Citations

ABSTRACTEpithelial‐mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single‐nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome‐wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT‐related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive‐cancer patients and 23,447 controls. A P‐value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07–1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69–0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

Abstract Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.

Abstract Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.

Abstract Genome-wide association studies (GWAS) of multiple myeloma (MM) in Northern Europeans have identified seven novel risk loci (2p23.3, 3p22.1, 3q26.2, 6p21.33, 7p15.3, 17p11.2, 22q13.1). We performed a multiethnic meta-analysis of these regions in 1,274 MM patients and 1,486 controls of European ancestry (EA) and 1,049 MM patients and 7,080 controls of African ancestry (AA), leveraging the differential linkage-disequilibrium of these populations in order to better localize the putative functional variants. We observed directionally consistent effects for all seven index SNPs in both populations, with four significantly associated (p&lt;0.05) with risk in EAs (3p22.1, 7p15.3, 17p11.2, 22q13.1), and two significantly associated with risk in AAs (7p15.3 and 22q13.1). In a fixed effects meta-analysis of six regions (excluding the HLA region on chromosome 6), variation in five of the regions (2p33.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) had statistically significant associations with risk (Table 1). In one region, the index variant had the strongest association [rs4487645 at 7p15.3, (OR = 1.30, p = 8.7×10−8)]. Five of the six most significantly associated variants identified in the multiethnic analyses overlapped with biologically relevant features indicating regulatory activity based on CD20+ (B lymphocyte) cells, showing evidence of potential function; those included a missense variant in (17p11.2, rs34562254, Pro251Leu) in TNFRSF13B, which encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-kb pathway. Our study shows that these regions are important in MM risk across ethnicities and further supports the use of multiple ethnic groups in genetic studies to enhance identification of risk variants. Table 1.Most significant associations for each region in the multiethnic meta-analysis.Individuals of European AncestryIndividuals of African AncestryMulitethnic Metar2 with IndexcCHRSNPRAaFreqbORP-valueFreqbORP-valueORP-valueP-het2rs732075G0.591.222.0×10−30.621.122.0×10−21.162.6×10−40.280.09/0.283rs73069394A0.191.243.0×10−30.621.181.5×10−21.201.3×10−50.550.77/0.963rs12637184G0.761.136.0×10−20.921.192.7×10−11.151.0×10−20.640.94/1.007rs4487645C0.671.237.0×10−40.891.485.5×10−51.308.7×10−80.07-d17rs34562254A0.121.452.4×10−50.131.212.2×10−31.312.5×10−60.120.33/0.9022rs139400T0.491.224.0×10−40.531.172.1×10−31.191.2×10−60.630.63/0.96aRisk allelebFrequency of the risk allele in European and African ancestry studiescr2 metrics based on 1000 Genomes Project AFR/EUR populationsdIndex SNP Citation Format: Kristin A. Rand, Chi Song, Eric Dean, Daniel Serie, Karen Curtin, Dennis Hazelett, Amie E. Hwang, Xin Sheng, Alex Stram, David J. Van Den Berg, Carol Ann Huff, Leon Bernal-Mizrachi, Michael H. Tomasson, Sikander Ailawadhi, Anneclaire De Roos, Seema Singhal, Karen Pawlish, Edward Peters, Catherine Bock, David V. Conti, Graham Colditz, Todd Zimmerman, Scott Huntsman, John Graff, African Ancestry Prostate Cancer GWAS Consortium,African Ancestry Breast Cancer GWAS Consortium, Stephen J. Chanock, Michael Lieber, Jayesh Mehta, Eric A. Klein, Nalini Janakiraman, Richard K. Severson, Angela R. Brooks-Wilson, Vincent Rajkumar, Elizabeth E. Brown, Laurence Kolonel, Susan Slager, Brian E. Henderson, Graham G. Giles, John J. Spinelli, Brian Chiu, Kenneth C. Anderson, Jeffrey Zonder, Robert Z. Orlowski, Sagar Lonial, Nicola Camp, Celine Vachon, Elad Ziv, Dan O. Stram, Christopher A. Haiman, Wendy Cozen. Multiple myeloma susceptibility loci examined in African and European ancestry populations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4629. doi:10.1158/1538-7445.AM2015-4629

