, R, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Pike, MC, Poole, EM, Schernhammer, E, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Song, H, Southey, MC, Spiewankiewicz, B, Sucheston-Campbell, L, Teo, S-H, Terry, KL, Thompson, PJ, Tangen, IL, Tworoger, SS, van Altena, AM, Vergote, I, Walsh, CS, Wang-Gohrke, S, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Wu, AH, Wu, X, Woo, Y-L, Yang, H, Zheng, W, Ziogas, A, Amankwah, E, Berchuck, A, Georgia Chenevix-Trench on behalf of the AOCS management group 95,96, Schildkraut, JM, Kelemen, LE, Ramus, SJ, Monteiro, ANA, Goode, EL, Narod, SA, Gayther, SA, Pharoah, PDP, Sellers, TA, and Phelan, CM
Abstract: Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68-0.90, p = 5.59 × 10-4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.
Published: 2015

16. Identification of six new susceptibility loci for invasive epithelial ovarian cancer

Author: Kuchenbaecker, KB, Ramus, SJ, Tyrer, J, Lee, A, Shen, HC, Beesley, J, Lawrenson, K, McGuffog, L, Healey, S, Lee, JM, Spindler, TJ, Lin, YG, Pejovic, T, Bean, Y, Li, Q, Coetzee, S, Hazelett, D, Miron, A, Southey, M, Terry, MB, Goldgar, DE, Buys, SS, Janavicius, R, Dorfling, CM, van Rensburg, EJ, Neuhausen, SL, Ding, YC, Hansen, TVO, Jonson, L, Gerdes, A-M, Ejlertsen, B, Barrowdale, D, Dennis, J, Benitez, J, Osorio, A, Garcia, MJ, Komenaka, I, Weitzel, JN, Ganschow, P, Peterlongo, P, Bernard, L, Viel, A, Bonanni, B, Peissel, B, Manoukian, S, Radice, P, Papi, L, Ottini, L, Fostira, F, Konstantopoulou, I, Garber, J, Frost, D, Perkins, J, Platte, R, Ellis, S, Godwin, AK, Schmutzler, RK, Meindl, A, Engel, C, Sutter, C, Sinilnikova, OM, Damiola, F, Mazoyer, S, Stoppa-Lyonnet, D, Claes, K, De Leeneer, K, Kirk, J, Rodriguez, GC, Piedmonte, M, O'Malley, DM, de la Hoya, M, Caldes, T, Aittomaeki, K, Nevanlinna, H, Collee, JM, Rookus, MA, Oosterwijk, JC, Tihomirova, L, Tung, N, Hamann, U, Isaccs, C, Tischkowitz, M, Imyanitov, EN, Caligo, MA, Campbell, IG, Hogervorst, FBL, Olah, E, Diez, O, Blanco, I, Brunet, J, Lazaroso, C, Angel Pujana, M, Jakubowska, A, Gronwald, J, Lubinski, J, Sukiennicki, G, Barkardottir, RB, Plante, M, Simard, J, Soucy, P, Montagna, M, Tognazzo, S, Teixeira, MR, Pankratz, VS, Wang, X, Lindor, N, Szabo, CI, Kauff, N, Vijai, J, Aghajanian, CA, Pfeiler, G, Berger, A, Singer, CF, Tea, M-K, Phelan, CM, Greene, MH, Mai, PL, Rennert, G, Mulligan, AM, Tchatchou, S, Andrulis, IL, Glendon, G, Toland, AE, Jensen, UB, Kruse, TA, Thomassen, M, Bojesen, A, Zidan, J, Friedman, E, Laitman, Y, Soller, M, Liljegren, A, Arver, B, Einbeigi, Z, Stenmark-Askmalm, M, Olopade, OI, Nussbaum, RL, Rebbeck, TR, Nathanson, KL, Domchek, SM, Lu, KH, Karlan, BY, Walsh, C, Lester, J, Hein, A, Ekici, AB, Beckmann, MW, Fasching, PA, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambrechts, S, Dicks, E, Doherty, JA, Wicklund, KG, Rossing, MA, Rudolph, A, Chang-Claude, J, Wang-Gohrke, S, Eilber, U, Moysich, KB, Odunsi, K, Sucheston, L, Lele, S, Wilkens, LR, Goodman, MT, Thompson, PJ, Shvetsov, YB, Runnebaum, IB, Duerst, M, Hillemanns, P, Doerk, T, Antonenkova, N, Bogdanova, N, Leminen, A, Pelttari, LM, Butzow, R, Modugno, F, Kelley, JL, Edwards, RP, Ness, RB, du Bois, A, Heitz, F, Schwaab, I, Harter, P, Matsuo, K, Hosono, S, Orsulic, S, Jensen, A, Kjaer, SK, Hogdall, E, Hasmad, HN, Azmi, MAN, Teo, S-H, Woo, Y-L, Fridley, BL, Goode, EL, Cunningham, JM, Vierkant, RA, Bruinsma, F, Giles, GG, Liang, D, Hildebrandt, MAT, Wu, X, Levine, DA, Bisogna, M, Berchuck, A, Iversen, ES, Schildkraut, JM, Concannon, P, Weber, RP, Cramer, DW, Terry, KL, Poole, EM, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Krakstad, C, Salvesen, HB, Tangen, IL, Bjorge, L, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Kellar, M, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Cybulski, C, Yang, H, Lissowska, J, Brinton, LA, Wentzensen, N, Hogdall, C, Lundvall, L, Nedergaard, L, Baker, H, Song, H, Eccles, D, McNeish, I, Paul, J, Carty, K, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Ji, B-T, Zheng, W, Shu, X-O, Gao, Y-T, Rosen, B, Risch, HA, McLaughlin, JR, Narod, SA, Monteiro, AN, Chen, A, Lin, H-Y, Permuth-Wey, J, Sellers, TA, Tsai, Y-Y, Chen, Z, Ziogas, A, Anton-Culver, H, Gentry-Maharaj, A, Menon, U, Harrington, P, Lee, AW, Wu, AH, Pearce, CL, Coetzee, G, Pike, MC, Dansonka-Mieszkowska, A, Timorek, A, Rzepecka, IK, Kupryjanczyk, J, Freedman, M, Noushmehr, H, Easton, DF, Offit, K, Couch, FJ, Gayther, S, Pharoah, PP, Antoniou, AC, Chenevix-Trench, G, Kuchenbaecker, KB, Ramus, SJ, Tyrer, J, Lee, A, Shen, HC, Beesley, J, Lawrenson, K, McGuffog, L, Healey, S, Lee, JM, Spindler, TJ, Lin, YG, Pejovic, T, Bean, Y, Li, Q, Coetzee, S, Hazelett, D, Miron, A, Southey, M, Terry, MB, Goldgar, DE, Buys, SS, Janavicius, R, Dorfling, CM, van Rensburg, EJ, Neuhausen, SL, Ding, YC, Hansen, TVO, Jonson, L, Gerdes, A-M, Ejlertsen, B, Barrowdale, D, Dennis, J, Benitez, J, Osorio, A, Garcia, MJ, Komenaka, I, Weitzel, JN, Ganschow, P, Peterlongo, P, Bernard, L, Viel, A, Bonanni, B, Peissel, B, Manoukian, S, Radice, P, Papi, L, Ottini, L, Fostira, F, Konstantopoulou, I, Garber, J, Frost, D, Perkins, J, Platte, R, Ellis, S, Godwin, AK, Schmutzler, RK, Meindl, A, Engel, C, Sutter, C, Sinilnikova, OM, Damiola, F, Mazoyer, S, Stoppa-Lyonnet, D, Claes, K, De Leeneer, K, Kirk, J, Rodriguez, GC, Piedmonte, M, O'Malley, DM, de la Hoya, M, Caldes, T, Aittomaeki, K, Nevanlinna, H, Collee, JM, Rookus, MA, Oosterwijk, JC, Tihomirova, L, Tung, N, Hamann, U, Isaccs, C, Tischkowitz, M, Imyanitov, EN, Caligo, MA, Campbell, IG, Hogervorst, FBL, Olah, E, Diez, O, Blanco, I, Brunet, J, Lazaroso, C, Angel Pujana, M, Jakubowska, A, Gronwald, J, Lubinski, J, Sukiennicki, G, Barkardottir, RB, Plante, M, Simard, J, Soucy, P, Montagna, M, Tognazzo, S, Teixeira, MR, Pankratz, VS, Wang, X, Lindor, N, Szabo, CI, Kauff, N, Vijai, J, Aghajanian, CA, Pfeiler, G, Berger, A, Singer, CF, Tea, M-K, Phelan, CM, Greene, MH, Mai, PL, Rennert, G, Mulligan, AM, Tchatchou, S, Andrulis, IL, Glendon, G, Toland, AE, Jensen, UB, Kruse, TA, Thomassen, M, Bojesen, A, Zidan, J, Friedman, E, Laitman, Y, Soller, M, Liljegren, A, Arver, B, Einbeigi, Z, Stenmark-Askmalm, M, Olopade, OI, Nussbaum, RL, Rebbeck, TR, Nathanson, KL, Domchek, SM, Lu, KH, Karlan, BY, Walsh, C, Lester, J, Hein, A, Ekici, AB, Beckmann, MW, Fasching, PA, Lambrechts, D, Van Nieuwenhuysen, E, Vergote, I, Lambrechts, S, Dicks, E, Doherty, JA, Wicklund, KG, Rossing, MA, Rudolph, A, Chang-Claude, J, Wang-Gohrke, S, Eilber, U, Moysich, KB, Odunsi, K, Sucheston, L, Lele, S, Wilkens, LR, Goodman, MT, Thompson, PJ, Shvetsov, YB, Runnebaum, IB, Duerst, M, Hillemanns, P, Doerk, T, Antonenkova, N, Bogdanova, N, Leminen, A, Pelttari, LM, Butzow, R, Modugno, F, Kelley, JL, Edwards, RP, Ness, RB, du Bois, A, Heitz, F, Schwaab, I, Harter, P, Matsuo, K, Hosono, S, Orsulic, S, Jensen, A, Kjaer, SK, Hogdall, E, Hasmad, HN, Azmi, MAN, Teo, S-H, Woo, Y-L, Fridley, BL, Goode, EL, Cunningham, JM, Vierkant, RA, Bruinsma, F, Giles, GG, Liang, D, Hildebrandt, MAT, Wu, X, Levine, DA, Bisogna, M, Berchuck, A, Iversen, ES, Schildkraut, JM, Concannon, P, Weber, RP, Cramer, DW, Terry, KL, Poole, EM, Tworoger, SS, Bandera, EV, Orlow, I, Olson, SH, Krakstad, C, Salvesen, HB, Tangen, IL, Bjorge, L, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Kellar, M, Brooks-Wilson, A, Kelemen, LE, Cook, LS, Le, ND, Cybulski, C, Yang, H, Lissowska, J, Brinton, LA, Wentzensen, N, Hogdall, C, Lundvall, L, Nedergaard, L, Baker, H, Song, H, Eccles, D, McNeish, I, Paul, J, Carty, K, Siddiqui, N, Glasspool, R, Whittemore, AS, Rothstein, JH, McGuire, V, Sieh, W, Ji, B-T, Zheng, W, Shu, X-O, Gao, Y-T, Rosen, B, Risch, HA, McLaughlin, JR, Narod, SA, Monteiro, AN, Chen, A, Lin, H-Y, Permuth-Wey, J, Sellers, TA, Tsai, Y-Y, Chen, Z, Ziogas, A, Anton-Culver, H, Gentry-Maharaj, A, Menon, U, Harrington, P, Lee, AW, Wu, AH, Pearce, CL, Coetzee, G, Pike, MC, Dansonka-Mieszkowska, A, Timorek, A, Rzepecka, IK, Kupryjanczyk, J, Freedman, M, Noushmehr, H, Easton, DF, Offit, K, Couch, FJ, Gayther, S, Pharoah, PP, Antoniou, AC, and Chenevix-Trench, G
Abstract: Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
Published: 2015

17. Genome-wide significant risk associations for mucinous ovarian carcinoma

Author: Kelemen, LE, Lawrenson, K, Tyrer, J, Li, Q, Lee, JM, Seo, J-H, Phelan, CM, Beesley, J, Chen, X, Spindler, TJ, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, YA, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Engelholm, SA, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Modugno, F, Moes-Sosnowska, J, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Nevanlinna, H, Adenan, NAM, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Tworoger, SS, van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Sawicki, W, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Sellers, TA, Freedman, ML, Chenevix-Trench, G, Pharoah, PDP, Gayther, SA, Berchuck, A, Kelemen, LE, Lawrenson, K, Tyrer, J, Li, Q, Lee, JM, Seo, J-H, Phelan, CM, Beesley, J, Chen, X, Spindler, TJ, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chen, YA, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Engelholm, SA, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, Jensen, A, Ji, B-T, Karlan, BY, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kjaer, SK, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, McNeish, I, Menon, U, Modugno, F, Moes-Sosnowska, J, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Nevanlinna, H, Adenan, NAM, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Paul, J, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Tworoger, SS, van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Sawicki, W, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Sellers, TA, Freedman, ML, Chenevix-Trench, G, Pharoah, PDP, Gayther, SA, and Berchuck, A
Abstract: Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at 2q31.1 (P = 7.5 × 10(-12)) and rs688187 at 19q13.2 (P = 6.8 × 10(-13)). We identified significant expression quantitative trait locus (eQTL) associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10(-4), false discovery rate (FDR) = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease.
Published: 2015

18. Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer

Author: Lawrenson, K, Li, Q, Kar, S, Seo, J-H, Tyrer, J, Spindler, TJ, Lee, J, Chen, Y, Karst, A, Drapkin, R, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chenevix-Trench, G, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, Du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, B-T, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, Nevanlinna, H, McNeish, I, Menon, U, Modugno, F, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Azmi, MAN, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Phelan, CM, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Sellers, TA, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Monteiro, A, Pharoah, PD, Gayther, SA, Freedman, ML, Grp, AOCS, Bowtell, D, Webb, PM, Defazio, A, Lawrenson, K, Li, Q, Kar, S, Seo, J-H, Tyrer, J, Spindler, TJ, Lee, J, Chen, Y, Karst, A, Drapkin, R, Aben, KKH, Anton-Culver, H, Antonenkova, N, Baker, H, Bandera, EV, Bean, Y, Beckmann, MW, Berchuck, A, Bisogna, M, Bjorge, L, Bogdanova, N, Brinton, LA, Brooks-Wilson, A, Bruinsma, F, Butzow, R, Campbell, IG, Carty, K, Chang-Claude, J, Chenevix-Trench, G, Chen, A, Chen, Z, Cook, LS, Cramer, DW, Cunningham, JM, Cybulski, C, Dansonka-Mieszkowska, A, Dennis, J, Dicks, E, Doherty, JA, Doerk, T, Du Bois, A, Duerst, M, Eccles, D, Easton, DT, Edwards, RP, Eilber, U, Ekici, AB, Fasching, PA, Fridley, BL, Gao, Y-T, Gentry-Maharaj, A, Giles, GG, Glasspool, R, Goode, EL, Goodman, MT, Grownwald, J, Harrington, P, Harter, P, Hasmad, HN, Hein, A, Heitz, F, Hildebrandt, MAT, Hillemanns, P, Hogdall, E, Hogdall, C, Hosono, S, Iversen, ES, Jakubowska, A, James, P, Jensen, A, Ji, B-T, Karlan, BY, Kjaer, SK, Kelemen, LE, Kellar, M, Kelley, JL, Kiemeney, LA, Krakstad, C, Kupryjanczyk, J, Lambrechts, D, Lambrechts, S, Le, ND, Lee, AW, Lele, S, Leminen, A, Lester, J, Levine, DA, Liang, D, Lissowska, J, Lu, K, Lubinski, J, Lundvall, L, Massuger, LFAG, Matsuo, K, McGuire, V, McLaughlin, JR, Nevanlinna, H, McNeish, I, Menon, U, Modugno, F, Moysich, KB, Narod, SA, Nedergaard, L, Ness, RB, Azmi, MAN, Odunsi, K, Olson, SH, Orlow, I, Orsulic, S, Weber, RP, Pearce, CL, Pejovic, T, Pelttari, LM, Permuth-Wey, J, Phelan, CM, Pike, MC, Poole, EM, Ramus, SJ, Risch, HA, Rosen, B, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Rzepecka, IK, Salvesen, HB, Schildkraut, JM, Schwaab, I, Sellers, TA, Shu, X-O, Shvetsov, YB, Siddiqui, N, Sieh, W, Song, H, Southey, MC, Sucheston, L, Tangen, IL, Teo, S-H, Terry, KL, Thompson, PJ, Timorek, A, Tsai, Y-Y, Tworoger, SS, Van Altena, AM, Van Nieuwenhuysen, E, Vergote, I, Vierkant, RA, Wang-Gohrke, S, Walsh, C, Wentzensen, N, Whittemore, AS, Wicklund, KG, Wilkens, LR, Woo, Y-L, Wu, X, Wu, AH, Yang, H, Zheng, W, Ziogas, A, Monteiro, A, Pharoah, PD, Gayther, SA, Freedman, ML, Grp, AOCS, Bowtell, D, Webb, PM, and Defazio, A
Abstract: Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
Published: 2015

19. Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA

Author: Earp, MA, Kelemen, LE, Magliocco, AM, Swenerton, KD, Chenevix-Trench, G, Lu, Y, Hein, A, Ekici, AB, Beckmann, MW, Fasching, PA, Lambrechts, D, Despierre, E, Vergote, I, Lambrechts, S, Doherty, JA, Rossing, MA, Chang-Claude, J, Rudolph, A, Friel, G, Moysich, KB, Odunsi, K, Sucheston-Campbell, L, Lurie, G, Goodman, MT, Carney, ME, Thompson, PJ, Runnebaum, IB, Duerst, M, Hillemanns, P, Doerk, T, Antonenkova, N, Bogdanova, N, Leminen, A, Nevanlinna, H, Pelttari, LM, Butzow, R, Bunker, CH, Modugno, F, Edwards, RP, Ness, RB, du Bois, A, Heitz, F, Schwaab, I, Harter, P, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, CK, Hogdall, E, Lundvall, L, Sellers, TA, Fridley, BL, Goode, EL, Cunningham, JM, Vierkant, RA, Giles, GG, Baglietto, L, Severi, G, Southey, MC, Liang, D, Wu, X, Lu, K, Hildebrandt, MAT, Levine, DA, Bisogna, M, Schildkraut, JM, Iversen, ES, Weber, RP, Berchuck, A, Cramer, DW, Terry, KL, Poole, EM, Tworoger, SS, Bandera, EV, Chandran, U, Orlow, I, Olson, SH, Wik, E, Salvesen, HB, Bjorge, L, Halle, MK, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, YT, Cybulski, C, Gronwald, J, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Garcia-Closas, M, Dicks, E, Dennis, J, Easton, DF, Song, H, Tyrer, JP, Pharoah, PDP, Eccles, D, Campbell, IG, Whittemore, AS, McGuire, V, Sieh, W, Rothstein, JH, Flanagan, JM, Paul, J, Brown, R, Phelan, CM, Risch, HA, McLaughlin, JR, Narod, SA, Ziogas, A, Anton-Culver, H, Gentry-Maharaj, A, Menon, U, Gayther, SA, Ramus, SJ, Wu, AH, Pearce, CL, Pike, MC, Dansonka-Mieszkowska, A, Rzepecka, IK, Szafron, LM, Kupryjanczyk, J, Cook, LS, Le, ND, Brooks-Wilson, A, Earp, MA, Kelemen, LE, Magliocco, AM, Swenerton, KD, Chenevix-Trench, G, Lu, Y, Hein, A, Ekici, AB, Beckmann, MW, Fasching, PA, Lambrechts, D, Despierre, E, Vergote, I, Lambrechts, S, Doherty, JA, Rossing, MA, Chang-Claude, J, Rudolph, A, Friel, G, Moysich, KB, Odunsi, K, Sucheston-Campbell, L, Lurie, G, Goodman, MT, Carney, ME, Thompson, PJ, Runnebaum, IB, Duerst, M, Hillemanns, P, Doerk, T, Antonenkova, N, Bogdanova, N, Leminen, A, Nevanlinna, H, Pelttari, LM, Butzow, R, Bunker, CH, Modugno, F, Edwards, RP, Ness, RB, du Bois, A, Heitz, F, Schwaab, I, Harter, P, Karlan, BY, Walsh, C, Lester, J, Jensen, A, Kjaer, SK, Hogdall, CK, Hogdall, E, Lundvall, L, Sellers, TA, Fridley, BL, Goode, EL, Cunningham, JM, Vierkant, RA, Giles, GG, Baglietto, L, Severi, G, Southey, MC, Liang, D, Wu, X, Lu, K, Hildebrandt, MAT, Levine, DA, Bisogna, M, Schildkraut, JM, Iversen, ES, Weber, RP, Berchuck, A, Cramer, DW, Terry, KL, Poole, EM, Tworoger, SS, Bandera, EV, Chandran, U, Orlow, I, Olson, SH, Wik, E, Salvesen, HB, Bjorge, L, Halle, MK, van Altena, AM, Aben, KKH, Kiemeney, LA, Massuger, LFAG, Pejovic, T, Bean, YT, Cybulski, C, Gronwald, J, Lubinski, J, Wentzensen, N, Brinton, LA, Lissowska, J, Garcia-Closas, M, Dicks, E, Dennis, J, Easton, DF, Song, H, Tyrer, JP, Pharoah, PDP, Eccles, D, Campbell, IG, Whittemore, AS, McGuire, V, Sieh, W, Rothstein, JH, Flanagan, JM, Paul, J, Brown, R, Phelan, CM, Risch, HA, McLaughlin, JR, Narod, SA, Ziogas, A, Anton-Culver, H, Gentry-Maharaj, A, Menon, U, Gayther, SA, Ramus, SJ, Wu, AH, Pearce, CL, Pike, MC, Dansonka-Mieszkowska, A, Rzepecka, IK, Szafron, LM, Kupryjanczyk, J, Cook, LS, Le, ND, and Brooks-Wilson, A
Abstract: Epithelial ovarian cancer (EOC) is a heterogeneous cancer with both genetic and environmental risk factors. Variants influencing the risk of developing the less-common EOC subtypes have not been fully investigated. We performed a genome-wide association study (GWAS) of EOC according to subtype by pooling genomic DNA from 545 cases and 398 controls of European descent, and testing for allelic associations. We evaluated for replication 188 variants from the GWAS [56 variants for mucinous, 55 for endometrioid and clear cell, 53 for low-malignant potential (LMP) serous, and 24 for invasive serous EOC], selected using pre-defined criteria. Genotypes from 13,188 cases and 23,164 controls of European descent were used to perform unconditional logistic regression under the log-additive genetic model; odds ratios (OR) and 95 % confidence intervals are reported. Nine variants tagging six loci were associated with subtype-specific EOC risk at P < 0.05, and had an OR that agreed in direction of effect with the GWAS results. Several of these variants are in or near genes with a biological rationale for conferring EOC risk, including ZFP36L1 and RAD51B for mucinous EOC (rs17106154, OR = 1.17, P = 0.029, n = 1,483 cases), GRB10 for endometrioid and clear cell EOC (rs2190503, P = 0.014, n = 2,903 cases), and C22orf26/BPIL2 for LMP serous EOC (rs9609538, OR = 0.86, P = 0.0043, n = 892 cases). In analyses that included the 75 GWAS samples, the association between rs9609538 (OR = 0.84, P = 0.0007) and LMP serous EOC risk remained statistically significant at P < 0.0012 adjusted for multiple testing. Replication in additional samples will be important to verify these results for the less-common EOC subtypes.
Published: 2014

20. Hormone-receptor expression and ovarian cancer survival: an Ovarian Tumor Tissue Analysis consortium study

Author: Sieh, W, Koebel, M, Longacre, TA, Bowtell, DD, defazio, A, Goodman, MT, Hogdall, E, Deen, S, Wentzensen, N, Moysich, KB, Brenton, JD, Clarke, BA, Menon, U, Gilks, CB, Kim, A, Madore, J, Fereday, S, George, J, Galletta, L, Lurie, G, Wilkens, LR, Carney, ME, Thompson, PJ, Matsuno, RK, Kjaer, SK, Jensen, A, Hogdall, C, Kalli, KR, Fridley, BL, Keeney, GL, Vierkant, RA, Cunningham, JM, Brinton, LA, Yang, HP, Sherman, ME, Garcia-Closas, M, Lissowska, J, Odunsi, K, Morrison, C, Lele, S, Bshara, W, Sucheston, L, Jimenez-Linan, M, Driver, K, Alsop, J, Mack, M, McGuire, V, Rothstein, JH, Rosen, BP, Bernardini, MQ, Mackay, H, Oza, A, Wozniak, EL, Benjamin, E, Gentry-Maharaj, A, Gayther, SA, Tinker, AV, Prentice, LM, Chow, C, Anglesio, MS, Johnatty, SE, Chenevix-Trench, G, Whittemore, AS, Pharoah, PDP, Goode, EL, Huntsman, DG, Ramus, SJ, Sieh, W, Koebel, M, Longacre, TA, Bowtell, DD, defazio, A, Goodman, MT, Hogdall, E, Deen, S, Wentzensen, N, Moysich, KB, Brenton, JD, Clarke, BA, Menon, U, Gilks, CB, Kim, A, Madore, J, Fereday, S, George, J, Galletta, L, Lurie, G, Wilkens, LR, Carney, ME, Thompson, PJ, Matsuno, RK, Kjaer, SK, Jensen, A, Hogdall, C, Kalli, KR, Fridley, BL, Keeney, GL, Vierkant, RA, Cunningham, JM, Brinton, LA, Yang, HP, Sherman, ME, Garcia-Closas, M, Lissowska, J, Odunsi, K, Morrison, C, Lele, S, Bshara, W, Sucheston, L, Jimenez-Linan, M, Driver, K, Alsop, J, Mack, M, McGuire, V, Rothstein, JH, Rosen, BP, Bernardini, MQ, Mackay, H, Oza, A, Wozniak, EL, Benjamin, E, Gentry-Maharaj, A, Gayther, SA, Tinker, AV, Prentice, LM, Chow, C, Anglesio, MS, Johnatty, SE, Chenevix-Trench, G, Whittemore, AS, Pharoah, PDP, Goode, EL, Huntsman, DG, and Ramus, SJ
Abstract: BACKGROUND: Few biomarkers of ovarian cancer prognosis have been established, partly because subtype-specific associations might be obscured in studies combining all histopathological subtypes. We examined whether tumour expression of the progesterone receptor (PR) and oestrogen receptor (ER) was associated with subtype-specific survival. METHODS: 12 studies participating in the Ovarian Tumor Tissue Analysis consortium contributed tissue microarray sections and clinical data to our study. Participants included in our analysis had been diagnosed with invasive serous, mucinous, endometrioid, or clear-cell carcinomas of the ovary. For a patient to be eligible, tissue microarrays, clinical follow-up data, age at diagnosis, and tumour grade and stage had to be available. Clinical data were obtained from medical records, cancer registries, death certificates, pathology reports, and review of histological slides. PR and ER statuses were assessed by central immunohistochemistry analysis done by masked pathologists. PR and ER staining was defined as negative (<1% tumour cell nuclei), weak (1 to <50%), or strong (≥50%). Associations with disease-specific survival were assessed. FINDINGS: 2933 women with invasive epithelial ovarian cancer were included: 1742 with high-grade serous carcinoma, 110 with low-grade serous carcinoma, 207 with mucinous carcinoma, 484 with endometrioid carcinoma, and 390 with clear-cell carcinoma. PR expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001) and high-grade serous carcinoma (log-rank p=0·0006), and ER expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001). We recorded no significant associations for mucinous, clear-cell, or low-grade serous carcinoma. Positive hormone-receptor expression (weak or strong staining for PR or ER, or both) was associated with significantly improved disease-specific survival in endometrioid carcinoma
Published: 2013

