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1. Genetic variation in the immunosuppression pathway genes and breast cancer susceptibility: a pooled analysis of 42,510 cases and 40,577 controls from the Breast Cancer Association Consortium

Author

Lei, J, Rudolph, A, Moysich, KB, Behrens, S, Goode, EL, Bolla, MK, Dennis, J, Dunning, AM, Easton, DF, Wang, Q, Benitez, J, Hopper, JL, Southey, MC, Schmidt, MK, Broeks, A, Fasching, PA, Haeberle, L, Peto, J, dos-Santos-Silva, I, Sawyer, EJ, Tomlinson, I, Burwinkel, B, Marmé, F, Guénel, P, Truong, T, Bojesen, SE, Flyger, H, Nielsen, SF, Nordestgaard, BG, González-Neira, A, Menéndez, P, Anton-Culver, H, Neuhausen, SL, Brenner, H, Arndt, V, Meindl, A, Schmutzler, RK, Brauch, H, Hamann, U, Nevanlinna, H, Fagerholm, R, Dörk, T, Bogdanova, NV, Mannermaa, A, Hartikainen, JM, Australian Ovarian Study Group, kConFab Investigators, Van Dijck, L, Smeets, A, Flesch-Janys, D, Eilber, U, Radice, P, Peterlongo, P, Couch, FJ, Hallberg, E, Giles, GG, Milne, RL, Haiman, CA, Schumacher, F, Simard, J, Goldberg, MS, Kristensen, V, Borresen-Dale, AL, Zheng, W, Beeghly-Fadiel, A, Winqvist, R, Grip, M, Andrulis, IL, Glendon, G, García-Closas, M, Figueroa, J, Czene, K, Brand, JS, Darabi, H, Eriksson, M, Hall, P, Li, J, Cox, A, Cross, SS, Pharoah, PDP, Shah, M, Kabisch, M, Torres, D, Jakubowska, A, Lubinski, J, Ademuyiwa, F, Ambrosone, CB, Swerdlow, A, Jones, M, and Chang-Claude, J

Subjects
Genetics, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity
Abstract

Immunosuppression plays a pivotal role in assisting tumors to evade immune destruction and promoting tumor development. We hypothesized that genetic variation in the immunosuppression pathway genes may be implicated in breast cancer tumorigenesis. We included 42,510 female breast cancer cases and 40,577 controls of European ancestry from 37 studies in the Breast Cancer Association Consortium (2015) with available genotype data for 3595 single nucleotide polymorphisms (SNPs) in 133 candidate genes. Associations between genotyped SNPs and overall breast cancer risk, and secondarily according to estrogen receptor (ER) status, were assessed using multiple logistic regression models. Gene-level associations were assessed based on principal component analysis. Gene expression analyses were conducted using RNA sequencing level 3 data from The Cancer Genome Atlas for 989 breast tumor samples and 113 matched normal tissue samples. SNP rs1905339 (A>G) in the STAT3 region was associated with an increased breast cancer risk (per allele odds ratio 1.05, 95 % confidence interval 1.03–1.08; p value = 1.4 × 10−6). The association did not differ significantly by ER status. On the gene level, in addition to TGFBR2 and CCND1, IL5 and GM-CSF showed the strongest associations with overall breast cancer risk (p value = 1.0 × 10−3 and 7.0 × 10−3, respectively). Furthermore, STAT3 and IL5 but not GM-CSF were differentially expressed between breast tumor tissue and normal tissue (p value = 2.5 × 10−3, 4.5 × 10−4 and 0.63, respectively). Our data provide evidence that the immunosuppression pathway genes STAT3,IL5, and GM-CSF may be novel susceptibility loci for breast cancer in women of European ancestry.

Published
2016

4. Mendelian randomisation study of smoking exposure in relation to breast cancer risk

Author

Park, HA, Neumeyer, S, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Augustinsson, A, Baten, A, Beane Freeman, LE, Becher, H, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bogdanova, NV, Bojesen, SE, Brauch, H, Brenner, H, Brucker, SY, Burwinkel, B, Campa, D, Canzian, F, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Børresen-Dale, A-L, Grenaker Alnæs, GI, Sahlberg, KK, Ottestad, L, Kåresen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebråten, O, Naume, B, Fosså, A, Kiserud, CE, Reinertsen, KV, Helland, Å, Riis, M, Geisler, J, Conroy, DM, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dörk, T, dos-Santos-Silva, I, Dwek, M, Eccles, DM, Eliassen, AH, Engel, C, Eriksson, M, Evans, DG, Fasching, PA, Flyger, H, Fritschi, L, García-Closas, M, García-Sáenz, JA, Gaudet, MM, Giles, GG, Glendon, G, Goldberg, MS, Goldgar, DE, González-Neira, A, Grip, M, Guénel, P, Hahnen, E, Haiman, CA, Håkansson, N, Hall, P, Hamann, U, Han, S, Harkness, EF, Hart, SN, He, W, Heemskerk-Gerritsen, BAM, Hopper, JL, Hunter, DJ, Clarke, C, Marsh, D, Scott, R, Baxter, R, Yip, D, Carpenter, J, Davis, A, Pathmanathan, N, Simpson, P, Graham, D, Sachchithananthan, M, Amor, D, Andrews, L, Antill, Y, Balleine, R, Beesley, J, Bennett, I, Bogwitz, M, Botes, L, Brennan, M, Brown, M, Buckley, M, Burke, J, Butow, P, Caldon, L, Campbell, I, Chauhan, D, Chauhan, M, Christian, A, Cohen, P, Colley, A, Crook, A, Cui, J, Cummings, M, Dawson, S-J, DeFazio, A, Delatycki, M, Dickson, R, Dixon, J, Edkins, T, Edwards, S, Farshid, G, Fellows, A, Fenton, G, Field, M, Flanagan, J, Fong, P, Forrest, L, Fox, S, French, J, Friedlander, M, Gaff, C, Gattas, M, George, P, Greening, S, Harris, M, Hart, S, Hayward, N, Hopper, J, Hoskins, C, Hunt, C, James, P, Jenkins, M, Kidd, A, Kirk, J, Koehler, J, Kollias, J, Lakhani, S, Lawrence, M, Lindeman, G, Lipton, L, Lobb, L, Mann, G, McLachlan, SA, Meiser, B, Milne, R, Nightingale, S, O’Connell, S, O’Sullivan, S, Ortega, DG, Pachter, N, Patterson, B, Pearn, A, Phillips, K, Pieper, E, Rickard, E, Robinson, B, Saleh, M, Salisbury, E, Saunders, C, Saunus, J, Scott, C, Sexton, A, Shelling, A, Southey, M, Spurdle, A, Taylor, J, Taylor, R, Thorne, H, Trainer, A, Tucker, K, Visvader, J, Walker, L, Williams, R, Winship, I, Young, MA, Jager, A, Jakubowska, A, John, EM, Jung, A, Kaaks, R, Kapoor, PM, Keeman, R, Khusnutdinova, E, Kitahara, CM, Koppert, LB, Koutros, S, Kristensen, VN, Kurian, AW, Lacey, J, Lambrechts, D, Le Marchand, L, Lo, W-Y, Lubiński, J, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, Mavroudis, D, Meindl, A, Menon, U, Milne, RL, Muranen, TA, Nevanlinna, H, Newman, WG, Nordestgaard, BG, Offit, K, Olshan, AF, Olsson, H, Park-Simon, T-W, Peterlongo, P, Peto, J, Plaseska-Karanfilska, D, Presneau, N, Radice, P, Rennert, G, Rennert, HS, Romero, A, Saloustros, E, Sawyer, EJ, Schmidt, MK, Schmutzler, RK, Schoemaker, MJ, Schwentner, L, Shah, M, Shu, X-O, Simard, J, Smeets, A, Southey, MC, Spinelli, JJ, Stevens, V, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Terry, MB, Tomlinson, I, Troester, MA, Truong, T, Vachon, CM, van Veen, EM, Vijai, J, Wang, S, Wendt, C, Winqvist, R, Wolk, A, Ziogas, A, Dunning, AM, Pharoah, PDP, Easton, DF, Zheng, W, Kraft, P, Chang-Claude, J, HUS Gynecology and Obstetrics, Department of Obstetrics and Gynecology, Park, Hanla A. [0000-0001-8055-3729], Dennis, Joe [0000-0003-4591-1214], Augustinsson, Annelie [0000-0003-3415-0536], Brenner, Hermann [0000-0002-6129-1572], Canzian, Federico [0000-0002-4261-4583], Cox, Angela [0000-0002-5138-1099], Devilee, Peter [0000-0002-8023-2009], Fasching, Peter A. [0000-0003-4885-8471], Harkness, Elaine F. [0000-0001-6625-7739], Hart, Steven N. [0000-0001-7714-2734], Heemskerk-Gerritsen, Bernadette A. M. [0000-0002-9724-6693], Jakubowska, Anna [0000-0002-5650-0501], Kapoor, Pooja Middha [0000-0001-5503-8215], Kurian, Allison W. [0000-0002-6175-9470], Newman, William G. [0000-0002-6382-4678], Peterlongo, Paolo [0000-0001-6951-6855], Peto, Julian [0000-0002-1685-8912], Sawyer, Elinor J. [0000-0001-8285-4111], Scott, Christopher [0000-0003-1340-0647], Smeets, Ann [0000-0002-5091-6602], Tomlinson, Ian [0000-0003-3037-1470], Truong, Thérèse [0000-0002-2943-6786], Pharoah, Paul D. P. [0000-0001-8494-732X], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Oncology, Medicin och hälsovetenskap, Cancer Research, Genotyping Techniques, Breast Neoplasms, Case-Control Studies, Cigarette Smoking, Female, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, ALCOHOL, Medical and Health Sciences, 0302 clinical medicine, Breast cancer, Pleiotropy, Epidemiology, Medicine, TOBACCO, Breast Neoplasms/epidemiology, Cigarette Smoking/adverse effects, WOMEN, ASSOCIATION, Single Nucleotide, 3. Good health, Substance abuse, 692/699/67/1347, 030220 oncology & carcinogenesis, Life Sciences & Biomedicine, 692/499, medicine.medical_specialty, 3122 Cancers, Single-nucleotide polymorphism, Article, 03 medical and health sciences, Internal medicine, ddc:610, Polymorphism, Genetic association, Science & Technology, business.industry, Cancer, medicine.disease, 030104 developmental biology, Clinical research, Risk factors, TISSUE, INFERENCE, CIGARETTE-SMOKING, business
Abstract

Background Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. Methods We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. Results Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78–1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. Conclusion Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Published
2021

5. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author

Ahearn, TU, Zhang, H, Michailidou, K, Milne, RL, Bolla, MK, Dennis, J, Dunning, AM, Lush, M, Wang, Q, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baten, A, Becher, H, Behrens, S, Benitez, J, Bermisheva, M, Blomqvist, C, Bojesen, SE, Bonanni, B, Børresen-Dale, A-L, Brauch, H, Brenner, H, Brooks-Wilson, A, Brüning, T, Burwinkel, B, Buys, SS, Canzian, F, Castelao, JE, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Clarke, CL, Sahlberg, KK, Ottestad, L, Kåresen, R, Schlichting, E, Holmen, MM, Sauer, T, Haakensen, V, Engebråten, O, Naume, B, Fosså, A, Kiserud, CE, Reinertsen, KV, Helland, Å, Riis, M, Geisler, J, Collée, JM, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Dörk, T, Dwek, M, Eccles, DM, Evans, DG, Fasching, PA, Figueroa, J, Floris, G, Gago-Dominguez, M, Gapstur, SM, García-Sáenz, JA, Gaudet, MM, Giles, GG, Goldberg, MS, González-Neira, A, Alnæs, GIG, Grip, M, Guénel, P, Haiman, CA, Hall, P, Hamann, U, Harkness, EF, Heemskerk-Gerritsen, BAM, Holleczek, B, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Howell, A, Clarke, C, Balleine, R, Baxter, R, Braye, S, Carpenter, J, Dahlstrom, J, Forbes, J, Lee, C, Marsh, D, Morey, A, Pathmanathan, N, Scott, R, Simpson, P, Spigelman, A, Wilcken, N, Yip, D, Zeps, N, Fox, S, Campbell, I, Bowtell, D, Spurdle, A, Webb, P, de Fazio, A, Tassell, M, Kirk, J, Lindeman, G, Price, M, Southey, M, Milne, R, Deb, S, Jakimovska, M, Jakubowska, A, John, EM, Jones, ME, Jung, A, Kaaks, R, Kauppila, S, Keeman, R, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Koutros, S, Kristensen, VN, Krüger, U, Kubelka-Sabit, K, Kurian, AW, Kyriacou, K, Lambrechts, D, Lee, DG, Lindblom, A, Linet, M, Lissowska, J, Llaneza, A, Lo, W-Y, MacInnis, RJ, Mannermaa, A, Manoochehri, M, Margolin, S, Martinez, ME, McLean, C, Meindl, A, Menon, U, Nevanlinna, H, Newman, WG, Nodora, J, Offit, K, Olsson, H, Orr, N, Park-Simon, T-W, Patel, AV, Peto, J, Pita, G, Plaseska-Karanfilska, D, Prentice, R, Punie, K, Pylkäs, K, Radice, P, Rennert, G, Romero, A, Rüdiger, T, Saloustros, E, Sampson, S, Sandler, DP, Sawyer, EJ, Schmutzler, RK, Schoemaker, MJ, Schöttker, B, Sherman, ME, Shu, X-O, Smichkoska, S, Southey, MC, Spinelli, JJ, Swerdlow, AJ, Tamimi, RM, Tapper, WJ, Taylor, JA, Teras, LR, Terry, MB, Torres, D, Troester, MA, Vachon, CM, van Deurzen, CHM, van Veen, EM, Wagner, P, Weinberg, CR, Wendt, C, Wesseling, J, Winqvist, R, Wolk, A, Yang, XR, Zheng, W, Couch, FJ, Simard, J, Kraft, P, Easton, DF, Pharoah, PDP, Schmidt, MK, García-Closas, M, Chatterjee, N, Ahearn, Thomas U [0000-0003-0771-7752], Easton, Douglas [0000-0003-2444-3247], Pharoah, Paul [0000-0001-8494-732X], Apollo - University of Cambridge Repository, Medicum, HUS Comprehensive Cancer Center, Department of Oncology, Clinicum, Department of Obstetrics and Gynecology, Biosciences, HUS Gynecology and Obstetrics, Clinical Genetics, Medical Oncology, and Pathology

Subjects
False discovery rate, Oncology, Common breast cancer susceptibility variants, Receptor, ErbB-2, Estrogen receptor, PROGRESSION, Etiologic heterogeneity, Logistic regression, Basic medicine, Breast cancer, 0302 clinical medicine, PRIMARY THERAPY, HETEROGENEITY, RC254-282, HISTOLOGICAL GRADE, 0303 health sciences, Breast Neoplasms/epidemiology, Receptors, Estrogen/genetics, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, INTERNATIONAL EXPERT CONSENSUS, humanities, Receptor, ErbB-2/genetics, 3. Good health, Receptors, Estrogen, Receptors, Progesterone/genetics, 030220 oncology & carcinogenesis, Female, Biomarkers, Tumor/genetics, Receptors, Progesterone, Medical Genetics, Research Article, Risk, medicine.medical_specialty, SUSCEPTIBILITY LOCI, 3122 Cancers, Breast Neoplasms, Single-nucleotide polymorphism, Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, Progesterone receptor, Biomarkers, Tumor, medicine, Genetic predisposition, Humans, ddc:610, GENOME-WIDE ASSOCIATION, Genetic association, Medicinsk genetik, 030304 developmental biology, Cancer och onkologi, medicine.disease, Cancer and Oncology, Clinical medicine, Genome-Wide Association Study
Abstract

Background Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. Methods Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate p Conclusion This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

Published
2020

6. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Author

Zhang, H, Ahearn, TU, Lecarpentier, J, Barnes, D, Beesley, J, Qi, G, Jiang, X, O’Mara, TA, Zhao, N, Bolla, MK, Dunning, AM, Dennis, J, Wang, Q, Ful, ZA, Aittomäki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Arun, BK, Auer, PL, Azzollini, J, Barrowdale, D, Becher, H, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bialkowska, K, Blanco, A, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bonanni, B, Bondavalli, D, Borg, A, Brauch, H, Brenner, H, Briceno, I, Broeks, A, Brucker, SY, Brüning, T, Burwinkel, B, Buys, SS, Byers, H, Caldés, T, Caligo, MA, Calvello, M, Campa, D, Castelao, JE, Chang-Claude, J, Chanock, SJ, Christiaens, M, Christiansen, H, Chung, WK, Claes, KBM, Clarke, CL, Cornelissen, S, Couch, FJ, Cox, A, Cross, SS, Czene, K, Daly, MB, Devilee, P, Diez, O, Domchek, SM, Dörk, T, Dwek, M, Eccles, DM, Ekici, AB, Evans, DG, Fasching, PA, Figueroa, J, Foretova, L, Fostira, F, Friedman, E, Frost, D, Gago-Dominguez, M, Gapstur, SM, Garber, J, García-Sáenz, JA, Gaudet, MM, Gayther, SA, Giles, GG, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Greene, MH, Gronwald, J, Guénel, P, Häberle, L, Hahnen, E, Haiman, CA, Hake, CR, Hall, P, Hamann, U, Harkness, EF, Heemskerk-Gerritsen, BAM, Hillemanns, P, Hogervorst, FBL, Holleczek, B, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Howell, A, Huebner, H, Hulick, PJ, Imyanitov, EN, Isaacs, C, Izatt, L, Jager, A, Jakimovska, M, Jakubowska, A, James, P, Janavicius, R, Janni, W, John, EM, Jones, ME, Jung, A, Kaaks, R, Kapoor, PM, Karlan, BY, Keeman, R, Khan, S, Khusnutdinova, E, Kitahara, CM, Ko, Y-D, Konstantopoulou, I, Koppert, LB, Koutros, S, Kristensen, VN, Laenkholm, A-V, Lambrechts, D, Larsson, SC, Laurent-Puig, P, Lazaro, C, Lazarova, E, Lejbkowicz, F, Leslie, G, Lesueur, F, Lindblom, A, Lissowska, J, Lo, W-Y, Loud, JT, Lubinski, J, Lukomska, A, MacInnis, RJ, Mannermaa, A, Manoochehri, M, Manoukian, S, Margolin, S, Martinez, ME, Matricardi, L, McGuffog, L, McLean, C, Mebirouk, N, Meindl, A, Menon, U, Miller, A, Mingazheva, E, Montagna, M, Mulligan, AM, Mulot, C, Muranen, TA, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Neven, P, Newman, WG, Nielsen, FC, Nikitina-Zake, L, Nodora, J, Offit, K, Olah, E, Olopade, OI, Olsson, H, Orr, N, Papi, L, Papp, J, Park-Simon, T-W, Parsons, MT, Peissel, B, Peixoto, A, Peshkin, B, Peterlongo, P, Peto, J, Phillips, K-A, Piedmonte, M, Plaseska-Karanfilska, D, Prajzendanc, K, Prentice, R, Prokofyeva, D, Rack, B, Radice, P, Ramus, SJ, Rantala, J, Rashid, MU, Rennert, G, Rennert, HS, Risch, HA, Romero, A, Rookus, MA, Rübner, M, Rüdiger, T, Saloustros, E, Sampson, S, Sandler, DP, Sawyer, EJ, Scheuner, MT, Schmutzler, RK, Schneeweiss, A, Schoemaker, MJ, Schöttker, B, Schürmann, P, Senter, L, Sharma, P, Sherman, ME, Shu, X-O, Singer, CF, Smichkoska, S, Soucy, P, Southey, MC, Spinelli, JJ, Stone, J, Stoppa-Lyonnet, D, Swerdlow, AJ, Szabo, CI, Tamimi, RM, Tapper, WJ, Taylor, JA, Teixeira, MR, Terry, M, Thomassen, M, Thull, DL, Tischkowitz, M, Toland, AE, Tollenaar, RAEM, Tomlinson, I, Torres, D, Troester, MA, Truong, T, Tung, N, Untch, M, Vachon, CM, van den Ouweland, AMW, van der Kolk, LE, van Veen, EM, vanRensburg, EJ, Vega, A, Wappenschmidt, B, Weinberg, CR, Weitzel, JN, Wildiers, H, Winqvist, R, Wolk, A, Yang, XR, Yannoukakos, D, Zheng, W, Zorn, KK, Milne, RL, Kraft, P, Simard, J, Pharoah, PDP, Michailidou, K, Antoniou, AC, Schmidt, MK, Chenevix-Trench, G, Easton, DF, Chatterjee, N, and García-Closas, M

Abstract

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1,2,3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P

Published
2020

7. rs2735383, located at a microRNA binding site in the 3'UTR of NBS1, is not associated with breast cancer risk

Author

Liu, J, Lončar, I, Collée, JM, Bolla, MK, Dennis, J, Michailidou, K, Wang, Q, Andrulis, IL, Barile, M, Beckmann, MW, Behrens, S, Benitez, J, Blomqvist, C, Boeckx, B, Bogdanova, NV, Bojesen, SE, Brauch, H, Brennan, P, Brenner, H, Broeks, A, Burwinkel, B, Chang-Claude, J, Chen, ST, Chenevix-Trench, G, Cheng, CY, Choi, JY, Couch, FJ, Cox, A, Cross, SS, Cuk, K, Czene, K, Dörk, T, Dos-Santos-Silva, I, Fasching, PA, Figueroa, J, Flyger, H, García-Closas, M, Giles, GG, Glendon, G, Goldberg, MS, González-Neira, A, Guénel, P, Haiman, CA, Hamann, U, Hart, SN, Hartman, M, Hatse, S, Hopper, JL, Ito, H, Jakubowska, A, Kabisch, M, Kang, D, Kosma, VM, Kristensen, VN, Le Marchand, L, Lee, E, Li, J, Lophatananon, A, Jan Lubinski, Mannermaa, A, Matsuo, K, Milne, RL, NBCS Collaborators, Neuhausen, SL, Nevanlinna, H, Orr, N, Perez, JI, Peto, J, Putti, TC, Pylkäs, K, Radice, P, Sangrajrang, S, Sawyer, EJ, Schmidt, MK, Schneeweiss, A, Shen, CY, Shrubsole, MJ, Shu, XO, Simard, J, Southey, MC, Swerdlow, A, Teo, SH, Tessier, DC, Thanasitthichai, S, Tomlinson, I, Torres, D, Truong, T, Tseng, CC, Vachon, C, Winqvist, R, Wu, AH, Yannoukakos, D, Zheng, W, Hall, P, Dunning, AM, Easton, DF, Hooning, MJ, van den Ouweland, AM, Martens, JW, Hollestelle, A, Dennis, Joe [0000-0003-4591-1214], Wang, Jean [0000-0002-9139-0627], Dunning, Alison [0000-0001-6651-7166], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
BRCA2 Protein, Binding Sites, Genotype, BRCA1 Protein, Nuclear Proteins, Breast Neoplasms, Cell Cycle Proteins, Polymorphism, Single Nucleotide, MicroRNAs, Risk Factors, Odds Ratio, Humans, Female, Genetic Predisposition to Disease, 3' Untranslated Regions, Alleles
Abstract

NBS1, also known as NBN, plays an important role in maintaining genomic stability. Interestingly, rs2735383 G > C, located in a microRNA binding site in the 3'-untranslated region (UTR) of NBS1, was shown to be associated with increased susceptibility to lung and colorectal cancer. However, the relation between rs2735383 and susceptibility to breast cancer is not yet clear. Therefore, we genotyped rs2735383 in 1,170 familial non-BRCA1/2 breast cancer cases and 1,077 controls using PCR-based restriction fragment length polymorphism (RFLP-PCR) analysis, but found no association between rs2735383CC and breast cancer risk (OR = 1.214, 95% CI = 0.936-1.574, P = 0.144). Because we could not exclude a small effect size due to a limited sample size, we further analyzed imputed rs2735383 genotypes (r$^{2}$ > 0.999) of 47,640 breast cancer cases and 46,656 controls from the Breast Cancer Association Consortium (BCAC). However, rs2735383CC was not associated with overall breast cancer risk in European (OR = 1.014, 95% CI = 0.969-1.060, P = 0.556) nor in Asian women (OR = 0.998, 95% CI = 0.905-1.100, P = 0.961). Subgroup analyses by age, age at menarche, age at menopause, menopausal status, number of pregnancies, breast feeding, family history and receptor status also did not reveal a significant association. This study therefore does not support the involvement of the genotype at NBS1 rs2735383 in breast cancer susceptibility.