Abstract Distinct subtypes of triple negative (TN) breast cancer have currently been identified by tumor expression profiling and are thought to be influenced by the tumor microenvironment. However, little is known about the relationship between distinguishing histopathologic features of TN tumors, which reflect aspects of both tumor behavior and tumor microenvironment, and molecular TN subtypes. We analyzed whole genome expression profiles of 593 TN tumors from the Triple Negative Breast Cancer Consortium (TNBCC) using the Illumina Whole Genome DASL array. Histopathologic review of mitotic index, grade, trabecular pattern, growth pattern, involution, presence of ductal carcinoma in situ, and degree of lymphoid infiltrate, necrosis, fibrosis, and lobulitis was completed for 310 of these tumors. Clusters were identified both agnostically and using genes associated with these histopathologic features, and subtypes were evaluated for enriched pathways and associations with histopathologic features. Agnostic clustering identified four stable clusters which represented a basal-like (BL) signature, a luminal signature with overexpression of androgen receptor and targets, an immune signature, and a stromal (STR) signature. Overall, the TN tumors tended to have little or no necrosis (91%), high grade (88%), a high mitotic index (80%), fibrosis (77%), an epicentric growth pattern (62%), incomplete lobular involution (55%), trabecular structures (37%), lymphocytic infiltration (25%), adjacent ductal carcinoma in situ (24%), and variable amounts of lobulitis. Using a combined total of 2,776 unique probes individually associated with the ten histopathologic features measured, we identified six distinct TN subtypes, with an additional BL and STR signature compared to the four agnostic subtypes. Our findings suggest that histopathologic features that reflect heterogeneity in tumor cell structure and behavior as well as the tumor microenvironment, particularly the presence of lymphocytic infiltrate, are critical for TN subtype identification. Further work is needed to validate these signatures and to better understand the immunologic pathways associated with each subtype. Citation Format: Kristen Purrington, Daniel Visscher, Drakoulis Yannoukakos, Jane Carpenter, Heli Nevanlinna, Arto Mannerma, Xianshu Wang, Graham Giles, Wei Zheng, Angela Cox, Hiltrud Brauch, Ute Hamann, Diana Eccles, Celine M. Vachon, Fergus J. Couch. Genes associated with histopathologic features of triple negative breast tumors predict molecular subtypes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1924. doi:10.1158/1538-7445.AM2015-1924

Abstract 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 &lt; 0.05 and FDR &lt; 0.05). These results were replicated (P &lt; 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.

Abstract Marginal zone lymphomas (MZL) are a group of indolent non-Hodgkin's B-cell lymphomas (NHL) comprising extranodal MZL of mucosa-associated lymphoid tissue (MALT) type, splenic MZL and nodal MZL. MZL comprises 7-12% of adult NHLs. The genetic etiology of MZL is poorly understood. To better understand the genetic risk factors for MZL, we conducted the first genome-wide association study (GWAS) of this lymphoid malignancy. The GWAS included 824 MZL cases and 6,220 controls of European ancestry from 22 studies of NHL. Genotyping was carried out at the Cancer Genomics Research Laboratory (CGR) of NCI using Illumina Human OmniExpress arrays. Standard genotyping quality controls were performed. Imputation of common SNPs was performed using IMPUTE2 software and 1000 Genomes Project release version 3 data. Association testing was subsequently performed using SNPTEST, assuming a log-additive genetic model adjusting for age, gender and three significant eigenvectors. We identified one locus at 6p21.32 within the HLA class II region that attained genome-wide significance (P&lt;5x10-8). When a small number of additional cases (n=58) and controls (n=66) genotyped using Taqman assays were included, rs9461741 (BTNL2) was associated with an increased risk of MZL (per-allele odds ratio = 2.38, 95% confidence interval: 1.74-3.24; P=4.32x10-8). Other SNPs at the 6p21.32 locus were also highly associated with MZL, suggesting that this is unlikely to be a chance finding. Promising signals yet to be confirmed were also observed on chromosomes 3 and 14. The BTNL2 protein has extracellular immunoglobulin domains and is expressed in multiple tissues including various immune organs and the gut and it inhibits T-cell activation. Genetic variability at BTNL2 has been associated with inflammatory and infectious phenotypes, highlighting the importance of this locus for immune diseases. In conclusion, findings from this GWAS identify the HLA class II region as an important susceptibility locus for MZL. Citation Format: Joseph Vijai, Zhaoming Wang, Sonja I. Berndt, Susan L. Slager, James R. Cerhan, Christine Skibola, Sophia S. Wang, Angela R. Brooks-Wilson, Silvia de Sanjose, Paige M. Bracci, Mads Melbye, Bengt Glimelius, Rebecca D. Jackson, Wendy Cozen, Nikolaus Becker, Lauren R. Teras, John J. Spinelli, Jenny Turner, Qing Lan, Mark P. Purdue, Kimberly A. Bertrand, Kenneth Offit, Paolo Vineis, Brian K. Link, Graham G. Giles, Anne Zelenuich-Jacquotte, Alain Monnereau, Maria Grazia Ennas, Demetrius Albanes, Laurie Burdett, Nathaniel Rothman, Stephen J. Chanock, Alexandra Nieters, On behalf of the NHL GWAS Consortium. A genome-wide association study suggests evidence of variants at 6p21.32 associated with marginal zone lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5071. doi:10.1158/1538-7445.AM2014-5071

Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P &lt; 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Abstract Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.