21. Analysis of Over 10,000 Cases Finds No Association between Previously Reported Candidate Polymorphisms and Ovarian Cancer Outcome

Author: White, KL, Vierkant, RA, Fogarty, ZC, Charbonneau, B, Block, MS, Pharoah, PDP, Chenevix-Trench, G, Rossing, MA, Cramer, DW, Pearce, CL, Schildkraut, JM, Menon, U, Kjaer, SK, Levine, DA, Gronwald, J, Culver, HA, Whittemore, AS, Karlan, BY, Lambrechts, D, Wentzensen, N, Kupryjanczyk, J, Chang-Claude, J, Bandera, EV, Hogdall, E, Heitz, F, Kaye, SB, Fasching, PA, Campbell, I, Goodman, MT, Pejovic, T, Bean, Y, Lurie, G, Eccles, D, Hein, A, Beckmann, MW, Ekici, AB, Paul, J, Brown, R, Flanagan, JM, Harter, P, Du Bois, A, Schwaab, I, Hogdall, CK, Lundvall, L, Olson, SH, Orlow, I, Paddock, LE, Rudolph, A, Eilber, U, Dansonka-Mieszkowska, A, Rzepecka, IK, Ziolkowska-Seta, I, Brinton, L, Yang, H, Garcia-Closas, M, Despierre, E, Lambrechts, S, Vergote, I, Walsh, C, Lester, J, Sieh, W, McGuire, V, Rothstein, JH, Ziogas, A, Lubinski, J, Cybulski, C, Menkiszak, J, Jensen, A, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Berchuck, A, Wu, AH, Pike, MC, Van denBerg, D, Terry, KL, Vitonis, AF, Doherty, JA, Johnatty, SE, Defazio, A, Song, H, Tyrer, J, Sellers, TA, Phelan, CM, Kalli, KR, Cunningham, JM, Fridley, BL, Goode, EL, White, KL, Vierkant, RA, Fogarty, ZC, Charbonneau, B, Block, MS, Pharoah, PDP, Chenevix-Trench, G, Rossing, MA, Cramer, DW, Pearce, CL, Schildkraut, JM, Menon, U, Kjaer, SK, Levine, DA, Gronwald, J, Culver, HA, Whittemore, AS, Karlan, BY, Lambrechts, D, Wentzensen, N, Kupryjanczyk, J, Chang-Claude, J, Bandera, EV, Hogdall, E, Heitz, F, Kaye, SB, Fasching, PA, Campbell, I, Goodman, MT, Pejovic, T, Bean, Y, Lurie, G, Eccles, D, Hein, A, Beckmann, MW, Ekici, AB, Paul, J, Brown, R, Flanagan, JM, Harter, P, Du Bois, A, Schwaab, I, Hogdall, CK, Lundvall, L, Olson, SH, Orlow, I, Paddock, LE, Rudolph, A, Eilber, U, Dansonka-Mieszkowska, A, Rzepecka, IK, Ziolkowska-Seta, I, Brinton, L, Yang, H, Garcia-Closas, M, Despierre, E, Lambrechts, S, Vergote, I, Walsh, C, Lester, J, Sieh, W, McGuire, V, Rothstein, JH, Ziogas, A, Lubinski, J, Cybulski, C, Menkiszak, J, Jensen, A, Gayther, SA, Ramus, SJ, Gentry-Maharaj, A, Berchuck, A, Wu, AH, Pike, MC, Van denBerg, D, Terry, KL, Vitonis, AF, Doherty, JA, Johnatty, SE, Defazio, A, Song, H, Tyrer, J, Sellers, TA, Phelan, CM, Kalli, KR, Cunningham, JM, Fridley, BL, and Goode, EL
Abstract: BACKGROUND: Ovarian cancer is a leading cause of cancer-related death among women. In an effort to understand contributors to disease outcome, we evaluated single-nucleotide polymorphisms (SNP) previously associated with ovarian cancer recurrence or survival, specifically in angiogenesis, inflammation, mitosis, and drug disposition genes. METHODS: Twenty-seven SNPs in VHL, HGF, IL18, PRKACB, ABCB1, CYP2C8, ERCC2, and ERCC1 previously associated with ovarian cancer outcome were genotyped in 10,084 invasive cases from 28 studies from the Ovarian Cancer Association Consortium with over 37,000-observed person-years and 4,478 deaths. Cox proportional hazards models were used to examine the association between candidate SNPs and ovarian cancer recurrence or survival with and without adjustment for key covariates. RESULTS: We observed no association between genotype and ovarian cancer recurrence or survival for any of the SNPs examined. CONCLUSIONS: These results refute prior associations between these SNPs and ovarian cancer outcome and underscore the importance of maximally powered genetic association studies. IMPACT: These variants should not be used in prognostic models. Alternate approaches to uncovering inherited prognostic factors, if they exist, are needed.
Published: 2013

22. Genome-wide association of familial late-onset alzheimer's disease replicates BIN1 and CLU and nominates CUGBP2 in interaction with APOE

Author: Wijsman, EM, Pankratz, ND, Choi, Y, Rothstein, JH, Faber, KM, Cheng, R, Lee, JH, Bird, TD, Bennett, DA, Diaz-Arrastia, R, Goate, AM, Farlow, M, Ghetti, B, Sweet, RA, Foroud, TM, Mayeux, R, Wijsman, EM, Pankratz, ND, Choi, Y, Rothstein, JH, Faber, KM, Cheng, R, Lee, JH, Bird, TD, Bennett, DA, Diaz-Arrastia, R, Goate, AM, Farlow, M, Ghetti, B, Sweet, RA, Foroud, TM, and Mayeux, R
Abstract: Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. The National Institute of Aging-Late Onset Alzheimer's Disease Family Study and the National Cell Repository for Alzheimer's Disease conducted a joint genome-wide association study (GWAS) of multiplex LOAD families (3,839 affected and unaffected individuals from 992 families plus additional unrelated neurologically evaluated normal subjects) using the 610 IlluminaQuad panel. This cohort represents the largest family-based GWAS of LOAD to date, with analyses limited here to the European-American subjects. SNPs near APOE gave highly significant results (e.g., rs2075650, p = 3.2×10-81), but no other genome-wide significant evidence for association was obtained in the full sample. Analyses that stratified on APOE genotypes identified SNPs on chromosome 10p14 in CUGBP2 with genome-wide significant evidence for association within APOE ε4 homozygotes (e.g., rs201119, p = 1.5×10-8). Association in this gene was replicated in an independent sample consisting of three cohorts. There was evidence of association for recently-reported LOAD risk loci, including BIN1 (rs7561528, p = 0.009 with, and p = 0.03 without, APOE adjustment) and CLU (rs11136000, p = 0.023 with, and p = 0.008 without, APOE adjustment), with weaker support for CR1. However, our results provide strong evidence that association with PICALM (rs3851179, p = 0.69 with, and p = 0.039 without, APOE adjustment) and EXOC3L2 is affected by correlation with APOE, and thus may represent spurious association. Our results indicate that genetic structure coupled with ascertainment bias resulting from the strong APOE association affect genome-wide results and interpretation of some recently reported associations. We show that a locus such as APOE, with large effects and strong association with disease, can lead to samples that require appropriate adjustment for this locus to avoid both false positive and false negative evidence of asso
Published: 2011

23. Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer

Author: Phelan, CM, Kuchenbaecker, KB, Tyrer, JP, Kar, SP, Lawrenson, K, Winham, SJ, Dennis, J, Pirie, A, Riggan, MJ, Chornokur, G, Earp, MA, Lyra, PC, Lee, JM, Coetzee, S, Beesley, J, McGuffog, L, Soucy, P, Dicks, E, Lee, A, Barrowdale, D, Lecarpentier, J, Leslie, G, Aalfs, CM, Aben, KKH, Adams, M, Adlard, J, Andrulis, IL, Anton-Culver, H, Antonenkova, N, AOCS Study Group, Aravantinos, G, Arnold, N, Arun, BK, Arver, B, Azzollini, J, Balmaña, J, Banerjee, SN, Barjhoux, L, Barkardottir, RB, Bean, Y, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bermisheva, M, Bernardini, MQ, Birrer, MJ, Bjorge, L, Black, A, Blankstein, K, Blok, MJ, Bodelon, C, Bogdanova, N, Bojesen, A, Bonanni, B, Borg, Å, Bradbury, AR, Brenton, JD, Brewer, C, Brinton, L, Broberg, P, Brooks-Wilson, A, Bruinsma, F, Brunet, J, Buecher, B, Butzow, R, Buys, SS, Caldes, T, Caligo, MA, Campbell, I, Cannioto, R, Carney, ME, Cescon, T, Chan, SB, Chang-Claude, J, Chanock, S, Chen, XQ, Chiew, Y-E, Chiquette, J, Chung, WK, Claes, KBM, Conner, T, Cook, LS, Cook, J, Cramer, DW, Cunningham, JM, D'Aloisio, AA, Daly, MB, Damiola, F, Damirovna, SD, Dansonka-Mieszkowska, A, Dao, F, Davidson, R, DeFazio, A, Delnatte, C, Doheny, KF, Diez, O, Ding, YC, Doherty, JA, Domchek, SM, Dorfling, CM, Dörk, T, Dossus, L, Duran, M, Dürst, M, Dworniczak, B, Eccles, D, Edwards, T, Eeles, R, Eilber, U, Ejlertsen, B, Ekici, AB, Ellis, S, Elvira, M, EMBRACE Study, Eng, KH, Engel, C, Evans, DG, Fasching, PA, Ferguson, S, Ferrer, SF, Flanagan, JM, Fogarty, ZC, Fortner, RT, Fostira, F, Foulkes, WD, Fountzilas, G, Fridley, BL, Friebel, TM, Friedman, E, Frost, D, Ganz, PA, Garber, J, García, MJ, Garcia-Barberan, V, Gehrig, A, GEMO Study Collaborators, Gentry-Maharaj, A, Gerdes, A-M, Giles, GG, Glasspool, R, Glendon, G, Godwin, AK, Goldgar, DE, Goranova, T, Gore, M, Greene, MH, Gronwald, J, Gruber, S, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hansen, TVO, Harrington, PA, Harris, HR, Hauke, J, HEBON Study, Hein, A, Henderson, A, Hildebrandt, MAT, Hillemanns, P, Hodgson, S, Høgdall, CK, Høgdall, E, Hogervorst, FBL, Holland, H, Hooning, MJ, Hosking, K, Huang, R-Y, Hulick, PJ, Hung, J, Hunter, DJ, Huntsman, DG, Huzarski, T, Imyanitov, EN, Isaacs, C, Iversen, ES, Izatt, L, Izquierdo, A, Jakubowska, A, James, P, Janavicius, R, Jernetz, M, Jensen, A, Jensen, UB, John, EM, Johnatty, S, Jones, ME, Kannisto, P, Karlan, BY, Karnezis, A, Kast, K, KConFab Investigators, Kennedy, CJ, Khusnutdinova, E, Kiemeney, LA, Kiiski, JI, Kim, S-W, Kjaer, SK, Köbel, M, Kopperud, RK, Kruse, TA, Kupryjanczyk, J, Kwong, A, Laitman, Y, Lambrechts, D, Larrañaga, N, Larson, MC, Lazaro, C, Le, ND, Le Marchand, L, Lee, JW, Lele, SB, Leminen, A, Leroux, D, Lester, J, Lesueur, F, Levine, DA, Liang, D, Liebrich, C, Lilyquist, J, Lipworth, L, Lissowska, J, Lu, KH, Lubinński, J, Luccarini, C, Lundvall, L, Mai, PL, Mendoza-Fandiño, G, Manoukian, S, Massuger, LFAG, May, T, Mazoyer, S, McAlpine, JN, McGuire, V, McLaughlin, McNeish, I, Meijers-Heijboer, H, Meindl, A, Menon, U, Mensenkamp, AR, Merritt, MA, Milne, RL, Mitchell, G, Modugno, F, Moes-Sosnowska, J, Moffitt, M, Montagna, M, Moysich, KB, Mulligan, AM, Musinsky, J, Nathanson, KL, Nedergaard, L, Ness, RB, Neuhausen, SL, Nevanlinna, H, Niederacher, D, Nussbaum, RL, Odunsi, K, Olah, E, Olopade, OI, Olsson, H, Olswold, C, O'Malley, DM, Ong, K-R, Onland-Moret, NC, OPAL Study Group, Orr, N, Orsulic, S, Osorio, A, Palli, D, Papi, L, Park-Simon, T-W, Paul, J, Pearce, CL, Pedersen, IS, Peeters, PHM, Peissel, B, Peixoto, A, Pejovic, T, Pelttari, LM, Permuth, JB, Peterlongo, P, Pezzani, L, Pfeiler, G, Phillips, K-A, Piedmonte, M, Pike, MC, Piskorz, AM, Poblete, Pocza, T, Poole, EM, Poppe, B, Porteous, ME, Prieur, F, Prokofyeva, D, Pugh, E, Pujana, MA, Pujol, P, Radice, P, Rantala, J, Rappaport-Fuerhauser, C, Rennert, G, Rhiem, K, Rice, P, Richardson, A, Robson, M, Rodriguez, GC, Rodríguez-Antona, C, Romm, J, Rookus, MA, Rossing, MA, Rothstein, JH, Rudolph, A, Runnebaum, IB, Salvesen, HB, Sandler, DP, Schoemaker, MJ, Senter, L, Setiawan, VW, Severi, G, Sharma, P, Shelford, T, Siddiqui, N, Side, LE, Sieh, W, Singer, CF, Sobol, H, Song, H, Southey, MC, Spurdle, AB, Stadler, Z, Steinemann, D, Stoppa-Lyonnet, D, Sucheston-Campbell, LE, Sukiennicki, G, Sutphen, R, Sutter, C, Swerdlow, AJ, Szabo, CI, Szafron, L, Tan, YY, Taylor, JA, Tea, M-K, Teixeira, MR, Teo, S-H, Terry, KL, Thompson, PJ, Thomsen, LCV, Thull, DL, Tihomirova, L, Tinker, AV, Tischkowitz, M, Tognazzo, S, Toland, AE, Tone, A, Trabert, B, Travis, RC, Trichopoulou, A, Tung, N, Tworoger, SS, Van Altena, AM, Van Den Berg, D, Van Der Hout, AH, Van Der Luijt, RB, Van Heetvelde, M, Van Nieuwenhuysen, E, Van Rensburg, EJ, Vanderstichele, A, Varon-Mateeva, R, Vega, A, Edwards, DV, Vergote, I, Vierkant, RA, Vijai, J, Vratimos, A, Walker, L, Walsh, C, Wand, D, Wang-Gohrke, S, Wappenschmidt, B, Webb, PM, Weinberg, CR, Weitzel, JN, Wentzensen, N, Whittemore, AS, Wijnen, JT, Wilkens, LR, Wolk, A, Woo, M, Wu, X, Wu, AH, Yang, H, Yannoukakos, D, Ziogas, A, Zorn, KK, Narod, SA, Easton, DF, Amos, CI, Schildkraut, JM, Ramus, SJ, Ottini, L, Goodman, MT, Park, SK, Kelemen, LE, Risch, HA, Thomassen, M, Offit, K, Simard, J, Schmutzler, RK, Hazelett, D, Monteiro, AN, Couch, FJ, Berchuck, A, Chenevix-Trench, G, Goode, EL, Sellers, TA, Gayther, SA, Antoniou, AC, and Pharoah, PDP
Subjects: ovarian cancer, endocrine system diseases, genome-wide association studies, epidemiology, female genital diseases and pregnancy complications, 3. Good health
Abstract: To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 $\textit{BRCA1}$ and $\textit{BRCA2}$ mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

