Cancer Risk Single Nucleotide Polymorphisms Research Articles

Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants.

The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.

Abstract C082: Breast cancer risk in Hispanic/Latina women and the 6q25 chromosomal region: Fine mapping and eQTL identification

Abstract Breast cancer subtype distribution differs between populations with dissimilar genetic ancestry backgrounds. Several breast cancer risk single nucleotide polymorphisms (SNPs) were discovered in individuals of European and Asian origin. Hispanic/Latina women remain underrepresented in studies and public databases. The 6q25 locus contains multiple breast cancer risk-associated SNPs. Some SNPs within this region have been associated with the expression of genes (eQTLs), such as the Estrogen Receptor 1 gene (ESR1). Two breast cancer genetic association studies in Hispanics/Latinas identified two SNPs (rs140068132 and rs3778609), near ESR1, that correlate with Indigenous American ancestry and reduce the odds of breast cancer, especially for Estrogen Receptor-negative (ER-) disease. The underrepresentation of Latin American populations in public databases has hindered the study of the mechanisms by which these SNPs confer a protective effect. We integrated genetic and transcriptomic data from breast cancer patients with high Indigenous American ancestry to test the association between the protective variants in the 6q25 region and tumor gene expression. Breast cancer patients were recruited at the National Cancer Institute in Peru to be part of The Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC, N=1809). Healthy women from a pregnancy outcomes study in Peru were included as controls (N=3334). Genome-wide genotype data were available and missing genotypes were imputed using the TOPMED Imputation Server to perform fine-mapping within the 6q25 locus. Logistic regression was used to test the association between each SNP and breast cancer risk. We exome-sequenced 155 breast tumors of these patients. Transcripts per million counts and imputed genotypes within the 6q25 region were used for eQTL analysis. Colocalization was performed using summary statistics from the fine-mapping and eQTL analysis, including SNPs with minor allele frequency >5%. Only two SNPs, rs140068132 and rs851984 were independently associated with breast cancer risk, as we previously reported. eQTL signals colocalized with the subregion in 6q25 that contains these breast cancer-associated SNPs. Within this subregion, the gene with more eQTLs using a nominal p-value of <=0.01 was MTHFD1L (136 eQTLs), followed by ESR1 (58) and CCDC170 (32). Colocalization showed that MTHFD1L and ESR1 eQTLs were more likely to overlap with breast cancer risk SNPs, including rs140068132. The protective rs140068132-G variant was associated with lower expression of MTHFD1L. MTHFD1L has been found deregulated in breast cancer and higher expression is associated with poor prognosis. Our preliminary results suggest that the rs140068132-G variant in the 6q25 region identified in Hispanic/Latina women might exert its protective effect through the downregulation of MTHFD1L. Analyses with additional samples will allow us to confirm this result and further explore the functional implications of the rs140068132 variant. Citation Format: Valentina A. Zavala, Xiaosong Huang, Sandro Casavilca-Zambrano, Jeannie Navarro-Vásquez, Carlos A. Castañeda, Guillermo Valencia, Zaida Morante, Monica Calderon, Julio E. Abugattas, Henry Gómez, Hugo A. Fuentes, Ruddy Liendo-Picoaga, Jose M. Cotrina, Silvia Neciosup, Katia Roque, Jule Vásquez, Luis MAs, Marco Gálvez-Nino, Sixto E. Sánchez, Michelle A. Williams, Elad Ziv, Jovanny Zabaleta, Bizu Gelaye, Tatiana Vidaurre Vidaurre, Laura Fejerman. Breast cancer risk in Hispanic/Latina women and the 6q25 chromosomal region: Fine mapping and eQTL identification [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C082.

Identification of Candidate mRNA Isoforms for Prostate Cancer-Risk SNPs Utilizing Iso-eQTL and sQTL Methods.