Published
2016

8. Fine-mapping of the 1p11.2 breast cancer susceptibility locus

Author

Horne, HN, Chung, CC, Zhang, H, Yu, K, Prokunina-Olsson, L, Michailidou, K, Bolla, MK, Wang, Q, Dennis, J, Hopper, JL, Southey, MC, Schmidt, MK, Broeks, A, Muir, K, Lophatananon, A, Fasching, PA, Beckmann, MW, Fletcher, O, Johnson, N, Sawyer, EJ, Tomlinson, I, Burwinkel, B, Marme, F, Guénel, P, Truong, T, Bojesen, SE, Flyger, H, Benitez, J, González-Neira, A, Anton-Culver, H, Neuhausen, SL, Brenner, H, Arndt, V, Meindl, A, Schmutzler, RK, Brauch, H, Hamann, U, Nevanlinna, H, Khan, S, Matsuo, K, Iwata, H, Dörk, T, Bogdanova, NV, Lindblom, A, Margolin, S, Mannermaa, A, Kosma, VM, Chenevix-Trench, G, Wu, AH, Ven Den Berg, D, Smeets, A, Zhao, H, Chang-Claude, J, Rudolph, A, Radice, P, Barile, M, Couch, FJ, Vachon, C, Giles, GG, Milne, RL, Haiman, CA, Marchand, LL, Goldberg, MS, Teo, SH, Taib, NAM, Kristensen, V, and Borresen-Dale, AL

Abstract

The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2:120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Perallelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P

Published
2016

9. Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Author

Couch, FJ, Kuchenbaecker, KB, Michailidou, K, Mendoza-Fandino, GA, Nord, S, Lilyquist, J, Olswold, C, Hallberg, E, Agata, S, Ahsan, H, Aittomäki, K, Ambrosone, C, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, L, Beckmann, MW, Benitez, J, Blank, SV, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Brauch, H, Brenner, H, Burwinkel, B, Buys, SS, Caldes, T, Caligo, MA, Canzian, F, Carpenter, J, Chang-Claude, J, Chanock, SJ, Chung, WK, Claes, KBM, Cox, A, Cross, SS, Cunningham, JM, Czene, K, Daly, MB, Damiola, F, Darabi, H, De La Hoya, M, Devilee, P, Diez, O, Ding, YC, Dolcetti, R, Domchek, SM, Dorfling, CM, Dos-Santos-Silva, I, Dumont, M, Dunning, AM, Eccles, DM, Ehrencrona, H, Ekici, AB, Eliassen, H, Ellis, S, Fasching, PA, Figueroa, J, Flesch-Janys, D, Försti, A, Fostira, F, Foulkes, WD, Friebel, T, Friedman, E, Frost, D, Gabrielson, M, Gammon, MD, Ganz, PA, Gapstur, SM, Garber, J, Gaudet, MM, Gayther, SA, Gerdes, AM, Ghoussaini, M, Giles, GG, Glendon, G, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Greene, MH, Gronwald, J, Guénel, P, Gunter, M, Haeberle, L, and Haiman, CA

Subjects
skin and connective tissue diseases
Abstract

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P

Published
2016

10. Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

Author

Hamdi, Y, Soucy, P, Adoue, V, Michailidou, K, Canisius, S, Lemaçon, A, Droit, A, Andrulis, IL, Anton-Culver, H, Arndt, V, Baynes, C, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Borresen-Dale, AL, Brand, JS, Brauch, H, Brenner, H, Broeks, A, Burwinkel, B, Chang-Claude, J, Couch, FJ, Cox, A, Cross, SS, Czene, K, Darabi, H, Dennis, J, Devilee, P, Dörk, T, Dos-Santos-Silva, I, Eriksson, M, Fasching, PA, Figueroa, J, Flyger, H, García-Closas, M, Giles, GG, Goldberg, MS, González-Neira, A, Grenaker-Alnæs, G, Guénel, P, Haeberle, L, Haiman, CA, Hamann, U, Hallberg, E, Hooning, MJ, Hopper, JL, Jakubowska, A, Jones, M, Kabisch, M, Kataja, V, Lambrechts, D, Le Marchand, L, Lindblom, A, Lubinski, J, Mannermaa, A, Maranian, M, Margolin, S, Marme, F, Milne, RL, Neuhausen, SL, Nevanlinna, H, Neven, P, Olswold, C, Peto, J, Plaseska-Karanfilska, D, Pylkäs, K, Radice, P, Rudolph, A, Sawyer, EJ, Schmidt, MK, Shu, XO, Southey, MC, and Swerdlow, A

Abstract

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance in expression of these genes in breast carcinomas.

Published
2016

11. Large-Scale Genomic Analyses Link Reproductive Aging to Hypothalamic Signaling, Breast Cancer Susceptibility, and BRCA1-Mediated DNA Repair EDITORIAL COMMENT

Author

Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, Lisette, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, Najaf, Corre, T, Hottenga, JJ (Jouke Jan), Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, AL, Boutin, TS, Brauch, H, Brenner, H, Bruning, T, Burwinkel, B, Campbell, A (Archie), Campbell, H, Chanock, SJ, Chapman, JR, Chen, YDI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, de Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Dork, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, XQ, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, Bert, Homuth, G, Hooning, Maartje, Hopper, JL, Hu, FB, Huang, JY, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, VM, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, JM, Li, X, Lindstrom, S, Liu, YM, Luan, JA, Lubinski, J, Magi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Muller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, Fernando, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK (Marjanka), Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, Caroline, Simard, J, Sorice, R, Southey, MC, Stockl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q (Qing), Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, Duijn, Cornelia, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, Jenny, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Systems Ecology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Internal Medicine, Epidemiology, Medical Oncology, and Clinical Genetics

Subjects
SDG 3 - Good Health and Well-being
Published
2015

12. The Transition to Parenthood for Lesbian Couples

Author

Abbie E. Goldberg Ms

Subjects
Gender Studies, Social support, Future studies, Transition (fiction), Gender studies, Lesbian, Psychology, Social Sciences (miscellaneous)
Abstract

While there is a slowly growing literature on lesbians with older children, the literature on the transition to parenthood for lesbian couples is scant. The current study examines aspects of the transition to parenthood experience for 29 lesbian couples. Specifically, this study explores aspects of couples' decision-making regarding alternative insemination (e.g., who would carry and bear the child, donor type), perceptions of social support across the transition to parenthood, and availability and use of legal safeguards (such as wills, powers of attorney, and coparent adoptions by nonbiological mothers). Future studies should explore how single lesbians manage the transition to parenthood. Research on lesbians and gay men who are pursuing parenthood through adoption is also needed.

Published
2006

13. Genetic Predisposition to In Situ and Invasive Lobular Carcinoma of the Breast

Author

Sawyer, E, Roylance, R, Petridis, C, Brook, MN, Nowinski, S, Papouli, E, Fletcher, O, Pinder, S, Hanby, A, Kohut, K, Gorman, P, Caneppele, M, Peto, J, Silva, ID, Johnson, N, Swann, R, Dwek, M, Perkins, KA, Gillett, C, Houlston, R, Ross, G, De Ieso, P, Southey, MC, Hopper, JL, Provenzano, E, Apicella, C, Wesseling, J, Cornelissen, S, Keeman, R, Fasching, PA, Jud, SM, Ekici, AB, Beckmann, MW, Kerin, MJ, Marme, F, Schneeweiss, A, Sohn, C, Burwinkel, B, Guenel, P, Laurent-Puig, P, Kerbrat, P, Bojesen, SE, Nordestgaard, BG, Nielsen, SF, Flyger, H, Milne, RL, Perez, JIA, Menendez, P, Benitez, J, Brenner, H, Dieffenbach, AK, Arndt, V, Stegmaier, C, Meindl, A, Lichtner, P, Schmutzler, RK, Lochmann, M, Brauch, H, Fischer, HP, Ko, YD, Nevanlinna, H, Muranen, TA, Aittomaki, K, Blomqvist, C, Bogdanova, NV, Dork, T, Lindblom, A, Margolin, S, Mannermaa, A, Kataja, V, Kosma, VM, Hartikainen, JM, Chenevix-Trench, G, Lambrechts, D, Weltens, C, van Limbergen, E, Hatse, S, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Radice, P, Peterlongo, P, Bonanni, B, Volorio, S, Giles, GG, Severi, G, Baglietto, L, McLean, CA, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Simard, J, Goldberg, MS, Labreche, F, Dumont, M, Kristensen, V, Winqvist, R, Pylkas, K, Jukkola-Vuorinen, A, Kauppila, S, Andrulis, IL, Knight, JA, Glendon, G, Mulligan, AM, Devillee, P, Tollenaar, RAEM, Seynaeve, Caroline, Kriege, Mieke, Figueroa, J, Chanock, SJ, Sherman, ME, Hooning, Maartje, Hollestelle, Antoinette, van den Ouweland, Ans, van Deurzen, Carolien, Li, JM, Czene, K, Humphreys, K, Cox, A, Cross, SS, Reed, MWR, Shah, M, Jakubowska, A, Lubinski, J, Jaworska-Bieniek, K, Durda, K, Swerdlow, A, Ashworth, A, Orr, N, Schoemaker, M, Couch, FJ, Hallberg, E, Gonzalez-Neira, A, Pita, G, Alonso, MR, Tessier, DC, Vincent, D, Bacot, F, Bolla, MK, Wang, Q (Qing), Dennis, J, Michailidou, K, Dunning, AM, Hall, P, Easton, D, Pharoah, P, Schmidt, Marjanka K, Tomlinson, I, Garcia-Closas, M, Medical Oncology, Clinical Genetics, and Pathology

Subjects
body regions, SDG 3 - Good Health and Well-being, skin and connective tissue diseases
Abstract

Invasive lobular breast cancer (ILC) accounts for 10-15% of all invasive breast carcinomas. It is generally ER positive (ER+) and often associated with lobular carcinoma in situ (LCIS). Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer, but these studies included predominantly ductal (IDC) carcinomas. To identify novel common polymorphisms that predispose to ILC and LCIS, we pooled data from 6,023 cases (5,622 ILC, 401 pure LCIS) and 34,271 controls from 36 studies genotyped using the iCOGS chip. Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases (482 ILC, 36 LCIS) and 1,467 controls. These analyses identified a lobular-specific SNP at 7q34 (rs11977670, OR (95% CI) for ILC = 1.13 (1.09-1.18), P = 6.0x10(-10); P-het for ILC vs IDC ER+ tumors = 1.8x10(-4)). Of the 75 known breast cancer polymorphisms that were genotyped, 56 were associated with ILC and 15 with LCIS at P

Published
2014

14. Common non-synonymous SNPs associated with breast cancer susceptibility: findings from the Breast Cancer Association Consortium

