A Somatically Acquired Enhancer of the Androgen Receptor Is a Noncoding Driver in Advanced Prostate Cancer.

Increased androgen receptor (AR) activity drives therapeutic resistance in advanced prostate cancer. The most common resistance mechanism is amplification of this locus presumably targeting the AR gene. Here, we identify and characterize a somatically acquired AR enhancer located 650 kb centromeric to the AR. Systematic perturbation of this enhancer using genome editing decreased proliferation by suppressing AR levels. Insertion of an additional copy of this region sufficed to increase proliferation under low androgen conditions and to decrease sensitivity to enzalutamide. Epigenetic data generated in localized prostate tumors and benign specimens support the notion that this region is a developmental enhancer. Collectively, these observations underscore the importance of epigenomic profiling in primary specimens and the value of deploying genome editing to functionally characterize noncoding elements. More broadly, this work identifies a therapeutic vulnerability for targeting the AR and emphasizes the importance of regulatory elements as highly recurrent oncogenic drivers.

Integrative eQTL-based analyses reveal the biology of breast cancer risk loci.

Germline determinants of gene expression in tumors are infrequently studied due to the complexity of transcript regulation caused by somatically acquired alterations. We performed expression quantitative trait locus (eQTL)-based analyses using the multi-level information provided in The Cancer Genome Atlas (TCGA). Of the factors we measured, cis-acting eQTLs accounted for 1.2% of the total variation of tumor gene expression, while somatic copy-number alteration and CpG methylation accounted for 7.3% and 3.3%, respectively. eQTL analyses of 15 previously reported breast cancer risk loci resulted in the discovery of three variants that are significantly associated with transcript levels (false discovery rate [FDR] < 0.1). Our trans-based analysis identified an additional three risk loci to act through ESR1, MYC, and KLF4. These findings provide a more comprehensive picture of gene expression determinants in breast cancer as well as insights into the underlying biology of breast cancer risk loci.

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies.

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

Allele-specific epigenetic activity in prostate cancer and normal prostate tissue implicates prostate cancer risk mechanisms.

Genome-wide association studies (GWASs) of prostate cancer have identified >250 significant risk loci, but the causal variants and mechanisms for these loci remain largely unknown. Here, we sought to identify and characterize risk-harboring regulatory elements by integrating epigenomes from primary prostate tumor and normal tissues of 27 individuals across the H3K27ac, H3K4me3, and H3K4me2 histone marks and FOXA1 and HOXB13 transcription factors. We identified 7,371 peaks with significant allele specificity (allele-specific quantitative trait locus [asQTL] peaks). Showcasing their relevance to prostate cancer risk, H3K27ac T-asQTL peaks were the single annotation most enriched for prostate cancer GWAS heritability (40×), significantly higher than corresponding non-asQTL H3K27ac peaks (14×) or coding regions (14×). Surprisingly, fine-mapped GWAS risk variants were most significantly enriched for asQTL peaks observed in tumors, including asQTL peaks that were differentially imbalanced with respect to tumor-normal states. These data pinpointed putative causal regulatory elements at 20 GWAS loci, of which 11 were detected only in the tumor samples. More broadly, tumor-specific asQTLs were enriched for expression QTLs in benign tissues as well as accessible regions found in stem cells, supporting a hypothesis where some germline variants become reactivated during or after transformation and can be captured by epigenomic profiling of the tumor. Our study demonstrates the power of allele specificity in chromatin signals to uncover GWAS mechanisms, highlights the relevance of tumor-specific regulation in the context of cancer risk, and prioritizes multiple loci for experimental follow-up.

H3K27ac HiChIP in prostate cell lines identifies risk genes for prostate cancer susceptibility.

