moPepGen: Rapid and Comprehensive Proteoform Identification

Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities at each step of this transformation multiply a single gene into a myriad of proteoforms. Proteogenomics is the study of how genomic and transcriptomic variation creates this proteoform diversity, and is limited by the challenges of modeling the complexities of gene-expression. We therefore created moPepGen, a graph-based algorithm that comprehensively enumerates proteoforms in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it detects and quantifies previously unobserved noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization. By enabling efficient identification and quantitation of previously hidden proteins in both existing and new proteomic data, moPepGen facilitates all proteogenomics applications. It is available at: https://github.com/uclahs-cds/package-moPepGen.

The genomic and evolutionary landscapes of anaplastic thyroid carcinoma

Anaplastic thyroid carcinoma is arguably the most lethal human malignancy. It often co-occurs with differentiated thyroid cancers, yet the molecular origins of its aggressivity are unknown. We sequenced tumor DNA from 329 regions of thyroid cancer, including 213 from patients with primary anaplastic thyroid carcinomas. We also whole genome sequenced 9 patients using multi-region sequencing of both differentiated and anaplastic thyroid cancer components. Using these data, we demonstrate thatanaplastic thyroid carcinomas have a higher burden of mutations than other thyroid cancers, with distinct mutational signatures and molecular subtypes. Further, different cancer driver genes are mutated in anaplastic and differentiated thyroid carcinomas, even those arising in a single patient. Finally, we unambiguously demonstrate that anaplastic thyroid carcinomas share a genomic origin with co-occurring differentiated carcinomas and emerge from a common malignant field through acquisition of characteristic clonal driver mutations.

NFTest: automated testing of Nextflow pipelines

MOTIVATION

The ongoing expansion in the volume of biomedical data has contributed to a growing complexity in the tools and technologies used in research with an increased reliance on complex workflows written in orchestration languages such as Nextflow to integrate algorithms into processing pipelines. The growing use of workflows involving various tools and algorithms has led to increased scrutiny of software development practices to avoid errors in individual tools and in the connections between them.

RESULTS

To facilitate test-driven development of Nextflow pipelines, we created NFTest, a framework for automated pipeline testing and validation with customizability options for Nextflow features. It is open-source, easy to initialize and use, and customizable to allow for testing of complex workflows with test success configurable through a broad range of assertions. NFTest simplifies the testing burden on developers by automating tests once defined and providing a flexible interface for running tests to validate workflows. This reduces the barrier to rigorous biomedical workflow testing and paves the way toward reducing computational errors in biomedicine.

AVAILABILITY AND IMPLEMENTATION

NFTest is an open-source Python framework under the GPLv2 license and is freely available at https://github.com/uclahs-cds/tool-NFTest. The call-sSNV Nextflow pipeline is available at: https://github.com/uclahs-cds/pipeline-call-sSNV.

PipeVal: light-weight extensible tool for file validation

MOTIVATION

The volume of biomedical data generated each year is growing exponentially as high-throughput molecular, imaging and mHealth technologies expand. This rise in data volume has contributed to an increasing reliance on and demand for computational methods, and consequently to increased attention to software quality and data integrity.

RESULTS

To simplify data verification in diverse data-processing pipelines, we created PipeVal, a light-weight, easy-to-use, extensible tool for file validation. It is open-source, easy to integrate with complex workflows, and modularized for extensibility for new file formats. PipeVal can be rapidly inserted into existing methods and pipelines to automatically validate and verify inputs and outputs. This can reduce wasted compute time attributed to file corruption or invalid file paths, and significantly improve the quality of data-intensive software.

AVAILABILITY AND IMPLEMENTATION

PipeVal is an open-source Python package under the GPLv2 license and it is freely available at https://github.com/uclahs-cds/package-PipeVal. The docker image is available at: https://github.com/uclahs-cds/package-PipeVal/pkgs/container/pipeval.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Oncolytic DNX-2401 virotherapy plus pembrolizumab in recurrent glioblastoma: a phase 1/2 trial

