Search

Supplementary Table S22: Segmented b-allele deficits

Supplementary Tables S16-S19, describing IHC results on NHS/HPFS data

Supplementary Tables S1, S3 through S15, S20, and S23

To understand the genetic drivers of immune recognition and evasion in colorectal cancer, we analyzed 1,211 colorectal cancer primary tumor samples, including 179 classified as microsatellite instability–high (MSI-high). This set includes The Cancer Genome Atlas colorectal cancer cohort of 592 samples, completed and analyzed here. MSI-high, a hypermutated, immunogenic subtype of colorectal cancer, had a high rate of significantly mutated genes in important immune-modulating pathways and in the antigen presentation machinery, including biallelic losses of B2M and HLA genes due to copy-number alterations and copy-neutral loss of heterozygosity. WNT/β-catenin signaling genes were significantly mutated in all colorectal cancer subtypes, and activated WNT/β-catenin signaling was correlated with the absence of T-cell infiltration. This large-scale genomic analysis of colorectal cancer demonstrates that MSI-high cases frequently undergo an immunoediting process that provides them with genetic events allowing immune escape despite high mutational load and frequent lymphocytic infiltration and, furthermore, that colorectal cancer tumors have genetic and methylation events associated with activated WNT signaling and T-cell exclusion.Significance: This multi-omic analysis of 1,211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to immune blockade therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not. Cancer Discov; 8(6); 730–49. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 663

Background The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatures of phenotypes such as clinical outcome has not been attained in almost any disease area. Here, we report a comprehensive analysis spanning prediction tasks from ulcerative colitis, atopic dermatitis, diabetes, to many cancer subtypes for a total of 24 binary and multiclass prediction problems and 26 survival analysis tasks. We systematically investigate the influence of gene subsets, normalization methods and prediction algorithms. Crucially, we also explore the novel use of deep representation learning methods on large transcriptomics compendia, such as GTEx and TCGA, to boost the performance of state-of-the-art methods. The resources and findings in this work should serve as both an up-to-date reference on attainable performance, and as a benchmarking resource for further research. Results Approaches that combine large numbers of genes outperformed single gene methods consistently and with a significant margin, but neither unsupervised nor semi-supervised representation learning techniques yielded consistent improvements in out-of-sample performance across datasets. Our findings suggest that using l2-regularized regression methods applied to centered log-ratio transformed transcript abundances provide the best predictive analyses overall. Conclusions Transcriptomics-based phenotype prediction benefits from proper normalization techniques and state-of-the-art regularized regression approaches. In our view, breakthrough performance is likely contingent on factors which are independent of normalization and general modeling techniques; these factors might include reduction of systematic errors in sequencing data, incorporation of other data types such as single-cell sequencing and proteomics, and improved use of prior knowledge.

Predictive biomarkers could allow more precise use of immune checkpoint inhibitors (ICIs) in treating advanced cancers. Given the central role of HLA molecules in immunity, variation at the HLA loci could differentially affect the response to ICIs. The aim of this epidemiological study was to determine the effect of HLA-A*03 as a biomarker for predicting response to immunotherapy.In this epidemiological study, we investigated the clinical outcomes (overall survival, progression free survival, and objective response rate) after treatment for advanced cancer in eight cohorts of patients: three observational cohorts of patients with various types of advanced tumours (the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets [MSK-IMPACT] cohort, the Dana-Farber Cancer Institute [DFCI] Profile cohort, and The Cancer Genome Atlas) and five clinical trials of patients with advanced bladder cancer (JAVELIN Solid Tumour) or renal cell carcinoma (CheckMate-009, CheckMate-010, CheckMate-025, and JAVELIN Renal 101). In total, these cohorts included 3335 patients treated with various ICI agents (anti-PD-1, anti-PD-L1, and anti-CTLA-4 inhibitors) and 10 917 patients treated with non-ICI cancer-directed therapeutic approaches. We initially modelled the association of HLA amino-acid variation with overall survival in the MSK-IMPACT discovery cohort, followed by a detailed analysis of the association between HLA-A*03 and clinical outcomes in MSK-IMPACT, with replication in the additional cohorts (two further observational cohorts and five clinical trials).HLA-A*03 was associated in an additive manner with reduced overall survival after ICI treatment in the MSK-IMPACT cohort (HR 1·48 per HLA-A*03 allele [95% CI 1·20-1·82], p=0·00022), the validation DFCI Profile cohort (HR 1·22 per HLA-A*03 allele, 1·05-1·42; p=0·0097), and in the JAVELIN Solid Tumour clinical trial for bladder cancer (HR 1·36 per HLA-A*03 allele, 1·01-1·85; p=0·047). The HLA-A*03 effect was observed across ICI agents and tumour types, but not in patients treated with alternative therapies. Patients with HLA-A*03 had shorter progression-free survival in the pooled patient population from the three CheckMate clinical trials of nivolumab for renal cell carcinoma (HR 1·31, 1·01-1·71; p=0·044), but not in those receiving control (everolimus) therapies. Objective responses were observed in none of eight HLA-A*03 homozygotes in the ICI group (compared with 59 [26·6%] of 222 HLA-A*03 non-carriers and 13 (17·1%) of 76 HLA-A*03 heterozygotes). HLA-A*03 was associated with shorter progression-free survival in patients receiving ICI in the JAVELIN Renal 101 randomised clinical trial for renal cell carcinoma (avelumab plus axitinib; HR 1·59 per HLA-A*03 allele, 1·16-2·16; p=0·0036), but not in those receiving control (sunitinib) therapy. Objective responses were recorded in one (12·5%) of eight HLA-A*03 homozygotes in the ICI group (compared with 162 [63·8%] of 254 HLA-A*03 non-carriers and 40 [55·6%] of 72 HLA-A*03 heterozygotes). HLA-A*03 was associated with impaired outcome in meta-analysis of all 3335 patients treated with ICI at genome-wide significance (p=2·01 × 10National Institutes of Health, Merck KGaA, and Pfizer.

