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Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations.Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

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Supplemental Table 1: Detailed characteristics of studies included in the ASSET meta-analysis of DNA damage repair and signaling genes. Supplemental Table 2: DNA repair gene, region, and final SNP selection data, using human reference genome assembly, GRCh38. Supplemental Table 3: List of all DNA repair genes and DNA repair pathways included in this study. Supplemental Table 4: Statistical associations (p-values) for cancer risk versus genetic variation within DNA repair pathways. Sensitivity analysis of Table 3, with RAD51B, MSH5, and BRCA2 gene removed from analysis. Statistically significant values are in bold (p < 0.05). Supplemental Table 5: Statistical associations (p-values) for cancer risk versus genetic variation within DNA repair pathways. Sensitivity analysis of Table 3, with 6 genes removed from the analysis -- all genes containing loci with individual SNP associations of p < 1 x 10-4. Statistically significant values are in bold (p < 0.05).

Supplemental Figure and Table Legend

Supplementary Figures 1-5, Tables 1-8. Supplementary Figure 1: Overview of the analytic approach. Supplementary Figure 2: QQ plots of SNPs with MAF ≥0.02 and imputation r2 ≥0.9 associated with Overall Survival in A. Supplementary Figure 3: ‘All OCAC’ histology-adjusted analysis. Supplementary Figure 4: Forest plots of promising SNPs. Supplementary Figure 5: KM-Plotter graphs of significant associations with outcome. Supplementary Table 1: All studies (OCAC & TCGA) eligible for analyses according to first-line chemotherapy. Supplementary Table 2: Description of individual OCAC studies included in the secondary 'all OCAC' analysis. Supplementary Table 3a: Overall Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 3b: Progression-free Survival estimates for selected SNPs (MAF ≥0.02) comparing iCOGS imputed (r2 ≥0.3) and iPLEX genotyped samples. Supplementary Table 4: SNPs with imputation r2 ≥0.9, EAF ≥0.02 and p ≤ 1E-05 for at least one of four outcomes analyzed in cases selected according to first-line chemotherapy. Supplementary Table 5: Meta-analysis of largest possible sample (TCGA, non-overlapping iCOGS and iplex genotyped) for selected promising SNPs analyzed in cases selected according to first-line chemotherapy. Supplementary Table 6: Significant association between protein-coding genes within 1Mb of promising SNPs and ovarian cancer outcomes. Supplementary Table 7: SNPs with imputation r-sq≥0.9 and p ≤ 1E-05 for Overall Survival in histology-adj 'all OCAC' analysis. Supplementary Table 8: iCOGS estimates for SNPs previously identified to be associated with response to chemotherapy as reported in the aNHGRI GWAS catalog.

Supplementary Tables S1-S3 from Microarray Analysis of Early Stage Serous Ovarian Cancers Shows Profiles Predictive of Favorable Outcome

Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC).Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped).Results: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6; Pcorrected = 0.01).Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed.Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446–54. ©2016 AACR.

Purpose: Although few women with advanced serous ovarian cancer are cured, detection of the disease at an early stage is associated with a much higher likelihood of survival. We previously used gene expression array analysis to distinguish subsets of advanced cancers based on disease outcome. In the present study, we report on gene expression of early-stage cancers and validate our prognostic model for advanced-stage cancers.Experimental Design: Frozen specimens from 39 stage I/II, 42 stage III/IV, and 20 low malignant potential cancers were obtained from four different sites. A linear discriminant model was used to predict survival based upon array data.Results: We validated the late-stage survival model and show that three of the most differentially expressed genes continue to be predictive of outcome. Most early-stage cancers (38 of 39 invasive, 15 of 20 low malignant potential) were classified as long-term survivors (median probabilities 0.97 and 0.86). MAL, the most differentially expressed gene, was further validated at the protein level and found to be an independent predictor of poor survival in an unselected group of advanced serous cancers (P = 0.0004).Conclusions: These data suggest that serous ovarian cancers detected at an early stage generally have a favorable underlying biology similar to advanced-stage cases that are long-term survivors. Conversely, most late-stage ovarian cancers seem to have a more virulent biology. This insight suggests that if screening approaches are to succeed it will be necessary to develop approaches that are able to detect these virulent cancers at an early stage.

Associations between continuous total lifetime number of ovulatory cycles and ovarian cancer by tumor aggressiveness considering mutual adjustment for LOC component factors: duration of oral contraceptive use and pregnancies, Ovarian Cancer Cohort Consortium (OC3).