Immune-mediated anti-tumoral responses, elicited by oncolytic viruses and augmented with checkpoint inhibition, may be an effective treatment approach for glioblastoma. Here in this multicenter phase 1/2 study we evaluated the combination of intratumoral delivery of oncolytic virus DNX-2401 followed by intravenous anti-PD-1 antibody pembrolizumab in recurrent glioblastoma, first in a dose-escalation and then in a dose-expansion phase, in 49 patients. The primary endpoints were overall safety and objective response rate. The primary safety endpoint was met, whereas the primary efficacy endpoint was not met. There were no dose-limiting toxicities, and full dose combined treatment was well tolerated. The objective response rate was 10.4% (90% confidence interval (CI) 4.2-20.7%), which was not statistically greater than the prespecified control rate of 5%. The secondary endpoint of overall survival at 12 months was 52.7% (95% CI 40.1-69.2%), which was statistically greater than the prespecified control rate of 20%. Median overall survival was 12.5 months (10.7-13.5 months). Objective responses led to longer survival (hazard ratio 0.20, 95% CI 0.05-0.87). A total of 56.2% (95% CI 41.1-70.5%) of patients had a clinical benefit defined as stable disease or better. Three patients completed treatment with durable responses and remain alive at 45, 48 and 60 months. Exploratory mutational, gene-expression and immunophenotypic analyses revealed that the balance between immune cell infiltration and expression of checkpoint inhibitors may potentially inform on response to treatment and mechanisms of resistance. Overall, the combination of intratumoral DNX-2401 followed by pembrolizumab was safe with notable survival benefit in select patients (ClinicalTrials.gov registration: NCT02798406).

A polygenic two-hit hypothesis for prostate cancer

Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

Abstract 932: Snapshot! Exploring sample diversity of sarcoma cancers across common data repositories

Sarcoma is a cancer which originates in the body's connective tissues of mesenchymal origin. These are tissues like bones and muscles that support or protect other parts of the body. About ~16,000 sarcomas are diagnosed annually in the US, with ~6,700 deaths attributed to the disease. Sarcomas are typically divided into two major groups: bone sarcomas and soft-tissue sarcomas, each of which has multiple subtypes. However, because of their diversity in site-of-origin, sarcomas vary greatly in their presentation and histological features. Based on The World Health Organization’s (WHO) current classification system that categorizes musculoskeletal soft tissue tumours (STT) and bone tissue tumours, there are 50+ subtypes of sarcoma recognized today. Unsurprisingly, given the relative rarity of sarcoma type tumors, sample procurement has proved a challenge for the field. Consequently, there currently exist major gaps in our understanding of the genetic and molecular hallmarks of various sarcoma subtypes. Here we examine the sample and subtype classifications of sarcoma across some of the major DNA sequencing studies and data repositories to provide an overview of the available sample space. We highlight areas where the sample procurement is lagging and discuss subtypes that are missing all-together. Inclusion of some of the major genomic correlates showcases some of the similarities shared by these sequencing efforts, while emphasizing key genetic differences between subtypes. This work provides a clear roadmap for clinicians on how to best prioritize future sarcoma sample procurement and sequencing.

Citation Format: Alfredo Enrique Gonzalez, Yash Patel, Chenghao Zhu, Takafumi N. Yamaguchi, Mao Tian, Sarah Hiyari, Ahmad A. Shihabi, Stefan Eng, Helena Winata, Jaron Arbert, Arpi Beshlikyan, Ardalan Davarifar, Alice Soragni, Paul C. Boutros. Snapshot! Exploring sample diversity of sarcoma cancers across common data repositories [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 932.

Abstract 3315: Evaluating biomarker potential of germline genomic factors for predicting clinical outcomes in prostate cancer

Prostate cancer is the second-most diagnosed cancer and the second leading cause of cancer death in American men. Early detection is common, but is followed by the more challenging task of prognosing a highly variable clinical course. Current clinical risk-assessment strategies such as serum abundance of prostate specific antigen (PSA), tumor size & extent, and tumor grade based on biopsy are highly imprecise: over a third of patients are over-treated. An improved method of risk stratification may lie in hereditary factors. Prostate cancer is one of the most strongly inherited (h2 = 57%), with accumulating evidence associating rare variants, common variants, and genetic ancestry to clinical outcomes. We have performed germline sequencing on blood from thousands of patients diagnosed with localized prostate cancer and with extensive follow-up data. We quantify the interactions of rare and common variants, and demonstrate that germline features provide insights into patient outcomes and optimal management strategies.