24. Racial and ethnic differences in epithelial ovarian cancer risk: an analysis from the Ovarian Cancer Association Consortium.

Author: Meagher NS, White KK, Wilkens LR, Bandera EV, Berchuck A, Carney ME, Cramer DW, Cushing-Haugen KL, Jordan S, Kaufmann SH, Le ND, Pike MC, Riggan M, Qin B, Rothstein JH, Titus L, Winham SJ, Anton-Culver H, Doherty JA, Goode EL, Pearce CL, Risch HA, Webb PM, Cook LS, Goodman MT, Harris HR, Le Marchand L, McGuire V, Pharoah PDP, Sarink D, Schildkraut JM, Sieh W, Terry KL, Thompson PJ, Whittemore AS, Wu AH, Peres LC, and Merritt MA
Subjects: Adult, Aged, Female, Humans, Middle Aged, Asian, Case-Control Studies, Contraceptives, Oral adverse effects, Ethnicity, Hispanic or Latino, Logistic Models, Native Hawaiian or Other Pacific Islander, Odds Ratio, Parity, Risk Factors, Smoking ethnology, Smoking epidemiology, Sterilization, Tubal statistics & numerical data, United States epidemiology, White, Carcinoma, Ovarian Epithelial ethnology, Carcinoma, Ovarian Epithelial epidemiology, Ovarian Neoplasms ethnology, Ovarian Neoplasms epidemiology
Abstract: Limited estimates exist on risk factors for epithelial ovarian cancer (EOC) in Asian, Hispanic, and Native Hawaiian/Pacific Islander women. Participants in this study included 1734 Asian (n = 785 case and 949 control participants), 266 Native Hawaiian/Pacific Islander (n = 99 case and 167 control participants), 1149 Hispanic (n = 505 case and 644 control participants), and 24 189 White (n = 9981 case and 14 208 control participants) from 11 studies in the Ovarian Cancer Association Consortium. Logistic regression models estimated odds ratios (ORs) and 95% CIs for risk associations by race and ethnicity. Heterogeneity in EOC risk associations by race and ethnicity (P ≤ .02) was observed for oral contraceptive (OC) use, parity, tubal ligation, and smoking. We observed inverse associations with EOC risk for OC use and parity across all groups; associations were strongest in Native Hawaiian/Pacific Islander and Asian women. The inverse association for tubal ligation with risk was most pronounced for Native Hawaiian/Pacific Islander participants (odds ratio (OR) = 0.25; 95% CI, 0.13-0.48) compared with Asian and White participants (OR = 0.68 [95% CI, 0.51-0.90] and OR = 0.78 [95% CI, 0.73-0.85], respectively). Differences in EOC risk factor associations were observed across racial and ethnic groups, which could be due, in part, to varying prevalence of EOC histotypes. Inclusion of greater diversity in future studies is essential to inform prevention strategies. This article is part of a Special Collection on Gynecological Cancers., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)
Published: 2024
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25. Variants in Vitamin D-related Genes and Prostate Cancer Risk in Black Men.

Author: Layne TM, Rothstein JH, Song X, Andersen SW, Benn EKT, Sieh W, and Klein RJ
Abstract: Background: The relationship between vitamin D and prostate cancer has primarily been characterized among White men. However, Black men have higher prostate cancer incidence and mortality rates, chronically low circulating vitamin D levels, and ancestry-specific genetic variants in vitamin D-related genes. Here, we examine six critical genes in the vitamin D pathway and prostate cancer risk in Black men., Methods: We assessed a total of 69 candidate variants in six genes ( GC, CYP27A1, CYP27B1, CYP24A1, VDR , and RXRA ) including functional variants previously associated with prostate cancer and circulating 25(OHD) in White men. Associations with prostate cancer risk were examined using genome-wide association study data for approximately 10,000 prostate cancer cases and 10,000 controls among Black men and over 85,000 cases and 91,000 controls among White men. A statistical significance threshold of 0.000724 was used to account for the 69 variants tested., Results: None of the variants examined were significantly associated with prostate cancer risk among Black men after multiple comparison adjustment. Four variants tested P<0.05 in Black men, including two in RXRA (rs41400444 OR=1.09, 95% CI: 1.01-1.17, P = 0.024 and rs10881574 OR = 0.93, 0.87-1.00, P = 0.046) and two in VDR (rs2853563 OR = 1.07, 1.01-1.13, P = 0.017 and rs1156882 OR = 1.06, 1.00-1.12, P = 0.045). Two variants in VDR were also positively associated with risk in White men (rs11568820 OR = 1.04, 1.02-1.06, P = 0.00024 and rs4516035 OR = 1.03, 1.01-1.04, P = 0.00055)., Conclusion: We observed suggestive non-significant associations between genetic variants in RXRA and VDR and prostate cancer risk in Black men. Future research exploring the relationship of vitamin D with cancer risk in Black men will need larger sample sizes to identify ancestry-specific variants relevant to risk in this population.
Published: 2024
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26. Mammographic density mediates the protective effect of early-life body size on breast cancer risk.

Author: Vabistsevits M, Davey Smith G, Richardson TG, Richmond RC, Sieh W, Rothstein JH, Habel LA, Alexeeff SE, Lloyd-Lewis B, and Sanderson E
Subjects: Humans, Female, Risk Factors, Child, Body Size, Adult, Polymorphism, Single Nucleotide, Middle Aged, Breast Neoplasms genetics, Breast Neoplasms diagnostic imaging, Breast Density, Adiposity genetics, Mammography, Mendelian Randomization Analysis, Menarche
Abstract: The unexplained protective effect of childhood adiposity on breast cancer risk may be mediated via mammographic density (MD). Here, we investigate a complex relationship between adiposity in childhood and adulthood, puberty onset, MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)), and their effects on breast cancer. We use Mendelian randomization (MR) and multivariable MR to estimate the total and direct effects of adiposity and age at menarche on MD phenotypes. Childhood adiposity has a decreasing effect on DA, while adulthood adiposity increases NDA. Later menarche increases DA/PD, but when accounting for childhood adiposity, this effect is attenuated. Next, we examine the effect of MD on breast cancer risk. DA/PD have a risk-increasing effect on breast cancer across all subtypes. The MD SNPs estimates are heterogeneous, and additional analyses suggest that different mechanisms may be linking MD and breast cancer. Finally, we evaluate the role of MD in the protective effect of childhood adiposity on breast cancer. Mediation MR analysis shows that 56% (95% CIs [32%-79%]) of this effect is mediated via DA. Our finding suggests that higher childhood adiposity decreases mammographic DA, subsequently reducing breast cancer risk. Understanding this mechanism is important for identifying potential intervention targets., (© 2024. The Author(s).)
Published: 2024
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27. Hybrid Magnetic Resonance Positron Emission Tomography Is Associated With Cardiac-Related Outcomes in Cardiac Sarcoidosis.

Author: Trivieri MG, Robson PM, Vergani V, LaRocca G, Romero-Daza AM, Abgral R, Devesa A, Azoulay LD, Karakatsanis NA, Parikh A, Panagiota C, Palmisano A, DePalo L, Chang HL, Rothstein JH, Fayad RA, Miller MA, Fuster V, Narula J, Dweck MR, Morgenthau A, Jacobi A, Padilla M, Kovacic JC, and Fayad ZA
Subjects: Humans, Fluorodeoxyglucose F18, Contrast Media, Radiopharmaceuticals, Predictive Value of Tests, Gadolinium, Positron-Emission Tomography methods, Magnetic Resonance Imaging methods, Magnetic Resonance Spectroscopy, Cardiomyopathies diagnostic imaging, Cardiomyopathies therapy, Cardiomyopathies complications, Myocarditis complications, Sarcoidosis diagnostic imaging, Sarcoidosis therapy, Sarcoidosis complications
Abstract: Background: Imaging with late gadolinium enhancement (LGE) magnetic resonance (MR) and 18 F-fluorodeoxyglucose ( 18 F-FDG) PET allows complementary assessment of myocardial injury and disease activity and has shown promise for improved characterization of active cardiac sarcoidosis (CS) based on the combined positive imaging outcome, MR(+)PET(+)., Objectives: This study aims to evaluate qualitative and quantitative assessments of hybrid MR/PET imaging in CS and to evaluate its association with cardiac-related outcomes., Methods: A total of 148 patients with suspected CS underwent hybrid MR/PET imaging. Patients were classified based on the presence/absence of LGE (MR+/MR-), presence/absence of 18 F-FDG (PET+/PET-), and pattern of 18 F-FDG uptake (focal/diffuse) into the following categories: MR(+)PET(+) FOCAL , MR(+)PET(+) DIFFUSE , MR(+)PET(-), MR(-)PET(+) FOCAL , MR(-)PET(+) DIFFUSE , MR(-)PET(-). Further analysis classified MR positivity based on %LGE exceeding 5.7% as MR(+/-) 5.7% . Quantitative values of standard uptake value, target-to-background ratio, target-to-normal-myocardium ratio (TNMRmax), and T2 were measured. The primary clinical endpoint was met by the occurrence of cardiac arrest, ventricular tachycardia, or secondary prevention implantable cardioverter-defibrillator (ICD) before the end of the study. The secondary endpoint was met by any of the primary endpoint criteria plus heart failure or heart block. MR/PET imaging results were compared between those meeting or not meeting the clinical endpoints., Results: Patients designated MR(+) 5.7% PET(+) FOCAL had increased odds of meeting the primary clinical endpoint compared to those with all other imaging classifications (unadjusted OR: 9.2 [95% CI: 3.0-28.7]; P = 0.0001), which was higher than the odds based on MR or PET alone. TNMRmax achieved an area under the receiver-operating characteristic curve of 0.90 for separating MR(+)PET(+) FOCAL from non-MR(+)PET(+) FOCAL , and 0.77 for separating those reaching the clinical endpoint from those not reaching the clinical endpoint., Conclusions: Hybrid MR/PET image-based classification of CS was statistically associated with clinical outcomes in CS. TNMRmax had modest sensitivity and specificity for quantifying the imaging-based classification MR(+)PET(+) FOCAL and was associated with outcomes. Use of combined MR and PET image-based classification may have use in prognostication and treatment management in CS., Competing Interests: Funding Support and Author Disclosures This work was supported by National Institutes of Health (NIH) grant R01 HL071021 (ZAF), NIH grant KL2 TR001435 (MGT), and AHA grant 20CDA35310099 (MGT). The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024. Published by Elsevier Inc.)
Published: 2024
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28. The mediating role of mammographic density in the protective effect of early-life adiposity on breast cancer risk: a multivariable Mendelian randomization study.