Repeated exposure to the acute proinflammatory environment that follows ovulation at the ovarian surface and distal fallopian tube over a woman's reproductive years may increase ovarian cancer risk. To address this, analyses included individual-level data from 558,709 naturally menopausal women across 20 prospective cohorts, among whom 3,246 developed invasive epithelial ovarian cancer (2,045 serous, 319 endometrioid, 184 mucinous, 121 clear cell, 577 other/unknown). Cox models were used to estimate multivariable-adjusted HRs between lifetime ovulatory cycles (LOC) and its components and ovarian cancer risk overall and by histotype. Women in the 90th percentile of LOC (>514 cycles) were almost twice as likely to be diagnosed with ovarian cancer than women in the 10th percentile (Significance:Although ovarian cancer is rare, risk of most ovarian cancers doubles as the number of lifetime ovulatory cycles increases from approximately 300 to 500. Thus, identifying an important area for cancer prevention research.

Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome.Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis.Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3).Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Participant and Clinical Information Form. Study forms used to obtain subject and clinical information.

Supplementary Figures 1-2, Tables 1-5. Supplemental Figure 1. Flow diagrams showing the design and collection of the reference set. Supplemental Figure 2. Clustering of the 90 analytes across all 505 subjects. Supplemental Table 1: Subjects in the final breast cancer reference set according to diagnosis and site of collection. Supplemental Table 2: The identity of the biomarkers analyzed and their membership in specific multiplexed panels. Supplemental Table 3: Subject demographics in the Breast Cancer Reference Sets. Supplemental Table 4: Significant differences in marker levels between subjects with benign breast disease without atypia compared to mammographic screen normal. Supplemental Table 5: The effect of co-variates on biomarker levels.

Background: DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility.Methods: We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling.Results: We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10−6), MSH5 (P < 5.09 × 10−6), and BRCA2 (P = 5.70 × 10−6). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.Conclusions: Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways.Impact: Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. Cancer Epidemiol Biomarkers Prev; 25(1); 193–200. ©2015 AACR.

Supplemental Table S1: Number of invasive EOC patients by study site. Supplemental Table S2: Results of Set 1 single variant analysis, for variants with P

Summary of 20 Ovarian Cancer Cohort Consortium (OC3) cohorts included in analysis of lifetime ovulatory cycles (LOC) and incident ovarian cancer.

Supplemental Figure Legends

Supplemental Figure 1: Manhattan plot, illustrating p-values from 60,297 SNP associations, generated from each of the 10 studies used in the meta-analysis. Statistical significance threshold is denoted by the red line (p = 5.09 x 10-6).

Supplementary Tables S1-6, Figures S1-2. Supplementary Table S1: Summary of serous EOC GWAS data sets; Supplementary Table S2: Genes in the six significant co-expression networks; Supplementary Table S3: GSEA results after LD-based clumping of SNPs; Supplementary Table S4: GSEA results for the replication data set (COGS); Supplementary Table S5: GSEA results for all networks with > 10 genes; Supplementary Table S6: Number of intragenic SNPs and genes covered by SNPs in the different analyses; Supplementary Figure S1: Q-Q plots of the minimum P-value among all SNPs in each gene with and without the modified Sidak correction; Supplementary Figure S2: Disease Association Protein-Protein Link Evaluator (DAPPLE) protein-protein interaction network

Background: Many circulating biomarkers have been reported for the diagnosis of breast cancer, but few, if any, have undergone rigorous credentialing using prospective cohorts and blinded evaluation.Methods: The NCI Early Detection Research Network (EDRN) has created a prospective, multicenter collection of plasma and serum samples from 832 subjects designed to evaluate circulating biomarkers for the detection and diagnosis of breast cancer. These samples are available to investigators who wish to evaluate their biomarkers using a set of blinded samples. The breast cancer reference set is composed of blood samples collected using a standard operating procedure at four U.S. medical centers from 2008 to 2010 from women undergoing either tissue diagnosis for breast cancer or routine screening mammography. The reference set contains samples from women with incident invasive cancer (n = 190), carcinoma in situ (n = 55), benign pathology with atypia (n = 63), benign disease with no atypia (n = 231), and women with no evidence of breast disease by screening mammography (BI-RADS 1 or 2, n = 276). Using a subset of plasma samples (n = 505) from the reference set, we analyzed 90 proteins by multiplexed immunoassays for their potential utility as diagnostic markers.Results: We found that none of these markers is useful for distinguishing cancer from benign controls. However, elevated CA-125 does appear to be a candidate marker for estrogen receptor–negative cancers.Conclusions: Markers that can distinguish benign breast conditions from invasive cancer have not yet been found.Impact: Availability of prospectively collected samples should improve future validation efforts. Cancer Epidemiol Biomarkers Prev; 24(2); 435–41. ©2014 AACR.