Citation Format: Nicole Zeltser, Kathleen E. Houlahan, Sarah M. Al-Hiyari, Stefan E. Eng, Yash Patel, Takafumi N. Yamaguchi, Shu Tao, Rong Rong Huang, Robert E. Reiter, Huihui Ye, Adam S. Kinnaird, Paul C. Boutros. Evaluating biomarker potential of germline genomic factors for predicting clinical outcomes in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3315.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Abstract 3071: A reconstruction of evolutionary trajectories in primary tissue and PDTOs in a patient with metastatic osteosarcoma

Metastatic osteosarcoma is a rare and highly lethal cancer that affects children and young adults. The rarity of osteosarcoma and its highly heterogeneous genetic composition have resulted in a lack of curative treatments for recurrent and metastatic disease.

In this study, we present the functional and molecular characterization of a case of a pediatric patient with left distal femur osteosarcoma and pulmonary metastases at presentation. Through longitudinal sampling over the course of the patient’s illness, we have procured tissue from the initial treatment-naïve diagnostic biopsy, primary tumor resection and multiple subsequent lung metastasectomies, and have developed patient-derived tumor organoids (PDTOs) from the viable samples. PDTOs are useful pre-clinical models that are representative of the source tissue and allow further interrogations of the biology of tumors. These models can also help with the identification of effective personalized therapies (Al Shihabi et al, 2021). We applied our mini-ring organoid screening technology (Phan et al, 2019; Nguyen et al, 2020) to perform high-throughput drug screening with different pharmacologic agents. We also performed deep whole-genome sequencing on all collected samples and corresponding organoids to reconstruct their evolutionary history, identify driver mutations and quantify heterogeneity in mutational processes across time and space.

Our preliminary data show that the subclonal content of the tumor and derivative organoids as well as the PDTO drug responses vary with the patient’s treatment history. We identify the genomic makeup of the subclones and posit changes that may be responsible for chemoresistance. Furthermore, our data shows correlations between the subclonal genomic composition of the PDTOs and source tissue, thereby reinforcing that PDTOs are capable of accurately recapitulating the subclonal heterogeneity of the parental tumor.

Citation Format: Ardy Davarifar, Jane Yanagawa, Ahmad Al Shihabi, Huyen T. Nguyen, Lydia Y. Liu, Adriana Salcedo, Alfredo Gonzalez, Takafumi N. Yamaguchi, Nicholas Bernthal, Scott D. Nelson, Noah Federman, Paul C. Boutros, Alice Soragni. A reconstruction of evolutionary trajectories in primary tissue and PDTOs in a patient with metastatic osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3071.

Virally programmed extracellular vesicles sensitize cancer cells to oncolytic virus and small molecule therapy

Recent advances in cancer therapeutics clearly demonstrate the need for innovative multiplex therapies that attack the tumour on multiple fronts. Oncolytic or “cancer-killing” viruses (OVs) represent up-and-coming multi-mechanistic immunotherapeutic drugs for the treatment of cancer. In this study, we perform an in-vitro screen based on virus-encoded artificial microRNAs (amiRNAs) and find that a unique amiRNA, herein termed amiR-4, confers a replicative advantage to the VSVΔ51 OV platform. Target validation of amiR-4 reveals ARID1A, a protein involved in chromatin remodelling, as an important player in resistance to OV replication. Virus-directed targeting of ARID1A coupled with small-molecule inhibition of the methyltransferase EZH2 leads to the synthetic lethal killing of both infected and uninfected tumour cells. The bystander killing of uninfected cells is mediated by intercellular transfer of extracellular vesicles carrying amiR-4 cargo. Altogether, our findings establish that OVs can serve as replicating vehicles for amiRNA therapeutics with the potential for combination with small molecule and immune checkpoint inhibitor therapy.

RNA-based viruses can be engineered to express artificial microRNAs (amiRNAs). Here, the authors identify a candidate amiRNA that confers a replicative advantage to oncolytic viruses, enhancing their anticancer potency, and show that intercellular transfer of extracellular vesicles carrying the amiRNA promotes bystander killing of uninfected cancer cells.

