Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition.

Checkpoint inhibitors (CPIs) augment adaptive immunity. Systematic pan-tumor analyses may reveal the relative importance of tumor-cell-intrinsic and microenvironmental features underpinning CPI sensitization. Here, we collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization. Clonal tumor mutation burden (TMB) was the strongest predictor of CPI response, followed by total TMB and CXCL9 expression. Subclonal TMB, somatic copy alteration burden, and histocompatibility leukocyte antigen (HLA) evolutionary divergence failed to attain pan-cancer significance. Dinucleotide variants were identified as a source of immunogenic epitopes associated with radical amino acid substitutions and enhanced peptide hydrophobicity/immunogenicity. Copy-number analysis revealed two additional determinants of CPI outcome supported by prior functional evidence: 9q34 (TRAF2) loss associated with response and CCND1 amplification associated with resistance. Finally, single-cell RNA sequencing (RNA-seq) of clonal neoantigen-reactive CD8 tumor-infiltrating lymphocytes (TILs), combined with bulk RNA-seq analysis of CPI-responding tumors, identified CCR5 and CXCL13 as T-cell-intrinsic markers of CPI sensitivity.

Evidence That STK19 Is Not an NRAS-dependent Melanoma Driver.

STK19 was proposed to be a cancer driver, and recent work by Yin et al. (2019) in Cell suggested that the frequently recurring STK19 D89N substitution represents a gain-of-function change, allowing increased phosphorylation of NRAS to enhance melanocyte transformation. Here we show that the STK19 gene has been incorrectly annotated, and that the expressed protein is 110 amino acids shorter than indicated by current databases. The "cancer driving" STK19 D89N substitution is thus outside the coding region. We also fail to detect evidence of the mutation affecting STK19 expression; instead, it is a UV signature mutation, found in the promoter of other genes as well. Furthermore, STK19 is exclusively nuclear and chromatin-associated, while no evidence for it being a kinase was found. The data in this Matters Arising article raise fundamental questions about the recently proposed role for STK19 in melanoma progression via a function as an NRAS kinase, suggested by Yin et al. (2019) in Cell. See also the response by Yin et al. (2020), published in this issue.

UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Timing the Landmark Events in the Evolution of Clear Cell Renal Cell Cancer: TRACERx Renal.

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5' UTR of TERT, targeting a MYC-MAX-MAD1 repressor associated with telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. This event occurs in childhood or adolescence, generally as the initiating event that precedes emergence of the tumor's most recent common ancestor by years to decades. Similar genomic changes drive inherited ccRCC. Modeling differences in age incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Early development of ccRCC follows well-defined evolutionary trajectories, offering opportunity for early intervention.

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

Genomic-transcriptomic evolution in lung cancer and metastasis.

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

Antibodies against endogenous retroviruses promote lung cancer immunotherapy.

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA.

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

Using DNA sequencing data to quantify T cell fraction and therapy response.

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes.

Pervasive chromosomal instability and karyotype order in tumour evolution.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.

Cancer evolution: Darwin and beyond.

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

Frequency of pathogenic germline variants in cancer susceptibility genes in 1336 renal cell carcinoma cases.

Renal cell carcinoma (RCC) occurs in a number of cancer predisposition syndromes, but the genetic architecture of susceptibility to RCC is not well defined. We investigated the frequency of pathogenic and likely pathogenic (P/LP) germline variants in cancer susceptibility genes (CSGs) within a large series of unselected RCC participants. Whole-genome sequencing data on 1336 RCC participants and 5834 controls recruited to the UK 100 000 Genomes Project, a nationwide multicentre study, was analyzed to identify rare P/LP short variants (single nucleotide variants and insertions/deletions ranging from 1 to 50 base pairs) and structural variants in 121 CSGs. Among 1336 RCC participants [mean: 61.3 years (±12 SD), range: 13-88 years; 64% male], 85 participants [6.4%; 95% CI (5.1, 7.8)] had one or more P/LP germline variant in a wider range of CSGs than previously recognized. A further 64 intragenic variants in CSGs previously associated with RCC were classified as a variant of uncertain significance (VUS) (24 'hot VUSs') and were considered to be of potential clinical relevance as further evaluation might results in their reclassification. Most patients with P variants in well-established CSGs known to predispose to renal cell carcinoma (RCC-CSGs) were aged <50 years. Burden test analysis for filtered variants in CSGs demonstrated a significant excess of CHEK2 variants in European RCC participants compared with the healthy European controls (P = 0.0019). Approximately, 6% of the patients with RCC unselected for family history have a germline variant requiring additional follow-up analysis. To improve diagnostic yield, we suggest expanding the panel of RCC-CSGs tested to include CHEK2 and all SDHx subunits and raising the eligibility criteria for age-based testing.

Genomic evolution and chemoresistance in germ-cell tumours.