Author: Vabistsevits M, Smith GD, Richardson TG, Richmond RC, Sieh W, Rothstein JH, Habel LA, Alexeeff SE, Lloyd-Lewis B, and Sanderson E
Abstract: Observational studies suggest that mammographic density (MD) may have a role in the unexplained protective effect of childhood adiposity on breast cancer risk. Here, we investigated a complex and interlinked relationship between puberty onset, adiposity, MD, and their effects on breast cancer using Mendelian randomization (MR). We estimated the effects of childhood and adulthood adiposity, and age at menarche on MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)) using MR and multivariable MR (MVMR), allowing us to disentangle their total and direct effects. Next, we examined the effect of MD on breast cancer risk, including risk of molecular subtypes, and accounting for genetic pleiotropy. Finally, we used MVMR to evaluate whether the protective effect of childhood adiposity on breast cancer was mediated by MD. Childhood adiposity had a strong inverse effect on mammographic DA, while adulthood adiposity increased NDA. Later menarche had an effect of increasing DA and PD, but when accounting for childhood adiposity, this effect attenuated to the null. DA and PD had a risk-increasing effect on breast cancer across all subtypes. The MD single-nucleotide polymorphism (SNP) estimates were extremely heterogeneous, and examination of the SNPs suggested different mechanisms may be linking MD and breast cancer. Finally, MR mediation analysis estimated that 56% (95% CIs [32% - 79%]) of the childhood adiposity effect on breast cancer risk was mediated via DA. In this work, we sought to disentangle the relationship between factors affecting MD and breast cancer. We showed that higher childhood adiposity decreases mammographic DA, which subsequently leads to reduced breast cancer risk. Understanding this mechanism is of great importance for identifying potential targets of intervention, since advocating weight gain in childhood would not be recommended., Competing Interests: Competing interests T.G.R. is employed by GSK outside of this work, for unrelated research. All other authors declare no competing interests.
Published: 2023
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29. Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women.

Author: Habel LA, Alexeeff SE, Achacoso N, Arasu VA, Gastounioti A, Gerstley L, Klein RJ, Liang RY, Lipson JA, Mankowski W, Margolies LR, Rothstein JH, Rubin DL, Shen L, Sistig A, Song X, Villaseñor MA, Westley M, Whittemore AS, Yaffe MJ, Wang P, Kontos D, and Sieh W
Subjects: Female, Humans, Breast Density, Cohort Studies, White, Breast diagnostic imaging, Mammography methods, Risk Factors, Case-Control Studies, Breast Neoplasms diagnostic imaging, Breast Neoplasms epidemiology
Abstract: Background: Breast density is strongly associated with breast cancer risk. Fully automated quantitative density assessment methods have recently been developed that could facilitate large-scale studies, although data on associations with long-term breast cancer risk are limited. We examined LIBRA assessments and breast cancer risk and compared results to prior assessments using Cumulus, an established computer-assisted method requiring manual thresholding., Methods: We conducted a cohort study among 21,150 non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were 40-74 years at enrollment, followed for up to 10 years, and had archived processed screening mammograms acquired on Hologic or General Electric full-field digital mammography (FFDM) machines and prior Cumulus density assessments available for analysis. Dense area (DA), non-dense area (NDA), and percent density (PD) were assessed using LIBRA software. Cox regression was used to estimate hazard ratios (HRs) for breast cancer associated with DA, NDA and PD modeled continuously in standard deviation (SD) increments, adjusting for age, mammogram year, body mass index, parity, first-degree family history of breast cancer, and menopausal hormone use. We also examined differences by machine type and breast view., Results: The adjusted HRs for breast cancer associated with each SD increment of DA, NDA and PD were 1.36 (95% confidence interval, 1.18-1.57), 0.85 (0.77-0.93) and 1.44 (1.26-1.66) for LIBRA and 1.44 (1.33-1.55), 0.81 (0.74-0.89) and 1.54 (1.34-1.77) for Cumulus, respectively. LIBRA results were generally similar by machine type and breast view, although associations were strongest for Hologic machines and mediolateral oblique views. Results were also similar during the first 2 years, 2-5 years and 5-10 years after the baseline mammogram., Conclusion: Associations with breast cancer risk were generally similar for LIBRA and Cumulus density measures and were sustained for up to 10 years. These findings support the suitability of fully automated LIBRA assessments on processed FFDM images for large-scale research on breast density and cancer risk., (© 2023. BioMed Central Ltd., part of Springer Nature.)
Published: 2023
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30. Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: an international multicentre analysis.

Author: May T, Bernardini M, Lheureux S, Aben KKH, Bandera EV, Beckmann MW, Benitez J, Berchuck A, Bjørge L, Carney ME, Cramer DW, deFazio A, Dörk T, Eccles DM, Friedlander M, García MJ, Goode EL, Hein A, Høgdall CK, Jensen A, Johnatty S, Kennedy CJ, Kiemeney LA, Kjær SK, Kupryjańczyk J, Matsuo K, McGuire V, Modugno F, Paddock LE, Pejovic T, Phelan CM, Riggan MJ, Rodriguez-Antona C, Rothstein JH, Sieh W, Song H, Terry KL, van Altena AM, Vanderstichele A, Vergote I, Thomsen LCV, Webb PM, Wentzensen N, Wilkens LR, Ziogas A, Jiang H, and Tone A
Subjects: Humans, Female, Middle Aged, Retrospective Studies, Neoplasm Staging, Kaplan-Meier Estimate, Ovarian Neoplasms surgery, Ovarian Neoplasms drug therapy, Cystadenocarcinoma, Serous surgery, Cystadenocarcinoma, Serous drug therapy
Abstract: Background: Women with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC., Methods: We performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves., Results: Of the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage., Conclusion: This multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice., Competing Interests: Competing interests: Stephanie Lheureux reports study grants from AstraZeneca, GSK and Roche, consulting fees from AstraZeneca, GSK, Roche, Novartis, Merck, Eisai Co. and Shattuck Labs, and speaker’s honororia from AstraZeneca, GSK, Eisai Co. and Merck. Line Bjørge is president of the Nordic Society of Gynaecological Oncology executive board. Anna deFazio sits on the Australia New Zealand Gynaecological Oncology Group (ANZGOG) Research Advisory Committee, the Clinical and Scientific Expert Advisory Panel of Ovarian Cancer Australia and the Scientific Advisory Committee of the Australian Gynaecological Cancer Foundation. She is chair of the Translational ANZGOG (TRANZGOG) Steering Committee, chair of the International Consortium for Low-Grade Serous Ovarian Cancer Steering Committee and chair of the ANZGOG Translational subcommittee. Michael Friedlander reports consulting fees from AstraZeneca, GSK, MSD, Eli Lilly and Company, Takeda and Novartis; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astra-Zeneca, GSK and ACT Genomics; and support for attending meetings and/or travel from AstraZeneca. He sits on the Australasian Gastrointestinal Trial Group independent data monitoring committee and is a Steering Committee member for Abbvie’s VELIA trial. Catherine Kennedy is a member of the International Society for Biological and Environmental Repositories Science Policy Committee and of the Australasian Biospecimen Network (ABNA) Management Committee. She is past president and treasurer of ABNA. Liv Cecilie Vestrheim Thomsen reports grants from AstraZeneca, and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Bayer and AstraZeneca. She sits on an advisory board for Eisai Co. Ignace Vergote reports consulting fees from Deciphera Pharmaceuticals, Jazz Pharmaceuticals and Oncoinvent AS, and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Agenus, AkseBio, AstraZeneca, Bristol Myers Squibb, Deciphera Pharmaceuticals, Eisai Co., F. Hoffmann-La Roche, Genmab, GSK, ImmunoGen, Jazz Pharmaceuticals, Karyopharm Therapeutics, MSD, Novocure, Novartis, Oncoinvent AS, Seagen and Sotio Biotech. He sits on a data safety monitoring board or advisory board for Agenus, AstraZeneca, Bristol Myers Squibb, Deciphera Pharmaceuticals, Eisai Co., F. Hoffmann-La Roche, Genmab, GSK, ImmunoGen, MSD, Novocure, Novartis, Seagen and Sotio Biotech. Penelope Webb reports a speaker’s honorarium from AstraZeneca. No other competing interests were declared., (© 2023 CMA Impact Inc. or its licensors.)
Published: 2023
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31. Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis.

Author: Fu Z, Brooks MM, Irvin S, Jordan S, Aben KKH, Anton-Culver H, Bandera EV, Beckmann MW, Berchuck A, Brooks-Wilson A, Chang-Claude J, Cook LS, Cramer DW, Cushing-Haugen KL, Doherty JA, Ekici AB, Fasching PA, Fortner RT, Gayther SA, Gentry-Maharaj A, Giles GG, Goode EL, Goodman MT, Harris HR, Hein A, Kaaks R, Kiemeney LA, Köbel M, Kotsopoulos J, Le ND, Lee AW, Matsuo K, McGuire V, McLaughlin JR, Menon U, Milne RL, Moysich KB, Pearce CL, Pike MC, Qin B, Ramus SJ, Riggan MJ, Rothstein JH, Schildkraut JM, Sieh W, Sutphen R, Terry KL, Thompson PJ, Titus L, van Altena AM, White E, Whittemore AS, Wu AH, Zheng W, Ziogas A, Taylor SE, Tang L, Songer T, Wentzensen N, Webb PM, Risch HA, and Modugno F
Subjects: Pregnancy, Humans, Female, Carcinoma, Ovarian Epithelial epidemiology, Risk Factors, Parity, Contraceptives, Oral adverse effects, Case-Control Studies, Ovarian Neoplasms epidemiology, Ovarian Neoplasms etiology, Ovarian Neoplasms pathology
Abstract: Background: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC., Methods: LOY was calculated using 12 algorithms. Odds ratios (ORs) and 95% confidence intervals (CIs) estimated the association between LOY or LOY components and EOC among 26 204 control participants and 21 267 case patients from 25 studies. To assess whether LOY components act through ovulation suppression alone, we compared beta coefficients obtained from regression models with expected estimates assuming 1 year of ovulation suppression has the same effect regardless of source., Results: LOY was associated with increased EOC risk (OR per year increase = 1.014, 95% CI = 1.009 to 1.020 to OR per year increase = 1.044, 95% CI = 1.041 to 1.048). Individual LOY components, except age at menarche, also associated with EOC. The estimated model coefficient for oral contraceptive use and pregnancies were 4.45 times and 12- to 15-fold greater than expected, respectively. LOY was associated with high-grade serous, low-grade serous, endometrioid, and clear cell histotypes (ORs per year increase = 1.054, 1.040, 1.065, and 1.098, respectively) but not mucinous tumors. Estimated coefficients of LOY components were close to expected estimates for high-grade serous but larger than expected for low-grade serous, endometrioid, and clear cell histotypes., Conclusions: LOY is positively associated with nonmucinous EOC. Differences between estimated and expected model coefficients for LOY components suggest factors beyond ovulation underlie the associations between LOY components and EOC in general and for non-HGSOC., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2023
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32. p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study.

Author: Köbel M, Kang EY, Weir A, Rambau PF, Lee CH, Nelson GS, Ghatage P, Meagher NS, Riggan MJ, Alsop J, Anglesio MS, Beckmann MW, Bisinotto C, Boisen M, Boros J, Brand AH, Brooks-Wilson A, Carney ME, Coulson P, Courtney-Brooks M, Cushing-Haugen KL, Cybulski C, Deen S, El-Bahrawy MA, Elishaev E, Erber R, Fereday S, Fischer A, Gayther SA, Barquin-Garcia A, Gentry-Maharaj A, Gilks CB, Gronwald H, Grube M, Harnett PR, Harris HR, Hartkopf AD, Hartmann A, Hein A, Hendley J, Hernandez BY, Huang Y, Jakubowska A, Jimenez-Linan M, Jones ME, Kennedy CJ, Kluz T, Koziak JM, Lesnock J, Lester J, Lubiński J, Longacre TA, Lycke M, Mateoiu C, McCauley BM, McGuire V, Ney B, Olawaiye A, Orsulic S, Osorio A, Paz-Ares L, Ramón Y Cajal T, Rothstein JH, Ruebner M, Schoemaker MJ, Shah M, Sharma R, Sherman ME, Shvetsov YB, Singh N, Steed H, Storr SJ, Talhouk A, Traficante N, Wang C, Whittemore AS, Widschwendter M, Wilkens LR, Winham SJ, Benitez J, Berchuck A, Bowtell DD, Candido Dos Reis FJ, Campbell I, Cook LS, DeFazio A, Doherty JA, Fasching PA, Fortner RT, García MJ, Goodman MT, Goode EL, Gronwald J, Huntsman DG, Karlan BY, Kelemen LE, Kommoss S, Le ND, Martin SG, Menon U, Modugno F, Pharoah PD, Schildkraut JM, Sieh W, Staebler A, Sundfeldt K, Swerdlow AJ, Ramus SJ, and Brenton JD
Subjects: Humans, Female, Tumor Suppressor Protein p53 genetics, Tumor Suppressor Protein p53 metabolism, Carcinoma, Ovarian Epithelial, Ovarian Neoplasms pathology, Carcinoma, Endometrioid metabolism
Abstract: Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36-3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11-2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC., (© 2023 The Authors. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.)
Published: 2023
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33. MiXcan: a framework for cell-type-aware transcriptome-wide association studies with an application to breast cancer.