Abstract IA-018: Molecular landmarks of tumor hypoxia across cancer types

Many primary tumor sub-regions have low levels of molecular oxygen, termed hypoxia. Hypoxic tumors are at elevated risk for local failure and distant metastasis, but the molecular hallmarks of tumor hypoxia remain poorly defined. To fill this gap, we quantified hypoxia in 8,006 tumors across 19 tumor types. In ten tumor types, hypoxia was associated with elevated genomic instability. In all 19 tumor types, hypoxic tumors exhibited characteristic driver mutation signatures. We observed widespread hypoxia-associated dysregulation of miRNAs across cancers and functionally validated miR-133a-3p as a hypoxia-modulated miRNA. In localized prostate cancer, hypoxia was associated with elevated rates of chromothripsis, allelic loss of PTEN and shorter telomeres. These associations are particularly enriched in polyclonal tumors, representing a constellation of features resembling tumor nimbosus – an aggressive cellular phenotype. Overall, this work establishes that tumor hypoxia may drive aggressive molecular features across cancers and shape the clinical trajectory of individual tumors.

Citation Format: Vinayak Bhandari, Christianne Hoey, Lydia Liu, Emilie Lalonde, Jessica Ray, Julie Livingstone, Robert Lesurf, Yu-Jia Shiah, Tina Vujcic, Xiaoyong Huang, Shadrielle M.G. Espiritu, Lawrence E. Heisler, Fouad Yousif, Vincent Huang, Takafumi N. Yamaguchi, Cindy Q. Yao, Veronica Y. Sabelnykova, Michael Fraser, Melvin L.K. Chua, Theodorus van der Kwast, Stanley K. Liu, Paul C. Boutros, Robert G. Bristow. Molecular landmarks of tumor hypoxia across cancer types [abstract]. In: Proceedings of the AACR Virtual Special Conference on Radiation Science and Medicine; 2021 Mar 2-3. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(8_Suppl):Abstract nr IA-018.

Precision Radiotherapy: Reduction in Radiation for Oropharyngeal Cancer in the 30 ROC Trial

BACKGROUND

Patients with human papillomavirus-related oropharyngeal cancers have excellent outcomes but experience clinically significant toxicities when treated with standard chemoradiotherapy (70 Gy). We hypothesized that functional imaging could identify patients who could be safely deescalated to 30 Gy of radiotherapy.

METHODS

In 19 patients, pre- and intratreatment dynamic fluorine-18-labeled fluoromisonidazole positron emission tomography (PET) was used to assess tumor hypoxia. Patients without hypoxia at baseline or intratreatment received 30 Gy; patients with persistent hypoxia received 70 Gy. Neck dissection was performed at 4 months in deescalated patients to assess pathologic response. Magnetic resonance imaging (weekly), circulating plasma cell-free DNA, RNA-sequencing, and whole-genome sequencing (WGS) were performed to identify potential molecular determinants of response. Samples from an independent prospective study were obtained to reproduce molecular findings. All statistical tests were 2-sided.

RESULTS

Fifteen of 19 patients had no hypoxia on baseline PET or resolution on intratreatment PET and were deescalated to 30 Gy. Of these 15 patients, 11 had a pathologic complete response. Two-year locoregional control and overall survival were 94.4% (95% confidence interval = 84.4% to 100%) and 94.7% (95% confidence interval = 85.2% to 100%), respectively. No acute grade 3 radiation-related toxicities were observed. Microenvironmental features on serial imaging correlated better with pathologic response than tumor burden metrics or circulating plasma cell-free DNA. A WGS-based DNA repair defect was associated with response (P = .02) and was reproduced in an independent cohort (P = .03).

CONCLUSIONS

Deescalation of radiotherapy to 30 Gy on the basis of intratreatment hypoxia imaging was feasible, safe, and associated with minimal toxicity. A DNA repair defect identified by WGS was predictive of response. Intratherapy personalization of chemoradiotherapy may facilitate marked deescalation of radiotherapy.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer

Prostate cancer is the second most commonly diagnosed malignancy among men worldwide. Recurrently mutated in primary and metastatic prostate tumors, FOXA1 encodes a pioneer transcription factor involved in disease onset and progression through both androgen receptor-dependent and androgen receptor-independent mechanisms. Despite its oncogenic properties however, the regulation of FOXA1 expression remains unknown. Here, we identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic single-nucleotide variants in primary prostate tumors. We find that deletion and repression of these cis-regulatory elements significantly decreases FOXA1 expression and prostate cancer cell growth. Six of the ten single-nucleotide variants mapping to FOXA1 regulatory plexus significantly alter the transactivation potential of cis-regulatory elements by modulating the binding of transcription factors. Collectively, our results identify cis-regulatory elements within the FOXA1 plexus mutated in primary prostate tumors as potential targets for therapeutic intervention.