Background Among patients with advanced renal cell carcinoma (RCC), those with sarcomatoid histology (sRCC) have the poorest prognosis. This analysis assessed the efficacy of avelumab plus axitinib versus sunitinib in patients with treatment-naive advanced sRCC. Methods The randomized, open-label, multicenter, phase III JAVELIN Renal 101 trial (NCT02684006) enrolled patients with treatment-naive advanced RCC. Patients were randomized 1 : 1 to receive either avelumab plus axitinib or sunitinib following standard doses and schedules. Assessments in this post hoc analysis of patients with sRCC included efficacy (including progression-free survival) and biomarker analyses. Results A total of 108 patients had sarcomatoid histology and were included in this post hoc analysis; 47 patients in the avelumab plus axitinib arm and 61 in the sunitinib arm. Patients in the avelumab plus axitinib arm had improved progression-free survival [stratified hazard ratio, 0.57 (95% confidence interval, 0.325-1.003)] and a higher objective response rate (46.8% versus 21.3%; complete response in 4.3% versus 0%) versus those in the sunitinib arm. Correlative gene expression analyses of patients with sRCC showed enrichment of gene pathway scores for cancer-associated fibroblasts and regulatory T cells, CD274 and CD8A expression, and tumors with The Cancer Genome Atlas m3 classification. Conclusions In this subgroup analysis of JAVELIN Renal 101, patients with sRCC in the avelumab plus axitinib arm had improved efficacy outcomes versus those in the sunitinib arm. Correlative analyses provide insight into this subtype of RCC and suggest that avelumab plus axitinib may increase the chance of overcoming the aggressive features of sRCC., Highlights • Patients with sarcomatoid renal cell carcinoma had improved progression-free survival with avelumab + axitinib versus sunitinib. • The objective response rate was 46.8% for patients in the avelumab + axitinib arm versus 21.3% for those in the sunitinib arm. • Correlative analyses showed enrichment for cancer-associated fibroblasts and regulatory T cells, and CD274 and CD8A expression. • Our findings suggest that avelumab + axitinib may improve the chance of overcoming the aggressive features of this subtype.

Purpose Molecular profiling of cancer is increasingly common as part of routine care in oncology, and germline and somatic profiling may provide insights and actionable targets for men with metastatic prostate cancer. However, all reported cases are of deidentified individuals without full medical and genomic data available in the public domain. Patient and methods We present a case of whole-genome tumor and germline sequencing in a patient with advanced prostate cancer, who has agreed to make his genomic and clinical data publicly available. Results We describe an 84-year-old Caucasian male with a Gleason 10 oligometastastic hormone-sensitive prostate cancer. Whole-genome sequencing provided insights into his tumor’s underlying mutational processes and the development of an SPOP mutation. It also revealed an androgen-receptor dependency of his cancer which was reflected in his durable response to radiation and hormonal therapy. Potentially actionable genomic lesions in the tumor were identified through a personalized medicine approach for potential future therapy, but at the moment, he remains in remission, illustrating the hormonal sensitivity of his SPOP-driven prostate cancer. We also placed this patient in the context of a large prostate-cancer cohort from the PCAWG (Pan-cancer Analysis of Whole Genomes) group. In this comparison, the patient’s cancer appears typical in terms of the number and type of somatic mutations, but it has a somewhat larger contribution from the mutational process associated with aging. Conclusion We combined the expertise of medical oncology and genomics approaches to develop a molecular tumor board to integrate the care and study of this patient, who continues to have an outstanding response to his combined modality treatment. This identifiable case potentially helps overcome barriers to clinical and genomic data sharing.

Background: Predictive biomarkers could allow more precise use of immune checkpoint inhibitors (ICI) in treating advanced cancers. Methods: We measured the effect of HLA variation on overall and progression-free survival in eight cohorts, including 3,339 patients with advanced cancer treated with various ICI agents and 10,867 treated with alternative therapies. Findings: HLA-A*03 associated in an additive fashion with reduced survival after ICI treatment in a discovery cohort (hazard ratio, 1·54 per HLA-A*03 allele; 95% confidence interval [CI] 1·20-1·96, p

In a recent phase 3 randomized trial of 700 patients with advanced urothelial cancer (JAVELIN Bladder 100; NCT02603432), avelumab/best supportive care (BSC) significantly prolonged overall survival relative to BSC alone as maintenance therapy after first-line chemotherapy. Exploratory biomarker analyses were performed to identify biological pathways that might affect survival benefit. Tumor molecular profiling by immunohistochemistry, whole-exome sequencing and whole-transcriptome sequencing revealed that avelumab survival benefit was positively associated with PD-L1 expression by tumor cells, tumor mutational burden, APOBEC mutation signatures, expression of genes underlying innate and adaptive immune activity and the number of alleles encoding high-affinity variants of activating Fc gamma receptors. Pathways connected to tissue growth and angiogenesis might have been associated with reduced survival benefit. Individual biomarkers did not comprehensively identify patients who could benefit from therapy; however, multi-parameter models incorporating genomic alteration, immune responses and tumor growth showed promising predictive utility. These results characterize the complex biologic pathways underlying survival benefit from immune checkpoint inhibition in advanced urothelial cancer and suggest that multiple biomarkers might be needed to identify patients who would benefit from treatment.

Additional file 1 Supplementary Figures and Tables.

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR = 0.42, 95% CI: 0.21–0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR = 1.53, 95% CI: 1.21–1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features., Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds.

Summary The CDK4/6 inhibitor, palbociclib (PAL), significantly improves progression-free survival in HR+/HER2− breast cancer when combined with anti-hormonals. We sought to discover PAL resistance mechanisms in preclinical models and through analysis of clinical transcriptome specimens, which coalesced on induction of MYC oncogene and Cyclin E/CDK2 activity. We propose that targeting the G1 kinases CDK2, CDK4, and CDK6 with a small-molecule overcomes resistance to CDK4/6 inhibition. We describe the pharmacodynamics and efficacy of PF-06873600 (PF3600), a pyridopyrimidine with potent inhibition of CDK2/4/6 activity and efficacy in multiple in vivo tumor models. Together with the clinical analysis, MYC activity predicts (PF3600) efficacy across multiple cell lineages. Finally, we find that CDK2/4/6 inhibition does not compromise tumor-specific immune checkpoint blockade responses in syngeneic models. We anticipate that (PF3600), currently in phase 1 clinical trials, offers a therapeutic option to cancer patients in whom CDK4/6 inhibition is insufficient to alter disease progression.

The ability to predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. This task is complicated because expression data are high dimensional whereas each experiment is usually small (e.g.,∼20,000 genes may be measured for∼100 subjects). However, thousands of transcriptomics experiments with hundreds of thousands of samples are available in public repositories. Can representation learning techniques leverage these public data to improve predictive performance on other tasks? Here, we report a comprehensive analysis using different gene sets, normalization schemes, and machine learning methods on a set of 24 binary and multiclass prediction problems and 26 survival analysis tasks. Methods that combine large numbers of genes outperformed single gene methods, but neither unsupervised nor semi-supervised representation learning techniques yielded consistent improvements in out-of-sample performance across datasets. Our findings suggest that usingl2-regularized regression methods applied to centered log-ratio transformed transcript abundances provide the best predictive analyses.