Author: Song X, Ji J, Rothstein JH, Alexeeff SE, Sakoda LC, Sistig A, Achacoso N, Jorgenson E, Whittemore AS, Klein RJ, Habel LA, Wang P, and Sieh W
Subjects: Female, Humans, Gene Expression Profiling, Breast metabolism, Genome-Wide Association Study, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Transcriptome, Breast Neoplasms genetics
Abstract: Human bulk tissue samples comprise multiple cell types with diverse roles in disease etiology. Conventional transcriptome-wide association study approaches predict genetically regulated gene expression at the tissue level, without considering cell-type heterogeneity, and test associations of predicted tissue-level expression with disease. Here we develop MiXcan, a cell-type-aware transcriptome-wide association study approach that predicts cell-type-level expression, identifies disease-associated genes via combination of cell-type-level association signals for multiple cell types, and provides insight into the disease-critical cell type. As a proof of concept, we conducted cell-type-aware analyses of breast cancer in 58,648 women and identified 12 transcriptome-wide significant genes using MiXcan compared with only eight genes using conventional approaches. Importantly, MiXcan identified genes with distinct associations in mammary epithelial versus stromal cells, including three new breast cancer susceptibility genes. These findings demonstrate that cell-type-aware transcriptome-wide analyses can reveal new insights into the genetic and cellular etiology of breast cancer and other diseases., (© 2023. The Author(s).)
Published: 2023
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34. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci.

Author: Chen H, Fan S, Stone J, Thompson DJ, Douglas J, Li S, Scott C, Bolla MK, Wang Q, Dennis J, Michailidou K, Li C, Peters U, Hopper JL, Southey MC, Nguyen-Dumont T, Nguyen TL, Fasching PA, Behrens A, Cadby G, Murphy RA, Aronson K, Howell A, Astley S, Couch F, Olson J, Milne RL, Giles GG, Haiman CA, Maskarinec G, Winham S, John EM, Kurian A, Eliassen H, Andrulis I, Evans DG, Newman WG, Hall P, Czene K, Swerdlow A, Jones M, Pollan M, Fernandez-Navarro P, McConnell DS, Kristensen VN, Rothstein JH, Wang P, Habel LA, Sieh W, Dunning AM, Pharoah PDP, Easton DF, Gierach GL, Tamimi RM, Vachon CM, and Lindström S
Subjects: Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide, Transcriptome, Breast Density genetics, Breast Neoplasms diagnostic imaging, Breast Neoplasms genetics
Abstract: Background: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants., Methods: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia., Results: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes., Conclusions: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer., (© 2022. The Author(s).)
Published: 2022
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35. Proteogenomic and metabolomic characterization of human glioblastoma.

Author: Wang LB, Karpova A, Gritsenko MA, Kyle JE, Cao S, Li Y, Rykunov D, Colaprico A, Rothstein JH, Hong R, Stathias V, Cornwell M, Petralia F, Wu Y, Reva B, Krug K, Pugliese P, Kawaler E, Olsen LK, Liang WW, Song X, Dou Y, Wendl MC, Caravan W, Liu W, Cui Zhou D, Ji J, Tsai CF, Petyuk VA, Moon J, Ma W, Chu RK, Weitz KK, Moore RJ, Monroe ME, Zhao R, Yang X, Yoo S, Krek A, Demopoulos A, Zhu H, Wyczalkowski MA, McMichael JF, Henderson BL, Lindgren CM, Boekweg H, Lu S, Baral J, Yao L, Stratton KG, Bramer LM, Zink E, Couvillion SP, Bloodsworth KJ, Satpathy S, Sieh W, Boca SM, Schürer S, Chen F, Wiznerowicz M, Ketchum KA, Boja ES, Kinsinger CR, Robles AI, Hiltke T, Thiagarajan M, Nesvizhskii AI, Zhang B, Mani DR, Ceccarelli M, Chen XS, Cottingham SL, Li QK, Kim AH, Fenyö D, Ruggles KV, Rodriguez H, Mesri M, Payne SH, Resnick AC, Wang P, Smith RD, Iavarone A, Chheda MG, Barnholtz-Sloan JS, Rodland KD, Liu T, and Ding L
Subjects: Brain Neoplasms pathology, Computational Biology methods, Glioblastoma pathology, Humans, Metabolomics methods, Mutation genetics, Phospholipase C gamma genetics, Phospholipase C gamma metabolism, Phosphorylation physiology, Protein Tyrosine Phosphatase, Non-Receptor Type 11 genetics, Proteomics methods, Brain Neoplasms metabolism, Glioblastoma genetics, Glioblastoma metabolism, Protein Tyrosine Phosphatase, Non-Receptor Type 11 metabolism, Proteogenomics methods
Abstract: Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment., Competing Interests: Declaration of interests S.Y. is employed by Sema4. A.H.K. consults for Monteris Medical. P.W. is a statistical consultant for Sema4. M.G.C. receives research support from Orbus Therapeutics and NeoimmuneTech Inc, and royalties from UpToDate., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2021
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36. Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies.

Author: Lee AW, Rosenzweig S, Wiensch A, Ramus SJ, Menon U, Gentry-Maharaj A, Ziogas A, Anton-Culver H, Whittemore AS, Sieh W, Rothstein JH, McGuire V, Wentzensen N, Bandera EV, Qin B, Terry KL, Cramer DW, Titus L, Schildkraut JM, Berchuck A, Goode EL, Kjaer SK, Jensen A, Jordan SJ, Ness RB, Modugno F, Moysich K, Thompson PJ, Goodman MT, Carney ME, Chang-Claude J, Rossing MA, Harris HR, Doherty JA, Risch HA, Khoja L, Alimujiang A, Phung MT, Brieger K, Mukherjee B, Pharoah PDP, Wu AH, Pike MC, Webb PM, and Pearce CL
Subjects: Case-Control Studies, Female, Humans, Parity, Pregnancy, Risk, United Kingdom epidemiology, United States epidemiology, Abortion, Induced statistics & numerical data, Abortion, Spontaneous epidemiology, Carcinoma, Ovarian Epithelial epidemiology, Ovarian Neoplasms epidemiology
Abstract: Background: Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated., Methods: A pooled analysis of 10 470 invasive epithelial ovarian cancer cases and 16 942 controls was conducted. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between incomplete pregnancies and invasive epithelial ovarian cancer were estimated using logistic regression. All models were conditioned on OCAC study, race and ethnicity, age, and education level and adjusted for number of complete pregnancies, oral contraceptive use, and history of breastfeeding. The same approach was used for histotype-specific analyses., Results: Ever having an incomplete pregnancy was associated with a 16% reduction in ovarian cancer risk (OR = 0.84, 95% CI = 0.79 to 0.89). There was a trend of decreasing risk with increasing number of incomplete pregnancies (2-sided Ptrend < .001). An inverse association was observed for all major histotypes; it was strongest for clear cell ovarian cancer., Conclusions: Incomplete pregnancies are associated with a reduced risk of invasive epithelial ovarian cancer. Pregnancy, including incomplete pregnancy, was associated with a greater reduction in risk of clear cell ovarian cancer, but the result was broadly consistent across histotypes. Future work should focus on understanding the mechanisms underlying this reduced risk., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2021
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37. Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers.

Author: Glubb DM, Thompson DJ, Aben KKH, Alsulimani A, Amant F, Annibali D, Attia J, Barricarte A, Beckmann MW, Berchuck A, Bermisheva M, Bernardini MQ, Bischof K, Bjorge L, Bodelon C, Brand AH, Brenton JD, Brinton LA, Bruinsma F, Buchanan DD, Burghaus S, Butzow R, Cai H, Carney ME, Chanock SJ, Chen C, Chen XQ, Chen Z, Cook LS, Cunningham JM, De Vivo I, deFazio A, Doherty JA, Dörk T, du Bois A, Dunning AM, Dürst M, Edwards T, Edwards RP, Ekici AB, Ewing A, Fasching PA, Ferguson S, Flanagan JM, Fostira F, Fountzilas G, Friedenreich CM, Gao B, Gaudet MM, Gawełko J, Gentry-Maharaj A, Giles GG, Glasspool R, Goodman MT, Gronwald J, Harris HR, Harter P, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Høgdall E, Høgdall CK, Holliday EG, Huntsman DG, Huzarski T, Jakubowska A, Jensen A, Jones ME, Karlan BY, Karnezis A, Kelley JL, Khusnutdinova E, Killeen JL, Kjaer SK, Klapdor R, Köbel M, Konopka B, Konstantopoulou I, Kopperud RK, Koti M, Kraft P, Kupryjanczyk J, Lambrechts D, Larson MC, Le Marchand L, Lele S, Lester J, Li AJ, Liang D, Liebrich C, Lipworth L, Lissowska J, Lu L, Lu KH, Macciotta A, Mattiello A, May T, McAlpine JN, McGuire V, McNeish IA, Menon U, Modugno F, Moysich KB, Nevanlinna H, Odunsi K, Olsson H, Orsulic S, Osorio A, Palli D, Park-Simon TW, Pearce CL, Pejovic T, Permuth JB, Podgorska A, Ramus SJ, Rebbeck TR, Riggan MJ, Risch HA, Rothstein JH, Runnebaum IB, Scott RJ, Sellers TA, Senz J, Setiawan VW, Siddiqui N, Sieh W, Spiewankiewicz B, Sutphen R, Swerdlow AJ, Szafron LM, Teo SH, Thompson PJ, Thomsen LCV, Titus L, Tone A, Tumino R, Turman C, Vanderstichele A, Edwards DV, Vergote I, Vierkant RA, Wang Z, Wang-Gohrke S, Webb PM, White E, Whittemore AS, Winham SJ, Wu X, Wu AH, Yannoukakos D, Spurdle AB, and O'Mara TA
Subjects: Carcinoma, Ovarian Epithelial genetics, Female, Genome-Wide Association Study, Humans, Quantitative Trait Loci genetics, Risk Factors, Endometrial Neoplasms genetics, Ovarian Neoplasms genetics
Abstract: Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers., Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data., Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers ( r G = 0.43, P = 2.66 × 10 -5 ). We found seven loci associated with risk for both cancers ( P Bonferroni < 2.4 × 10 -9 ). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified ( P < 5 × 10 -7 ). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation., Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis., Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings., (©2020 American Association for Cancer Research.)
Published: 2021
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38. Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk.

Author: Sieh W, Rothstein JH, Klein RJ, Alexeeff SE, Sakoda LC, Jorgenson E, McBride RB, Graff RE, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Rubin DL, Yaffe MJ, Easton DF, Schaefer C, Risch N, Whittemore AS, and Habel LA
Subjects: Adult, Aged, Aged, 80 and over, Female, Genome-Wide Association Study, Humans, Mammography, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, Breast Density, Breast Neoplasms diagnostic imaging, Breast Neoplasms genetics, Genetic Predisposition to Disease
Abstract: Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10 -8 , tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.
Published: 2020
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39. Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium.

Author: Martins FC, Couturier DL, Paterson A, Karnezis AN, Chow C, Nazeran TM, Odunsi A, Gentry-Maharaj A, Vrvilo A, Hein A, Talhouk A, Osorio A, Hartkopf AD, Brooks-Wilson A, DeFazio A, Fischer A, Hartmann A, Hernandez BY, McCauley BM, Karpinskyj C, de Sousa CB, Høgdall C, Tiezzi DG, Herpel E, Taran FA, Modugno F, Keeney G, Nelson G, Steed H, Song H, Luk H, Benitez J, Alsop J, Koziak JM, Lester J, Rothstein JH, de Andrade JM, Lundvall L, Paz-Ares L, Robles-Díaz L, Wilkens LR, Garcia MJ, Intermaggio MP, Alcaraz ML, Brett MA, Beckmann MW, Jimenez-Linan M, Anglesio M, Carney ME, Schneider M, Traficante N, Pejovic N, Singh N, Le N, Sinn P, Ghatage P, Erber R, Edwards R, Vierkant R, Ness RB, Leung S, Orsulic S, Brucker SY, Kaufmann SH, Fereday S, Gayther S, Winham SJ, Kommoss S, Pejovic T, Longacre TA, McGuire V, Rhenius V, Sieh W, Shvetsov YB, Whittemore AS, Staebler A, Karlan BY, Rodriguez-Antona C, Bowtell DD, Goode EL, Høgdall E, Candido Dos Reis FJ, Gronwald J, Chang-Claude J, Moysich KB, Kelemen LE, Cook LS, Goodman MT, Fasching PA, Crawford R, Deen S, Menon U, Huntsman DG, Köbel M, Ramus SJ, Pharoah PDP, and Brenton JD
Subjects: Adenocarcinoma, Clear Cell enzymology, Adenocarcinoma, Clear Cell mortality, Adenocarcinoma, Clear Cell pathology, Age Factors, Biomarkers, Tumor biosynthesis, Biomarkers, Tumor genetics, Carcinoma, Ovarian Epithelial enzymology, Carcinoma, Ovarian Epithelial genetics, Carcinoma, Ovarian Epithelial mortality, Carcinoma, Ovarian Epithelial pathology, Cohort Studies, Down-Regulation, Female, Gene Knockout Techniques, Humans, Middle Aged, Neoplasm Staging, Ovarian Neoplasms enzymology, Ovarian Neoplasms genetics, Ovarian Neoplasms mortality, Ovarian Neoplasms pathology, PTEN Phosphohydrolase deficiency, PTEN Phosphohydrolase genetics, Prospective Studies, Receptors, Androgen biosynthesis, Receptors, Estrogen biosynthesis, Receptors, Progesterone biosynthesis, Tissue Array Analysis, Tumor Suppressor Proteins biosynthesis, Tumor Suppressor Proteins deficiency, PTEN Phosphohydrolase biosynthesis
Abstract: Background: PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study., Methods: Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran-Mantel-Haenszel tests., Results: Downregulation of cytoplasmic PTEN expression was most frequent in ENOC (most frequently in younger patients; p value = 0.0001) and CCOC and was associated with longer overall survival in HGSOC (hazard ratio: 0.78, 95% CI: 0.65-0.94, p value = 0.022). PTEN expression was associated with ER, PR and AR expression (p values: 0.0008, 0.062 and 0.0002, respectively) in HGSOC and with lower CD8 counts in CCOC (p value < 0.0001). Heterogeneous expression of PTEN was more prevalent in advanced HGSOC (p value = 0.019) and associated with higher CD8 counts (p value = 0.0016)., Conclusions: PTEN loss is a frequent driver in ovarian carcinoma associating distinctly with expression of hormonal receptors and CD8+ TIL counts in HGSOC and CCOC histotypes.
Published: 2020
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40. Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women.