Supplementary Table 4 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

High-risk susceptibility genes explain CCND1, CCND2, CCND3, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, and CDKN2D—and risk of invasive epithelial ovarian cancer. We used a two-stage, multicenter, case-control study. In stage 1, 88 SNPs that tag common variation in these genes were genotyped in three studies from the United Kingdom, United States, and Denmark (∼1,500 cases and 2,500 controls). Genotype frequencies in cases and controls were compared using logistic regression. In stage 2, eight other studies from Australia, Poland, and the United States (∼2,000 cases and ∼3,200 controls) were genotyped for the five most significant SNPs from stage 1. No SNP was significant in the stage 2 data alone. Using the combined stages 1 and 2 data set, CDKN2A rs3731257 and CDKN1B rs2066827 were associated with disease risk (unadjusted P trend = 0.008 and 0.036, respectively), but these were not significant after adjusting for multiple testing. Carrying the minor allele of these SNPs was found to be associated with reduced risk [OR, 0.91 (0.85–0.98) for rs3731257; and OR, 0.93 (0.87–0.995) for rs2066827]. In conclusion, we have found evidence that a single tagged SNP in both the CDKN2A and CDKN1B genes may be associated with reduced ovarian cancer risk. This study highlights the need for multicenter collaborations for genetic association studies. [Cancer Res 2007;67(7):3027–35]

Supplementary Figure 1 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Tables 1-4 from Tagging Single Nucleotide Polymorphisms in Cell Cycle Control Genes and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Table 2 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Table 3 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Figure 2 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

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Despite the strikingly grave prognosis for older patients with glioblastomas, significant variability in patient outcome is experienced. To explore the potential for developing improved prognostic capabilities based on the elucidation of potential biological relationships, we did analyses of genes commonly mutated, amplified, or deleted in glioblastomas and DNA microarray gene expression data from tumors of glioblastoma patients of age >50 for whom survival is known. No prognostic significance was associated with genetic changes in epidermal growth factor receptor (amplified in 17 of 41 patients), TP53 (mutated in 11 of 41 patients), p16INK4A (deleted in 15 of 33 patients), or phosphatase and tensin homologue (mutated in 15 of 41 patients). Statistical analysis of the gene expression data in connection with survival involved exploration of regression models on small subsets of genes, based on computational search over multiple regression models with cross-validation to assess predictive validity. The analysis generated a set of regression models that, when weighted and combined according to posterior probabilities implied by the statistical analysis, identify patterns in expression of a small subset of genes that are associated with survival and have value in assessing survival risks. The dominant genes across such multiple regression models involve three key genes—SPARC (Osteonectin), Doublecortex, and Semaphorin3B—which play key roles in cellular migration processes. Additional analysis, based on statistical graphical association models constructed using similar computational analysis methods, reveals other genes which support the view that multiple mediators of tumor invasion may be important prognostic factor in glioblastomas in older patients.

The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r2 = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07–1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01–1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region. [Cancer Res 2009;69(6):2349–57]

Supplementary Table 1 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Tables 1-2 from Gene Expression Profiling and Genetic Markers in Glioblastoma Survival

Sequencing-based genetic tests to identify individuals at increased risk of hereditary breast and ovarian cancers have resulted in the identification of more than 40,000 sequence variants of BRCA1 and BRCA2. A majority of these variants are considered to be variants of uncertain significance (VUS) because their impact on disease risk remains unknown, largely due to lack of sufficient familial linkage and epidemiological data. Several assays have been developed to examine the effect of VUS on protein function, which can be used to assess their impact on cancer susceptibility. In this study, we report the functional characterization of 88 BRCA2 variants, including several previously uncharacterized variants, using a well-established mouse embryonic stem cell (mESC)-based assay. We have examined their ability to rescue the lethality of Brca2 null mESC as well as sensitivity to six DNA damaging agents including ionizing radiation and a PARP inhibitor. We have also examined the impact of BRCA2 variants on splicing. In addition, we have developed a computational model to determine the probability of impact on function of the variants that can be used for risk assessment. In contrast to the previous VarCall models that are based on a single functional assay, we have developed a new platform to analyze the data from multiple functional assays separately and in combination. We have validated our VarCall models using 12 known pathogenic and 10 neutral variants and demonstrated their usefulness in determining the pathogenicity of BRCA2 variants that are listed as VUS or as variants with conflicting functional interpretation.