4547 Background: In the phase 3 JAVELIN Renal 101 trial (NCT02684006), treatment-naive patients (pts) with aRCC demonstrated prolonged progression-free survival (PFS) and a higher objective response rate with A + Ax vs S. We report the association of blood-based biomarkers with differential responses to treatment. Methods: Biomarkers in pretreatment (pre-tx) and on-treatment (on-tx) blood samples from 886 enrolled pts were correlated with clinical outcomes and molecular profiling data from corresponding tumor samples. Analyses include blood counts of unique populations, T-cell receptor sequencing, circulating cytokines, and serum proteomics by mass spectrometry MALDI-TOF. Results: At baseline, higher pre-tx monocyte counts were associated with shorter PFS in the A + Ax arm (Table). In the S arm, higher pre-tx levels of multiple T-cell–related metrics, including the percent of productively rearranged peripheral T cells, were associated with longer PFS but had no association in the A + Ax arm (Table). Higher pre-tx neutrophil counts were associated with shorter PFS in both arms, but neutrophil-to-lymphocyte ratio (NLR) was only associated with PFS for the S arm (Table). On-therapy biomarkers showed differential post-tx changes in T-cell numbers and clones at C2D1. Tx-specific differences were also seen in non–T-cell populations such as monocytes and neutrophils at multiple time points through C3D1. Serum levels of pre- and on-tx VEGF, CRP, and several interleukins showed differential associations with PFS (eg, higher pre-tx VEGF was associated with shorter PFS in only the S arm) (Table). Specific genomic alterations in tumor tissues were associated with differences in several pre- and on-tx angiokines & cytokines. Conclusions: Response to treatment with first-line A + Ax or S was associated with immune fitness and tx-specific immunomodulation. We identified peripheral biomarkers in pts with aRCC associated with the presence of impactful genomic alterations and differential clinical outcomes. Clinical trial information: NCT02684006. [Table: see text]

Summary Large-scale genomic characterization of tumors from prospective cohort studies may yield new insights into cancer pathogenesis. We performed whole-exome sequencing of 619 incident colorectal cancers (CRCs) and integrated the results with tumor immunity, pathology, and survival data. We identified recurrently mutated genes in CRC, such as BCL9L, RBM10, CTCF, and KLF5, that were not previously appreciated in this disease. Furthermore, we investigated the genomic correlates of immune-cell infiltration and found that higher neoantigen load was positively associated with overall lymphocytic infiltration, tumor-infiltrating lymphocytes (TILs), memory T cells, and CRC-specific survival. The association with TILs was evident even within microsatellite-stable tumors. We also found positive selection of mutations in HLA genes and other components of the antigen-processing machinery in TIL-rich tumors. These results may inform immunotherapeutic approaches in CRC. More generally, this study demonstrates a framework for future integrative molecular epidemiology research in colorectal and other malignancies., Graphical Abstract, Highlights • Whole-exome sequencing of 619 colorectal cancers with clinicopathologic annotations • Discovery of significantly mutated genes in colorectal cancer • Neoantigen load correlation with infiltrating lymphocytes and memory T cells • Positive selection for HLA mutations in immune-cell-infiltrated tumors, Through whole-exome sequencing of annotated colorectal tumors, Giannakis et al. identify additional colorectal cancer driver genes and correlate high neoantigen load with increased lymphocytic infiltration and improved survival. They also find positive selection for HLA mutations in immune-cell-infiltrated tumors. These results may inform immunotherapeutic approaches in colorectal cancer.

We report on molecular analyses of baseline tumor samples from the phase 3 JAVELIN Renal 101 trial (n = 886; NCT02684006 ), which demonstrated significantly prolonged progression-free survival (PFS) with first-line avelumab + axitinib versus sunitinib in advanced renal cell carcinoma (aRCC). We found that neither expression of the commonly assessed biomarker programmed cell death ligand 1 (PD-L1) nor tumor mutational burden differentiated PFS in either study arm. Similarly, the presence of FcɣR single nucleotide polymorphisms was unimpactful. We identified important biological features associated with differential PFS between the treatment arms, including new immunomodulatory and angiogenesis gene expression signatures (GESs), previously undescribed mutational profiles and their corresponding GESs, and several HLA types. These findings provide insight into the determinants of response to combined PD-1/PD-L1 and angiogenic pathway inhibition and may aid in the development of strategies for improved patient care in aRCC. Biomarker analysis of the phase 3 JAVELIN Renal 101 trial uncovers molecular determinants of therapy-specific outcomes, which may inform personalized treatment strategies for patients with advanced renal cell carcinoma.

Introduction: PF-06801591 is a humanized IgG4 monoclonal antibody that binds to the programmed cell death (PD-1) receptor and blocks its interaction with PD-1/2 ligands (PD-L1/2). In a phase 1 dose expansion study (NCT02573259), 106 patients with locally advanced or metastatic non-small cell lung cancer (NSCLC; n=68) or urothelial carcinoma (UC; n=38) were treated with PF-06891591 300 mg subcutaneously monthly. 12 patients with NSCLC (17.9%) and 7 with UC (18.4%) had a best overall response of partial response (PR). Response rates were higher in patients with high (≥1%) vs low ( Citation Format: Byoung Chul Cho, Konstantin Penkov, Igor Bondarenko, Joanna Pikiel, Hee Kyung Ahn, Alison Forgie, Ira Jacobs, Vinicius Bonato, Xinmeng Jasmine Mu, Keith Ching, Jeffrey Chou, Melissa L. Johnson. Molecular markers in a phase I dose expansion study of PF-06801591 in locally advanced or metastatic non-small-cell lung cancer and urothelial carcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT138.

744 Background: The phase 3 JAVELIN Renal 101 trial in patients (pts) with advanced RCC demonstrated a progression-free survival (PFS) benefit and higher objective response rate (ORR) with avelumab + axitinib (A+Ax) vs sunitinib (S) (Motzer NEJM 2019). PFS and ORR favored A+Ax in all MSKCC risk groups, but median PFS varied. Here, we report results from analyses of baseline tumor samples to define molecular characteristics underlying risk group classifications. Methods: Nephrectomy or tumor samples from pts enrolled in the study were characterized by immunohistochemistry (CD8 and PD-L1), whole exome sequencing, or gene expression profiling (n = 705–850). Gene expression signatures (GES), pathway activation status, and mutational profiles were examined in relation to MSKCC risk groups. Results: Of the 886 total pts enrolled, 23%, 66%, and 11% had favorable (F), intermediate (I), or poor (P) MSKCC risk factors at baseline. In the F, I, and P groups, the ORR was 66%/38%, 50%/24%, and 31%/9%; median PFS was NR/16.7 mo, 13.3 mo/7.9 mo, and 5.6 mo/2.8 mo for the A+Ax/S arms, respectively. Neither the presence of PD-L1+ immune cells nor CD8+ cells differentiated the subgroups; however, the presence of PD-L1+ tumor cells was highest in the P group (p=0.0159). When compared to the I and P groups, the F group was enriched for NOTCH2 mutations (p=0.0002), displayed high FLT1 expression (p=0.007), and showed a trend favoring angiogenesis GES (JAVELIN Renal 101 and IMmotion150). The I group displayed few distinguishing characteristics (low neutrophil GES [p=0.02] and elevated homeobox gene expression [p=0.00052]). Relative to the F group, the P group showed higher cell cycle gene expression (p=0.0057) and PTEN mutation frequency, wild-type NOTCH2 genotype, elevated IMmotion150 Myeloid inflamed GES (p=0.0024), and macrophage-specific GES (p=0.0327), as well as GES for TH2 (p=0.0002), hypoxia (p=0.0199), glycolysis (p=0.0066), and the lowest expression of a dendritic cell GES (p=0.0209). Conclusions: In advanced RCC patients, biological differences within each MSKCC risk category may impact response to treatment and may help explain why these groups perform differently. Clinical trial information: NCT02684006.

