Analysis of 7,815 cancer exomes reveals associations between mutational processes and somatic driver mutations.

Driver mutations are the genetic variants responsible for oncogenesis, but how specific somatic mutational events arise in cells remains poorly understood. Mutational signatures derive from the frequency of mutated trinucleotides in a given cancer sample, and they provide an avenue for investigating the underlying mutational processes that operate in cancer. Here we analyse somatic mutations from 7,815 cancer exomes from The Cancer Genome Atlas (TCGA) across 26 cancer types. We curate a list of 50 known cancer driver mutations by analysing recurrence in our cohort and annotations of known cancer-associated genes from the Cancer Gene Census, IntOGen database and Cancer Genome Interpreter. We then use these datasets to perform binary univariate logistic regression and establish the statistical relationship between individual driver mutations and known mutational signatures across different cancer types. Our analysis led to the identification of 39 significant associations between driver mutations and mutational signatures (P < 0.004, with a false discovery rate of < 5%). We first validate our methodology by establishing statistical links for known and novel associations between driver mutations and the mutational signature arising from Polymerase Epsilon proofreading deficiency. We then examine associations between driver mutations and mutational signatures for AID/APOBEC enzyme activity and deficient mismatch repair. We also identify negative associations (odds ratio < 1) between mutational signatures and driver mutations, and here we examine the role of aging and cigarette smoke mutagenesis in the generation of driver mutations in IDH1 and KRAS in brain cancers and lung adenocarcinomas respectively. Our study provides statistical foundations for hypothesised links between otherwise independent biological processes and we uncover previously unexplored relationships between driver mutations and mutagenic processes during cancer development. These associations give insights into how cancers acquire advantageous mutations and can provide direction to guide further mechanistic studies into cancer pathogenesis.

Rapid Protocol Development, Study Startup and Enrolment of a Prospective Study of COVID-19 Vaccination for Patients with Cancer: A Collaborative Approach.

BACKGROUND: COVID-19 is an unprecedented global health emergency. It has been highly disruptive for patients with cancer, both due to an increased burden of severe illness and due to pressure on healthcare systems. COVID-19 vaccination has been an important public health measure for this patient group. AIM: The aim of this study was to describe the rapid design and startup of a multicentre study of COVID-19 vaccine response for vulnerable patients with cancer. Study startup: We set up a multicentre prospective observational study of COVID-19 vaccination response for Australian patients with cancer. Due to intensive collaboration between health services, the funding body and laboratories, we were able to develop a protocol and enrol the first patient within 52 days of the initial study proposal. Rapid startup was further enabled by prompt availability of funding and by high-level engagement of institutional review boards, allowing expedited review. Study enrolment: We rapidly enroled more than 500 patients, 80% within 4 months of study opening. Engagement and follow-up were maintained throughout the course of up to five serial vaccination doses. CONCLUSION: Our study is an example of intensive collaboration inspired by the COVID-19 pandemic and may serve as an example of an agile research response to real-time public health challenges.

Integrated Genetic, Epigenetic, and Transcriptional Profiling Identifies Molecular Pathways in the Development of Laterally Spreading Tumors.

Laterally spreading tumors (LST) are colorectal adenomas that develop into extremely large lesions with predominantly slow progression to cancer, depending on lesion subtype. Comparing and contrasting the molecular profiles of LSTs and colorectal cancers offers an opportunity to delineate key molecular alterations that drive malignant transformation in the colorectum. In a discovery cohort of 11 LSTs and paired normal mucosa, we performed a comprehensive and unbiased screen of the genome, epigenome, and transcriptome followed by bioinformatics integration of these data and validation in an additional 84 large, benign colorectal lesions. Mutation rates in LSTs were comparable with microsatellite-stable colorectal cancers (2.4 vs. 2.6 mutations per megabase); however, copy number alterations were infrequent (averaging only 1.5 per LST). Frequent genetic, epigenetic, and transcriptional alterations were identified in genes not previously implicated in colorectal neoplasia (ANO5, MED12L, EPB41L4A, RGMB, SLITRK1, SLITRK5, NRXN1, ANK2). Alterations to pathways commonly mutated in colorectal cancers, namely, the p53, PI3K, and TGFß pathways, were rare. Instead, LST-altered genes converged on axonal guidance, Wnt, and actin cytoskeleton signaling. These integrated omics data identify molecular features associated with noncancerous LSTs and highlight that mutation load, which is relatively high in LSTs, is a poor predictor of invasive potential. IMPLICATIONS: The novel genetic, epigenetic, and transcriptional changes associated with LST development reveal important insights into why some adenomas do not progress to cancer. The finding that LSTs exhibit a mutational load similar to colorectal carcinomas has implications for the validity of molecular biomarkers for assessing cancer risk. Mol Cancer Res; 14(12); 1217-28. ©2016 AACR.