Single nucleotide polymorphisms (SNPs) impacting the alternative splicing (AS) process (sQTLs) or isoform expression (iso-eQTL) are implicated as important cancer regulatory elements. To find the sQTL and iso-eQTL, we retrieved prostate cancer (PrCa) tissue RNA-seq and genotype data originating from 385 PrCa European patients from The Cancer Genome Atlas. We conducted RNA-seq analysis with isoform-based and splice event-based approaches. The MatrixEQTL was used to identify PrCa-associated sQTLs and iso-eQTLs. The overlap between sQTL and iso-eQTL with GWAS loci and those that are differentially expressed between cancer and normal tissue were identified. The cis-acting associations (FDR < 0.05) for PrCa-risk SNPs identified 42, 123, and 90 PrCa-associated cassette exons, intron retention, and mRNA isoforms belonging to 25, 95, and 83 genes, respectively; while assessment of trans-acting association (FDR < 0.05) yielded 59, 65, and 196 PrCa-associated cassette exons, intron retention and mRNA isoforms belonging to 35, 55, and 181 genes, respectively. The results suggest that functional PrCa-associated SNPs can play a role in PrCa genesis by making an important contribution to the dysregulation of AS and, consequently, impacting the expression of the mRNA isoforms.

Abstract 5883: Development and testing of a polygenic risk score for proliferative breast cancers

Abstract Background: Identification of women at elevated risk for highly proliferative, poor prognosis breast cancers could have important implications for screening and prevention. Genome-wide association studies (GWAS) have found &amp;gt;200 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, with many SNPs differentially associated with ER status or intrinsic subtype. We hypothesized that some of these SNPs are preferentially associated with more proliferative tumors, while others are preferentially associated with less proliferative tumors. In this study, we aimed to build a polygenic risk score (PRS) predictive of proliferative tumors, using the GWAS-identified SNPs. Methods: We used data from 3 studies that included array-based SNP genotyping and tumor transcriptomic data: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 Trial (total n=2,467). Our outcome was the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. Using the breast cancer risk SNPs, we built respective linear regression models to predict ROR-P, with genetic ancestry, study, and ER status as covariates. We performed 5-fold cross-validation and used the model r2 to identify the optimal p-value threshold for including SNPs in the PRS. To decrease uncertainty of our estimates, we performed 100 repeats across the pooled datasets. To test whether this model predicted poor prognosis breast cancers, we first used it to impute ROR-P among genotyped breast cancer cases in UK Biobank (UKB). We then examined the association between “genetically predicted” ROR-P and breast cancer-specific survival using Cox proportional hazards models adjusted for genetic ancestry and age at diagnosis. Results: Associations between 224 breast cancer SNPs and ROR-P were tested. The best-performing model in cross-validation contained 96 SNPs, each associated with ROR-P at p &amp;lt; 0.45, with model r2 0.054. The SNPs with the strongest positive correlations with ROR-P included those discovered in GWAS for HER2-positive and ER-negative cancers, both of which tend to be highly proliferative. Among 7,247 incident cancers in UKB, higher genetically predicted ROR-P was associated with shorter survival, with a per-standard deviation hazard ratio of 1.14 (95% CI 1.05-1.24, p = 0.002). Conclusions: We used breast cancer susceptibility SNPs to construct a PRS fitted to ROR-P, a prognostic signature recapitulating tumor proliferation. This PRS was associated with worse clinical outcomes in breast cancer cases from UKB. Our results suggest that correlations between SNPs and tumor gene expression can be used to “tune” PRS to tumor phenotype, e.g. proliferation. Highly proliferative tumors are more likely to present as advanced cancers even among women getting routine screening. If replicated in other datasets, our findings could be used to identify women who may especially benefit from tailored screening and prevention. Citation Format: Yiwey Shieh, Jacquelyn Roger, Scott Huntsman, Donglei Hu, Jovia L. Nierenberg, Pooja Middha Kapoor, Christina Yau, Gillian Hirst, Laura van 't Veer, Laura Esserman. Development and testing of a polygenic risk score for proliferative breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5883.

Three-Dimensional Genome Organization in Breast and Gynecological Cancers: How Chromatin Folding Influences Tumorigenic Transcriptional Programs.

