Journal Article

Integrated structural variation and point mutation signatures in cancer genomes using correlated topic models

Wang, Yi Kan, Grewal, Diljot, Shah, Sohrab P., Funnell, Tyler, Bashashati, Ali, McKinney, Steven, Zhang, Allen W.

2019

Overview

Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n = 755 samples total). We show how introducing correlated structure both within and between modes of mutation can increase accuracy of signature discovery, particularly in the context of sparse data. Our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, and provides a statistical modeling framework to incorporate additional features of interest for future studies.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Analysis / Artificial intelligence / Bioinformatics / Biology and Life Sciences / Breast cancer / Cancer / Cancer genetics / Computational Biology - methods / Correlation / Data mining / Deoxyribonucleic acid / DNA / DNA repair / DNA sequencing / Epidemiology / Etiology / Etiology (Medicine) / Formalism (Literary criticism) / Future predictions / Gene mutation / Gene mutations / Gene sequencing / Genetic aspects / Genetic Variation - genetics / Genome / Genomes / Genomics / Hormones / Humans / Learning algorithms / Machine Learning / Mathematical models / Medical research / Medicine and Health Sciences / Models, Statistical / Mutation / Neoplasms - genetics / Novels / Nucleotides / Observations / Oncology / Ovarian cancer / Point mutation / Point Mutation - genetics / Prognosis / Research and Analysis Methods / Sequence Analysis, DNA - methods / Signatures / Software / Statistical methods / Statistical models / Transcriptome - genetics / Tumors / Whole genome sequencing