Purpose BRCA1 pathogenic variant heterozygotes are at a substantially increased risk for breast and ovarian cancer. The widespread uptake of testing has led to a significant increase in the detection of missense variants in BRCA1, the vast majority of which are variants of uncertain clinical significance (VUS), posing a challenge to genetic counseling. Here, we harness a wealth of functional data for thousands of variants to aid in variant classification. Methods We have collected, curated, and harmonized functional data for 2701 missense variants representing 24.5% of possible missense variants in BRCA1. Results were harmonized across studies by converting data into binary categorical variables (functional impact versus no functional impact). Using a panel of reference variants we identified a subset of assays with high sensitivity and specificity (≥80%) and apply the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant interpretation guidelines to assign evidence criteria for classification. Results Integration of data from validated assays provided ACMG/AMP evidence criteria in favor of pathogenicity for 297 variants or against pathogenicity for 2058 representing 96.2% of current VUS functionally assessed. We also explore discordant results and identify limitations in the approach. Conclusion High quality functional data are available for BRCA1 missense variants and provide evidence for classification of 2355 VUS according to their pathogenicity.

Genetic testing for BRCA1, a DNA repair protein, can identify carriers of pathogenic variants associated with a substantially increased risk for breast and ovarian cancers. However, an association with increased risk is unclear for a large fraction of BRCA1 variants present in the human population. Most of these variants of uncertain clinical significance lead to amino acid changes in the BRCA1 protein. Functional assays are valuable tools to assess the potential pathogenicity of these variants. Here, we systematically probed the effects of substitutions in the C terminus of BRCA1: the N- and C-terminal borders of its tandem BRCT domain, the BRCT-[N-C] linker region, and the α1 and α′1 helices in BRCT-[N] and -[C]. Using a validated transcriptional assay based on a fusion of the GAL4 DNA-binding domain to the BRCA1 C terminus (amino acids 1396–1863), we assessed the functional impact of 99 missense variants of BRCA1. We include the data obtained for these 99 missense variants in a joint analysis to generate the likelihood of pathogenicity for 347 missense variants in BRCA1 using VarCall, a Bayesian integrative statistical model. The results from this analysis increase our understanding of BRCA1 regions less tolerant to changes, identify functional borders of structural domains, and predict the likelihood of pathogenicity for 98% of all BRCA1 missense variants in this region recorded in the population. This knowledge will be critical for improving risk assessment and clinical treatment of carriers of BRCA1 variants.

Introduction: Heart regeneration has been proposed as a treatment for heart failure. However, the challenge of detecting bona fide heart regeneration has complicated the validation of potential regenerative factors. We sought to develop a method for quantifying cardiomyogenesis in the mouse heart using multicolor lineage tracing. Hypothesis: We hypothesized that multicolor lineage tracing in combination with modeling of nearest neighbor distances could be used to quantify clonal expansion of cardiomyocytes (CMs) during growth and regeneration. Methods: Myh6- MerCreMer ; R26R-Rainbow bitransgenic mice underwent cryoinjury (CI) or sham injury on postnatal day 1 (P1). Tamoxifen was then administered such that limited numbers of CMs were randomly labeled with mCerulean, mOrange, or mCherry fluorophores. Hearts were collected at 21 days post CI. We analyzed a total of 81 sections, across 6 hearts (3 with sham injury and 3 with cryoinury). Images of entire cardiac sections were manually segmented to generate positional information for each labeled CM. Results: We used the nearest neighbor distributions of CMs carrying the same fluorophore and CMs carrying different fluorophores to develop a Bayesian model for estimating the probability that two CMs are clonally related. We found that, across a range of recombination efficiency, CMs carrying the same fluorophore within 30 μm are likely to be clonally related. By classifying CMs based on this distance threshold, we were able to confirm that clonally related CMs are smaller than non-clonally related CMs (165.20 ± 13.79 μm 2 vs 252.37 ± 20.51 μm 2 , p = 0.007, Welch t-test). We also confirmed that rates of cardiomyogenesis in cryoinjured and sham injured hearts are approximately the same (8.57 ± 2.69 % in cryoinjured hearts vs 9.45 ± 1.23 % in sham hearts, p=0.788). Conclusions: We have developed a robust and objective approach for quantifying cardiomyogenesis in the mouse heart. This method can be applied to studies of heart regeneration and can also be adapted to other tissues.