A growing body of research on the transcriptome and cancer genome has demonstrated that many gynecological tumor-specific gene mutations are located in cis-regulatory elements. Through chromosomal looping, cis-regulatory elements interact which each other to control gene expression by bringing distant regulatory elements, such as enhancers and insulators, into close proximity with promoters. It is well known that chromatin connections may be disrupted in cancer cells, promoting transcriptional dysregulation and the expression of abnormal tumor suppressor genes and oncogenes. In this review, we examine the roles of alterations in 3D chromatin interactions. This includes changes in CTCF protein function, cancer-risk single nucleotide polymorphisms, viral integration, and hormonal response as part of the mechanisms that lead to the acquisition of enhancers or super-enhancers. The translocation of existing enhancers, as well as enhancer loss or acquisition of insulator elements that interact with gene promoters, is also revised. Remarkably, similar processes that modify 3D chromatin contacts in gene promoters may also influence the expression of non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), which have emerged as key regulators of gene expression in a variety of cancers, including gynecological malignancies.

Functional Screenings Identify Regulatory Variants Associated with Breast Cancer Susceptibility.

Genome-wide association studies (GWAS) have identified more than 2000 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, most of which are located in the non-coding region. However, the causal SNPs functioning as gene regulatory elements still remain largely undisclosed. Here, we applied a Dinucleotide Parallel Reporter sequencing (DiR-seq) assay to evaluate 288 breast cancer risk SNPs in nine different breast cancer cell lines. Further multi-omics analysis with the ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing), DNase-seq (DNase I hypersensitive sites sequencing) and histone modification ChIP-seq (Chromatin Immunoprecipitation sequencing) nominated seven functional SNPs in breast cancer cells. Functional investigations show that rs4808611 affects breast cancer progression by altering the gene expression of NR2F6. For the other site, rs2236007, the alteration promotes the binding of the suppressive transcription factor EGR1 and results in the downregulation of PAX9 expression. The downregulated expression of PAX9 causes cancer malignancies and is associated with the poor prognosis of breast cancer patients. Our findings contribute to defining the functional risk SNPs and the related genes for breast cancer risk prediction.

How Cancer Risk SNPs May Contribute to Prostate Cancer Disparities.

Disparities in cancer incidence, prevalence, burden, and outcome exist among specific population groups in the United States. Researchers have identified germline genetic risk single-nucleotide polymorphisms (SNP) that differ by ancestry and may contribute to some of these differences. In this issue of Cancer Research, Han and colleagues found the prostate cancer risk SNP rs4713266 is associated with increased risk of patients with African ancestry. The authors investigated the functional role of the risk SNP, finding that it alters activity of a NEDD9 enhancer and increases NEDD9 expression. The study provides epidemiologic and mechanistic insight into factors that may drive prostate cancer disparities.See related article by Han et al., p. 3766.

Genetics of prostate cancer and its utility in treatment and screening.

Prostate cancer heritability is attributed to a combination of rare, moderate to highly penetrant genetic variants as well as commonly occurring variants conferring modest risks [single nucleotide polymorphisms (SNPs)]. Some of the former type of variants (e.g., BRCA2 mutations) predispose particularly to aggressive prostate cancer and confer poorer prognoses compared to men who do not carry mutations. Molecularly targeted treatments such as PARP inhibitors have improved outcomes in men carrying somatic and/or germline DNA repair gene mutations. Ongoing clinical trials are exploring other molecular targeted approaches based on prostate cancer somatic alterations. Genome wide association studies have identified >250 loci that associate with prostate cancer risk. Multi-ancestry analyses have identified shared as well as population specific risk SNPs. Prostate cancer risk SNPs can be used to estimate a polygenic risk score (PRS) to determine an individual's genetic risk of prostate cancer. The odds ratio of prostate cancer development in men whose PRS lies in the top 1% of the risk profile ranges from 9 to 11. Ongoing studies are investigating the utility of a prostate cancer PRS to target population screening to those at highest risk. With the advent of personalized medicine and development of DNA sequencing technologies, access to clinical genetic testing is increasing, and oncology guidelines from bodies such as NCCN and ESMO have been updated to provide criteria for germline testing of "at risk" healthy men as well as those with prostate cancer. Both germline and somatic prostate cancer research have significantly evolved in the past decade and will lead to further development of precision medicine approaches to prostate cancer treatment as well as potentially developing precision population screening models.