Germ-cell tumours (GCTs) are derived from germ cells and occur most frequently in the testes. GCTs are histologically heterogeneous and distinctly curable with chemotherapy. Gains of chromosome arm 12p and aneuploidy are nearly universal in GCTs, but specific somatic genomic features driving tumour initiation, chemosensitivity and progression are incompletely characterized. Here, using clinical whole-exome and transcriptome sequencing of precursor, primary (testicular and mediastinal) and chemoresistant metastatic human GCTs, we show that the primary somatic feature of GCTs is highly recurrent chromosome arm level amplifications and reciprocal deletions (reciprocal loss of heterozygosity), variations that are significantly enriched in GCTs compared to 19 other cancer types. These tumours also acquire KRAS mutations during the development from precursor to primary disease, and primary testicular GCTs (TGCTs) are uniformly wild type for TP53. In addition, by functional measurement of apoptotic signalling (BH3 profiling) of fresh tumour and adjacent tissue, we find that primary TGCTs have high mitochondrial priming that facilitates chemotherapy-induced apoptosis. Finally, by phylogenetic analysis of serial TGCTs that emerge with chemotherapy resistance, we show how TGCTs gain additional reciprocal loss of heterozygosity and that this is associated with loss of pluripotency markers (NANOG and POU5F1) in chemoresistant teratomas or transformed carcinomas. Our results demonstrate the distinct genomic features underlying the origins of this disease and associated with the chemosensitivity phenotype, as well as the rare progression to chemoresistance. These results identify the convergence of cancer genomics, mitochondrial priming and GCT evolution, and may provide insights into chemosensitivity and resistance in other cancers.

Identification of conserved evolutionary trajectories in tumors.

MOTIVATION: As multi-region, time-series and single-cell sequencing data become more widely available; it is becoming clear that certain tumors share evolutionary characteristics with others. In the last few years, several computational methods have been developed with the goal of inferring the subclonal composition and evolutionary history of tumors from tumor biopsy sequencing data. However, the phylogenetic trees that they report differ significantly between tumors (even those with similar characteristics). RESULTS: In this article, we present a novel combinatorial optimization method, CONETT, for detection of recurrent tumor evolution trajectories. Our method constructs a consensus tree of conserved evolutionary trajectories based on the information about temporal order of alteration events in a set of tumors. We apply our method to previously published datasets of 100 clear-cell renal cell carcinoma and 99 non-small-cell lung cancer patients and identify both conserved trajectories that were reported in the original studies, as well as new trajectories. AVAILABILITY AND IMPLEMENTATION: CONETT is implemented in C++ and available at https://github.com/ehodzic/CONETT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PhISCS-BnB: a fast branch and bound algorithm for the perfect tumor phylogeny reconstruction problem.

MOTIVATION: Recent advances in single-cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program, or a constraint satisfaction program, which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology. RESULTS: We introduce PhISCS-BnB (phylogeny inference using SCS via branch and bound), a branch and bound algorithm to compute the most likely perfect phylogeny on an input genotype matrix extracted from an SCS dataset. PhISCS-BnB not only offers an optimality guarantee, but is also 10-100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a recently published large melanoma dataset derived from the sublineages of a cell line involving 20 clones with 2367 mutations, which returned the optimal tumor phylogeny in <4 h. The resulting phylogeny agrees with and extends the published results by providing a more detailed picture on the clonal evolution of the tumor. AVAILABILITY AND IMPLEMENTATION: https://github.com/algo-cancer/PhISCS-BnB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Germ line mutations in shelterin complex genes are associated with familial chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) can be familial; however, thus far no rare germ line disruptive alleles for CLL have been identified. We performed whole-exome sequencing of 66 CLL families, identifying 4 families where loss-of-function mutations in protection of telomeres 1 (POT1) co-segregated with CLL. The p.Tyr36Cys mutation is predicted to disrupt the interaction between POT1 and the telomeric overhang. The c.1164-1G>A splice-site, p.Gln358SerfsTer13 frameshift, and p.Gln376Arg missense mutations are likely to impact the interaction between POT1 and adrenocortical dysplasia homolog (ACD), which is a part of the telomere-capping shelterin complex. We also identified mutations in ACD (c.752-2A>C) and another shelterin component, telomeric repeat binding factor 2, interacting protein (p.Ala104Pro and p.Arg133Gln), in 3 CLL families. In a complementary analysis of 1083 cases and 5854 controls, the POT1 p.Gln376Arg variant, which has a global minor allele frequency of 0.0005, conferred a 3.61-fold increased risk of CLL (P = .009). This study further highlights telomere dysregulation as a key process in CLL development.

Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis.