Author

Milne, RL, Burwinkel, B, Michailidou, K, Arias-Perez, JI, Zamora, MP, Menendez-Rodriguez, P, Hardisson, D, Mendiola, M, Gonzalez-Neira, A, Pita, G, Alonso, MR, Dennis, J, Wang, Q (Qing), Bolla, MK, Swerdlow, A, Ashworth, A, Orr, N, Schoemaker, M, Ko, YD, Brauch, H, Hamann, U, Andrulis, IL, Knight, JA, Glendon, G, Tchatchou, S, Matsuo, K, Ito, H, Iwata, H, Tajima, K, Li, JM, Brand, JS, Brenner, H, Dieffenbach, AK, Arndt, V, Stegmaier, C, Lambrechts, D, Peuteman, G, Christiaens, MR, Smeets, A, Jakubowska, A, Lubinski, J, Jaworska-Bieniek, K, Durda, K, Hartman, M, Hui, M, Lim, WY, Chan, CW, Marme, F, Yang, RX, Bugert, P, Lindblom, A, Margolin, S, Garcia-Closas, M, Chanock, SJ, Lissowska, J, Figueroa, JD, Bojesen, SE, Nordestgaard, BG, Flyger, H, Hooning, Maartje, Kriege, Mieke, van den Ouweland, Ans, Koppert, Linetta, Fletcher, O, Johnson, N, dos-Santos-Silva, I, Peto, J, Zheng, W, Deming-Halverson, S, Shrubsole, MJ, Long, JR, Chang-Claude, J, Rudolph, A, Seibold, P, Flesch-Janys, D, Winqvist, R, Pylkas, K, Jukkola-Vuorinen, A, Grip, M, Cox, A, Cross, SS, Reed, MWR, Schmidt, MK (Marjanka), Broeks, A, Cornelissen, S, Braaf, L, Kang, D, Choi, JY, Park, SK, Noh, DY, Simard, J, Dumont, M, Goldberg, MS, Labreche, F, Fasching, PA, Hein, A, Ekici, AB, Beckmann, MW, Radice, P, Peterlongo, P, Azzollini, J, Barile, M, Sawyer, E, Tomlinson, I, Kerin, M, Miller, N, Hopper, JL, Schmidt, DF, Makalic, E, Southey, MC, Teo, SH, Yip, CH, Sivanandan, K, Tay, WT, Shen, CY, Hsiung, CN, Yu, JC, Hou, MF, Guenel, P, Sanchez, M, Mulot, C, Blot, W, Cai, QY, Nevanlinna, H, Muranen, TA, Aittomaki, K, Blomqvist, C, Wu, AH, Tseng, CC, van den Berg, D, Stram, DO, Bogdanova, N, Dork, T, Muir, K, Lophatananon, A, Stewart-Brown, S, Siriwanarangsan, P, Mannermaa, A, Kataja, V, Kosma, VM, Hartikainen, JM, Shu, XO, Lu, W, Gao, YT, Zhang, B, Couch, FJ, Toland, AE, Yannoukakos, D, Sangrajrang, S, Mckay, J, Wang, XS, Olson, JE, Vachon, C, Purrington, K, Severi, G, Baglietto, L, Haiman, CA, Henderson, BE, Schumacher, F, Le Marchand, L, Devilee, P, Tollenaar, RAEM, Seynaeve, Caroline, Czene, K, Eriksson, M, Humphreys, K, Darabi, H, Ahmed, S (Shahana), Shah, M, Pharoah, PDP, Hall, P, Giles, GG, Benitez, J, Dunning, AM, Chenevix-Trench, G, Easton, DF, Clinical Genetics, Cardiothoracic Surgery, Medical Oncology, and Surgery

Subjects
SDG 3 - Good Health and Well-being
Abstract

Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 x 10 26], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 x 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 x 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 x 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 x 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.

Published
2014

15. The Community Competence Scale-Short Form

Author

H. Russell Searight, Barry M. Katz, James D'Andrea Ms, Frank H. Gilner, and Michael A. Goldberg Ms

Subjects
Health (social science), Social Psychology, Psychometrics, business.industry, fungi, Discriminant validity, Test validity, humanities, Clinical Psychology, Nursing, Elderly persons, Internal consistency, Medicine, Residence, Geriatrics and Gerontology, business, Gerontology, Competence (human resources), Reliability (statistics)
Abstract

The Community Competence Scale-Short Form (CCS-SF) is a recently developed competency-based instrument designed to assess the functional capabilities of elderly persons, and hence to aid in the determination of appropriate residential placements. Although the CCS-SF items were originally developed to assess elderly persons, the utility of the short form has only been examined with psychiatric patients. In the present study the CCS-SF was administered to 64 elderly subjects living in a community retirement residence or in a supervised nursing home setting. Results suggest that the CCS-SF has excellent test-retest reliability, internal consistency, and discriminant validity. Hence the CCS-SF appears to have excellent potential as a pre-placement screening instrument for use in determining the most appropriate type of residential placement for geriatric patients. Suggestions for further research to support the utilizing of the CCS-SF for the elderly are made.

Published
1991

22. Associations between cigarette smoking, obesity, sociodemographic characteristics and remote-sensing-derived estimates of ambient PM2.5: results from a Canadian population-based survey.

Author

Villeneuve PJ, Goldberg MS, Burnett RT, van Donkelaar A, Chen H, and Martin RV

Abstract

Objectives Long-term exposure to ambient fine particles (PM(2.5)) has been shown to increase mortality. Variables measured on the same spatial scales of air pollution may confound associations, and so the authors' objectives were to evaluate the associations between PM(2.5) and individual-level measures of smoking, obesity and sociodemographic status. The authors present an approach to evaluate the impact that uncontrolled confounding from smoking may have on associations between PM(2.5) and mortality. Methods Individual-level behavioural and sociodemographic data were obtained from a 2003 national survey of 122548 Canadians. Estimates of ground-level PM(2.5) at a resolution of 10x10 km between 2001 and 2006 were derived from satellite remote sensing. Exposures were assigned to the residence of the participants at the time of the survey. Differences in the prevalence of smoking across concentrations of PM(2.5) and RRs drawn from the literature were used to model the bias on rate ratios. Results Participants in areas with higher concentrations of PM(2.5) had a higher income and educational attainment, smoked less and were more likely immigrants. Smoking had a negative confounding effect on the associations between PM(2.5) and mortality. To compensate for this bias, for a 10 [mu]g/m(3) increase in PM(2.5), mortality from lung cancer and heart disease in the referent exposure group needed to be increased by 6.9% and 3.2%, respectively. Conclusions Associations were found between sociodemographic and lifestyle characteristics and PM(2.5) at a resolution of 10x10 km. The authors present a model to adjust for uncontrolled confounding of smoking that can be readily adapted to exposures measured at different spatial resolutions. [ABSTRACT FROM AUTHOR]

Published
2011

23. Death and injury rates of U.S. military personnel in Iraq.

Author

Goldberg MS and Goldberg, Matthew S

Abstract

In the first 6.5 years of Operation Iraqi Freedom (OIF), U.S. military casualties exceeded 3,400 hostile deaths, 800 nonhostile deaths (due to disease, nonbattle injury, and other causes), and over 31,000 troops wounded in action. Casualty rates in Iraq have been considerably lower that during the Vietnam conflict, and a greater proportion of troops wounded in Iraq survive their wounds. Before the surge in troop levels that began in early 2007, the survival rate was 90.4% in Iraq as compared to 86.5% in Vietnam. Wounded-in-action rates increased during the first few months of the surge, but declined below presurge levels after the number of U.S. brigades in Iraq climbed from 15 to its maximum level of 20. Wounds during the surge were somewhat more lethal than previously, but because there were fewer wounding incidents the net effect was a reduction in the hostile death rate. [ABSTRACT FROM AUTHOR]

Published
2010
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24. The intersection of sound principles of environmental epidemiologic research and ethical guidelines and review: an example from Canada of an environmental case-control study.

Author

Goldberg MS and Goldberg, Mark S

Abstract

The present article challenges the ways in which ethical guidelines are implemented in reviewing the design and conduct of research involving human participants in observational studies in Canada. Fieldwork procedures should be designed in such a way as to be valid scientifically but also acceptable in terms of local ethical considerations, such as confidentiality of participant's identity and information, and other social norms. To set the stage, I present briefly essential information regarding the valid design and conduct of observational epidemiologic studies. As an example of the difficulties encountered in implementing these procedures, I present my experience in gaining ethical approval for a population-based, case-control study of environmental causes of postmenopausal breast cancer. [ABSTRACT FROM AUTHOR]

Published
2010

25. Factors associated with pattern of care before surgery for breast cancer in Quebec between 1992 and 1997.

Author

Shen N, Mayo NE, Scott SC, Hanley JA, Goldberg MS, Abrahamowicz M, and Tamblyn R

Abstract

BACKGROUND: Practice guidelines for breast cancer emphasize the importance of establishing an accurate diagnosis using a minimum number of procedures and selecting optimal treatment regimens. Understanding the determinants of waiting time is essential to develop optimum interventions to reduce delay. OBJECTIVES: The purpose of this study is to estimate the extent to which variability in 1) the number of procedures before surgery and 2) waiting time from initial procedure to surgery are explainable by factors related to the woman, to the provider, and to the care setting. RESEARCH DESIGN: Records of physicians' fee-for-service claims were obtained for 23,370 women undergoing breast cancer surgery in Quebec between 1992 and 1997. Multilevel logistic regression was used to determine predictors of having multiple procedures before surgery. Hierarchical linear regression models were used to identify predictors of waiting time, separately for women with lymph node involvement and without this involvement. RESULTS: Overall, 23% of the women had 3 or more procedures before surgery with significant variation found across hospitals and surgeons. Number of procedures was a strong predictor of waiting time. Waiting time also varied by stage, age, comorbidity, a history of benign disease, surgical setting, calendar time, month of initial procedure, and hospital teaching status. CONCLUSION: Although variability in waiting time was more strongly influenced by the characteristics of the women rather than by physician- or hospital-related factors, most variation remained unexplained by the factors included in this study. To reduce overall waiting time, strategies would need to be systemically applied. [ABSTRACT FROM AUTHOR]

Published
2003
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26. Fine particulate air pollution and all-cause mortality within the Harvard Six-Cities Study: variations in risk by period of exposure.

Author

Villeneuve PJ, Goldberg MS, Krewski D, Burnett RT, Chen Y, Villeneuve, Paul J, Goldberg, Mark S, Krewski, Daniel, Burnett, Richard T, and Chen, Yue

Abstract

Purpose: We used Poisson regression methods to examine the relation between temporal changes in the levels of fine particulate air pollution (PM(2.5)) and the risk of mortality among participants of the Harvard Six Cities longitudinal study.Methods: Our analyses were based on 1430 deaths that occurred between 1974 and 1991 in a cohort that accumulated 105,714 person-years of follow-up. For each city, indices of PM(2.5) were derived using daily samples. Individual level data were collected on several risk factors including: smoking, education, body mass index (BMI), and occupational exposure to dusts. Time-dependent indices of PM(2.5) were created across 13 calendar periods (< 1979, 1979, 1980, em leader, 1989, >/= 1990) to explore whether recent or chronic exposures were more important predictors of mortality.Results: The relative risk (RR) of mortality calculated using Poisson regression based on average city-specific exposures that remained constant during follow-up was 1.31 [95% confidence interval (CI) = 1.12-1.52] per 18.6 microg/m(3) of PM(2.5). This result was similar to the risk calculated using the Cox model (RR = 1.26, 95% CI = 1.08-1.46). The RR of mortality was attenuated when the Poisson regression model included a time-dependent estimate of exposure (RR = 1.19, 95% CI = 1.04-1.36). There was little variation in RR across time-dependent indices of PM(2.5).Conclusions: The attenuated risk of mortality that was observed with a time-dependent index of PM(2.5) is due to the combined influence of city-specific variations in mortality rates and decreasing levels of air pollution that occurred during follow-up. The RR of mortality associated with PM(2.5) did not depend on when exposure occurred in relation to death, possibly because of little variation between the time-dependent city-specific exposure indices. [ABSTRACT FROM AUTHOR]

Published
2002
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34. Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