Genetic Colorectal Cancer and Adenoma Risk Variants Are Associated with Increasing Cumulative Adenoma Counts.

The genetic basis for most individuals with high cumulative lifetime colonic adenomas is unknown. We investigated associations between known colorectal cancer-risk single-nucleotide polymorphisms (SNP) and increasing cumulative adenoma counts. The Cooperative Studies Program #380 screening colonoscopy cohort includes 612 selected participants age 50 to 75 with genotyped blood samples and 10 years of clinical follow-up. We evaluated 41 published "colorectal cancer-risk SNPs" for associations with individual cumulative adenoma counts or having ≥10 cumulative adenomas. SNPs were analyzed singly or combined in a polygenic risk score (PRS). The PRS was constructed from eight published SNPs associated with multiple adenomas, termed "adenoma-risk SNPs." Four colorectal cancer-risk SNPs were associated with increasing cumulative adenoma counts (P < 0.05): rs12241008 (gene: VTI1A), rs2423279 (BMP2/HAO1), rs3184504 (SH2B3), and rs961253 (FERMT1/BMP2), with risk allele risk ratios of 1.31, 1.29, 1.24, and 1.23, respectively. Three colorectal cancer-risk SNPs were associated with ≥10 cumulative adenomas (P < 0.05), with risk allele odds ratios of 2.09 (rs3184504), 2.30 (rs961253), and 1.94 (rs3217901). A weighted PRS comprised of adenoma-risk SNPs was associated with higher cumulative adenomas (weighted rate ratio = 1.57; P = 0.03). In this mostly male veteran colorectal cancer screening cohort, several known colorectal cancer-risk SNPs were associated with increasing cumulative adenoma counts and the finding of ≥10 cumulative adenomas. In addition, an increasing burden of adenoma-risk SNPs, measured by a weighted PRS, was associated with higher cumulative adenomas. Future work will seek to validate these findings in different populations and then augment current colorectal cancer risk prediction tools with precancerous, adenoma genetic data.

Abstract B15: Bladder cancer susceptibility polymorphisms and mortality from non-muscle and muscle-invasive bladder cancer

Abstract Introduction: Genome-wide association studies (GWAS) have identified several common germline single-nucleotide polymorphisms (SNPs) associated with increased risk of bladder cancer. Little is known about whether these variants are also associated with overall and bladder cancer-specific mortality. We examined the association between 13 GWAS-identified bladder cancer risk SNPs and overall and bladder cancer-specific survival in 316 bladder cancer cases recruited as part of a population-based case-control study. Methods: Residents of New Hampshire with primary bladder cancer diagnosed between 2002-2004 were identified from the New Hampshire State Cancer Registry. Medical history and lifestyle factors were collected via in-person interviews at time of enrollment. DNA was isolated from peripheral blood or buccal specimens and genotyping was performed using the Illumina Human610-Quad BeadChip. Date and cause of death were ascertained from the National Death Index with follow-up through December 31, 2013. Non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) were examined separately. We used Cox proportional hazards models to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for overall and bladder cancer-specific survival, assuming a log-additive genetic model. HR estimates for MIBC individuals were adjusted for age at diagnosis, sex, smoking status, American Joint Committee on Cancer stage, initial treatment (including extent of resection, cystectomy, and use of chemotherapy or radiation), and three principal components for genetic ancestry. HR estimates for NMIBC were additionally adjusted for 2004 World Health Organization/International Society of Urologic Pathologists classification. An alpha of 0.05 was used to determine statistical significance. Results: Among 43 participants with MIBC, 30 deaths occurred over a median follow-up of 6.4 years, including 19 from bladder cancer. Among 273 participants with NMIBC, 94 deaths occurred over a median follow-up of 10.3 years, including 23 from bladder cancer. The risk allele [A] of enhancer-associated intergenic SNP rs710521 near TP63 was associated with poorer overall survival after MIBC diagnosis (HR=3.21, 95% CI=1.26-8.16). The risk allele [C] of synonymous SNP rs10936599 of MYNN/TERC was associated with better overall survival after NMIBC diagnosis (HR=0.66, 95% CI=0.46-0.94). No associations with bladder cancer-specific survival were identified. Conclusions: Common bladder cancer susceptibility variants rs710521 and rs10936599 may be associated with overall survival after diagnosis of MIBC and NMIBC, respectively. Citation Format: Reno C. Leeming, Michael S. Zens, John D. Seigne, Brock C. Christensen, Diane Gilbert-Diamond, Margaret R. Karagas, Michael N. Passarelli. Bladder cancer susceptibility polymorphisms and mortality from non-muscle and muscle-invasive bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr B15.

Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function

BackgroundGenome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.MethodsWe used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks.ResultsEach tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be ‘cores’ of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes.ConclusionsThis approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.

Colorectal cancer susceptibility loci and influence on survival.

Genome-wide association studies (GWAS) have identified multiple single-nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. To evaluate the potential influence of colorectal cancer susceptibility SNPs on disease prognosis, we investigated whether GWAS-identified colorectal cancer risk SNPs and polygenic risk scores (PRSs) might be associated with survival among colorectal cancer patients. A total of 1374 colorectal cancer patients were recruited from the Korean National Cancer Center. For genotyping, 30 colorectal cancer-susceptibility SNPs previously identified by GWAS were selected. The Cox proportional hazard model was used to evaluate associations of these risk SNPs and PRSs with disease-free survival (DFS) and overall survival (OS). The prognostic values were compared between genetic and nongenetic models using Harrell's c index. During the follow-up period (median: 88, 91 months for DFS and OS), 570 DFS (41.5%) and 487 OS (35.4%) events were observed. We found that 5 SNPs were significantly associated with DFS or OS among colorectal cancer patients at P < .05: rs10936599 at 3q26.2 (MYNN), rs704017 at 10q22.3 (ZMIZ1-AS1), rs11196172 at 10q25.2 (TCF7L2), rs3802842 at 11q23.1 (COLCA1-2), and rs9929218 at 16q22.1 (CDH1). The PRSs constructed using these 5 SNPs were associated with worse survival (DFS: Ptrend = .02 unweighted PRS, Ptrend = .01 weighted PRS, OS: Ptrend = 3.7 × 10-3 unweighted, Ptrend = .02 weighted PRS). Our results suggest that several colorectal cancer susceptibility SNPs might also be related to survival by influencing disease progression.

Subtype-specific associations between breast cancer risk polymorphisms and the survival of early-stage breast cancer

BackgroundLimited evidence suggests that inherited predisposing risk variants might affect the disease outcome. In this study, we analyzed the effect of genome-wide association studies—identified breast cancer-risk single nucleotide polymorphisms on survival of early-stage breast cancer patients in a Chinese population.MethodsThis retrospective study investigated the relationship between 21 GWAS-identified breast cancer-risk single nucleotide polymorphisms and the outcome of 1177 early stage breast cancer patients with a long median follow-up time of 174 months. Cox proportional hazards regression models were used to estimate the hazard ratios and their 95% confidence intervals. Primary endpoints were breast cancer special survival and overall survival while secondary endpoints were invasive disease free survival and distant disease free survival.ResultsMultivariate survival analysis showed only the rs2046210 GA genotype significantly decreased the risk of recurrence and death for early stage breast cancer. After grouping breast cancer subtypes, significantly reduced survival was associated with the variant alleles of rs9485372 for luminal A and rs4415084 for triple negative breast cancer. Importantly, all three single-nucleotide polymorphisms, rs889312, rs4951011 and rs9485372 had remarkable effects on survival of luminal B EBC, either individually or synergistically. Furthermore, statistically significant multiplicative interactions were found between rs4415084 and age at diagnosis and between rs3803662 and tumor grade.ConclusionsOur results demonstrate that breast cancer risk susceptibility loci identified by GWAS may influence the outcome of early stage breast cancer patients’ depending on intrinsic tumor subtypes in Chinese women.

Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data.

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.

