Cancer genomics

About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXX^trunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXX^trunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.

Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance.

Mutations in BRCA1 and/or BRCA2 (BRCA1/2) are the most common indication of deficiency in the homologous recombination (HR) DNA repair pathway. However, recent genome-wide analyses have shown that the same pattern of mutations found in BRCA1/2-mutant tumors is also present in several other tumors. Here, we present a new computational tool called Signature Multivariate Analysis (SigMA), which can be used to accurately detect the mutational signature associated with HR deficiency from targeted gene panels. Whereas previous methods require whole-genome or whole-exome data, our method detects the HR-deficiency signature even from low mutation counts, by using a likelihood-based measure combined with machine-learning techniques. Cell lines that we identify as HR deficient show a significant response to poly (ADP-ribose) polymerase (PARP) inhibitors; patients with ovarian cancer whom we found to be HR deficient show a significantly longer overall survival with platinum regimens. By enabling panel-based identification of mutational signatures, our method substantially increases the number of patients that may be considered for treatments targeting HR deficiency.

Cancer is often seen as a disease of mutations and chromosomal abnormalities. However, some cancers, including pediatric rhabdoid tumors (RTs), lack recurrent alterations targetable by current drugs and need alternative, informed therapeutic options. To nominate potential targets, we performed a high-throughput small-molecule screen complemented by a genome-scale CRISPR-Cas9 gene-knockout screen in a large number of RT and control cell lines. These approaches converged to reveal several receptor tyrosine kinases (RTKs) as therapeutic targets, with RTK inhibition effective in suppressing RT cell growth in vitro and against a xenograft model in vivo. RT cell lines highly express and activate (phosphorylate) different RTKs, creating dependency without mutation or amplification. Downstream of RTK signaling, we identified PTPN11, encoding the pro-growth signaling protein SHP2, as a shared dependency across all RT cell lines. This study demonstrates that large-scale perturbational screening can uncover vulnerabilities in cancers with "quiet" genomes.

BACKGROUND: Genomic rearrangements exert a heavy influence on the molecular landscape of cancer. New analytical approaches integrating somatic structural variants (SSVs) with altered gene features represent a framework by which we can assign global significance to a core set of genes, analogous to established methods that identify genes non-randomly targeted by somatic mutation or copy number alteration. While recent studies have defined broad patterns of association involving gene transcription and nearby SSV breakpoints, global alterations in DNA methylation in the context of SSVs remain largely unexplored. RESULTS: By data integration of whole genome sequencing, RNA sequencing, and DNA methylation arrays from more than 1400 human cancers, we identify hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of a somatic structural variant (SSV) breakpoint is recurrently associated with altered expression or DNA methylation, respectively, independently of copy number alterations. CGIs with SSV-associated increased methylation are predominantly promoter-associated, while CGIs with SSV-associated decreased methylation are enriched for gene body CGIs. Rearrangement of genomic regions normally having higher or lower methylation is often involved in SSV-associated CGI methylation alterations. Across cancers, the overall structural variation burden is associated with a global decrease in methylation, increased expression in methyltransferase genes and DNA damage response genes, and decreased immune cell infiltration. CONCLUSION: Genomic rearrangement appears to have a major role in shaping the cancer DNA methylome, to be considered alongside commonly accepted mechanisms including histone modifications and disruption of DNA methyltransferases.

Background: The classical genetic model of colorectal cancer presents APC mutations as the earliest genomic alterations, followed by KRAS and TP53 mutations. However, the timing and relative order of clonal expansion and other types of genomic alterations, such as genomic rearrangements, are still unclear.

Results: Here, we perform comprehensive bioinformatic analysis to dissect the relative timing of somatic genetic alterations in 63 colorectal cancers with whole-genome sequencing data. Utilizing allele fractions of somatic single nucleotide variants as molecular clocks while accounting for the presence of copy number changes and structural alterations, we identify key events in the evolution of colorectal tumors. We find that driver point mutations, gene fusions, and arm-level copy losses typically arise early in tumorigenesis; different mechanisms act on distinct genomic regions to drive DNA copy changes; and chromothripsis-clustered rearrangements previously thought to occur as a single catastrophic event-is frequent and may occur multiple times independently in the same tumor through different mechanisms. Furthermore, our computational approach reveals that, in contrast to recent studies, selection is often present on subclones and that multiple evolutionary models can operate in a single tumor at different stages.

Conclusion: Combining these results, we present a refined tumor progression model which significantly expands our understanding of the tumorigenic process of human colorectal cancer.

Keywords: Aneuploidy; Kataegis; Tumor evolution; Tumor heterogeneity.