Author: McBride RB, Fei K, Rothstein JH, Alexeeff SE, Song X, Sakoda LC, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Yaffe MJ, Rubin DL, Whittemore AS, Habel LA, and Sieh W
Subjects: Adult, Aged, Aged, 80 and over, Alcohol Drinking adverse effects, Breast diagnostic imaging, Breast physiopathology, Breast Neoplasms diagnosis, Breast Neoplasms physiopathology, Breast Neoplasms prevention & control, Cohort Studies, Female, Humans, Middle Aged, Risk Assessment statistics & numerical data, Risk Factors, Tobacco Smoking adverse effects, Alcohol Drinking epidemiology, Breast Density, Breast Neoplasms epidemiology, Mammography statistics & numerical data, Tobacco Smoking epidemiology
Abstract: Background: Percent density (PD) is a strong risk factor for breast cancer that is potentially modifiable by lifestyle factors. PD is a composite of the dense (DA) and nondense (NDA) areas of a mammogram, representing predominantly fibroglandular or fatty tissues, respectively. Alcohol and tobacco use have been associated with increased breast cancer risk. However, their effects on mammographic density (MD) phenotypes are poorly understood., Methods: We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis., Results: Alcohol use was positively associated with PD ( P trend = 0.01), unassociated with DA ( P trend = 0.23), and inversely associated with NDA ( P trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD ( P trend = 0.0008), unassociated with DA ( P trend = 0.93), and positively associated with NDA ( P trend <0.0001). These trends were stronger in normal and overweight women than in obese women., Conclusions: These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA., Impact: PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health., (©2020 American Association for Cancer Research.)
Published: 2020
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41. Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

Author: Schaffter T, Buist DSM, Lee CI, Nikulin Y, Ribli D, Guan Y, Lotter W, Jie Z, Du H, Wang S, Feng J, Feng M, Kim HE, Albiol F, Albiol A, Morrell S, Wojna Z, Ahsen ME, Asif U, Jimeno Yepes A, Yohanandan S, Rabinovici-Cohen S, Yi D, Hoff B, Yu T, Chaibub Neto E, Rubin DL, Lindholm P, Margolies LR, McBride RB, Rothstein JH, Sieh W, Ben-Ari R, Harrer S, Trister A, Friend S, Norman T, Sahiner B, Strand F, Guinney J, Stolovitzky G, Mackey L, Cahoon J, Shen L, Sohn JH, Trivedi H, Shen Y, Buturovic L, Pereira JC, Cardoso JS, Castro E, Kalleberg KT, Pelka O, Nedjar I, Geras KJ, Nensa F, Goan E, Koitka S, Caballero L, Cox DD, Krishnaswamy P, Pandey G, Friedrich CM, Perrin D, Fookes C, Shi B, Cardoso Negrie G, Kawczynski M, Cho K, Khoo CS, Lo JY, Sorensen AG, and Jung H
Subjects: Adult, Aged, Algorithms, Artificial Intelligence, Early Detection of Cancer, Female, Humans, Middle Aged, Radiology, Sensitivity and Specificity, Sweden, United States, Breast Neoplasms diagnostic imaging, Deep Learning, Image Interpretation, Computer-Assisted methods, Mammography methods, Radiologists
Abstract: Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives., Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms., Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016., Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated., Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity., Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation.
Published: 2020
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42. Deep Learning to Improve Breast Cancer Detection on Screening Mammography.

Author: Shen L, Margolies LR, Rothstein JH, Fluder E, McBride R, and Sieh W
Subjects: Algorithms, Breast Neoplasms diagnosis, Databases, Factual, Diagnosis, Computer-Assisted, Early Detection of Cancer, Female, Humans, Breast Neoplasms diagnostic imaging, Deep Learning, Mammography
Abstract: The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep learning algorithm that can accurately detect breast cancer on screening mammograms using an "end-to-end" training approach that efficiently leverages training datasets with either complete clinical annotation or only the cancer status (label) of the whole image. In this approach, lesion annotations are required only in the initial training stage, and subsequent stages require only image-level labels, eliminating the reliance on rarely available lesion annotations. Our all convolutional network method for classifying screening mammograms attained excellent performance in comparison with previous methods. On an independent test set of digitized film mammograms from the Digital Database for Screening Mammography (CBIS-DDSM), the best single model achieved a per-image AUC of 0.88, and four-model averaging improved the AUC to 0.91 (sensitivity: 86.1%, specificity: 80.1%). On an independent test set of full-field digital mammography (FFDM) images from the INbreast database, the best single model achieved a per-image AUC of 0.95, and four-model averaging improved the AUC to 0.98 (sensitivity: 86.7%, specificity: 96.1%). We also demonstrate that a whole image classifier trained using our end-to-end approach on the CBIS-DDSM digitized film mammograms can be transferred to INbreast FFDM images using only a subset of the INbreast data for fine-tuning and without further reliance on the availability of lesion annotations. These findings show that automatic deep learning methods can be readily trained to attain high accuracy on heterogeneous mammography platforms, and hold tremendous promise for improving clinical tools to reduce false positive and false negative screening mammography results. Code and model available at: https://github.com/lishen/end2end-all-conv .
Published: 2019
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43. Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography.

Author: Alexeeff SE, Odo NU, McBride R, McGuire V, Achacoso N, Rothstein JH, Lipson JA, Liang RY, Acton L, Yaffe MJ, Whittemore AS, Rubin DL, Sieh W, and Habel LA
Subjects: Adult, Aged, Breast Neoplasms diagnostic imaging, Female, Humans, Menarche physiology, Menopause physiology, Middle Aged, Parity, White People, Breast Density physiology, Breast Neoplasms epidemiology, Mammography methods, Reproductive History
Abstract: Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40-74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc., Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc., San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Published: 2019
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44. Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women.

Author: Grant DJ, Manichaikul A, Alberg AJ, Bandera EV, Barnholtz-Sloan J, Bondy M, Cote ML, Funkhouser E, Moorman PG, Peres LC, Peters ES, Schwartz AG, Terry PD, Wang XQ, Keku TO, Hoyo C, Berchuck A, Sandler DP, Taylor JA, O'Brien KM, Velez Edwards DR, Edwards TL, Beeghly-Fadiel A, Wentzensen N, Pearce CL, Wu AH, Whittemore AS, McGuire V, Sieh W, Rothstein JH, Modugno F, Ness R, Moysich K, Rossing MA, Doherty JA, Sellers TA, Permuth-Way JB, Monteiro AN, Levine DA, Setiawan VW, Haiman CA, LeMarchand L, Wilkens LR, Karlan BY, Menon U, Ramus S, Gayther S, Gentry-Maharaj A, Terry KL, Cramer DW, Goode EL, Larson MC, Kaufmann SH, Cannioto R, Odunsi K, Etter JL, Huang RY, Bernardini MQ, Tone AA, May T, Goodman MT, Thompson PJ, Carney ME, Tworoger SS, Poole EM, Lambrechts D, Vergote I, Vanderstichele A, Van Nieuwenhuysen E, Anton-Culver H, Ziogas A, Brenton JD, Bjorge L, Salvensen HB, Kiemeney LA, Massuger LFAG, Pejovic T, Bruegl A, Moffitt M, Cook L, Le ND, Brooks-Wilson A, Kelemen LE, Pharoah PDP, Song H, Campbell I, Eccles D, DeFazio A, Kennedy CJ, and Schildkraut JM
Subjects: Bayes Theorem, Carcinoma, Ovarian Epithelial metabolism, Carcinoma, Ovarian Epithelial pathology, ErbB Receptors genetics, Female, Genetic Association Studies, Humans, Logistic Models, Middle Aged, Neoplasm Grading, Ovarian Neoplasms metabolism, Ovarian Neoplasms pathology, Polymorphism, Single Nucleotide, Vitamin D biosynthesis, Black or African American genetics, Carcinoma, Ovarian Epithelial genetics, Glucuronosyltransferase genetics, Ovarian Neoplasms genetics, Receptors, Calcitriol genetics
Abstract: An association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom-designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high-grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 1.2 × 10 -6 , BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6-3.4, P = 1.6 × 10 -5 , BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 2.3 × 10 -5 , BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC., (© 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)
Published: 2019
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45. rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology.

Author: Kelemen LE, Earp M, Fridley BL, Chenevix-Trench G, Fasching PA, Beckmann MW, Ekici AB, Hein A, Lambrechts D, Lambrechts S, Van Nieuwenhuysen E, Vergote I, Rossing MA, Doherty JA, Chang-Claude J, Behrens S, Moysich KB, Cannioto R, Lele S, Odunsi K, Goodman MT, Shvetsov YB, Thompson PJ, Wilkens LR, Dörk T, Antonenkova N, Bogdanova N, Hillemanns P, Runnebaum IB, du Bois A, Harter P, Heitz F, Schwaab I, Butzow R, Pelttari LM, Nevanlinna H, Modugno F, Edwards RP, Kelley JL, Ness RB, Karlan BY, Lester J, Orsulic S, Walsh C, Kjaer SK, Jensen A, Cunningham JM, Vierkant RA, Giles GG, Bruinsma F, Southey MC, Hildebrandt MAT, Liang D, Lu K, Wu X, Sellers TA, Levine DA, Schildkraut JM, Iversen ES, Terry KL, Cramer DW, Tworoger SS, Poole EM, Bandera EV, Olson SH, Orlow I, Vestrheim Thomsen LC, Bjorge L, Krakstad C, Tangen IL, Kiemeney LA, Aben KKH, Massuger LFAG, van Altena AM, Pejovic T, Bean Y, Kellar M, Cook LS, Le ND, Brooks-Wilson A, Gronwald J, Cybulski C, Jakubowska A, Lubiński J, Wentzensen N, Brinton LA, Lissowska J, Hogdall E, Engelholm SA, Hogdall C, Lundvall L, Nedergaard L, Pharoah PDP, Dicks E, Song H, Tyrer JP, McNeish I, Siddiqui N, Carty K, Glasspool R, Paul J, Campbell IG, Eccles D, Whittemore AS, McGuire V, Rothstein JH, Sieh W, Narod SA, Phelan CM, McLaughlin JR, Risch HA, Anton-Culver H, Ziogas A, Menon U, Gayther SA, Gentry-Maharaj A, Ramus SJ, Wu AH, Pearce CL, Lee AW, Pike MC, Kupryjanczyk J, Podgorska A, Plisiecka-Halasa J, Sawicki W, Goode EL, and Berchuck A
Subjects: Adenocarcinoma, Mucinous metabolism, Adenocarcinoma, Mucinous pathology, Case-Control Studies, Female, Genetic Association Studies, Humans, Hydro-Lyases, Logistic Models, Middle Aged, Odds Ratio, Ovarian Neoplasms metabolism, Ovarian Neoplasms pathology, Proteins metabolism, Quantitative Trait Loci, RNA, Antisense metabolism, Risk, Signal Transduction, Thymidylate Synthase metabolism, Adenocarcinoma, Mucinous genetics, Gene Expression Regulation, Neoplastic, Ovarian Neoplasms genetics, Polymorphism, Single Nucleotide, Proteins genetics, RNA, Antisense genetics, Thymidylate Synthase genetics
Abstract: Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed ( p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa ( r = 0.51, p = 1.7 × 10 -28 ), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.
Published: 2018
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46. Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility.

Author: Earp M, Tyrer JP, Winham SJ, Lin HY, Chornokur G, Dennis J, Aben KKH, Anton-Culver H, Antonenkova N, Bandera EV, Bean YT, Beckmann MW, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Bunker CH, Butzow R, Campbell IG, Carty K, Chang-Claude J, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, Despierre E, Doherty JA, Dörk T, du Bois A, Dürst M, Easton DF, Eccles DM, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gentry-Maharaj A, Giles GG, Glasspool R, Goodman MT, Gronwald J, Harter P, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall CK, Høgdall E, Hosono S, Iversen ES, Jakubowska A, Jensen A, Ji BT, Jung AY, Karlan BY, Kellar M, Kiemeney LA, Kiong Lim B, Kjaer SK, Krakstad C, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lele S, Lester J, Levine DA, Li Z, Liang D, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Milne RL, Modugno F, Moysich KB, Ness RB, Nevanlinna H, Odunsi K, Olson SH, Orlow I, Orsulic S, Paul J, Pejovic T, Pelttari LM, Permuth JB, Pike MC, Poole EM, Rosen B, Rossing MA, Rothstein JH, Runnebaum IB, Rzepecka IK, Schernhammer E, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Spiewankiewicz B, Sucheston-Campbell L, Tangen IL, Teo SH, Terry KL, Thompson PJ, Thomsen L, Tworoger SS, van Altena AM, Vergote I, Vestrheim Thomsen LC, Vierkant RA, Walsh CS, Wang-Gohrke S, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Woo YL, Wu AH, Wu X, Xiang YB, Yang H, Zheng W, Ziogas A, Lee AW, Pearce CL, Berchuck A, Schildkraut JM, Ramus SJ, Monteiro ANA, Narod SA, Sellers TA, Gayther SA, Kelemen LE, Chenevix-Trench G, Risch HA, Pharoah PDP, Goode EL, and Phelan CM
Subjects: Carcinoma, Ovarian Epithelial pathology, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genotype, Humans, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Risk Factors, A Kinase Anchor Proteins genetics, Carcinoma, Ovarian Epithelial genetics, Monomeric GTP-Binding Proteins genetics, Rho Guanine Nucleotide Exchange Factors genetics
Abstract: Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations., Competing Interests: The authors have declared that no competing interests exist.
Published: 2018
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47. Adult height is associated with increased risk of ovarian cancer: a Mendelian randomisation study.