Evaluating the breast cancer predisposition role of rare variants in genes associated with low-penetrance breast cancer risk SNPs

BackgroundGenome-wide association studies (GWASs) have identified numerous single-nucleotide polymorphisms (SNPs) associated with small increases in breast cancer risk. Studies to date suggest that some SNPs alter the expression of the associated genes, which potentially mediates risk modification. On this basis, we hypothesised that some of these genes may be enriched for rare coding variants associated with a higher breast cancer risk.MethodsThe coding regions and exon-intron boundaries of 56 genes that have either been proposed by GWASs to be the regulatory targets of the SNPs and/or located < 500 kb from the risk SNPs were sequenced in index cases from 1043 familial breast cancer families that previously had negative test results for BRCA1 and BRCA2 mutations and 944 population-matched cancer-free control participants from an Australian population. Rare (minor allele frequency ≤ 0.001 in the Exome Aggregation Consortium and Exome Variant Server databases) loss-of-function (LoF) and missense variants were studied.ResultsLoF variants were rare in both the cases and control participants across all the candidate genes, with only 38 different LoF variants observed in a total of 39 carriers. For the majority of genes (n = 36), no LoF variants were detected in either the case or control cohorts. No individual gene showed a significant excess of LoF or missense variants in the cases compared with control participants. Among all candidate genes as a group, the total number of carriers with LoF variants was higher in the cases than in the control participants (26 cases and 13 control participants), as was the total number of carriers with missense variants (406 versus 353), but neither reached statistical significance (p = 0.077 and p = 0.512, respectively). The genes contributing most of the excess of LoF variants in the cases included TET2, NRIP1, RAD51B and SNX32 (12 cases versus 2 control participants), whereas ZNF283 and CASP8 contributed largely to the excess of missense variants (25 cases versus 8 control participants).ConclusionsOur data suggest that rare LoF and missense variants in genes associated with low-penetrance breast cancer risk SNPs may contribute some additional risk, but as a group these genes are unlikely to be major contributors to breast cancer heritability.

Systematic identification of regulatory variants associated with cancer risk

BackgroundMost cancer risk-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are noncoding and it is challenging to assess their functional impacts. To systematically identify the SNPs that affect gene expression by modulating activities of distal regulatory elements, we adapt the self-transcribing active regulatory region sequencing (STARR-seq) strategy, a high-throughput technique to functionally quantify enhancer activities.ResultsFrom 10,673 SNPs linked with 996 cancer risk-associated SNPs identified in previous GWAS studies, we identify 575 SNPs in the fragments that positively regulate gene expression, and 758 SNPs in the fragments with negative regulatory activities. Among them, 70 variants are regulatory variants for which the two alleles confer different regulatory activities. We analyze in depth two regulatory variants—breast cancer risk SNP rs11055880 and leukemia risk-associated SNP rs12142375—and demonstrate their endogenous regulatory activities on expression of ATF7IP and PDE4B genes, respectively, using a CRISPR-Cas9 approach.ConclusionsBy identifying regulatory variants associated with cancer susceptibility and studying their molecular functions, we hope to help the interpretation of GWAS results and provide improved information for cancer risk assessment.

Abstract 1444: Validation of prostate cancer risk variants by CRISPR/Cas9 mediated genome editing at the MSMB locus