FOXA1 pioneer transcription factor is recurrently mutated in primary and metastatic prostate tumors. Here, authors identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic SNVs in primary prostate tumors and characterize their role in regulating FOXA1 expression and prostate cancer cell growth.

Cistrome Partitioning Reveals Convergence of Somatic Mutations and Risk Variants on Master Transcription Regulators in Primary Prostate Tumors

Thousands of noncoding somatic single-nucleotide variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1, and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators' tumor cistromes, exemplified at the 8q24 locus harboring both risk variants and somatic SNVs in cis-regulatory elements upregulating MYC expression. However, Massively Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual cis-regulatory elements. Instead, similar to inherited risk variants, SNVs accumulate in cistromes of master transcription regulators required for prostate cancer development.

The genomic landscape of metastatic castration-resistant prostate cancers reveals multiple distinct genotypes with potential clinical impact

Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.

Genome-wide germline correlates of the epigenetic landscape of prostate cancer

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.

Molecular landmarks of tumor hypoxia across cancer types

Many primary-tumor subregions have low levels of molecular oxygen, termed hypoxia. Hypoxic tumors are at elevated risk for local failure and distant metastasis, but the molecular hallmarks of tumor hypoxia remain poorly defined. To fill this gap, we quantified hypoxia in 8,006 tumors across 19 tumor types. In ten tumor types, hypoxia was associated with elevated genomic instability. In all 19 tumor types, hypoxic tumors exhibited characteristic driver-mutation signatures. We observed widespread hypoxia-associated dysregulation of microRNAs (miRNAs) across cancers and functionally validated miR-133a-3p as a hypoxia-modulated miRNA. In localized prostate cancer, hypoxia was associated with elevated rates of chromothripsis, allelic loss of PTEN and shorter telomeres. These associations are particularly enriched in polyclonal tumors, representing a constellation of features resembling tumor nimbosus, an aggressive cellular phenotype. Overall, this work establishes that tumor hypoxia may drive aggressive molecular features across cancers and shape the clinical trajectory of individual tumors.

Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.

Combining accurate tumor genome simulation with crowdsourcing to benchmark somatic structural variant detection

BACKGROUND

The phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness, and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries; however, there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold standards, extensive resource requirements, and difficulties arising from the need to share personal genomic information.

RESULTS

To facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowdsourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches.

CONCLUSIONS

The synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon .

Valection: design optimization for validation and verification studies

Background

Platform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile.

Results

To determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets.

Conclusions

Valection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2391-z) contains supplementary material, which is available to authorized users.

Abstract 2432: The genomic consequences of tumor hypoxia in human cancers

Introduction: Localized prostate cancers are classified into risk-groups using clinical measurements like grade and stage to inform treatment decisions. However, these groupings are imprecise: ~30% of intermediate-risk patients suffer relapse of their disease despite precision image-guided radiotherapy or radical prostatectomy. One reason for this variability in response to treatment is the underlying cellular and molecular heterogeneity of tumors. Prostate tumor cells exist within a microenvironment characterized by gradients of oxygen levels and prostate tumors with low levels of oxygen (hypoxia) have poor clinical outcomes.

Methods and Results: To understand the correlates of hypoxia in cancer we conducted a pan-cancer analysis of copy number alterations (CNAs) and single nucleotide variants (SNVs) across 19 cancer types. We measured hypoxia using multiple mRNA-based signatures and discovered numerous CNAs and SNVs enriched or depleted in hypoxic tumors, highlighting the role of hypoxia in shaping the genomic landscape of multiple tumor types. Next, we examined 548 patients with localized prostate cancer and statistically assessed the association of hypoxia with CNAs, SNVs, genomic rearrangements, focal genomic events (i.e. kataegis, chromothripsis), telomere length, clinical indices (i.e. grade, stage) and subclonal architecture. Tumor hypoxia is associated with specific CNAs and SNVs in prostate cancer driver genes. To translate these findings into a biomarker for prostate cancer precision medicine, we integrated tumor microenvironmental data with genomic and pathological information to stratify patients into distinct prognostic groups.