68 Background: Immune checkpoint inhibitors have achieved unprecedented success in several cancer types, yet only a subset of patients derives clinical benefit. Better understanding of tumor-immune interactions is imperative to improve clinical outcomes. Bayesian causal machine learning was applied on real world data to elucidate the molecular drivers of immune subtypes of tumors. Methods: Using a Reverse Engineering Forward Simulation (REFS) platform, ensembles of causal models were built on genomics, transcriptomics, and clinical data from 681 non-small cell lung carcinoma (NSCLC), 328 lung adeno (LUAD) and 353 lung squamous cell (LUSC), and 413 head and neck squamous cell carcinoma (HNSCC) patients from TCGA. The outcomes modeled were six tumor immune subtypes (Thorsson et al., 2018): wound-healing, IFNγ dominant, inflammatory, lymphocyte-depleted, immunologically quiet, and TGFβ dominant. Causal drivers of immune subtypes were identified from average causal effect (ACE) of the variables, as computed from the counterfactual simulations. ACE was defined as median of posterior distribution of odds ratio (1 vs 0 for discrete; 95th vs. 5th %ile for continuous variables). Results: The models showed impressive k-fold cross validation predictive performance (AUC ~ 0.8-0.9) for the most prevalent immune subtypes in TCGA: wound-healing and IFNg dominant in both LUAD and HNSCC, as well as inflammatory in LUAD. The potential causal drivers of the tumor immune subtypes and their ACE are listed in Table. The findings suggest that macrophage activation and polarization, which is driven in part by metabolic reprogramming, is a primary driver of tumor immune subtypes. Conclusions: Bayesian causal modeling revealed literature-supported hypotheses regarding predictors of response (CXCL13) and resistance (STK11 mutation, mTOR pathway) to PD-(L)1 blockade therapy. The additional target pathways such as AKT1/mTOR may be actionable for altering immunogenicity of tumors. [Table: see text]

Inhibitors targeting the PDCD1 (programmed cell death 1, PD-1) immune checkpoint pathway have revolutionized cancer treatment strategies. The TIME (Tumor Immunity in the MicroEnvironment) classification based on tumor CD274 (PDCD1 ligand 1, PD-L1) expression and tumor-infiltrating lymphocytes (TIL) has been proposed to predict response to immunotherapy. It remains to be determined clinical, pathological, and molecular features of TIME subtypes of colorectal cancer. Using 812 colon and rectal carcinoma cases from the Nurses' Health Study and Health Professionals Follow-up Study, we examined the association of tumor characteristics and survival outcomes with four TIME subtypes (TIME 1, CD274(low)/TIL(absent); TIME 2, CD274(high)/TIL(present); TIME 3, CD274(low)/TIL(present); and TIME 4, CD274(high)/TIL(absent)). In survival analyses, Cox proportional hazards models were adjusted for potential confounders, including microsatellite instability (MSI) status, CpG island methylator phenotype (CIMP) status, LINE-1 methylation level, and KRAS, BRAF, and PIK3CA mutation status. TIME subtypes 1, 2, 3 and 4 had 218 (27%), 117 (14%), 103 (13%), and 374 (46%) colorectal cancer cases, respectively. Compared with TIL-absent subtypes (TIME 1 and 4), TIL-present subtypes (TIME 2 and 3) were associated with high-level MSI, high-degree CIMP, BRAF mutation, and higher amounts of neoantigens (p < 0.001). TIME subtypes were not significantly associated with colorectal cancer-specific or overall survival. In conclusion, TIL-present TIME subtypes of colorectal cancer are associated with high levels of MSI and neoantigen load, supporting better responsiveness to cancer immunotherapy. Further studies examining tumor molecular alterations and additional factors in the tumor microenvironment may inform development of immunoprevention and immunotherapy strategies.

Colorectal cancer (CRC) heritability has been estimated to be around 30%. However, mutations in the known CRC susceptibility genes explain CRC risk in under 10% of the cases. Germline mutations in DNA-repair genes (DRGs) have recently been reported in CRC but their contribution to CRC risk is largely unknown. We evaluated the gene-level germline mutation enrichment of 40 DRGs in 680 unselected CRC individuals compared to 27728 ancestry-matched cancer-free adults. Significant findings were then examined in independent cohorts of 1661 unselected CRC cases and 1456 early-onset CRC cases. Of 680 individuals in the discovery set, 31 (4.56%) individuals harbored germline pathogenic mutations in known CRC susceptibility genes while another 33 (4.85%) individuals had DRG mutations that have not been previously associated with CRC risk. Germline pathogenic mutations inATMandPALB2were enriched in both the discovery (OR= 2.81; P= 0.035 and OR= 4.91; P= 0.024, respectively) and validation sets (OR= 2.97; Adjusted P= 0.0013 and OR= 3.42; Adjusted P= 0.034, forATMandPALB2respectively). Biallelic loss ofATMwas evident in all cases with matched tumor profiling. CRC cases also had higher rates of actionable mutations in the HR pathway that can substantially increase the risk of developing cancers other than CRC. Our analysis provides evidence forATMandPALB2as CRC risk genes, underscoring the importance of the homologous recombination pathway in CRC. In addition, we identified frequent complete homologous recombination deficiency in CRC tumors, representing a unique opportunity to explore targeted therapeutic interventions such as PARPi.