Author

Barrdahl, M, Rudolph, A, Hopper, JL, Southey, MC, Broeks, A, Fasching, PA, Beckmann, MW, Gago-Dominguez, M, Castelao, JE, Guénel, P, Truong, T, Bojesen, SE, Gapstur, SM, Gaudet, MM, Brenner, H, Arndt, V, Brauch, H, Hamann, U, Mannermaa, A, Lambrechts, D, Jongen, L, Flesch-Janys, D, Thoene, K, Couch, FJ, Giles, GG, Simard, J, Goldberg, MS, Figueroa, J, Michailidou, K, Bolla, MK, Dennis, J, Wang, Q, Eilber, U, Behrens, S, Czene, K, Hall, P, Cox, A, Cross, S, Swerdlow, A, Schoemaker, MJ, Dunning, AM, Kaaks, R, Pharoah, PDP, Schmidt, M, Garcia-Closas, M, Easton, DF, Milne, RL, and Chang-Claude, J

Subjects
breast cancer, gene-environment, single nucleotide polymorphism, Breast Cancer Association Consortium, interaction, 3. Good health
Abstract

Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (OR$_{int}$ = 0.77, 95% CI: 0.67-0.88, p$_{int}$ = 1.8 × 10$^{-4}$. The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (OR$_{int}$ =1.36, 95% CI: 1.16-1.59, pint = 1.9 × 10$^{-5}$ in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (OR$_{int}$ = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10$^{-5}$ and between 8q23-rs13267382 and age at first full-term pregnancy (OR$_{int}$ = 0.89, 95% CI: 0.83-0.95, p$_{int}$ = 5.2 × 10$^{-4}$. While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

35. Association analysis identifies 65 new breast cancer risk loci

Author

Michailidou, K, Lindström, S, Dennis, J, Beesley, J, Hui, S, Kar, S, Lemaçon, A, Soucy, P, Glubb, D, Rostamianfar, A, Bolla, MK, Wang, Q, Tyrer, J, Dicks, E, Lee, A, Wang, Z, Allen, J, Keeman, R, Eilber, U, French, JD, Qing Chen, X, Fachal, L, McCue, K, McCart Reed, AE, Ghoussaini, M, Carroll, JS, Jiang, X, Finucane, H, Adams, M, Adank, MA, Ahsan, H, Aittomäki, K, Anton-Culver, H, Antonenkova, NN, Arndt, V, Aronson, KJ, Arun, B, Auer, PL, Bacot, F, Barrdahl, M, Baynes, C, Beckmann, MW, Behrens, S, Benitez, J, Bermisheva, M, Bernstein, L, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bonanni, B, Børresen-Dale, A-L, Brand, JS, Brauch, H, Brennan, P, Brenner, H, Brinton, L, Broberg, P, Brock, IW, Broeks, A, Brooks-Wilson, A, Brucker, SY, Brüning, T, Burwinkel, B, Butterbach, K, Cai, Q, Cai, H, Caldés, T, Canzian, F, Carracedo, A, Carter, BD, Castelao, JE, Chan, TL, David Cheng, T-Y, Seng Chia, K, Choi, J-Y, Christiansen, H, Clarke, CL, NBCS Collaborators, Collée, M, Conroy, DM, Cordina-Duverger, E, Cornelissen, S, Cox, DG, Cox, A, Cross, SS, Cunningham, JM, Czene, K, Daly, MB, Devilee, P, Doheny, KF, Dörk, T, Dos-Santos-Silva, I, Dumont, M, Durcan, L, Dwek, M, Eccles, DM, Ekici, AB, Eliassen, AH, Ellberg, C, Elvira, M, Engel, C, Eriksson, M, Fasching, PA, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Fritschi, L, Gaborieau, V, Gabrielson, M, Gago-Dominguez, M, Gao, Y-T, Gapstur, SM, García-Sáenz, JA, Gaudet, MM, Georgoulias, V, Giles, GG, Glendon, G, Goldberg, MS, Goldgar, DE, González-Neira, A, Grenaker Alnæs, GI, Grip, M, Gronwald, J, Grundy, A, Guénel, P, Haeberle, L, Hahnen, E, Haiman, CA, Håkansson, N, Hamann, U, Hamel, N, Hankinson, S, Harrington, P, Hart, SN, Hartikainen, JM, Hartman, M, Hein, A, Heyworth, J, Hicks, B, Hillemanns, P, Ho, DN, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Hou, M-F, Hsiung, C-N, Huang, G, Humphreys, K, Ishiguro, J, Ito, H, Iwasaki, M, Iwata, H, Jakubowska, A, Janni, W, John, EM, Johnson, N, Jones, K, Jones, M, Jukkola-Vuorinen, A, Kaaks, R, Kabisch, M, Kaczmarek, K, Kang, D, Kasuga, Y, Kerin, MJ, Khan, S, Khusnutdinova, E, Kiiski, JI, Kim, S-W, Knight, JA, Kosma, V-M, Kristensen, VN, Krüger, U, Kwong, A, Lambrechts, D, Le Marchand, L, Lee, E, Lee, MH, Lee, JW, Neng Lee, C, Lejbkowicz, F, Li, J, Lilyquist, J, Lindblom, A, Lissowska, J, Lo, W-Y, Loibl, S, Long, J, Lophatananon, A, Lubinski, J, Luccarini, C, Lux, MP, Ma, ESK, MacInnis, RJ, Maishman, T, Makalic, E, Malone, KE, Kostovska, IM, Mannermaa, A, Manoukian, S, Manson, JE, Margolin, S, Mariapun, S, Martinez, ME, Matsuo, K, Mavroudis, D, McKay, J, McLean, C, Meijers-Heijboer, H, Meindl, A, Menéndez, P, Menon, U, Meyer, J, Miao, H, Miller, N, Taib, NAM, Muir, K, Mulligan, AM, Mulot, C, Neuhausen, SL, Nevanlinna, H, Neven, P, Nielsen, SF, Noh, D-Y, Nordestgaard, BG, Norman, A, Olopade, OI, Olson, JE, Olsson, H, Olswold, C, Orr, N, Pankratz, VS, Park, SK, Park-Simon, T-W, Lloyd, R, Perez, JIA, Peterlongo, P, Peto, J, Phillips, K-A, Pinchev, M, Plaseska-Karanfilska, D, Prentice, R, Presneau, N, Prokofyeva, D, Pugh, E, Pylkäs, K, Rack, B, Radice, P, Rahman, N, Rennert, G, Rennert, HS, Rhenius, V, Romero, A, Romm, J, Ruddy, KJ, Rüdiger, T, Rudolph, A, Ruebner, M, Rutgers, EJT, Saloustros, E, Sandler, DP, Sangrajrang, S, Sawyer, EJ, Schmidt, DF, Schmutzler, RK, Schneeweiss, A, Schoemaker, MJ, Schumacher, F, Schürmann, P, Scott, RJ, Scott, C, Seal, S, Seynaeve, C, Shah, M, Sharma, P, Shen, C-Y, Sheng, G, Sherman, ME, Shrubsole, MJ, Shu, X-O, Smeets, A, Sohn, C, Southey, MC, Spinelli, JJ, Stegmaier, C, Stewart-Brown, S, Stone, J, Stram, DO, Surowy, H, Swerdlow, A, Tamimi, R, Taylor, JA, Tengström, M, Teo, SH, Beth Terry, M, Tessier, DC, Thanasitthichai, S, Thöne, K, Tollenaar, RAEM, Tomlinson, I, Tong, L, Torres, D, Truong, T, Tseng, C-C, Tsugane, S, Ulmer, H-U, Ursin, G, Untch, M, Vachon, C, Van Asperen, CJ, Van Den Berg, D, Van Den Ouweland, AMW, Van Der Kolk, L, Van Der Luijt, RB, Vincent, D, Vollenweider, J, Waisfisz, Q, Wang-Gohrke, S, Weinberg, CR, Wendt, C, Whittemore, AS, Wildiers, H, Willett, W, Winqvist, R, Wolk, A, Wu, AH, Xia, L, Yamaji, T, Yang, XR, Har Yip, C, Yoo, K-Y, Yu, J-C, Zheng, W, Zheng, Y, Zhu, B, Ziogas, A, Ziv, E, ABCTB Investigators, ConFab/AOCS Investigators, Lakhani, Antoniou, AC, Droit, A, Andrulis, IL, Amos, CI, Couch, FJ, Pharoah, PDP, Chang-Claude, J, Hall, P, Hunter, DJ, Milne, RL, García-Closas, M, Schmidt, MK, Chanock, SJ, Dunning, AM, Edwards, SL, Bader, GD, Chenevix-Trench, G, Simard, J, Kraft, P, and Easton, DF

Subjects
ConFab/AOCS Investigators, ABCTB Investigators, skin and connective tissue diseases, 3. Good health, NBCS Collaborators
Abstract

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

36. rs2735383, located at a microRNA binding site in the 3'UTR of NBS1, is not associated with breast cancer risk

Author

Liu, J, Lončar, I, Collée, JM, Bolla, MK, Dennis, J, Michailidou, K, Wang, Q, Andrulis, IL, Barile, M, Beckmann, MW, Behrens, S, Benitez, J, Blomqvist, C, Boeckx, B, Bogdanova, NV, Bojesen, SE, Brauch, H, Brennan, P, Brenner, H, Broeks, A, Burwinkel, B, Chang-Claude, J, Chen, S-T, Chenevix-Trench, G, Cheng, CY, Choi, J-Y, Couch, FJ, Cox, A, Cross, SS, Cuk, K, Czene, K, Dörk, T, Dos-Santos-Silva, I, Fasching, PA, Figueroa, J, Flyger, H, García-Closas, M, Giles, GG, Glendon, G, Goldberg, MS, González-Neira, A, Guénel, P, Haiman, CA, Hamann, U, Hart, SN, Hartman, M, Hatse, S, Hopper, JL, Ito, H, Jakubowska, A, Kabisch, M, Kang, D, Kosma, V-M, Kristensen, VN, Le Marchand, L, Lee, E, Li, J, Lophatananon, A, Lubinski, Jan, Mannermaa, A, Matsuo, K, Milne, RL, NBCS Collaborators, Neuhausen, SL, Nevanlinna, H, Orr, N, Perez, JIA, Peto, J, Putti, TC, Pylkäs, K, Radice, P, Sangrajrang, S, Sawyer, EJ, Schmidt, MK, Schneeweiss, A, Shen, C-Y, Shrubsole, MJ, Shu, X-O, Simard, J, Southey, MC, Swerdlow, A, Teo, SH, Tessier, DC, Thanasitthichai, S, Tomlinson, I, Torres, D, Truong, T, Tseng, C-C, Vachon, C, Winqvist, R, Wu, AH, Yannoukakos, D, Zheng, W, Hall, P, Dunning, AM, Easton, DF, Hooning, MJ, Van Den Ouweland, AMW, Martens, JWM, and Hollestelle, A

Subjects
BRCA2 Protein, Binding Sites, Genotype, BRCA1 Protein, Nuclear Proteins, Breast Neoplasms, Cell Cycle Proteins, Polymorphism, Single Nucleotide, 3. Good health, MicroRNAs, Risk Factors, Odds Ratio, Humans, Female, Genetic Predisposition to Disease, 3' Untranslated Regions, Alleles
Abstract

NBS1, also known as NBN, plays an important role in maintaining genomic stability. Interestingly, rs2735383 G > C, located in a microRNA binding site in the 3'-untranslated region (UTR) of NBS1, was shown to be associated with increased susceptibility to lung and colorectal cancer. However, the relation between rs2735383 and susceptibility to breast cancer is not yet clear. Therefore, we genotyped rs2735383 in 1,170 familial non-BRCA1/2 breast cancer cases and 1,077 controls using PCR-based restriction fragment length polymorphism (RFLP-PCR) analysis, but found no association between rs2735383CC and breast cancer risk (OR = 1.214, 95% CI = 0.936-1.574, P = 0.144). Because we could not exclude a small effect size due to a limited sample size, we further analyzed imputed rs2735383 genotypes (r$^{2}$ > 0.999) of 47,640 breast cancer cases and 46,656 controls from the Breast Cancer Association Consortium (BCAC). However, rs2735383CC was not associated with overall breast cancer risk in European (OR = 1.014, 95% CI = 0.969-1.060, P = 0.556) nor in Asian women (OR = 0.998, 95% CI = 0.905-1.100, P = 0.961). Subgroup analyses by age, age at menarche, age at menopause, menopausal status, number of pregnancies, breast feeding, family history and receptor status also did not reveal a significant association. This study therefore does not support the involvement of the genotype at NBS1 rs2735383 in breast cancer susceptibility.

37. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

Author

Lawrenson, K, Kar, S, McCue, K, Kuchenbaeker, K, Michailidou, K, Tyrer, J, Beesley, J, Ramus, SJ, Li, Q, Delgado, MK, Lee, JM, Aittomäki, K, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Bandera, EV, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, MW, Benitez, J, Berchuck, A, Bisogna, M, Bjorge, L, Blomqvist, C, Blot, W, Bogdanova, N, Bojesen, A, Bojesen, SE, Bolla, MK, Bonanni, B, Børresen-Dale, A-L, Brauch, H, Brennan, P, Brenner, H, Bruinsma, F, Brunet, J, Buhari, SA, Burwinkel, B, Butzow, R, Buys, SS, Cai, Q, Caldes, T, Campbell, I, Canniotto, R, Chang-Claude, J, Chiquette, J, Choi, J-Y, Claes, KBM, GEMO Study Collaborators, Cook, LS, Cox, A, Cramer, DW, Cross, SS, Cybulski, C, Czene, K, Daly, MB, Damiola, F, Dansonka-Mieszkowska, A, Darabi, H, Dennis, J, Devilee, P, Diez, O, Doherty, JA, Domchek, SM, Dorfling, CM, Dörk, T, Dumont, M, Ehrencrona, H, Ejlertsen, B, Ellis, S, EMBRACE, Engel, C, Lee, E, Evans, DG, Fasching, PA, Feliubadalo, L, Figueroa, J, Flesch-Janys, D, Fletcher, O, Flyger, H, Foretova, L, Fostira, F, Foulkes, WD, Fridley, BL, Friedman, E, Frost, D, Gambino, G, Ganz, PA, Garber, J, García-Closas, M, Gentry-Maharaj, A, Ghoussaini, M, Giles, GG, Glasspool, R, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Goode, EL, Goodman, MT, Greene, MH, Gronwald, J, Guénel, P, Haiman, CA, Hall, P, Hallberg, E, Hamann, U, Hansen, TVO, Harrington, PA, Hartman, M, Hassan, N, Healey, S, Hereditary Breast And Ovarian Cancer Research Group Netherlands (HEBON), Heitz, F, Herzog, J, Høgdall, E, Høgdall, CK, Hogervorst, FBL, Hollestelle, A, Hopper, JL, Hulick, PJ, Huzarski, T, Imyanitov, EN, KConFab Investigators, Australian Ovarian Cancer Study Group, Isaacs, C, Ito, H, Jakubowska, A, Janavicius, R, Jensen, A, John, EM, Johnson, N, Kabisch, M, Kang, D, Kapuscinski, M, Karlan, BY, Khan, S, Kiemeney, LA, Kjaer, SK, Knight, JA, Konstantopoulou, I, Kosma, V-M, Kristensen, V, Kupryjanczyk, J, Kwong, A, De La Hoya, M, Laitman, Y, Lambrechts, D, Le, N, De Leeneer, K, Lester, J, Levine, DA, Li, J, Lindblom, A, Long, J, Lophatananon, A, Loud, JT, Lu, K, Lubinski, J, Mannermaa, A, Manoukian, S, Le Marchand, L, Margolin, S, Marme, F, Massuger, LFAG, Matsuo, K, Mazoyer, S, McGuffog, L, McLean, C, McNeish, I, Meindl, A, Menon, U, Mensenkamp, AR, Milne, RL, Montagna, M, Moysich, KB, Muir, K, Mulligan, AM, Nathanson, KL, Ness, RB, Neuhausen, SL, Nevanlinna, H, Nord, S, Nussbaum, RL, Odunsi, K, Offit, K, Olah, E, Olopade, OI, Olson, JE, Olswold, C, O'Malley, D, Orlow, I, Orr, N, Osorio, A, Park, SK, Pearce, CL, Pejovic, T, Peterlongo, P, Pfeiler, G, Phelan, CM, Poole, EM, Pylkäs, K, Radice, P, Rantala, J, Rashid, MU, Rennert, G, Rhenius, V, Rhiem, K, Risch, HA, Rodriguez, G, Rossing, MA, Rudolph, A, Salvesen, HB, Sangrajrang, S, Sawyer, EJ, Schildkraut, JM, Schmidt, MK, Schmutzler, RK, Sellers, TA, Seynaeve, C, Shah, M, Shen, C-Y, Shu, X-O, Sieh, W, Singer, CF, Sinilnikova, OM, Slager, S, Song, H, Soucy, P, Southey, MC, Stenmark-Askmalm, M, Stoppa-Lyonnet, D, Sutter, C, Swerdlow, A, Tchatchou, S, Teixeira, MR, Teo, SH, Terry, KL, Terry, MB, Thomassen, M, Tibiletti, MG, Tihomirova, L, Tognazzo, S, Toland, AE, Tomlinson, I, Torres, D, Truong, T, Tseng, C-C, Tung, N, Tworoger, SS, Vachon, C, Van Den Ouweland, AMW, Van Doorn, HC, Van Rensburg, EJ, Van't Veer, LJ, Vanderstichele, A, Vergote, I, Vijai, J, Wang, Q, Wang-Gohrke, S, Weitzel, JN, Wentzensen, N, Whittemore, AS, Wildiers, H, Winqvist, R, Wu, AH, Yannoukakos, D, Yoon, S-Y, Yu, J-C, Zheng, W, Zheng, Y, Khanna, KK, Simard, J, Monteiro, AN, French, JD, Couch, FJ, Freedman, ML, Easton, DF, Dunning, AM, Pharoah, PD, Edwards, SL, Chenevix-Trench, G, Antoniou, AC, and Gayther, SA

Subjects
Ovarian Neoplasms, Genotype, Black People, Breast Neoplasms, Polymorphism, Single Nucleotide, 3. Good health, Asian People, Humans, Female, Genetic Predisposition to Disease, RNA, Messenger, Chromosomes, Human, Pair 19, Alleles, Genome-Wide Association Study
Abstract

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P

38. Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Author

Couch, FJ, Kuchenbaecker, KB, Michailidou, K, Mendoza-Fandino, GA, Nord, S, Lilyquist, J, Olswold, C, Hallberg, E, Agata, S, Ahsan, H, Aittomäki, K, Ambrosone, C, Andrulis, IL, Anton-Culver, H, Arndt, V, Arun, BK, Arver, B, Barile, M, Barkardottir, RB, Barrowdale, D, Beckmann, L, Beckmann, MW, Benitez, J, Blank, SV, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Brauch, H, Brenner, H, Burwinkel, B, Buys, SS, Caldes, T, Caligo, MA, Canzian, F, Carpenter, J, Chang-Claude, J, Chanock, SJ, Chung, WK, Claes, KBM, Cox, A, Cross, SS, Cunningham, JM, Czene, K, Daly, MB, Damiola, F, Darabi, H, De La Hoya, M, Devilee, P, Diez, O, Ding, YC, Dolcetti, R, Domchek, SM, Dorfling, CM, Dos-Santos-Silva, I, Dumont, M, Dunning, AM, Eccles, DM, Ehrencrona, H, Ekici, AB, Eliassen, H, Ellis, S, Fasching, PA, Figueroa, J, Flesch-Janys, D, Försti, A, Fostira, F, Foulkes, WD, Friebel, T, Friedman, E, Frost, D, Gabrielson, M, Gammon, MD, Ganz, PA, Gapstur, SM, Garber, J, Gaudet, MM, Gayther, SA, Gerdes, A-M, Ghoussaini, M, Giles, GG, Glendon, G, Godwin, AK, Goldberg, MS, Goldgar, DE, González-Neira, A, Greene, MH, Gronwald, J, Guénel, P, Gunter, M, Haeberle, L, Haiman, CA, Hamann, U, Hansen, TVO, Hart, S, Healey, S, Heikkinen, T, Henderson, BE, Herzog, J, Hogervorst, FBL, Hollestelle, A, Hooning, MJ, Hoover, RN, Hopper, JL, Humphreys, K, Hunter, DJ, Huzarski, T, Imyanitov, EN, Isaacs, C, Jakubowska, A, James, P, Janavicius, R, Jensen, UB, John, EM, Jones, M, Kabisch, M, Kar, S, Karlan, BY, Khan, S, Khaw, K-T, Kibriya, MG, Knight, JA, Ko, Y-D, Konstantopoulou, I, Kosma, V-M, Kristensen, V, Kwong, A, Laitman, Y, Lambrechts, D, Lazaro, C, Lee, E, Le Marchand, L, Lester, J, Lindblom, A, Lindor, N, Lindstrom, S, Liu, J, Long, J, Lubinski, J, Mai, PL, Makalic, E, Malone, KE, Mannermaa, A, Manoukian, S, Margolin, S, Marme, F, Martens, JWM, McGuffog, L, Meindl, A, Miller, A, Milne, RL, Miron, P, Montagna, M, Mazoyer, S, Mulligan, AM, Muranen, TA, Nathanson, KL, Neuhausen, SL, Nevanlinna, H, Nordestgaard, BG, Nussbaum, RL, Offit, K, Olah, E, Olopade, OI, Olson, JE, Osorio, A, Park, SK, Peeters, PH, Peissel, B, Peterlongo, P, Peto, J, Phelan, CM, Pilarski, R, Poppe, B, Pylkäs, K, Radice, P, Rahman, N, Rantala, J, Rappaport, C, Rennert, G, Richardson, A, Robson, M, Romieu, I, Rudolph, A, Rutgers, EJ, Sanchez, M-J, Santella, RM, Sawyer, EJ, Schmidt, DF, Schmidt, MK, Schmutzler, RK, Schumacher, F, Scott, R, Senter, L, Sharma, P, Simard, J, Singer, CF, Sinilnikova, OM, Soucy, P, Southey, M, Steinemann, D, Stenmark-Askmalm, M, Stoppa-Lyonnet, D, Swerdlow, A, Szabo, CI, Tamimi, R, Tapper, W, Teixeira, MR, Teo, S-H, Terry, MB, Thomassen, M, Thompson, D, Tihomirova, L, Toland, AE, Tollenaar, RAEM, Tomlinson, I, Truong, T, Tsimiklis, H, Teulé, A, Tumino, R, Tung, N, Turnbull, C, Ursin, G, Van Deurzen, CHM, Van Rensburg, EJ, Varon-Mateeva, R, Wang, Z, Wang-Gohrke, S, Weiderpass, E, Weitzel, JN, Whittemore, A, Wildiers, H, Winqvist, R, Yang, XR, Yannoukakos, D, Yao, S, Zamora, MP, Zheng, W, Hall, P, Kraft, P, Vachon, C, Slager, S, Chenevix-Trench, G, Pharoah, PDP, Monteiro, AAN, García-Closas, M, Easton, DF, and Antoniou, AC

Subjects
Heterozygote, tRNA Methyltransferases, Genotype, BRCA1 Protein, Breast Neoplasms, Polymorphism, Single Nucleotide, 3. Good health, Cyclophilins, Receptors, Estrogen, Risk Factors, Chromosomes, Human, Pair 2, Mutation, Humans, Female, Genetic Predisposition to Disease, Genome-Wide Association Study
Abstract

This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms11375, Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P

39. Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

Author

Hamdi, Y, Soucy, P, Adoue, V, Michailidou, K, Canisius, S, Lemaçon, A, Droit, A, Andrulis, IL, Anton-Culver, H, Arndt, V, Baynes, C, Blomqvist, C, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bonanni, B, Borresen-Dale, A-L, Brand, JS, Brauch, H, Brenner, H, Broeks, A, Burwinkel, B, Chang-Claude, J, Collaborators, N, Couch, FJ, Cox, A, Cross, SS, Czene, K, Darabi, H, Dennis, J, Devilee, P, Dörk, T, Dos-Santos-Silva, I, Eriksson, M, Fasching, PA, Figueroa, J, Flyger, H, García-Closas, M, Giles, GG, Goldberg, MS, González-Neira, A, Grenaker-Alnæs, G, Guénel, P, Haeberle, L, Haiman, CA, Hamann, U, Hallberg, E, Hooning, MJ, Hopper, JL, Jakubowska, A, Jones, M, Kabisch, M, Kataja, V, Lambrechts, D, Le Marchand, L, Lindblom, A, Lubinski, J, Mannermaa, A, Maranian, M, Margolin, S, Marme, F, Milne, RL, Neuhausen, SL, Nevanlinna, H, Neven, P, Olswold, C, Peto, J, Plaseska-Karanfilska, D, Pylkäs, K, Radice, P, Rudolph, A, Sawyer, EJ, Schmidt, MK, Shu, X-O, Southey, MC, Swerdlow, A, Tollenaar, RAEM, Tomlinson, I, Torres, D, Truong, T, Vachon, C, Van Den Ouweland, AMW, Wang, Q, Winqvist, R, KConFab/Aocs Investigators, Zheng, W, Benitez, J, Chenevix-Trench, G, Dunning, AM, Pharoah, PDP, Kristensen, V, Hall, P, Easton, DF, Pastinen, T, Nord, S, and Simard, J

Subjects
breast cancer, association studies, differential allelic expression, cis-regulatory variants, 3. Good health, genetic susceptibility
Abstract

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, $\textit{cis}$-acting variants represent an important source of phenotypic variation. Consequently, $\textit{cis}$-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, $\textit{P}$ = 5.6x10$^{-6}$). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, $\textit{HELQ}$, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, $\textit{MRPS18C}$ encoding the Mitochondrial Ribosomal Protein S18C and $\textit{FAM175A (ABRAXAS)}$, encoding a $\textit{BRCA1}$ BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with $\textit{HELQ }$ ($\textit{P}$ = 8.28x10$^{-14}$), $\textit{MRPS18C}$ ($\textit{P}$ = 1.94x10$^{-27}$) and $\textit{FAM175A }$ ($\textit{P}$ = 3.83x10$^{-3}$), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.

41. Predicting adjuvant radiation therapy benefit in cutaneous squamous cell carcinoma with the 40-gene expression profile.

Author

Ruiz ES, Brito K, Karn EE, Vidimos AT, Campbell SR, Wang DM, Siegel JJ, Covington KR, Cook RW, Goldberg MS, and Koyfman SA

Abstract

Aim: To independently confirm that the 40-gene expression profile (40-GEP) test can identify patients with high-risk cutaneous squamous cell carcinoma who are more or less likely to benefit from adjuvant radiation therapy (ART). Materials & methods: Primary cutaneous squamous cell carcinoma tumors from two academic centers received retrospective 40-GEP testing and were analyzed for 5-year metastasis-free survival and projected time to event. Results: Random sampling of matched patient pairs ( n  = 52 ART-treated; 371 no ART) showed a median 50% decrease in 5-year progression rate for ART-treated patients (vs no ART) with 40-GEP Class 2B. Class 2A was associated with a modest ART benefit, but not Class 1. Conclusion: The 40-GEP identified patients most likely to benefit from ART (Class 2B) and those that can consider deferring treatment (Class 1).

Published
2024
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42. RE: External validation of the Melanoma Institute Australia sentinel lymph metastasis risk prediction tool using the National Cancer Database.

Author

Prieto PA, Goldberg MS, and Martin B

Subjects
Humans, Australia epidemiology, Risk Assessment statistics & numerical data, Sentinel Lymph Node Biopsy statistics & numerical data, Sentinel Lymph Node pathology, Melanoma pathology, Melanoma epidemiology, Skin Neoplasms pathology, Skin Neoplasms epidemiology, Databases, Factual, Lymphatic Metastasis pathology
Abstract

Competing Interests: Conflicts of interest Dr Prieto is on the speaker’s bureau for Castle Biosciences, Inc. Drs Goldberg and Martin are employees and stock/option holders at Castle Biosciences, Inc.

Published
2024
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43. Appropriate Statistical Methods to Assess Cross-study Diagnostic 23-Gene Expression Profile Test Performance for Cutaneous Melanocytic Neoplasms.

Author

Goldberg MS, Cockerell CJ, Rogers JH, Siegel JJ, Russell BH, Hosler GA, and Marks E

Abstract

Abstract: Comparing studies of molecular ancillary diagnostic tests for difficult-to-diagnose cutaneous melanocytic neoplasms presents a methodological challenge, given the disparate ways accuracy metrics are calculated. A recent report by Boothby-Shoemaker et al investigating the real-world accuracy of the 23-gene expression profile (23-GEP) test highlights this methodological difficulty, reporting lower accuracy than previously observed. However, their calculation method-with indeterminate test results defined as either false positive or false negative-was different than those used in previous studies. We corrected for these differences and recalculated their reported accuracy metrics in the same manner as the previous studies to enable appropriate comparison with previously published reports. This corrected analysis showed a sensitivity of 92.1% (95% confidence interval [CI], 82.1%-100%) and specificity of 94.4% (91.6%-96.9%). We then compared these results directly to previous studies with >25 benign and >25 malignant cases with outcomes and/or concordant histopathological diagnosis by ≥3 dermatopathologists. All studies assessed had enrollment imbalances of benign versus malignant patients (0.8-7.0 ratio), so balanced cohorts were resampled according to the lowest common denominator to calculate point estimates and CIs for accuracy metrics. Overall, we found no statistically significant differences in the ranges of 23-GEP sensitivity, 90.4%-96.3% (95% CI, 80.8%-100%), specificity, 87.3%-96.2% (78.2%-100%), positive predictive value, 88.5%-96.1% (81.5%-100%), or negative predictive value, 91.1%-96.3% (83.6%-100%) between previous studies and the cohort from Boothby-Shoemaker et al with this unified methodological approach. Rigorous standardization of calculation methods is necessary when the goal is direct cross-study comparability., Competing Interests: E. Marks has served as a consultant for Castle Biosciences, Inc. C. J. Cockerell has served as a consultant and advisory board member for Castle Biosciences, Inc. J. H. Rogers, J. J. Siegel, B. H. Russell, and M. S. Goldberg are employees and shareholders of Castle Biosciences, Inc., the current laboratory where the 23-gene expression profile test is performed. The remaining authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

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2024
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44. Diagnostic discordance among histopathological reviewers of melanocytic lesions.

Author

Hosler GA, Goldberg MS, Estrada SI, O'Neil B, Amin SM, and Plaza JA

Subjects
Humans, Female, Male, Adult, Middle Aged, Melanocytes pathology, Aged, Diagnosis, Differential, Skin Neoplasms pathology, Skin Neoplasms diagnosis, Melanoma pathology, Melanoma diagnosis
Abstract

Background: Histopathological examination is adequate for the diagnosis of most cutaneous melanocytic neoplasms. However, there is a subset that is either difficult to definitively diagnose or would have diagnostic disagreement upon review by multiple dermatopathologists if a more exhaustive review was performed., Methods: Melanocytic lesions underwent an independent, blinded diagnostic histopathological review of hematoxylin and eosin-stained sections. Each lesion was reviewed by three to six dermatopathologists and categorized as benign, malignant, or unknown malignant potential (UMP). Diagnoses were grouped as concordant (all the same designation); opposing (received benign and malignant designations); majority (single designation with the highest number of diagnoses, no benign/malignant opposing designations); and non-definitive (equal number of non-opposing designations [i.e., benign/UMP or malignant/UMP]). Lesions with equivocal designations (concordant or majority UMP, opposing, majority, and non-definitive) were utilized in a patient treatment model of projected surgical treatment discrepancies., Results: In total, 3317 cases were reviewed, and 23.8% of lesions received equivocal diagnoses. Of these, 7.3% were majority benign, 4.8% were majority malignant, 2.7% were majority UMP, 0.5% were concordant UMP, 6.9% were opposing, and 1.6% were non-definitive. Patient treatment models of those with equivocal lesions (n = 788) revealed a potential of overall surgical treatment variations ranging from 18% to 72%, with the highest variation amongst lesions with opposing, non-definitive, or majority UMP (40%-72%) diagnoses., Conclusion: Histopathologic review in this large cohort demonstrated substantial diagnostic variation, with 23.8% of cases receiving equivocal diagnoses. We identified diagnostic ambiguity even in lesions where a definitive diagnosis was previously rendered by a single real-world dermatopathologist. The combined clinical impact of diagnostic discordance or a final diagnosis of UMP is highlighted by high diagnosis-dependent treatment variation in the patient treatment model, which could be underreported in a real-world setting, where review by more than one to two dermatopathologists is relatively rare., (© 2024 Castle Biosciences, Inc and The Authors. Journal of Cutaneous Pathology published by John Wiley & Sons Ltd.)

Published
2024
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45. RAB32 Ser71Arg in autosomal dominant Parkinson's disease: linkage, association, and functional analyses.

Author

Gustavsson EK, Follett J, Trinh J, Barodia SK, Real R, Liu Z, Grant-Peters M, Fox JD, Appel-Cresswell S, Stoessl AJ, Rajput A, Rajput AH, Auer R, Tilney R, Sturm M, Haack TB, Lesage S, Tesson C, Brice A, Vilariño-Güell C, Ryten M, Goldberg MS, West AB, Hu MT, Morris HR, Sharma M, Gan-Or Z, Samanci B, Lis P, Periñan MT, Amouri R, Ben Sassi S, Hentati F, Tonelli F, Alessi DR, and Farrer MJ

Subjects
Adult, Aged, Female, Humans, Male, Middle Aged, Canada epidemiology, Case-Control Studies, Exome Sequencing, Genetic Linkage genetics, Genetic Predisposition to Disease genetics, Genotype, Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 genetics, Tunisia, Parkinson Disease genetics, rab GTP-Binding Proteins genetics
Abstract