Genome-wide association studies (GWASs) have identified more than 200 prostate cancer (PrCa) risk regions, which provide potential insights into causal mechanisms. Multiple lines of evidence show that a significant proportion of PrCa risk can be explained by germline causal variants that dysregulate nearby target genes in prostate-relevant tissues, thus altering disease risk. The traditional approach to explore this hypothesis has been correlating GWAS variants with steady-state transcript levels, referred to as expression quantitative trait loci (eQTLs). In this work, we assess the utility of chromosome conformation capture (3C) coupled with immunoprecipitation (HiChIP) to identify target genes for PrCa GWAS risk loci. We find that interactome data confirm previously reported PrCa target genes identified through GWAS/eQTL overlap (e.g., MLPH). Interestingly, HiChIP identifies links between PrCa GWAS variants and genes well-known to play a role in prostate cancer biology (e.g., AR) that are not detected by eQTL-based methods. HiChIP predicted enhancer elements at the AR and NKX3-1 prostate cancer risk loci, and both were experimentally confirmed to regulate expression of the corresponding genes through CRISPR interference (CRISPRi) perturbation in LNCaP cells. Our results demonstrate that looping data harbor additional information beyond eQTLs and expand the number of PrCa GWAS loci that can be linked to candidate susceptibility genes.

Allele-Specific QTL Fine Mapping with PLASMA.

Although quantitative trait locus (QTL) associations have been identified for many molecular traits such as gene expression, it remains challenging to distinguish the causal nucleotide from nearby variants. In addition to traditional QTLs by association, allele-specific (AS) QTLs are a powerful measure of cis-regulation that are concordant with traditional QTLs but typically less susceptible to technical/environmental noise. However, existing methods for estimating causal variant probabilities (i.e., fine mapping) cannot produce valid estimates from asQTL signals due to complexities in linkage disequilibrium (LD). We introduce PLASMA (Population Allele-Specific Mapping), a fine-mapping method that integrates QTL and asQTL information to improve accuracy. In simulations, PLASMA accurately prioritizes causal variants over a wide range of genetic architectures. Applied to RNA-seq data from 524 kidney tumor samples, PLASMA achieves a greater power at 50 samples than conventional QTL-based fine mapping at 500 samples, with more than 17% of loci fine mapped to within five causal variants, compared to 2% by QTL-based fine mapping, and a 6.9-fold overall reduction in median credible set size compared to QTL-based fine mapping when applied to H3K27AC ChIP-seq from just 28 prostate tumor/normal samples. Variants in the PLASMA credible sets for RNA-seq and ChIP-seq were enriched for open chromatin and chromatin looping, respectively, at a comparable or greater degree than credible variants from existing methods while containing far fewer markers. Our results demonstrate how integrating AS activity can substantially improve the detection of causal variants from existing molecular data.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women.

OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7). CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

Exome sequencing reveals recurrent germ line variants in patients with familial Waldenström macroglobulinemia.

Familial aggregation of Waldenström macroglobulinemia (WM) cases, and the clustering of B-cell lymphoproliferative disorders among first-degree relatives of WM patients, has been reported. Nevertheless, the possible contribution of inherited susceptibility to familial WM remains unrevealed. We performed whole exome sequencing on germ line DNA obtained from 4 family members in which coinheritance for WM was documented in 3 of them, and screened additional independent 246 cases by using gene-specific mutation sequencing. Among the shared germ line variants, LAPTM5(c403t) and HCLS1(g496a) were the most recurrent, being present in 3/3 affected members of the index family, detected in 8% of the unrelated familial cases, and present in 0.5% of the nonfamilial cases and in <0.05 of a control population. LAPTM5 and HCLS1 appeared as relevant WM candidate genes that characterized familial WM individuals and were also functionally relevant to the tumor clone. These findings highlight potentially novel contributors for the genetic predisposition to familial WM and indicate that LAPTM5(c403t) and HCLS1(g496a) may represent predisposition alleles in patients with familial WM.

Inference of transcriptional regulation in cancers.

Despite the rapid accumulation of tumor-profiling data and transcription factor (TF) ChIP-seq profiles, efforts integrating TF binding with the tumor-profiling data to understand how TFs regulate tumor gene expression are still limited. To systematically search for cancer-associated TFs, we comprehensively integrated 686 ENCODE ChIP-seq profiles representing 150 TFs with 7484 TCGA tumor data in 18 cancer types. For efficient and accurate inference on gene regulatory rules across a large number and variety of datasets, we developed an algorithm, RABIT (regression analysis with background integration). In each tumor sample, RABIT tests whether the TF target genes from ChIP-seq show strong differential regulation after controlling for background effect from copy number alteration and DNA methylation. When multiple ChIP-seq profiles are available for a TF, RABIT prioritizes the most relevant ChIP-seq profile in each tumor. In each cancer type, RABIT further tests whether the TF expression and somatic mutation variations are correlated with differential expression patterns of its target genes across tumors. Our predicted TF impact on tumor gene expression is highly consistent with the knowledge from cancer-related gene databases and reveals many previously unidentified aspects of transcriptional regulation in tumor progression. We also applied RABIT on RNA-binding protein motifs and found that some alternative splicing factors could affect tumor-specific gene expression by binding to target gene 3'UTR regions. Thus, RABIT (rabit.dfci.harvard.edu) is a general platform for predicting the oncogenic role of gene expression regulators.