To understand the genetic drivers of immune recognition and evasion in colorectal cancer, we analyzed 1,211 colorectal cancer primary tumor samples, including 179 classified as microsatellite instability–high (MSI-high). This set includes The Cancer Genome Atlas colorectal cancer cohort of 592 samples, completed and analyzed here. MSI-high, a hypermutated, immunogenic subtype of colorectal cancer, had a high rate of significantly mutated genes in important immune-modulating pathways and in the antigen presentation machinery, including biallelic losses of B2M and HLA genes due to copy-number alterations and copy-neutral loss of heterozygosity. WNT/β-catenin signaling genes were significantly mutated in all colorectal cancer subtypes, and activated WNT/β-catenin signaling was correlated with the absence of T-cell infiltration. This large-scale genomic analysis of colorectal cancer demonstrates that MSI-high cases frequently undergo an immunoediting process that provides them with genetic events allowing immune escape despite high mutational load and frequent lymphocytic infiltration and, furthermore, that colorectal cancer tumors have genetic and methylation events associated with activated WNT signaling and T-cell exclusion. Significance: This multi-omic analysis of 1,211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to immune blockade therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not. Cancer Discov; 8(6); 730–49. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 663

Colorectal cancer (CRC) heritability has been estimated to be around 30%. However, mutations in the known CRC-susceptibility genes explain CRC risk in fewer than 10% of affected individuals. Germline mutations in DNA-repair genes (DRGs) have recently been reported in CRC, but their contribution to CRC risk is largely unknown. We evaluated the gene-level germline mutation enrichment of 40 DRGs in 680 unselected CRC individuals and 27,728 ancestry-matched cancer-free adults. Significant findings were then examined in independent cohorts of 1,661 unselected CRC individuals and 1,456 individuals with early-onset CRC. Of the 680 individuals in the discovery set, 31 (4.56%) individuals harbored germline pathogenic mutations in known CRC-susceptibility genes, and another 33 (4.85%) individuals had DRG mutations that have not been previously associated with CRC risk. Germline pathogenic mutations in ATM and PALB2 were enriched in both the discovery (OR = 2.81 and p = 0.035 for ATM and OR = 4.91 and p = 0.024 for PALB2) and validation (OR = 2.97 and adjusted p = 0.0013 for ATM and OR = 3.42 and adjusted p = 0.034 for PALB2) sets. Biallelic loss of ATM was evident in all individuals with matched tumor profiling. CRC individuals also had higher rates of actionable mutations in the HR pathway, which can substantially increase the risk of developing cancers other than CRC. Our analysis provides evidence for ATM and PALB2 as CRC-risk genes, underscoring the importance of the homologous recombination pathway in CRC. In addition, we identified frequent complete homologous recombination deficiency in CRC tumors, representing a unique opportunity to explore targeted therapeutic interventions such as poly-ADP ribose polymerase inhibitor (PARPi).

Background: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are effective for the treatment of EGFR-mutant non-small lung cancer (NSCLC). In almost all cases, however, the response duration is limited and resistance ultimately emerges. Transformation of NSCLC to small cell lung cancer (SCLC) occurs as one of the resistance mechanisms to EGFR-TKIs. To date, the mechanism associated with this transformation is largely unknown, necessitating the need to establish an effective treatment strategy for patients with transformed SCLC (tSCLC). Methods: We isolated cancer cells that grow as floating aggregates (F) and adherent monolayers (Ad) from the pleural effusion of three patients with tSCLC to establish patient derived cell lines (DFCI112F, DFI112ad, DFCI190F, DFCI190ad, DFCI283F, DFCI283ad). In parallel, patient derived xenograft (PDX) models from these patients were successfully established by subcutaneous implantation of pleural effusions in NSG mice. Transcriptomic and genomic characterization of the cell lines were performed using whole-exome sequencing (WES) and RNA sequencing. These cell lines were further treated with a panel of agents, to screen for effective combination therapies. Results: Biological characterization of the created cell lines revealed that the floating aggregates have neuroendocrine (NE) features, while the adherent cell population presents non-NE/mesenchymal characteristics. The histology of the PDX tumors was confirmed as SCLC. According to WES, all tSCLC cell lines retained the original activating EGFR mutations. RB1 and TP53 were universally inactivated. Co-culturing the floating-NE cells with the adherent non-NE cells promoted the proliferation of the floating-NE cells in vitro. NE cells (DFCI112F) and non-NE cells (DFCI112ad) were injected into nude mice either as single or admixed populations. Tumor growth was observed only in admixed cell populations. In an effort to target both NE and non-NE populations, we performed a drug screen and demonstrated that MEK inhibitors are selectively efficacious against non-NE populations. We further evaluated the MEK inhibitor combination therapies with agents targeting NE populations (cisplatin, ABT-263 and JQ1), which effectively eliminated both NE and non-NE components in vitro. Our further study demonstrated that ABT-263 in combination with MEK inhibitors presented a synergistic effect, which could be a promising therapeutic combination for tSCLC patients. Conclusion: We demonstrate that the cancer cell lines established from tSCLC patients consist of heterogeneous population of cells with NE and non-NE/mesenchymal characteristics. The crosstalk between these two cell populations is observed and our findings underscore the importance of targeting tumor heterogeneity as a promising treatment strategy for patients with tSCLC. Citation Format: Atsuko Ogino, Xinmeng Jasmine Mu, Mika Lin, Antonio Calles, Stephen Wang, Man Xu, Lynette M. Scholl, Geoffrey R. Oxnard, Paul Kirschmeier, Pasi A. Jänne. Effective MEK inhibitor combinations to target tumor heterogeneity in EGFR mutant transformed SCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3783.

101 Background: The phase 3 JAVELIN Renal 101 trial in previously untreated patients (pts) with aRCC demonstrated a progression-free survival (PFS) benefit and higher objective response rate with A+Ax vs S (Motzer, ESMO 2018; LBA6_PR). Here, we report outcomes from biomarker analyses of baseline tumor samples. Methods: We correlated efficacy with the results of molecular analyses of tissue samples from all 886 pts enrolled in JAVELIN Renal 101. Nephrectomy or tumor samples were characterized by immunohistochemistry (CD8 and PD-L1), whole-exome sequencing (WES), and RNAseq. WES and RNAseq were used to examine somatic mutations and analyze relevant gene expression signatures (GES) in relation to clinical outcomes. GES analyses included published and de novo signatures: effector T cell (Teff), angiogenesis (angio),T cell-inflamed (Tinf), and a novel immune-related signature incorporating pathway indicators for T- and NK-cell activation and IFNγ signaling, among others. Results: PD-L1 expression (≥1% immune cells) was associated with the longest PFS in the A+Ax arm and the shortest in the S arm (HR, 0.63; 95% CI, 0.49, 0.81). Significant treatment arm–specific differences in PFS were observed relative to wildtype when mutations in genes such as CD1631L, PTEN, or DNMT1 were present. Tumor mutational burden did not distinguish pts with respect to PFS. High-angio GES was associated with significantly improved PFS in the S arm but did not differentiate PFS in the A+Ax arm. In the low-angio subset, A+Ax improved PFS vs S. Pts with high Teff and Tinf in the A+Ax arm had longer PFS vs the S arm. In the A+Ax arm, PFS was enhanced in patients with immune GES–positive tumors vs those in the negative group (HR, 0.63; 95% CI, 0.46, 0.86; 2-sided p = 0.004), as well as in an independent dataset (JAVELIN Renal 100; Choueiri, Lancet Oncol, 2018) (HR, 0.46; 95% CI, 0.20, 1.05; 2-sided p = 0.064). Updated efficacy, including overall survival, will be presented. Conclusions: These findings define molecular features that differentiate therapy-specific outcomes in first-line aRCC and may inform personalized therapy strategies for pts with aRCC. Funding: Pfizer and Merck KGaA. Clinical trial information: NCT02684006.

