Uncovering Clinically Relevant Gene Fusions with Integrated Genomic and Transcriptomic Profiling of Metastatic Cancers.

PURPOSE: Gene fusions are important oncogenic drivers and many are actionable. Whole-genome and transcriptome (WGS and RNA-seq, respectively) sequencing can discover novel clinically relevant fusions. EXPERIMENTAL DESIGN: Using WGS and RNA-seq, we reviewed the prevalence of fusions in a cohort of 570 patients with cancer, and compared prevalence to that predicted with commercially available panels. Fusions were annotated using a consensus variant calling pipeline (MAVIS) and required that a contig of the breakpoint could be constructed and supported from ≥2 structural variant detection approaches. RESULTS: In 570 patients with advanced cancer, MAVIS identified 81 recurrent fusions by WGS and 111 by RNA-seq, of which 18 fusions by WGS and 19 by RNA-seq were noted in at least 3 separate patients. The most common fusions were EML4-ALK in thoracic malignancies (9/69, 13%), and CMTM8-CMTM7 in colorectal cancer (4/73, 5.5%). Combined genomic and transcriptomic analysis identified novel fusion partners for clinically relevant genes, such as NTRK2 (novel partners: SHC3, DAPK1), and NTRK3 (novel partners: POLG, PIBF1). CONCLUSIONS: Utilizing WGS/RNA-seq facilitates identification of novel fusions in clinically relevant genes, and detected a greater proportion than commercially available panels are expected to find. A significant benefit of WGS and RNA-seq is the innate ability to retrospectively identify variants that becomes clinically relevant over time, without the need for additional testing, which is not possible with panel-based approaches.

Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes.

Advanced and metastatic tumors with complex treatment histories drive cancer mortality. Here we describe the POG570 cohort, a comprehensive whole-genome, transcriptome and clinical dataset, amenable for exploration of the impacts of therapies on genomic landscapes. Previous exposure to DNA-damaging chemotherapies and mutations affecting DNA repair genes, including POLQ and genes encoding Polζ, were associated with genome-wide, therapy-induced mutagenesis. Exposure to platinum therapies coincided with signatures SBS31 and DSB5 and, when combined with DNA synthesis inhibitors, signature SBS17b. Alterations in ESR1, EGFR, CTNNB1, FGFR1, VEGFA and DPYD were consistent with drug resistance and sensitivity. Recurrent noncoding events were found in regulatory region hotspots of genes including TERT, PLEKHS1, AP2A1 and ADGRG6. Mutation burden and immune signatures corresponded with overall survival and response to immunotherapy. Our data offer a rich resource for investigation of advanced cancers and interpretation of whole-genome and transcriptome sequencing in the context of a cancer clinic.

Recurrent tumor-specific regulation of alternative polyadenylation of cancer-related genes.

BACKGROUND: Alternative polyadenylation (APA) results in messenger RNA molecules with different 3' untranslated regions (3' UTRs), affecting the molecules' stability, localization, and translation. APA is pervasive and implicated in cancer. Earlier reports on APA focused on 3' UTR length modifications and commonly characterized APA events as 3' UTR shortening or lengthening. However, such characterization oversimplifies the processing of 3' ends of transcripts and fails to adequately describe the various scenarios we observe. RESULTS: We built a cloud-based targeted de novo transcript assembly and analysis pipeline that incorporates our previously developed cleavage site prediction tool, KLEAT. We applied this pipeline to elucidate the APA profiles of 114 genes in 9939 tumor and 729 tissue normal samples from The Cancer Genome Atlas (TCGA). The full set of 10,668 RNA-Seq samples from 33 cancer types has not been utilized by previous APA studies. By comparing the frequencies of predicted cleavage sites between normal and tumor sample groups, we identified 77 events (i.e. gene-cancer type pairs) of tumor-specific APA regulation in 13 cancer types; for 15 genes, such regulation is recurrent across multiple cancers. Our results also support a previous report showing the 3' UTR shortening of FGF2 in multiple cancers. However, over half of the events we identified display complex changes to 3' UTR length that resist simple classification like shortening or lengthening. CONCLUSIONS: Recurrent tumor-specific regulation of APA is widespread in cancer. However, the regulation pattern that we observed in TCGA RNA-seq data cannot be described as straightforward 3' UTR shortening or lengthening. Continued investigation into this complex, nuanced regulatory landscape will provide further insight into its role in tumor formation and development.