Background: Parkinson's disease is a progressive neurodegenerative disorder with multifactorial causes, among which genetic risk factors play a part. The RAB GTPases are regulators and substrates of LRRK2, and variants in the LRRK2 gene are important risk factors for Parkinson's disease. We aimed to explore genetic variability in RAB GTPases within cases of familial Parkinson's disease., Methods: We did whole-exome sequencing in probands from families in Canada and Tunisia with Parkinson's disease without a genetic cause, who were recruited from the Centre for Applied Neurogenetics (Vancouver, BC, Canada), an international consortium that includes people with Parkinson's disease from 36 sites in 24 countries. 61 RAB GTPases were genetically screened, and candidate variants were genotyped in relatives of the probands to assess disease segregation by linkage analysis. Genotyping was also done to assess variant frequencies in individuals with idiopathic Parkinson's disease and controls, matched for age and sex, who were also from the Centre for Applied Neurogenetics but unrelated to the probands or each other. All participants were aged 18 years or older. The sequencing and genotyping findings were validated by case-control association analyses using bioinformatic data obtained from publicly available clinicogenomic databases (AMP-PD, GP2, and 100 000 Genomes Project) and a private German clinical diagnostic database (University of Tübingen). Clinical and pathological findings were summarised and haplotypes were determined. In-vitro studies were done to investigate protein interactions and enzyme activities., Findings: Between June 1, 2010, and May 31, 2017, 130 probands from Canada and Tunisia (47 [36%] female and 83 [64%] male; mean age 72·7 years [SD 11·7; range 38-96]; 109 White European ancestry, 18 north African, two east Asian, and one Hispanic] underwent whole-exome sequencing. 15 variants in RAB GTPase genes were identified, of which the RAB32 variant c.213C>G (Ser71Arg) cosegregated with autosomal dominant Parkinson's disease in three families (nine affected individuals; non-parametric linkage Z score=1·95; p=0·03). 2604 unrelated individuals with Parkinson's disease and 344 matched controls were additionally genotyped, and five more people originating from five countries (Canada, Italy, Poland, Turkey, and Tunisia) were identified with the RAB32 variant. From the database searches, in which 6043 individuals with Parkinson's disease and 62 549 controls were included, another eight individuals were identified with the RAB32 variant from four countries (Canada, Germany, UK, and USA). Overall, the association of RAB32 c.213C>G (Ser71Arg) with Parkinson's disease was significant (odds ratio [OR] 13·17, 95% CI 2·15-87·23; p=0·0055; I 2 =99·96%). In the people who had the variant, Parkinson's disease presented at age 54·6 years (SD 12·75, range 31-81, n=16), and two-thirds had a family history of parkinsonism. RAB32 Ser71Arg heterozygotes shared a common haplotype, although penetrance was incomplete. Findings in one individual at autopsy showed sparse neurofibrillary tangle pathology in the midbrain and thalamus, without Lewy body pathology. In functional studies, RAB32 Arg71 activated LRRK2 kinase to a level greater than RAB32 Ser71., Interpretation: RAB32 Ser71Arg is a novel genetic risk factor for Parkinson's disease, with reduced penetrance. The variant was found in individuals with Parkinson's disease from multiple ethnic groups, with the same haplotype. In-vitro assays show that RAB32 Arg71 activates LRRK2 kinase, which indicates that genetically distinct causes of familial parkinsonism share the same mechanism. The discovery of RAB32 Ser71Arg also suggests several genetically inherited causes of Parkinson's disease originated to control intracellular immunity. This shared aetiology should be considered in future translational research, while the global epidemiology of RAB32 Ser71Arg needs to be assessed to inform genetic counselling., Funding: National Institutes of Health, the Canada Excellence Research Chairs program, Aligning Science Across Parkinson's, the Michael J Fox Foundation for Parkinson's Research, and the UK Medical Research Council., Competing Interests: Declaration of interests AR receives unrestricted research support from the Dr Ali Rajput Endowment for Parkinson's Disease and Movement Disorders; in the past 2 years AR has received honoraria from Quebec Consortium for Drug Discovery–Brain Canada and Ipsen Biopharmaceuticals Canada. MSG reports grants from National Institutes of Health (NIH)–National Institute of Neurological Disorders and Stroke (NINDS) and the Michael J Fox Foundation for Parkinson's Research. AJS has received fees from Neurocrine (Chair, Data and Safety Monitoring Board [DSMB]), AskBio (Member, DSMB) and Capsida (advisor), receives a stipend from the International Parkinson's and Movement Disorders Society (Editor-in-Chief, Movement Disorders) and grant funding from Michael J Fox Foundation, Weston Brain Institute, and Brain Canada. ZG-O received consultancy fees from Bial Biotec, Bial, Capsida, Handl Therapeutics, Idorsia, Neuron23, Ono Therapeutics, Prevail Therapeutics, UCB, and Vanqua. He reports grants from the Michael J Fox Foundation for Parkinson's Research, The Weston Family Foundation, The Silverstein Foundation, NIH, and the Canadian Consortium on Neurodegeneration in Aging. HRM is employed by University College Londn. In the last 12 months he reports paid consultancy from Roche, Aprinoia, AI Therapeutics, and Amylyx; lecture fees or honoraria from BMJ, Kyowa Kirin, Movement Disorders Society; and research grants from Parkinson's UK, Cure Parkinson's Trust, PSP Association, Medical Research Council, and Michael J Fox Foundation. HRM is a co-applicant on a patent application related to C9ORF72: method for diagnosing a neurodegenerative disease (PCT/GB2012/052140). MJF reports US patents associated with LRRK2 mutations and mouse models (8409809 and 8455243), and methods of treating neurodegenerative disease (20110092565). SA-C has received honoraria from Merz, and grant funding from the Pacific Parkinson's Research Institute, the Weston Family Foundation, Parkinson Canada, Canadian Institutes of Health Research (CIHR), the VGH and UBC Hospital Foundation, Rick's Heart Foundation, and the Jack and Darlene Poole Foundation. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Published
2024
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46. A clinical impact study of dermatologists' use of diagnostic gene expression profile testing to guide patient management.

Author

Witkowski A, Jarell AD, Ahmed KL, Siegel JJ, Russell BH, Rogers JH, Goldberg MS, Fernandes NF, Ludzik J, and Farberg AS

Abstract

Aim: Cutaneous melanocytic neoplasms with diagnostic and/or clinical ambiguity pose patient management challenges. Methods: Six randomized case scenarios with diagnostic/clinical uncertainty were described with/without a benign or malignant diagnostic gene expression profile (GEP) result. Results: Clinical impact was assessed by reporting the mean increase/decrease of management changes normalized to baseline (n = 32 dermatologists). Benign GEP results prompted clinicians to decrease surgical margins (84.2%). Malignant GEP results escalated surgical excision recommendations (100%). A majority (72.2%) reduced and nearly all (98.9%) increased follow-up frequency for benign or malignant GEP results, respectively. There was an overall increase in management plan confidence with GEP results. Conclusion: Diagnostic GEP tests help guide clinical decision-making in a variety of diagnostically ambiguous or clinicopathologically discordant scenarios., Competing Interests: The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties., (© 2024 The Authors.)

Published
2024
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47. Basal activity of PINK1 and PRKN in cell models and rodent brain.

Author

Watzlawik JO, Fiesel FC, Fiorino G, Bustillos BA, Baninameh Z, Markham BN, Hou X, Hayes CS, Bredenberg JM, Kurchaba NW, Fričová D, Siuda J, Wszolek ZK, Noda S, Sato S, Hattori N, Prasad AA, Kirik D, Fox HS, Stauch KL, Goldberg MS, and Springer W

Subjects
Animals, Humans, Neurons metabolism, Mitochondria metabolism, Mice, Mitophagy physiology, Rats, Models, Biological, Mice, Inbred C57BL, Signal Transduction, Protein Kinases metabolism, Brain metabolism, Ubiquitin-Protein Ligases metabolism
Abstract

The ubiquitin kinase-ligase pair PINK1-PRKN recognizes and transiently labels damaged mitochondria with ubiquitin phosphorylated at Ser65 (p-S65-Ub) to mediate their selective degradation (mitophagy). Complete loss of PINK1 or PRKN function unequivocally leads to early-onset Parkinson disease, but it is debated whether impairments in mitophagy contribute to disease later in life. While the pathway has been extensively studied in cell culture upon acute and massive mitochondrial stress, basal levels of activation under endogenous conditions and especially in vivo in the brain remain undetermined. Using rodent samples, patient-derived cells, and isogenic neurons, we here identified age-dependent, brain region-, and cell type-specific effects and determined expression levels and extent of basal and maximal activation of PINK1 and PRKN. Our work highlights the importance of defining critical risk and therapeutically relevant levels of PINK1-PRKN signaling which will further improve diagnosis and prognosis and will lead to better stratification of patients for future clinical trials.

Published
2024
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48. Alterations of PINK1-PRKN signaling in mice during normal aging.

Author

Baninameh Z, Watzlawik JO, Hou X, Richardson T, Kurchaba NW, Yan T, Di Florio DN, Fairweather D, Kang L, Nguyen JH, Kanekiyo T, Dickson DW, Noda S, Sato S, Hattori N, Goldberg MS, Ganley IG, Stauch KL, Fiesel FC, and Springer W

Abstract

The ubiquitin kinase-ligase pair PINK1-PRKN identifies and selectively marks damaged mitochondria for elimination via the autophagy-lysosome system (mitophagy). While this cytoprotective pathway has been extensively studied in vitro upon acute and complete depolarization of mitochondria, the significance of PINK1-PRKN mitophagy in vivo is less well established. Here we used a novel approach to study PINK1-PRKN signaling in different energetically demanding tissues of mice during normal aging. We demonstrate a generally increased expression of both genes and enhanced enzymatic activity with aging across tissue types. Collectively our data suggest a distinct regulation of PINK1-PRKN signaling under basal conditions with the most pronounced activation and flux of the pathway in mouse heart compared to brain or skeletal muscle. Our biochemical analyses complement existing mitophagy reporter readouts and provide an important baseline assessment in vivo, setting the stage for further investigations of the PINK1-PRKN pathway during stress and in relevant disease conditions.

Published
2024
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49. Improving systemic therapy selection for inflammatory skin diseases: A clinical need survey.

Author

Brownstone ND, Farberg AS, Litchman GH, Quick AP, Siegel JJ, Hurton LV, Goldberg MS, and Lio PA

Abstract

Background: Empirical decisions to select therapies for psoriasis (PSO) and atopic dermatitis (AD) can lead to delays in disease control and increased health care costs. However, routine molecular testing for AD and PSO are lacking., Objective: To examine (1) how clinicians choose systemic therapies for patients with PSO and AD without molecular testing and (2) to determine how often the current approach leads to patients switching medications., Methods: A 20-question survey designed to assess clinician strategies for systemic treatment of AD and PSO was made available to attendees of a national dermatology conference in 2022., Results: Clinicians participating in the survey (265/414, 64% response rate) ranked "reported efficacy" as the most important factor governing treatment choice ( P  < .001). However, 62% (165/265) of clinicians estimated that 2 or more systemic medications were typically required to achieve efficacy. Over 90% (239/265) of respondents would or would likely find a molecular test to guide therapeutic selection useful., Limitations: To facilitate ease of recall, questions focused on systemic therapies as a whole and not individual therapies., Conclusion: Clinicians want a molecular test to help determine the most efficacious drug for individual patients., Competing Interests: Dr Brownstone received a stipend paid for by Castle Biosciences, Inc. Dr Farberg is a consultant for Castle Biosciences, Inc and on the advisory board for Amgen, Boehringer Ingelheim, Eli Lilly, Galderma, Incyte, Janssen, Novartis, Ortho Dermatologics, Pfizer, and Sun Pharma. Drs Quick, Siegel, Hurton, and Goldberg are employees and option and stockholders for Castle Biosciences, Inc. Dr Lio reports research grants/funding from AbbVie, AOBiome, Eczema Foundation, National Eczema Association; is on the speaker's bureau for AbbVie, Eli Lilly, Galderma, Hyphens Pharma, Incyte, La Roche-Posay/L’Oreal, MyOR Diagnostics, ParentMD, Pfizer, Pierre-Fabre Dermatologie, and Regeneron/Sanofi Genzyme; reports consulting/advisory boards for AbbVie, Almirall, Amyris, Arbonne, ASLAN, Bodewell, Boston Skin Science, Bristol-Myers Squibb, Burt’s Bees, Castle Biosciences, Codex Labs, Concerto Biosci, Dermavant, Dermira, DermVeda, Eli Lilly, Galderma, IntraDerm, Janssen, Johnson & Johnson, Kaleido Biosci, Kimberly Clark, LEO Pharma, Lipidor, L’Oreal, Menlo Therapeutics, Merck, Micreos, MyOR Diagnostics, Regeneron/Sanofi Genzyme, Sibel Health, Skinfix, Sonica, Theraplex, UCB, Unilever, Verrica, and Yobee Care; reports stock options with LearnSkin/Learn Health, Medable, Micreos, Modernizing Medicine, and Yobee Care. In addition, Dr Lio has a patent pending for a Theraplex product with royalties paid and is a Board member and Scientific Advisory Committee Member of the National Eczema Association. Author Litchman has no conflicts of interest to declare., (© 2024 by the American Academy of Dermatology, Inc. Published by Elsevier Inc.)

Published
2024
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50. Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients.

Author

Wysong A, Somani AK, Ibrahim SF, Cañueto J, Fitzgerald AL, Siegel JJ, Prasai A, Goldberg MS, Farberg AS, Regula C, Bar A, Kasprzak J, Brodland DG, Koyfman SA, and Arron ST

Abstract

Introduction: The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old., Methods: This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP., Results: Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models)., Conclusion: The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions., (© 2024. The Author(s).)

Published
2024
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