The association between germline BRCA2 variants and sensitivity to platinum-based chemotherapy among men with metastatic prostate cancer.

BACKGROUND: Breast cancer 2 (BRCA2)-associated breast and ovarian cancers are sensitive to platinum-based chemotherapy. It is unknown whether BRCA2-associated prostate cancer responds favorably to such treatment. METHODS: A retrospective analysis of a single-institution cohort of men with castration-resistant, metastatic prostate cancer was performed to determine the association between carrier status of pathogenic BRCA2 germline variants and prostate-specific antigen response to carboplatin-based chemotherapy. From 2001 through 2015, 8081 adult men with prostate cancer who had a consultation and/or underwent treatment at Dana-Farber Cancer Institute provided blood samples and consented to analyses of biologic material and clinical records. A subgroup of 141 men received at least 2 doses of carboplatin and docetaxel for castration-resistant disease (94% were also taxane refractory). These patients were categorized according to the absence or presence of pathogenic germline mutations in BRCA2 based on DNA sequencing from whole blood. The primary outcome was the response rate to carboplatin/docetaxel chemotherapy, defined according to a decline in prostate-specific antigen that exceeded 50% within 12 weeks of initiating this regimen. Associations between BRCA2 mutation status and response to carboplatin-based chemotherapy were tested using the Fisher exact test, with a 2-sided P value < .05 as the threshold for significance. RESULTS: Pathogenic germline BRCA2 variants were observed in 8 of 141 men (5.7%; 95% confidence interval, 2.5%-10.9%). Six of 8 BRCA2 carriers (75%) experienced prostate-specific antigen declines >50% within 12 weeks, compared with 23 of 133 noncarriers (17%; absolute difference, 58%; 95% confidence interval, 27%-88%; P < .001). Prostate cancer cell lines functionally corroborated these clinical findings. CONCLUSIONS: BRCA2-associated, castration-resistant prostate cancer is associated with a higher likelihood of response to carboplatin-based chemotherapy than non-BRCA2-associated prostate cancer. Cancer 2017;123:3532-9. © 2017 American Cancer Society.

Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types.

The majority of trait-associated loci discovered through genome-wide association studies are located outside of known protein coding regions. Consequently, it is difficult to ascertain the mechanism underlying these variants and to pinpoint the causal alleles. Expression quantitative trait loci (eQTLs) provide an organizing principle to address both of these issues. eQTLs are genetic loci that correlate with RNA transcript levels. Large-scale data sets such as the Cancer Genome Atlas (TCGA) provide an ideal opportunity to systematically evaluate eQTLs as they have generated multiple data types on hundreds of samples. We evaluated the determinants of gene expression (germline variants and somatic copy number and methylation) and performed cis-eQTL analyses for mRNA expression and miRNA expression in five tumor types (breast, colon, kidney, lung and prostate). We next tested 149 known cancer risk loci for eQTL effects, and observed that 42 (28.2%) were significantly associated with at least one transcript. Lastly, we described a fine-mapping strategy for these 42 eQTL target-gene associations based on an integrated strategy that combines the eQTL level of significance and the regulatory potential as measured by DNaseI hypersensitivity. For each of the risk loci, our analyses suggested 1 to 81 candidate causal variants that may be prioritized for downstream functional analysis. In summary, our study provided a comprehensive landscape of the genetic determinants of gene expression in different tumor types and ranked the genes and loci for further functional assessment of known cancer risk loci.

Macrocytic anemia and mitochondriopathy resulting from a defect in sideroflexin 4.

We used exome sequencing to identify mutations in sideroflexin 4 (SFXN4) in two children with mitochondrial disease (the more severe case also presented with macrocytic anemia). SFXN4 is an uncharacterized mitochondrial protein that localizes to the mitochondrial inner membrane. sfxn4 knockdown in zebrafish recapitulated the mitochondrial respiratory defect observed in both individuals and the macrocytic anemia with megaloblastic features of the more severe case. In vitro and in vivo complementation studies with fibroblasts from the affected individuals and zebrafish demonstrated the requirement of SFXN4 for mitochondrial respiratory homeostasis and erythropoiesis. Our findings establish mutations in SFXN4 as a cause of mitochondriopathy and macrocytic anemia.