BACKGROUND: The focus of tumour-specific antigen analyses has been on single nucleotide variants (SNVs), with the contribution of small insertions and deletions (indels) less well characterised. We investigated whether the frameshift nature of indel mutations, which create novel open reading frames and a large quantity of mutagenic peptides highly distinct from self, might contribute to the immunogenic phenotype. METHODS: We analysed whole-exome sequencing data from 5777 solid tumours, spanning 19 cancer types from The Cancer Genome Atlas. We compared the proportion and number of indels across the cohort, with a subset of results replicated in two independent datasets. We assessed in-silico tumour-specific neoantigen predictions by mutation type with pan-cancer analysis, together with RNAseq profiling in renal clear cell carcinoma cases (n=392), to compare immune gene expression across patient subgroups. Associations between indel burden and treatment response were assessed across four checkpoint inhibitor datasets. FINDINGS: We observed renal cell carcinomas to have the highest proportion (0·12) and number of indel mutations across the pan-cancer cohort (p<2·2 × 10-16), more than double the median proportion of indel mutations in all other cancer types examined. Analysis of tumour-specific neoantigens showed that enrichment of indel mutations for high-affinity binders was three times that of non-synonymous SNV mutations. Furthermore, neoantigens derived from indel mutations were nine times enriched for mutant specific binding, as compared with non-synonymous SNV derived neoantigens. Immune gene expression analysis in the renal clear cell carcinoma cohort showed that the presence of mutant-specific neoantigens was associated with upregulation of antigen presentation genes, which correlated (r=0·78) with T-cell activation as measured by CD8-positive expression. Finally, analysis of checkpoint inhibitor response data revealed frameshift indel count to be significantly associated with checkpoint inhibitor response across three separate melanoma cohorts (p=4·7 × 10-4). INTERPRETATION: Renal cell carcinomas have the highest pan-cancer proportion and number of indel mutations. Evidence suggests indels are a highly immunogenic mutational class, which can trigger an increased abundance of neoantigens and greater mutant-binding specificity. FUNDING: Cancer Research UK, UK National Institute for Health Research (NIHR) at the Royal Marsden Hospital National Health Service Foundation Trust, Institute of Cancer Research and University College London Hospitals Biomedical Research Centres, the UK Medical Research Council, the Rosetrees Trust, Novo Nordisk Foundation, the Prostate Cancer Foundation, the Breast Cancer Research Foundation, the European Research Council.

Multi-stage genome-wide association study identifies new susceptibility locus for testicular germ cell tumour on chromosome 3q25.

Recent genome-wide association studies (GWAS) and subsequent meta-analyses have identified over 25 SNPs at 18 loci, together accounting for >15% of the genetic susceptibility to testicular germ cell tumour (TGCT). To identify further common SNPs associated with TGCT, here we report a three-stage experiment, involving 4098 cases and 18 972 controls. Stage 1 comprised previously published GWAS analysis of 307 291 SNPs in 986 cases and 4946 controls. In Stage 2, we used previously published customised Illumina iSelect genotyping array (iCOGs) data across 694 SNPs in 1064 cases and 10 082 controls. Here, we report new genotyping of eight SNPs showing some evidence of association in combined analysis of Stage 1 and Stage 2 in an additional 2048 cases of TGCT and 3944 controls (Stage 3). Through fixed-effects meta-analysis across three stages, we identified a novel locus at 3q25.31 (rs1510272) demonstrating association with TGCT [per-allele odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.06-1.27; P = 1.2 × 10(-9)].

Pathway-based analysis of GWAs data identifies association of sex determination genes with susceptibility to testicular germ cell tumors.

Genome-wide association (GWA) studies of testicular germ cell tumor (TGCT) have identified 18 susceptibility loci, some containing genes encoding proteins important in male germ cell development. Deletions of one of these genes, DMRT1, lead to male-to-female sex reversal and are associated with development of gonadoblastoma. To further explore genetic association with TGCT, we undertook a pathway-based analysis of SNP marker associations in the Penn GWAs (349 TGCT cases and 919 controls). We analyzed a custom-built sex determination gene set consisting of 32 genes using three different methods of pathway-based analysis. The sex determination gene set ranked highly compared with canonical gene sets, and it was associated with TGCT (FDRG = 2.28 × 10(-5), FDRM = 0.014 and FDRI = 0.008 for Gene Set Analysis-SNP (GSA-SNP), Meta-Analysis Gene Set Enrichment of Variant Associations (MAGENTA) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (i-GSEA4GWAS) analysis, respectively). The association remained after removal of DMRT1 from the gene set (FDRG = 0.0002, FDRM = 0.055 and FDRI = 0.009). Using data from the NCI GWA scan (582 TGCT cases and 1056 controls) and UK scan (986 TGCT cases and 4946 controls), we replicated these findings (NCI: FDRG = 0.006, FDRM = 0.014, FDRI = 0.033, and UK: FDRG = 1.04 × 10(-6), FDRM = 0.016, FDRI = 0.025). After removal of DMRT1 from the gene set, the sex determination gene set remains associated with TGCT in the NCI (FDRG = 0.039, FDRM = 0.050 and FDRI = 0.055) and UK scans (FDRG = 3.00 × 10(-5), FDRM = 0.056 and FDRI = 0.044). With the exception of DMRT1, genes in the sex determination gene set have not previously been identified as TGCT susceptibility loci in these GWA scans, demonstrating the complementary nature of a pathway-based approach for genome-wide analysis of TGCT.