Author: Dixon-Suen SC, Nagle CM, Thrift AP, Pharoah PDP, Ewing A, Pearce CL, Zheng W, Chenevix-Trench G, Fasching PA, Beckmann MW, Lambrechts D, Vergote I, Lambrechts S, Van Nieuwenhuysen E, Rossing MA, Doherty JA, Wicklund KG, Chang-Claude J, Jung AY, Moysich KB, Odunsi K, Goodman MT, Wilkens LR, Thompson PJ, Shvetsov YB, Dörk T, Park-Simon TW, Hillemanns P, Bogdanova N, Butzow R, Nevanlinna H, Pelttari LM, Leminen A, Modugno F, Ness RB, Edwards RP, Kelley JL, Heitz F, du Bois A, Harter P, Schwaab I, Karlan BY, Lester J, Orsulic S, Rimel BJ, Kjær SK, Høgdall E, Jensen A, Goode EL, Fridley BL, Cunningham JM, Winham SJ, Giles GG, Bruinsma F, Milne RL, Southey MC, Hildebrandt MAT, Wu X, Lu KH, Liang D, Levine DA, Bisogna M, Schildkraut JM, Berchuck A, Cramer DW, Terry KL, Bandera EV, Olson SH, Salvesen HB, Thomsen LCV, Kopperud RK, Bjorge L, Kiemeney LA, Massuger LFAG, Pejovic T, Bruegl A, Cook LS, Le ND, Swenerton KD, Brooks-Wilson A, Kelemen LE, Lubiński J, Huzarski T, Gronwald J, Menkiszak J, Wentzensen N, Brinton L, Yang H, Lissowska J, Høgdall CK, Lundvall L, Song H, Tyrer JP, Campbell I, Eccles D, Paul J, Glasspool R, Siddiqui N, Whittemore AS, Sieh W, McGuire V, Rothstein JH, Narod SA, Phelan C, Risch HA, McLaughlin JR, Anton-Culver H, Ziogas A, Menon U, Gayther SA, Ramus SJ, Gentry-Maharaj A, Wu AH, Pike MC, Tseng CC, Kupryjanczyk J, Dansonka-Mieszkowska A, Budzilowska A, Rzepecka IK, and Webb PM
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Body Height genetics, Carcinoma, Ovarian Epithelial genetics, Case-Control Studies, Female, Genetic Predisposition to Disease, Geography, Humans, Mendelian Randomization Analysis, Middle Aged, Ovarian Neoplasms genetics, Risk Factors, Young Adult, Body Height physiology, Carcinoma, Ovarian Epithelial epidemiology, Ovarian Neoplasms epidemiology
Abstract: Background: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias., Methods: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis., Results: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours., Conclusions: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.
Published: 2018
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48. MyD88 and TLR4 Expression in Epithelial Ovarian Cancer.

Author: Block MS, Vierkant RA, Rambau PF, Winham SJ, Wagner P, Traficante N, Tołoczko A, Tiezzi DG, Taran FA, Sinn P, Sieh W, Sharma R, Rothstein JH, Ramón Y Cajal T, Paz-Ares L, Oszurek O, Orsulic S, Ness RB, Nelson G, Modugno F, Menkiszak J, McGuire V, McCauley BM, Mack M, Lubiński J, Longacre TA, Li Z, Lester J, Kennedy CJ, Kalli KR, Jung AY, Johnatty SE, Jimenez-Linan M, Jensen A, Intermaggio MP, Hung J, Herpel E, Hernandez BY, Hartkopf AD, Harnett PR, Ghatage P, García-Bueno JM, Gao B, Fereday S, Eilber U, Edwards RP, de Sousa CB, de Andrade JM, Chudecka-Głaz A, Chenevix-Trench G, Cazorla A, Brucker SY, Alsop J, Whittemore AS, Steed H, Staebler A, Moysich KB, Menon U, Koziak JM, Kommoss S, Kjaer SK, Kelemen LE, Karlan BY, Huntsman DG, Høgdall E, Gronwald J, Goodman MT, Gilks B, García MJ, Fasching PA, de Fazio A, Deen S, Chang-Claude J, Candido Dos Reis FJ, Campbell IG, Brenton JD, Bowtell DD, Benítez J, Pharoah PDP, Köbel M, Ramus SJ, and Goode EL
Subjects: Adult, Aged, Biomarkers, Tumor metabolism, Carcinoma, Ovarian Epithelial mortality, Female, Humans, Immunohistochemistry methods, Middle Aged, Ovarian Neoplasms mortality, Survival Analysis, Tissue Array Analysis methods, Carcinoma, Ovarian Epithelial metabolism, Myeloid Differentiation Factor 88 metabolism, Ovarian Neoplasms metabolism, Toll-Like Receptor 4 metabolism
Abstract: Objective: To evaluate myeloid differentiation primary response gene 88 (MyD88) and Toll-like receptor 4 (TLR4) expression in relation to clinical features of epithelial ovarian cancer, histologic subtypes, and overall survival., Patients and Methods: We conducted centralized immunohistochemical staining, semi-quantitative scoring, and survival analysis in 5263 patients participating in the Ovarian Tumor Tissue Analysis consortium. Patients were diagnosed between January 1, 1978, and December 31, 2014, including 2865 high-grade serous ovarian carcinomas (HGSOCs), with more than 12,000 person-years of follow-up time. Tissue microarrays were stained for MyD88 and TLR4, and staining intensity was classified using a 2-tiered system for each marker (weak vs strong)., Results: Expression of MyD88 and TLR4 was similar in all histotypes except clear cell ovarian cancer, which showed reduced expression compared with other histotypes (P<.001 for both). In HGSOC, strong MyD88 expression was modestly associated with shortened overall survival (hazard ratio [HR], 1.13; 95% CI, 1.01-1.26; P=.04) but was also associated with advanced stage (P<.001). The expression of TLR4 was not associated with survival. In low-grade serous ovarian cancer (LGSOC), strong expression of both MyD88 and TLR4 was associated with favorable survival (HR [95% CI], 0.49 [0.29-0.84] and 0.44 [0.21-0.89], respectively; P=.009 and P=.02, respectively)., Conclusion: Results are consistent with an association between strong MyD88 staining and advanced stage and poorer survival in HGSOC and demonstrate correlation between strong MyD88 and TLR4 staining and improved survival in LGSOC, highlighting the biological differences between the 2 serous histotypes., (Copyright © 2017 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)
Published: 2018
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49. Dose-Response Association of CD8+ Tumor-Infiltrating Lymphocytes and Survival Time in High-Grade Serous Ovarian Cancer.

Author: Goode EL, Block MS, Kalli KR, Vierkant RA, Chen W, Fogarty ZC, Gentry-Maharaj A, Tołoczko A, Hein A, Bouligny AL, Jensen A, Osorio A, Hartkopf A, Ryan A, Chudecka-Głaz A, Magliocco AM, Hartmann A, Jung AY, Gao B, Hernandez BY, Fridley BL, McCauley BM, Kennedy CJ, Wang C, Karpinskyj C, de Sousa CB, Tiezzi DG, Wachter DL, Herpel E, Taran FA, Modugno F, Nelson G, Lubiński J, Menkiszak J, Alsop J, Lester J, García-Donas J, Nation J, Hung, Palacios J, Rothstein JH, Kelley JL, de Andrade JM, Robles-Díaz L, Intermaggio MP, Widschwendter M, Beckmann MW, Ruebner M, Jimenez-Linan M, Singh N, Oszurek O, Harnett PR, Rambau PF, Sinn P, Wagner P, Ghatage P, Sharma R, Edwards RP, Ness RB, Orsulic S, Brucker SY, Johnatty SE, Longacre TA, Ursula E, McGuire V, Sieh W, Natanzon Y, Li Z, Whittemore AS, Anna A, Staebler A, Karlan BY, Gilks B, Bowtell DD, Høgdall E, Candido dos Reis FJ, Steed H, Campbell IG, Gronwald J, Benítez J, Koziak JM, Chang-Claude J, Moysich KB, Kelemen LE, Cook LS, Goodman MT, García MJ, Fasching PA, Kommoss S, Deen S, Kjaer SK, Menon U, Brenton JD, Pharoah PDP, Chenevix-Trench G, Huntsman DG, Winham SJ, Köbel M, and Ramus SJ
Subjects: BRCA2 Protein genetics, Carcinoma, Ovarian Epithelial immunology, Carcinoma, Ovarian Epithelial pathology, Cohort Studies, Cystadenocarcinoma, Serous genetics, Cystadenocarcinoma, Serous pathology, Female, Humans, Middle Aged, Mutation, Neoplasm Grading, Ovarian Neoplasms genetics, Ovarian Neoplasms pathology, Prospective Studies, Survival Analysis, Treatment Outcome, CD8 Antigens metabolism, Carcinoma, Ovarian Epithelial drug therapy, Cystadenocarcinoma, Serous immunology, Lymphocytes, Tumor-Infiltrating immunology, Ovarian Neoplasms immunology
Abstract: Importance: Cytotoxic CD8+ tumor-infiltrating lymphocytes (TILs) participate in immune control of epithelial ovarian cancer; however, little is known about prognostic patterns of CD8+ TILs by histotype and in relation to other clinical factors., Objective: To define the prognostic role of CD8+ TILs in epithelial ovarian cancer., Design, Setting, and Participants: This was a multicenter observational, prospective survival cohort study of the Ovarian Tumor Tissue Analysis Consortium. More than 5500 patients, including 3196 with high-grade serous ovarian carcinomas (HGSOCs), were followed prospectively for over 24 650 person-years., Exposures: Following immunohistochemical analysis, CD8+ TILs were identified within the epithelial components of tumor islets. Patients were grouped based on the estimated number of CD8+ TILs per high-powered field: negative (none), low (1-2), moderate (3-19), and high (≥20). CD8+ TILs in a subset of patients were also assessed in a quantitative, uncategorized manner, and the functional form of associations with survival was assessed using penalized B-splines., Main Outcomes and Measures: Overall survival time., Results: The final sample included 5577 women; mean age at diagnosis was 58.4 years (median, 58.2 years). Among the 5 major invasive histotypes, HGSOCs showed the most infiltration. CD8+ TILs in HGSOCs were significantly associated with longer overall survival; median survival was 2.8 years for patients with no CD8+ TILs and 3.0 years, 3.8 years, and 5.1 years for patients with low, moderate, or high levels of CD8+ TILs, respectively (P value for trend = 4.2 × 10−16). A survival benefit was also observed among women with endometrioid and mucinous carcinomas, but not for those with the other histotypes. Among HGSOCs, CD8+ TILs were favorable regardless of extent of residual disease following cytoreduction, known standard treatment, and germline BRCA1 pathogenic mutation, but were not prognostic for BRCA2 mutation carriers. Evaluation of uncategorized CD8+ TIL counts showed a near-log-linear functional form., Conclusions and Relevance: This study demonstrates the histotype-specific nature of immune infiltration and provides definitive evidence for a dose-response relationship between CD8+ TILs and HGSOC survival. That the extent of infiltration is prognostic, not merely its presence or absence, suggests that understanding factors that drive infiltration will be the key to unraveling outcome heterogeneity in this cancer.
Published: 2017
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50. Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women.

Author: Alexeeff SE, Odo NU, Lipson JA, Achacoso N, Rothstein JH, Yaffe MJ, Liang RY, Acton L, McGuire V, Whittemore AS, Rubin DL, Sieh W, and Habel LA
Subjects: Cohort Studies, Female, Humans, Middle Aged, Adiposity physiology, Breast pathology, Mammography methods, Menarche physiology
Abstract: Background: High mammographic density is strongly associated with increased breast cancer risk. Some, but not all, risk factors for breast cancer are also associated with higher mammographic density. Methods: The study cohort ( N = 24,840) was drawn from the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California and included non-Hispanic white females ages 40 to 74 years with a full-field digital mammogram (FFDM). Percent density (PD) and dense area (DA) were measured by a radiological technologist using Cumulus. The association of age at menarche and late adolescent body mass index (BMI) with PD and DA were modeled using linear regression adjusted for confounders. Results: Age at menarche and late adolescent BMI were negatively correlated. Age at menarche was positively associated with PD ( P value for trend <0.0001) and DA ( P value for trend <0.0001) in fully adjusted models. Compared with the reference category of ages 12 to 13 years at menarche, menarche at age >16 years was associated with an increase in PD of 1.47% (95% CI, 0.69-2.25) and an increase in DA of 1.59 cm 2 (95% CI, 0.48-2.70). Late adolescent BMI was inversely associated with PD ( P < 0.0001) and DA ( P < 0.0001) in fully adjusted models. Conclusions: Age at menarche and late adolescent BMI are both associated with Cumulus measures of mammographic density on processed FFDM images. Impact: Age at menarche and late adolescent BMI may act through different pathways. The long-term effects of age at menarche on cancer risk may be mediated through factors besides mammographic density. Cancer Epidemiol Biomarkers Prev; 26(9); 1450-8. ©2017 AACR ., (©2017 American Association for Cancer Research.)
Published: 2017
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