Malignant rhabdoid tumors (MRT) are highly aggressive pediatric cancers that respond poorly to current therapies. In this study, we screened several MRT cell lines with large-scale RNAi, CRISPR-Cas9, and small-molecule libraries to identify potential drug targets specific for these cancers. We discovered MDM2 and MDM4, the canonical negative regulators of p53, as significant vulnerabilities. Using two compounds currently in clinical development, idasanutlin (MDM2-specific) and ATSP-7041 (MDM2/4-dual), we show that MRT cells were more sensitive than other p53 wild-type cancer cell lines to inhibition of MDM2 alone as well as dual inhibition of MDM2/4. These compounds caused significant upregulation of the p53 pathway in MRT cells, and sensitivity was ablated by CRISPR-Cas9–mediated inactivation of TP53. We show that loss of SMARCB1, a subunit of the SWI/SNF (BAF) complex mutated in nearly all MRTs, sensitized cells to MDM2 and MDM2/4 inhibition by enhancing p53-mediated apoptosis. Both MDM2 and MDM2/4 inhibition slowed MRT xenograft growth in vivo, with a 5-day idasanutlin pulse causing marked regression of all xenografts, including durable complete responses in 50% of mice. Together, these studies identify a genetic connection between mutations in the SWI/SNF chromatin-remodeling complex and the tumor suppressor gene TP53 and provide preclinical evidence to support the targeting of MDM2 and MDM4 in this often-fatal pediatric cancer.

Glioblastoma is a malignant brain tumor characterized by rapid growth, diffuse invasion and therapeutic resistance. We recently used microRNA expression profiles to subclassify glioblastoma into five genetically and clinically distinct subclasses, and showed that microRNAs both define and contribute to the phenotypes of these subclasses. Here we show that miR-29a activates a multi-faceted growth and invasion program that promotes glioblastoma aggressiveness.

Bromodomain-containing protein 9 (BRD9) is a recently identified subunit of SWI/SNF(BAF) chromatin remodeling complexes, yet its function is poorly understood. Here, using a genome-wide CRISPR-Cas9 screen, we show that BRD9 is a specific vulnerability in pediatric malignant rhabdoid tumors (RTs), which are driven by inactivation of the SMARCB1 subunit of SWI/SNF. We find that BRD9 exists in a unique SWI/SNF sub-complex that lacks SMARCB1, which has been considered a core subunit. While SMARCB1-containing SWI/SNF complexes are bound preferentially at enhancers, we show that BRD9-containing complexes exist at both promoters and enhancers. Mechanistically, we show that SMARCB1 loss causes increased BRD9 incorporation into SWI/SNF thus providing insight into BRD9 vulnerability in RTs. Underlying the dependency, while its bromodomain is dispensable, the DUF3512 domain of BRD9 is essential for SWI/SNF integrity in the absence of SMARCB1. Collectively, our results reveal a BRD9-containing SWI/SNF subcomplex is required for the survival of SMARCB1-mutant RTs.

Characterization of intratumoral heterogeneity is critical to cancer therapy, as the presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss of heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct the underlying subclonal architecture. By examining several tumor types, we show that HoneyBADGER is effective at identifying deletions, amplifications, and copy-neutral loss-of-heterozygosity events and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure and were likely driven by alternative, nonclonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer.

A systematic cataloging of genes affected by genomic rearrangement, using multiple patient cohorts and cancer types, can provide insight into cancer-relevant alterations outside of exomes. By integrative analysis of whole-genome sequencing (predominantly low pass) and gene expression data from 1,448 cancers involving 18 histopathological types in The Cancer Genome Atlas, we identified hundreds of genes for which the nearby presence (within 100 kb) of a somatic structural variant (SV) breakpoint is associated with altered expression. While genomic rearrangements are associated with widespread copy-number alteration (CNA) patterns, approximately 1,100 genes-including overexpressed cancer driver genes (e.g., TERT, ERBB2, CDK12, CDK4) and underexpressed tumor suppressors (e.g., TP53, RB1, PTEN, STK11)-show SV-associated deregulation independent of CNA. SVs associated with the disruption of topologically associated domains, enhancer hijacking, or fusion transcripts are implicated in gene upregulation. For cancer-relevant pathways, SVs considerably expand our understanding of how genes are affected beyond point mutation or CNA.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

Microsatellite instability (MSI) refers to the hypermutability of short repetitive sequences in the genome caused by impaired DNA mismatch repair. Although MSI has been studied for decades, large amounts of sequencing data now available allows us to examine the molecular fingerprints of MSI in greater detail. Here, we analyse ∼8,000 exomes and ∼1,000 whole genomes of cancer patients across 23 cancer types. Our analysis reveals that the frequency of MSI events is highly variable within and across tumour types. We also identify genes in DNA repair and oncogenic pathways recurrently subject to MSI and uncover non-coding loci that frequently display MSI. Finally, we propose a highly accurate exome-based predictive model for the MSI phenotype. These results advance our understanding of the genomic drivers and consequences of MSI, and our comprehensive catalogue of tumour-type-specific MSI loci will enable panel-based MSI testing to identify patients who are likely to benefit from immunotherapy.

Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay.

Purpose Histologic transformation of EGFR mutant lung adenocarcinoma (LADC) into small-cell lung cancer (SCLC) has been described as one of the major resistant mechanisms for epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). However, the molecular pathogenesis is still unclear. Methods We investigated 21 patients with advanced EGFR-mutant LADCs that were transformed into EGFR TKI-resistant SCLCs. Among them, whole genome sequencing was applied for nine tumors acquired at various time points from four patients to reconstruct their clonal evolutionary history and to detect genetic predictors for small-cell transformation. The findings were validated by immunohistochemistry in 210 lung cancer tissues. Results We identified that EGFR TKI-resistant LADCs and SCLCs share a common clonal origin and undergo branched evolutionary trajectories. The clonal divergence of SCLC ancestors from the LADC cells occurred before the first EGFR TKI treatments, and the complete inactivation of both RB1 and TP53 were observed from the early LADC stages in sequenced tumors. We extended the findings by immunohistochemistry in the early-stage LADC tissues of 75 patients treated with EGFR TKIs; inactivation of both Rb and p53 was strikingly more frequent in the small-cell-transformed group than in the nontransformed group (82% v 3%; odds ratio, 131; 95% CI, 19.9 to 859). Among patients registered in a predefined cohort (n = 65), an EGFR mutant LADC that harbored completely inactivated Rb and p53 had a 43× greater risk of small-cell transformation (relative risk, 42.8; 95% CI, 5.88 to 311). Branch-specific mutational signature analysis revealed that apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC)-induced hypermutation was frequent in the branches toward small-cell transformation. Conclusion EGFR TKI-resistant SCLCs are branched out early from the LADC clones that harbor completely inactivated RB1 and TP53. The evaluation of RB1 and TP53 status in EGFR TKI-treated LADCs is informative in predicting small-cell transformation.

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2, and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. Cancer Res; 77(13); 1-11. ©2017 AACR.

Molecular alterations involving the PI3K/AKT/mTOR pathway (including mutation, copy number, protein, or RNA) were examined across 11,219 human cancers representing 32 major types. Within specific mutated genes, frequency, mutation hotspot residues, in silico predictions, and functional assays were all informative in distinguishing the subset of genetic variants more likely to have functional relevance. Multiple oncogenic pathways including PI3K/AKT/mTOR converged on similar sets of downstream transcriptional targets. In addition to mutation, structural variations and partial copy losses involving PTEN and STK11 showed evidence for having functional relevance. A substantial fraction of cancers showed high mTOR pathway activity without an associated canonical genetic or genomic alteration, including cancers harboring IDH1 or VHL mutations, suggesting multiple mechanisms for pathway activation.

Genes encoding subunits of SWI/SNF (BAF) chromatin remodelling complexes are collectively altered in over 20% of human malignancies, but the mechanisms by which these complexes alter chromatin to modulate transcription and cell fate are poorly understood. Utilizing mouse embryonic fibroblast and cancer cell line models, here we show via ChIP-seq and biochemical assays that SWI/SNF complexes are preferentially targeted to distal lineage specific enhancers and interact with p300 to modulate histone H3 lysine 27 acetylation. We identify a greater requirement for SWI/SNF at typical enhancers than at most super-enhancers and at enhancers in untranscribed regions than in transcribed regions. Our data further demonstrate that SWI/SNF-dependent distal enhancers are essential for controlling expression of genes linked to developmental processes. Our findings thus establish SWI/SNF complexes as regulators of the enhancer landscape and provide insight into the roles of SWI/SNF in cellular fate control.

SMARCB1 (also known as SNF5, INI1, and BAF47), a core subunit of the SWI/SNF (BAF) chromatin-remodeling complex, is inactivated in nearly all pediatric rhabdoid tumors. These aggressive cancers are among the most genomically stable, suggesting an epigenetic mechanism by which SMARCB1 loss drives transformation. Here we show that, despite having indistinguishable mutational landscapes, human rhabdoid tumors exhibit distinct enhancer H3K27ac signatures, which identify remnants of differentiation programs. We show that SMARCB1 is required for the integrity of SWI/SNF complexes and that its loss alters enhancer targeting-markedly impairing SWI/SNF binding to typical enhancers, particularly those required for differentiation, while maintaining SWI/SNF binding at super-enhancers. We show that these retained super-enhancers are essential for rhabdoid tumor survival, including some that are shared by all subtypes, such as SPRY1, and other lineage-specific super-enhancers, such as SOX2 in brain-derived rhabdoid tumors. Taken together, our findings identify a new chromatin-based epigenetic mechanism underlying the tumor-suppressive activity of SMARCB1.