Abstract Genome wide association studies (GWAS) have identified nuermous single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. While numerous in silico analyses suggest that the majority of these SNPs may function through regulation of gene expression, wet lab experiments to distinguish the causative variants from their linkage disequilibrium (LD) partners is still needed. Here, we demonstrate how genome editing can investigate the role of individual polymorphisms on gene expression. Here, we focus on the prostate cancer-associated SNP rs10993994, which is in the promoter of the MSMB gene that encodes for the prostate-secreted protein beta-MSP. This SNP is notable because it associates with seminal and serum levels of beta-MSP, PSA, and hK2; mRNA levels of MSMB and the nearby androgen receptor co-activator NCOA4 in the prostate; and mRNA levels of MSMB in the stomach. Intriguingly, rs10993994 is not a gastric cancer risk SNP suggesting that there may be other variants with prostate-specific function responsible for the observed prostate cancer association. Using data from the FANTOM5 project, we show that rs7098889, in LD with rs10993994, is located in one of the most prostate-specific enhancers. We had previously shown that this SNP is associated with beta-MSP independent of rs10993994. To distinguish the effects of these two SNPs on gene expression, we generated a series of double gRNA mediated CRISPR/Cas9 deletions of the relevant regulatory elements. Removing the element containing rs7098889 flanking region results in ~10 to 20 fold increase of MSMB expression in the prostate cancer LNCaP cell line but not in the gastric cancer AGS cell line. There is no change in NCOA4 in either cell line. Removing rs10993994 flanking region results in over 10 fold increase of MSMB expression and ~50% decrease of NCOA4 in LNCaP. As both LNCaP and AGS are heterozygous for both SNPs, we then generated single clones in which only one allele was removed. For rs7098889, an over 300 fold increase of MSMB expression was observed in two out of the three clones with the T but not the C allele. Transcripts from high expressers all came from one allele. Similarly, single clone analysis showed 40 to 60 fold up-regulation of MSMB expression in two out of three clones with the C but not the T allele of rs10993994. This is consistent with the observation for rs7098889 since rs7098889T and rs10993994C are on the same haplotype. Our work demonstrates dramatic and locus specific effect of individual polymorphisms on gene expression, which strongly support the notion that an important function of disease risk variants is through regulation of gene expression. Citation Format: Xing Wang, James Hayes, Xing Xu, Dipti Mehtad, Xiaoni Gao, Hans Lilja, Robert Klein. Validation of prostate cancer risk variants by CRISPR/Cas9 mediated genome editing at the MSMB locus [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1444. doi:10.1158/1538-7445.AM2017-1444

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods.

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients. This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation. The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics. Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Genetic Breast Cancer Susceptibility Variants and Prognosis in the Prospectively Randomized SUCCESS A Study.

Large-scale genotyping studies have identified over 70 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. However, knowledge regarding genetic risk factors associated with the prognosis is limited. The aim of this study was therefore to investigate the prognostic effect of nine known breast cancer risk SNPs. BC patients (n = 1687) randomly sampled in an adjuvant, randomized phase III trial (SUCCESS A study) were genotyped for nine BC risk SNPs: rs17468277 (CASP8) , rs2981582 (FGFR2) , rs13281615(8q24), rs3817198 (LSP1) , rs889312 (MAP3K1) , rs3803662 (TOX3) , rs13387042(2q35), rs4973768 (SLC4A7) , rs6504950 (COX11) . Cox proportional hazards models were used to test the SNPs' association with overall survival (OS) and progression-free survival (PFS). Additional analyses were carried out for molecular subgroups. rs3817198 in LSP1 (lymphocyte-specific protein 1) was the only SNP that significantly influenced OS (p = 0.01) and PFS (p < 0.01) in the likelihood ratio test comparing the genetic survival model with the clinical survival model. In the molecular subgroups, triple-negative patients with two minor alleles in rs3817198 had a much better prognosis relative to OS (adjusted HR 0.03; 95% CI 0.002 - 0.279) and PFS (HR 0.09; 95% CI 0.02 - 0.36) than patients with the common alleles. The same effect on PFS was shown for patients with luminal A tumors (HR 0.19; 95% CI 0.05 - 0.84), whereas patients with luminal B tumors had a poorer PFS with two minor alleles (HR 2.13; 95% CI 1.02 - 4.40). The variant in rs3817198 has a prognostic effect particularly in the subgroup of patients with triple-negative BC, suggesting a possible link with immunomodulation and BC.

Previous GWAS hits in relation to young-onset breast cancer.

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered. Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects. Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR=1.39; p=7.0×10-6), rs12662670-G (ESR1, RR=1.56; p=5.7×10-4), rs2981579-A (FGFR2, RR=1.24; p=0.002), and rs999737-G (RAD51B, RR=1.37; p=0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p=2.2×10-7) and consistent with a multiplicative joint effect (multiplicative-fit p=0.27). With the multiplicative formulation, the case sister's genetic risk score exceeded that of her unaffected sister in 59% of families. The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.