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Defective Gene Detective Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823 ; see the Perspective by Quintana-Murci ) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles.

In the human genome, it has been estimated that considerably more sequence is under natural selection in non-coding regions [such as transcription-factor binding sites (TF-binding sites) and non-coding RNAs (ncRNAs)] compared to protein-coding ones. However, less attention has been paid to them. To study selective pressure on non-coding elements, we use next-generation sequencing data from the recently completed pilot phase of the 1000 Genomes Project, which, compared to traditional methods, allows for the characterization of a full spectrum of genomic variations, including single-nucleotide polymorphisms (SNPs), short insertions and deletions (indels) and structural variations (SVs). We develop a framework for combining these variation data with non-coding elements, calculating various population-based metrics to compare classes and subclasses of elements, and developing element-aware aggregation procedures to probe the internal structure of an element. Overall, we find that TF-binding sites and ncRNAs are less selectively constrained for SNPs than coding sequences (CDSs), but more constrained than a neutral reference. We also determine that the relative amounts of constraint for the three types of variations are, in general, correlated, but there are some differences: counter-intuitively, TF-binding sites and ncRNAs are more selectively constrained for indels than for SNPs, compared to CDSs. After inspecting the overall properties of a class of elements, we analyze selective pressure on subclasses within an element class, and show that the extent of selection is associated with the genomic properties of each subclass. We find, for instance, that ncRNAs with higher expression levels tend to be under stronger purifying selection, and the actual regions of TF-binding motifs are under stronger selective pressure than the corresponding peak regions. Further, we develop element-aware aggregation plots to analyze selective pressure across the linear structure of an element, with the confidence intervals evaluated using both simple bootstrapping and block bootstrapping techniques. We find, for example, that both micro-RNAs (particularly the seed regions) and their binding targets are under stronger selective pressure for SNPs than their immediate genomic surroundings. In addition, we demonstrate that substitutions in TF-binding motifs inversely correlate with site conservation, and SNPs unfavorable for motifs are under more selective constraints than favorable SNPs. Finally, to further investigate intra-element differences, we show that SVs have the tendency to use distinctive modes and mechanisms when they interact with genomic elements, such as enveloping whole gene(s) rather than disrupting them partially, as well as duplicating TF motifs in tandem.

We report somatic mutations of RNF43 in over 18% of colorectal adenocarcinomas and endometrial carcinomas. RNF43 encodes an E3 ubiquitin ligase that negatively regulates Wnt signaling. Truncating mutations of RNF43 are more prevalent in microsatellite-unstable tumors and show mutual exclusivity with inactivating APC mutations in colorectal adenocarcinomas. These results indicate that RNF43 is one of the most commonly mutated genes in colorectal and endometrial cancers.

Background: Immune checkpoint blockade has shown activity in microsatellite-instability high (MSI-H) colorectal cancers (CRCs). However, despite a very high mutational and neoantigen load among virtually all MSI-H tumors, the response rate is around 40-50%. In addition, for the majority of CRCs, which are microsatellite stable (MSS), immune checkpoint inhibitors have so far proven ineffective. Thus, to better understand the genetic drivers of immune evasion in CRC, we integrated next generation sequencing data from over 1200 tumors with transcriptional and immunohistochemical measures of immune infiltration. Methods: We molecularly characterized 1,211 colorectal cancers, including 592 tumors from The Cancer Genome Atlas with whole exome sequencing (WES) and whole transcriptome (RNAseq) data and 619 cancers from two prospective cohort studies with WES and immunohistochemical (IHC) annotations. To identify driver gene alterations and their selection pressures specific to MSI-high tumors, we developed a statistical method to identify significantly mutated microsatellite tracts and we further developed a method to identify copy neutral loss of heterozygosity (CN-LOH) events. We used an established immune-gene transcriptional signature as well as IHC stains against specific subsets of immune-infiltrating cells to identify genetic events associated with immune evasion. Results: We demonstrated that WNT-signaling and immune-related genes are significantly mutated in colorectal cancer. In MSI-H CRCs, we found biallelic antigen-presentation machinery (APM) mutations in the HLA Class I genes, B2M and TAP2, in addition to recurrent mutations in NLRC5 and RFX5, which downregulated HLA Class I expression. In all CRCs, we showed that WNT-signaling activity and APC-biallelic mutations are inversely associated with both transcriptional and IHC measures of T-cell infiltration. Specifically, nuclear CTNNB1 expression was inversely correlated with overall tumor-infiltrating lymphocytes (p = 0.027), CD8+ subset of T-cells (p = 0.0019) and CD45RO+ subset of T-cells (0.0080). Meanwhile, colorectal tumors with biallelic disruptive mutations in APC had a significantly decreased activated T-cell transcriptional signature (p = 4e-12) relative to samples with no disruptive mutations in APC. We further showed that in MSS tumors, AXIN2 (a key WNT-signaling effector) super-enhancer hypomethylation, independent of the APC mutation status, was further associated with decreased T-cell activity. Conclusions: In this largest CRC genomic analysis to date, we identify genetic events that are associated with immune evasion in this disease. Specifically, we find evidence of immuno-editing in MSI-H tumors through disruptive mutations in APM. In the MSS and MSI-H subtype of CRCs, we use transcriptional and immunohistochemical orthogonal analyses to demonstrate exclusion of an effective immune infiltrate in CRC through an active WNT-signaling pathway. Our results shed light on the underlying molecular mechanisms of immune exclusion in CRC and have direct implications for novel combination immunotherapy trials for patients with this disease. This abstract is also being presented as Poster B23. Citation Format: Marios Giannakis, Catherine Grasso, Daniel Wells, Tsuyoshi Hamada, Xinmeng Jasmine Mu, Michael Quist, Jonathan Nowak, Reiko Nishihara, Charles M. Connolly, Sachet Shukla, William M. Grady, David Wheeler, Catherine J. Wu, Jesse Zaretsky, Levi Garraway, Thomas Hudson, Charles Fuchs, Antoni Ribas, Riki Peters, Shuji Ogino. Genetic mechanisms of immune evasion in colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr PR03.