By replacing lost or dysfunctional myocardium, tissue regeneration is a promising approach to treat heart failure. However, the challenge of detecting bona fide heart regeneration limits the validation of potential regenerative factors. One method to detect new cardiomyocytes is multicolor lineage tracing with clonal analysis. Clonal analysis experiments can be difficult to undertake, because labeling conditions that are too sparse lack sensitivity for rare events such as cardiomyocyte proliferation, and diffuse labeling limits the ability to resolve clones. Presented here is a protocol to undertake clonal analysis of the neonatal mouse heart by using statistical modeling of nearest neighbor distributions to resolve cardiomyocyte clones. This approach enables resolution of clones over a range of labeling conditions and provides a robust analytical approach for quantifying cardiomyocyte proliferation and regeneration. This protocol can be adapted to other tissues and can be broadly used to study tissue regeneration.

Repeated exposure to the acute proinflammatory environment that follows ovulation at the ovarian surface and distal fallopian tube over a woman's reproductive years may increase ovarian cancer risk. To address this, analyses included individual-level data from 558,709 naturally menopausal women across 20 prospective cohorts, among whom 3,246 developed invasive epithelial ovarian cancer (2,045 serous, 319 endometrioid, 184 mucinous, 121 clear cell, 577 other/unknown). Cox models were used to estimate multivariable-adjusted HRs between lifetime ovulatory cycles (LOC) and its components and ovarian cancer risk overall and by histotype. Women in the 90th percentile of LOC (>514 cycles) were almost twice as likely to be diagnosed with ovarian cancer than women in the 10th percentile ( Significance: Although ovarian cancer is rare, risk of most ovarian cancers doubles as the number of lifetime ovulatory cycles increases from approximately 300 to 500. Thus, identifying an important area for cancer prevention research.

Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans e...

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ≥99% probability of pathogenicity, and 73 had ≥95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

Several transient receptor potential (TRP) ion channels can be directly activated by hot or cold temperature with high sensitivity. However, the structures and molecular mechanism giving rise to their high temperature sensitivity are not fully understood. One hypothesized mechanism assumes that temperature activation is driven by the exposure of hydrophobic residues to solvent. This mechanism further predicts that residues are exposed to solvent in a coordinated fashion, but without necessarily being located in close proximity to each other. However, there is little experimental evidence supporting this mechanism in TRP channels. Here, we combined high-throughput mutagenesis, functional screening, and deep sequencing to identify mutations from a total of ~7,300 TRPV1 random mutant clones. We found that strong decreases in hydrophobicity of amino acids are better tolerated for activation by capsaicin than for activation by hot temperature, suggesting that strong hydrophobicity might be specifically required for temperature activation. Altogether, our work provides initial correlative support for a previously hypothesized temperature mechanism in TRP ion channels.

The effects of stone size on the process and comminution efficiency of shock wave lithotripsy (SWL) were investigated in experiments, numerical simulations and scale analysis. Cylindrical BegoStone phantoms with approximately equal height and diameter of either 4, 7 or 10 mm, in a total aggregated mass of about 1.5 g, were treated in an electromagnetic shock wave lithotripter field. The resultant stone comminution was found to correlate closely with the average peak pressure, P+(avg), incident on the stones. The P+(avg) threshold necessary to initiate stone fragmentation in water increased from 7.9 to 8.8 to 12.7 MPa, respectively, as stone size decreased from 10 to 7 to 4 mm. Similar changes in the P+(avg) threshold were observed for the 7- and 10-mm stones treated in 1,3-butanediol, in which cavitation is suppressed, suggesting that the observed size dependency is due to changes in stress distribution within stones of different size. Moreover, the slope of the correlation curve between stone comminution and ln(P¯+(avg)) in water increased with decreasing stone size, whereas the opposite trend was observed in 1,3-butanediol. The progression of stone comminution in SWL exhibited size-dependence: the 7- and 10-mm stones fragmented into progressively smaller pieces, whereas a significant portion (>30%) of the 4-mm stones reached a stalemate within the size range of 2.8 ∼ 4 mm, even after 1000 shocks. Analytical scaling considerations suggest size-dependent fragmentation behavior, a hypothesis further supported by numerical model calculations that reveal changing patterns of constructive and destructive wave interference and, thus, variations in the maximum tensile stress or stress integral produced in cylindrical and spherical stone of different sizes.

