Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Funnell T

PROVIDER: S-EPMC6402697 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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

Funnell Tyler T Zhang Allen W AW Grewal Diljot D McKinney Steven S Bashashati Ali A Wang Yi Kan YK Shah Sohrab P SP

PLoS computational biology 20190222 2

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 sequenc ...[more]

PMID: 30794536

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Project description:Genetic variation amongst individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single-nucleotide changes. In this manuscript we explore variation on an intermediate scale-particularly insertions, deletions, and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number among individuals. Sequencing of a subset of structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence-map of human structural variation-an important standard for genotyping platforms and a prelude to future individual genome sequencing projects. Keywords: comparative genomic hybridization The DNA samples are a panel of 8 Hapmap samples, described by E. Eichler et al. (2007, Nature 447, 161-165). This set of 7 female, and one male samples are from from the Coriell Cell Repository, and is comprised of samples from four populations: four Yoruban, two CEPH, one Chinese, and one Japanese. The reference sample, NA15510, is female and also from the Corriel Cell Repository. This sample has been extensively characterized, (for example in Tuzan et al. 2005, Nature Genetics 10, p1038) and has been recommended for use in CNV detection programs to allow meaningful comparison of data between studies (discussed in Scherer, et al. 2007, Nature Genetics Supplement 39: S7-S15). Each of these samples was hybridized in pairs with the reversed labeling polarities. Additionally, 3 self-self control hybridizations were carried out for the reference sample, NA15510, one on each hybridization date.

Dataset Information

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

Publications

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

Similar Datasets

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