Multiple regions within 8q24 independently affect risk for prostate cancer.

After the recent discovery that common genetic variation in 8q24 influences inherited risk of prostate cancer, we genotyped 2,973 SNPs in up to 7,518 men with and without prostate cancer from five populations. We identified seven risk variants, five of them previously undescribed, spanning 430 kb and each independently predicting risk for prostate cancer (P = 7.9 x 10(-19) for the strongest association, and P < 1.5 x 10(-4) for five of the variants, after controlling for each of the others). The variants define common genotypes that span a more than fivefold range of susceptibility to cancer in some populations. None of the prostate cancer risk variants aligns to a known gene or alters the coding sequence of an encoded protein.

Calling amplified haplotypes in next generation tumor sequence data.

During tumor initiation and progression, cancer cells acquire a selective advantage, allowing them to outcompete their normal counterparts. Identification of the genetic changes that underlie these tumor acquired traits can provide deeper insights into the biology of tumorigenesis. Regions of copy number alterations and germline DNA variants are some of the elements subject to selection during tumor evolution. Integrated examination of inherited variation and somatic alterations holds the potential to reveal specific nucleotide alleles that a tumor "prefers" to have amplified. Next-generation sequencing of tumor and matched normal tissues provides a high-resolution platform to identify and analyze such somatic amplicons. Within an amplicon, examination of informative (e.g., heterozygous) sites deviating from a 1:1 ratio may suggest selection of that allele. A naive approach examines the reads for each heterozygous site in isolation; however, this ignores available valuable linkage information across sites. We, therefore, present a novel hidden Markov model-based method-Haplotype Amplification in Tumor Sequences (HATS)-that analyzes tumor and normal sequence data, along with training data for phasing purposes, to infer amplified alleles and haplotypes in regions of copy number gain. Our method is designed to handle rare variants and biases in read data. We assess the performance of HATS using simulated amplified regions generated from varying copy number and coverage levels, followed by amplicons in real data. We demonstrate that HATS infers the amplified alleles more accurately than does the naive approach, especially at low to intermediate coverage levels and in cases (including high coverage) possessing stromal contamination or allelic bias.

Genetic and functional analyses implicate the NUDT11, HNF1B, and SLC22A3 genes in prostate cancer pathogenesis.

One of the central goals of human genetics is to discover the genes and pathways driving human traits. To date, most of the common risk alleles discovered through genome-wide association studies (GWAS) map to nonprotein-coding regions. Because of our relatively poorer understanding of this part of the genome, the functional consequences of trait-associated variants pose a considerable challenge. To identify the genes through which risk loci act, we hypothesized that the risk variants are regulatory elements. For each of 12 known risk polymorphisms, we evaluated the correlation between risk allele status and transcript abundance for all annotated protein-coding transcripts within a 1-Mb interval. A total of 103 transcripts were evaluated in 662 prostate tissue samples [normal (n = 407) and tumor (n = 255)] from 483 individuals [European Americans (n = 233), Japanese (n = 127), and African Americans (n = 123)]. In a pooled analysis, 4 of the 12 risk variants were strongly associated with five transcripts (NUDT11, MSMB, NCOA4, SLC22A3, and HNF1B) in histologically normal tissue (P ≤ 0.001). Although associations were also observed in tumor tissue, they tended to be more attenuated. Previously, we showed that MSMB and NCOA4 participate in prostate cancer pathogenesis. Suppressing the expression of NUDT11, SLC22A3, and HNF1B influences cellular phenotypes associated with tumor-related properties in prostate cancer cells. Taken together, the data suggest that these transcripts contribute to prostate cancer pathogenesis.

Transferability of tag SNPs in genetic association studies in multiple populations.

A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.

Epstein-Barr virus exploits intrinsic B-lymphocyte transcription programs to achieve immortal cell growth.