Colorectal cancer (CRC), a common malignancy, is a biologically heterogeneous disease. Next-generation sequencing (NGS) has enabled CRC characterization by identifying somatically mutated genes which now allow us to better define colorectal tumor subtypes (e.g. by mutated pathways). However, the relationship of such CRC subtypes to patient survival and genetic and lifestyle risk factors has not been comprehensively studied. To identify somatic mutations in CRC cases, we designed a targeted AmpliSeq panel of CRC related genes and genomic regions informed by whole exome sequencing data from ~1,200 CRC cases. The sequencing was conducted on Illumina HiSeq 2500 with a mean coverage of 740x and 240x for DNA extracted from FFPE tumor tissues and matched normal samples, respectively. Strelka, MuTect, VarDict, and Varscan2 were used to identify somatic single nucleotide variants and indels. Sanger sequencing was performed to validate a subset of variants. To date, we have sequenced ~2,400 CRC tumors and matched control tissues from four studies participating in the Colon Cancer Family Registry (CCFR) and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). In most tumors, we identified non-silent mutations in genes belonging to the WNT (77%), p53 (44%), IGF2/PI3K (22%), RTK-RAS (47%), and TGF-beta (26%) signaling pathways. Among the 15% of tumors that could be classified as hypermutated, based on the number of mutations, 39% exhibited non-silent mutations in MLH1, MLH3, MSH2, MSH6, and PMS2 and 41% exhibited non-silent mutations in POLE and POLD1. In a subset of studies with available survival data, we used Cox regression to assess the association of hypermutation status and the presence of non-silencing mutations in key signaling pathways with overall (OS) and disease-specific (DSS) survival. OS and DSS were significantly more favorable in cases with hypermutated vs. non-hypermutated CRC (HR=0.77, 95% CI: 0.60-0.98, p=0.04 and HR=0.35, 95% CI: 0.22-0.57, p=2x10-5, respectively); these associations were most pronounced for POLE/POLD1 mutated hypermutated CRC (HR=0.69, 95% CI: 0.46-1.02, p=0.06, HR=0.21, 95% CI: 0.08-0.56, p=2x10-3, respectively). There was no significant association of mutations in WNT, p53, IGF2/PI3K, RTK-RAS, or TGF-beta pathways with survival (p>0.05). The comprehensive molecular characterization of this large panel of CRC cases will support further studies of molecular subtypes of CRC with clinical, lifestyle, and environmental factors. A better understanding of molecular mechanisms of CRC will be valuable in developing strategies for prevention, diagnosis, and treatment of this life-threatening disease. Citation Format: Syed Zaidi, Amanda Phipps, Tabitha Harrison, Catherine Grasso, Robert Steinfelder, Quang Trinh, Charles Connolly, Barbara Banbury, Adilya Rafikova, Philipp Hofer, Stefanie Brezina, Marios Giannakis, Xinmeng Jasmine Mu, Michael Quist, Charles Fuchs, Levi Garraway, Li Hsu, Lincoln Stein, Andrea Gsur, Shuji Ogino, Steven Gallinger, Polly Newcomb, Peter Campbell, Wei Sun, Thomas Hudson, Ulrike Peters. Deep targeted tumor sequencing of colorectal cancer cases to study associations of molecular subtypes with clinical, genetic, and lifestyle risk factors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1224.

The interferon (IFN)-related cytokine interleukin (IL)-29 (also known as IFN-lambda1) inhibits virus replication by inducing a cellular antiviral response similar to that activated by IFN-alpha/beta. However, because it binds to a unique receptor, this cytokine may function cooperatively with IFN-alpha/beta or IFN-gamma during natural infections to inhibit virus replication, and might also be useful therapeutically in combination with other cytokines to treat chronic viral infections such as hepatitis C (HCV). We therefore investigated the ability of IL-29 and IFN-alpha or IFN-gamma to cooperatively inhibit virus replication and induce antiviral gene expression. Compared with the individual cytokines alone, the combination of IL-29 with IFN-alpha or IFN-gamma was more effective at blocking vesicular stomatitis virus and HCV replication, and this cooperative antiviral activity correlated with the magnitude of induced antiviral gene expression. Although the combined effects of IL-29 and IFN-alpha were primarily additive, the IL-29/IFN-gamma combination synergistically induced multiple genes and had the greatest antiviral activity. Two different mechanisms contributed to the enhanced gene expression induced by the cytokine combinations: increased activation of ISRE promoter elements and simultaneous activation of both ISRE and GAS elements within the same promoter. These findings provide new insight into the coregulation of a critical innate immune response by functionally distinct cytokine families.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)

Introduction: Using patient derived xenograft (PDX) models has become an effective way for investigating response to standard or new therapeutics in cancer. Human cancer cells injected in mice are allowed to establish tumors and subjected to desired treatments. The PDX tumors are later harvested and characterized, often by massive parallel sequencing. However, a major challenge with analyzing these data is the presence of stromal mouse genomic material, frequently resulting in artifacts in downstream variant detection. We present a computational method to eliminate mouse contamination in PDX. Method: We used the Burrows-Wheeler Aligner to map reads obtained from sequencing the PDX samples to a combined human and mouse reference genome . We remove reads that are mapped to the mouse reference. The remaining reads are then processed through standard mutation calling pipelines for somatic mutation detection. To test the efficacy of our method, we created in silico mixtures of human and mouse whole-exome sequencing reads from a melanoma patient’s tumor and an immortalized mouse cell line captured with human exome baits. We then carried out a sensitivity analysis to examine how changing the mean target coverage of sequencing, or mouse contamination levels affects our results. For each of the computational experiments, we evaluated somatic mutations detected from the synthetic samples in comparison to the original human sample. Results: We calculated the sensitivity and specificity of detecting somatic mutations to determine our algorithm’s performance. In all instances, we found greater than 99% for both sensitivity and specificity. Conclusions: Our results demonstrate that our method works accurately towards removing mouse reads in PDX samples. This task could also be applied to separating sequence reads from other species. Citation Format: Ali Amin-Mansour, Judit Jané-Valbuena, Xinmeng Jasmine Mu, Levi Garraway. A computational framework for removing mouse contamination in tumors sequenced from patient-derived xenografts [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 1564. doi:10.1158/1538-7445.AM2017-1564