Impact: These data suggest that the aggressiveness of cancers is driven by the interplay of the tumor microenvironment and its genomic mutational profile.

Citation Format: Vinayak Bhandari, Shadrielle M. Espiritu, Lydia Y. Liu, Emilie Lalonde, Takafumi N. Yamaguchi, Lawrence E. Heisler, Julie Livingstone, Vincent Huang, Yu-Jia Shiah, Veronica Y. Sabelnykova, Fouad Yousif, Melvin L. Chua, Michael Fraser, Theodorus van der Kwast, Paul C. Boutros, Robert G. Bristow. The genomic consequences of tumor hypoxia in human cancers [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 2432.

Germline contamination and leakage in whole genome somatic single nucleotide variant detection

BACKGROUND

The clinical sequencing of cancer genomes to personalize therapy is becoming routine across the world. However, concerns over patient re-identification from these data lead to questions about how tightly access should be controlled. It is not thought to be possible to re-identify patients from somatic variant data. However, somatic variant detection pipelines can mistakenly identify germline variants as somatic ones, a process called "germline leakage". The rate of germline leakage across different somatic variant detection pipelines is not well-understood, and it is uncertain whether or not somatic variant calls should be considered re-identifiable. To fill this gap, we quantified germline leakage across 259 sets of whole-genome somatic single nucleotide variant (SNVs) predictions made by 21 teams as part of the ICGC-TCGA DREAM Somatic Mutation Calling Challenge.

RESULTS

The median somatic SNV prediction set contained 4325 somatic SNVs and leaked one germline polymorphism. The level of germline leakage was inversely correlated with somatic SNV prediction accuracy and positively correlated with the amount of infiltrating normal cells. The specific germline variants leaked differed by tumour and algorithm. To aid in quantitation and correction of leakage, we created a tool, called GermlineFilter, for use in public-facing somatic SNV databases.

CONCLUSIONS

The potential for patient re-identification from leaked germline variants in somatic SNV predictions has led to divergent open data access policies, based on different assessments of the risks. Indeed, a single, well-publicized re-identification event could reshape public perceptions of the values of genomic data sharing. We find that modern somatic SNV prediction pipelines have low germline-leakage rates, which can be further reduced, especially for cloud-sharing, using pre-filtering software.

Cribriform and intraductal prostate cancer are associated with increased genomic instability and distinct genomic alterations

BACKGROUND

Invasive cribriform and intraductal carcinoma (CR/IDC) is associated with adverse outcome of prostate cancer patients. The aim of this study was to determine the molecular aberrations associated with CR/IDC in primary prostate cancer, focusing on genomic instability and somatic copy number alterations (CNA).

METHODS

Whole-slide images of The Cancer Genome Atlas Project (TCGA, N = 260) and the Canadian Prostate Cancer Genome Network (CPC-GENE, N = 199) radical prostatectomy datasets were reviewed for Gleason score (GS) and presence of CR/IDC. Genomic instability was assessed by calculating the percentage of genome altered (PGA). Somatic copy number alterations (CNA) were determined using Fisher-Boschloo tests and logistic regression. Primary analysis were performed on TCGA (N = 260) as discovery and CPC-GENE (N = 199) as validation set.

RESULTS

CR/IDC growth was present in 80/260 (31%) TCGA and 76/199 (38%) CPC-GENE cases. Patients with CR/IDC and ≥ GS 7 had significantly higher PGA than men without this pattern in both TCGA (2.2 fold; p = 0.0003) and CPC-GENE (1.7 fold; p = 0.004) cohorts. CR/IDC growth was associated with deletions of 8p, 16q, 10q23, 13q22, 17p13, 21q22, and amplification of 8q24. CNAs comprised a total of 1299 gene deletions and 369 amplifications in the TCGA dataset, of which 474 and 328 events were independently validated, respectively. Several of the affected genes were known to be associated with aggressive prostate cancer such as loss of PTEN, CDH1, BCAR1 and gain of MYC. Point mutations in TP53, SPOP and FOXA1were also associated with CR/IDC, but occurred less frequently than CNAs.

CONCLUSIONS

CR/IDC growth is associated with increased genomic instability clustering to genetic regions involved in aggressive prostate cancer. Therefore, CR/IDC is a pathologic substrate for progressive molecular tumour derangement.

Exploring genetic suppression interactions on a global scale

Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.