Epstein-Barr virus nuclear antigen 2 (EBNA2) regulation of transcription through the cell transcription factor RBPJ is essential for resting B-lymphocyte (RBL) conversion to immortal lymphoblast cell lines (LCLs). ChIP-seq of EBNA2 and RBPJ sites in LCL DNA found EBNA2 at 5,151 and RBPJ at 10,529 sites. EBNA2 sites were enriched for RBPJ (78%), early B-cell factor (EBF, 39%), RUNX (43%), ETS (39%), NFκB (22%), and PU.1 (22%) motifs. These motif associations were confirmed by LCL RBPJ ChIP-seq finding 72% RBPJ occupancy and Encyclopedia Of DNA Elements LCL ChIP-seq finding EBF, NFκB RELA, and PU.1 at 54%, 31%, and 17% of EBNA2 sites. EBNA2 and RBPJ were predominantly at intergene and intron sites and only 14% at promoter sites. K-means clustering of EBNA2 site transcription factors identified RELA-ETS, EBF-RUNX, EBF, ETS, RBPJ, and repressive RUNX clusters, which ranked from highest to lowest in H3K4me1 signals and nucleosome depletion, indicative of active chromatin. Surprisingly, although quantitatively less, the same genome sites in RBLs exhibited similar high-level H3K4me1 signals and nucleosome depletion. The EBV genome also had an LMP1 promoter EBF site, which proved critical for EBNA2 activation. LCL HiC data mapped intergenic EBNA2 sites to EBNA2 up-regulated genes. FISH and chromatin conformation capture linked EBNA2/RBPJ enhancers 428 kb 5' of MYC to MYC. These data indicate that EBNA2 evolved to target RBL H3K4me1 modified, nucleosome-depleted, nonpromoter sites to drive B-lymphocyte proliferation in primary human infection. The primed RBL program likely supports antigen-induced proliferation.

Demonstrating stratification in a European American population.

Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.

Single nucleotide polymorphisms and risk of recurrence of renal-cell carcinoma: a cohort study.

BACKGROUND: Germline genetic polymorphisms might affect the risk of recurrence in patients with localised renal-cell carcinoma. We investigated the association between genetic polymorphisms and recurrence of renal-cell carcinoma. METHODS: We analysed germline DNA samples extracted from patients with localised renal-cell carcinoma treated at the Dana-Farber/Harvard Cancer Center (Boston, MA, USA). We selected a discovery cohort from a prospective database at the Dana-Farber/Harvard Cancer Center and selected a validation cohort from department records at the Brigham and Women's Hospital (Boston, MA, USA). We validated the findings from the discovery cohort in the validation cohort. We genotyped 70 genes involved in the pathogenesis of renal-cell carcinoma (including the VHL/HIF/VEGF and PI3K/AKT/mTOR pathways, and genes involved in immune regulation and metabolism) for single nucleotide polymorphisms. We assessed the association between genotype and recurrence-free survival, adjusted for baseline characteristics, with the Cox proportional hazards model, the Kaplan-Meier method, and the log-rank test. We used a false discovery rate q value to adjust for multiple comparisons. FINDINGS: We included 554 patients (403 in the discovery cohort and 151 in the validation cohort). We successfully genotyped 290 single nucleotide polymorphisms in the discovery cohort, but excluded five because they did not have a variant group for comparison. The polymorphism rs11762213, which causes a synonymous aminoacid change in MET (144G→A, located in exon 2), was associated with recurrence-free survival. Patients with one or two copies of the minor (risk) allele had an increased risk of recurrence or death (hazard ratio [HR] 1·86, 95% CI 1·17-2·95; p=0·0084) in multivariate analysis. Median recurrence-free survival for carriers of the risk allele was 19 months (95% CI 9-not reached) versus 50 months (95% CI 37-75) for patients without the risk allele. In the validation cohort the HR was 2·45 (95% CI 1·01-5·95; p=0·048). INTERPRETATION: Patients with localised renal-cell carcinoma and the MET polymorphism rs11762213 might have an increased risk of recurrence after nephrectomy. If these results are further validated in a similar population, they could be incorporated into future prognostic instruments, potentially aiding the design of adjuvant clinical trials of MET inhibitors and management of renal-cell carcinoma. FUNDING: Conquer Cancer Foundation and American Society of Clinical Oncology (Career Development Award); The Trust Family Research Fund for Kidney Cancer; US National Institutes of Health, National Cancer Institute Kidney Cancer Specialized Program of Research Excellence.