1500 Background: Twin studies showed that 30% of all colorectal cancer (CRC) patients have an inherited genetic susceptibility. Several CRC predisposition genes have been described to date. However, mutations in these genes explain the risk in only 5-10% of CRC cases. In this study, we hypothesized that some of the CRC heritability may be explained by excess disruptive germline mutations in DNA repair genes (DRGs). Methods: Exome sequencing data of 716 in the discovery cohort (CanSeq and NHS/HPFS studies) and 1609 CRC patients in the validation cohort (TCGA and NSCCG studies) were used to evaluate germline variants in a pre-selected group of 42 DRGs and 12 known CRC risk genes. Frequencies of disruptive mutations in our cohorts were examined relative to 27173 non-Finnish European cancer-free adults from the ExAC cohort to evaluate for enrichment. Results: Of 716 patients in the discovery cohort, 27 (3.8%) patients harbored germline mutations in APC (n = 11), MSH6 (n = 2), MUTYH (n = 11), CHEK2 (n = 1) and TP53 (n = 2). Interestingly, germline mutations in ATM and PALB2 were significantly enriched in our CRC discovery cohort (OR = 2.7; P = 0.044; and OR = 4.8; P = 0.026, respectively). Evaluation of germline data from another 1609 CRC patients (validation cohort) also showed significantly higher rates of ATM mutations (5; 0.7%; OR = 2.1; P = 0.044), and a trend for enrichment of PALB2 mutations (3; 0.4%; OR = 2.8; P = 0.056). Secondary analysis of actionable germline mutations in a highly penetrant cancer risk gene set ( ATM, BRCA1, BRCA2, BRIP1 and PALB2) suggest a broader enrichment trend in CRC patients for these genes (Discovery: OR = 1.7; P = 0.06; Validation: OR = 2; P = 1.96e-04). Conclusions: Our analysis of germline variants in 2325 CRC patients showed the first robust evidence for germline ATM mutations to confer a higher risk of developing CRC. We also presented evidence to support PALB2 as a potential novel CRC risk gene. Overall, our study shows that mutations in some DRGs may explain some of the missing CRC heritability. It also indicates that a significant percentage of CRC patients, who carry mutations in highly actionable genes where cancer screening recommendations for patients and families do exist, are not captured with current testing recommendations.

e13027 Background: As classic adenoma-carcinoma sequence is the main process underlying most colorectal cancer (CRC), early detection and removal of colorectal adenomas is crucial in preventing CRC. Although adenomatous polyps are usually sporadic, several inherited CRC syndromes such as Familial adenomatous polyposis, MUTYH-associated polyposis and Lynch syndrome can present initially with colon polyps. The identification of germline defects in patients with colon polyps is thus critical for proper cancer risk counseling and CRC prevention. Current guidelines recommend germline testing for patients with more than 20 polyps or those with more than 10 polyps and a family history of CRC. However, the diagnostic yield of germline testing on otherwise healthy individuals with 10 or fewer colon polyps has not been well studied. Here, we performed a pilot study to evaluate the clinical actionability of germline genetic testing on these patients. Methods: A total of 13 cancer-free adults, who presented with colon polyps (n < 10) and who otherwise were not selected based on age of onset or family history underwent germline Exome Sequencing. Variants in 13 well-established CRC risk genes ( APC, CHEK2, MYH, MLH1, MSH2, MSH6, PMS2, NTHL1, BMPR1A, SMAD4, PTEN, STK11, TP53) were evaluated for pathogenicity. Results: A total of 13 patients (12 male, 1 female) were evaluated. The median age of presentation was 69 (range 49 to 88). The median number of adenomatous colon polyps was 1 (range 1 to 8). Two (15.4%, 95% CI = 1.9 - 45.4, Binomial Exact) patients had at least one disruptive mutation in the examined genes. One of these patients had a truncating mutation in APC (p.Arg216*) and presented with two tubulovillous adenomas at age 49. The second patient had 8 adenomas in distal colon and rectum at age 64, and harbored a known pathogenic mutation in MSH6(p.Arg1035*). Conclusions: This pilot study provides evidence that a relatively high percentage of patients presenting with a few colon polyps may have inherited defects in highly actionable genes. If validated in larger cohorts with appropriate population controls, these findings may influence the clinical care of such patients and their families and suggest germline molecular testing in those patients.

Investigating genomic structural variants at basepair resolution is crucial for understanding their formation mechanisms. We identify and analyze 8,943 deletion breakpoints in 1,092 samples from the 1000 Genomes Project. We find breakpoints have more nearby SNPs and indels than the genomic average, likely a consequence of relaxed selection. By investigating the correlation of breakpoints with DNA methylation, Hi-C interactions, and histone marks and the substitution patterns of nucleotides near them, we find that breakpoints with the signature of non-allelic homologous recombination (NAHR) are associated with open chromatin. We hypothesize that some NAHR deletions occur without DNA replication and cell division, in embryonic and germline cells. In contrast, breakpoints associated with non-homologous (NH) mechanisms often have sequence micro-insertions, templated from later replicating genomic sites, spaced at two characteristic distances from the breakpoint. These micro-insertions are consistent with template-switching events and suggest a particular spatiotemporal configuration for DNA during the events.

Identification of noncoding drivers from thousands of somatic alterations in a typical tumor is a difficult and unsolved problem. We report a computational framework, FunSeq2, to annotate and prioritize these mutations. The framework combines an adjustable data context integrating large-scale genomics and cancer resources with a streamlined variant-prioritization pipeline. The pipeline has a weighted scoring system combining: inter- and intra-species conservation; loss- and gain-of-function events for transcription-factor binding; enhancer-gene linkages and network centrality; and per-element recurrence across samples. We further highlight putative drivers with information specific to a particular sample, such as differential expression. FunSeq2 is available from funseq2.gersteinlab.org. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0480-5) contains supplementary material, which is available to authorized users.

Short insertions and deletions (indels) are the second most abundant form of human genetic variation, but our understanding of their origins and functional effects lags behind that of other types of variants. Using population-scale sequencing, we have identified a high-quality set of 1.6 million indels from 179 individuals representing three diverse human populations. We show that rates of indel mutagenesis are highly heterogeneous, with 43%–48% of indels occurring in 4.03% of the genome, whereas in the remaining 96% their prevalence is 16 times lower than SNPs. Polymerase slippage can explain upwards of three-fourths of all indels, with the remainder being mostly simple deletions in complex sequence. However, insertions do occur and are significantly associated with pseudo-palindromic sequence features compatible with the fork stalling and template switching (FoSTeS) mechanism more commonly associated with large structural variations. We introduce a quantitative model of polymerase slippage, which enables us to identify indel-hypermutagenic protein-coding genes, some of which are associated with recurrent mutations leading to disease. Accounting for mutational rate heterogeneity due to sequence context, we find that indels across functional sequence are generally subject to stronger purifying selection than SNPs. We find that indel length modulates selection strength, and that indels affecting multiple functionally constrained nucleotides undergo stronger purifying selection. We further find that indels are enriched in associations with gene expression and find evidence for a contribution of nonsense-mediated decay. Finally, we show that indels can be integrated in existing genome-wide association studies (GWAS); although we do not find direct evidence that potentially causal protein-coding indels are enriched with associations to known disease-associated SNPs, our findings suggest that the causal variant underlying some of these associations may be indels.