Background: Germline genetic testing of individuals with a diagnosis of triple negative breast cancer, young age at diagnosis, or a family history of breast and/or ovarian cancer has led to the identification of many unique BRCA2 missense variants of uncertain significance (VUS). VUS in BRCA2 are predominantly missense mutations that have unclear relevance to breast, ovarian, and other cancers. Thus, patients found to have a germline BRCA2 VUS do not know if the variant is associated with high risks of these cancers similar to truncating mutations, intermediate risks more similar to CHEK2 mutations, or low risks of no clinical significance. Furthermore, it is unclear if germline BRCA2 VUS, or somatic VUS identified by tumor sequencing, are associated with hypersensitivity to selected DNA damaging and cross-linking agents. Methods: We have used a homology directed repair (HDR) cell-based assay to characterize missense variants in the DNA binding domain (DBD) of BRCA2. The method has been validated using known pathogenic and known non-pathogenic BRCA2 missense variants and has 100% sensitivity (95% confidence interval (CI): 75.3%–100%) and 100% specificity (95% CI: 81.5%–100%) for pathogenic BRCA2 variants. A classifier of variant pathogenicity based on the mean and variances of the distributions of the HDR results of the known pathogenic and neutral variants has been established. We have also developed PARP inhibitor and cisplatin drug response assays for BRCA2 missense variants. Results: Assessment of 207 BRCA2 missense variants, identified in public databases such as BRCA exchange and ClinVar, by the HDR assay identified 71 deleterious variants with >99% probability of pathogenicity, 116 neutral variants with >99% probability of neutrality, and 20 with hypomorphic activity and potentially intermediate risk. A combination of the functional data and sequence-based predictors of protein activity in a Bayesian prediction model resulted in classification of the deleterious variants as pathogenic cancer predisposing variants and the neutral variants as non-pathogenic with low clinical significance. The influence of the deleterious/pathogenic variants on PARPi and cisplatin response was also assessed. Conclusion: The HDR assay is effective for characterization of BRCA2 VUS. The combination of functional data and in silico prediction models provides a robust tool for clinical annotation of BRCA2 VUS. HDR function of BRCA2 missense variants is strongly correlated with response to targeted therapy. Citation Format: Couch FJ, Shimelis H, Hart SN, Moore RM, Thomas A, Lipton GB, Iversen E. Cancer risks and response to targeted therapy associated with BRCA2 variants of uncertain significance [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr GS4-06.

Background: Previous studies show inconsistent relations between child care and obesity, but few assessed longitudinal associations during infancy and even fewer included racially diverse children. We examined associations of time infants spent in child care, both overall and in different types of care, with weight status at 6 and 12 months. Methods: We examined 664 infants living in central North Carolina. We conducted adjusted multivariable linear regressions examining (1) child care from birth to 6 months and 6-month weight-for-length (WFL) z-score, and (2) child care from birth to 12 months and 12-month WFL z-score. We assessed any child care and child care by type, including relative care, informal care by a nonrelative, formal child care, and a combination of care (e.g., relative and informal care). Results: Nearly 70% of infants were black and 49% were female. After adjustment for potential confounders, any child care was not associated with WFL z-score at 6 months (0.07; 95% confidence intervals [CI] −0.02 to 0.16; p = 0.13) or 12 months (0.05; 95% CI −0.02 to 0.12; p = 0.19). However, greater combination care was associated with higher WFL z-score at 6 months (0.68; 95% CI 0.23–1.13; p = 0.003) and greater care by a relative was associated with higher WFL z-score at 12 months (0.16; 95% CI 0.05–0.26; p = 0.005). Conclusions: Although we did not observe associations with any child care, combination care and relative care during infancy were associated with higher weight. Interventions aimed at preventing excessive weight gain in early life may target relatives who provide regular care for infants.