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Identification of relevant genetic alterations in cancer using topological data analysis
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Identification of relevant genetic alterations in cancer using topological data analysis
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Journal Article
Identification of relevant genetic alterations in cancer using topological data analysis
2020
Overview
Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that
ADAMTS12
−/−
mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of
ADAMTS12
as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.
Rare cancer mutations are often missed using recurrence-based statistical approaches, but are usually accompanied by changes in expression. Here the authors leverage this information to uncover several elusive candidate cancer-associated genes using topological data analysis.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ 45/23
/ 631/114
/ 64/110
/ Adenocarcinoma of Lung - genetics
/ Animals
/ Cancer
/ Computational Biology - methods
/ Genes
/ Genetic Predisposition to Disease - genetics
/ Humanities and Social Sciences
/ Lungs
/ Mice
/ Mutation
/ Neoplasm Recurrence, Local - genetics
/ RNA
/ Science
/ Topology
/ Tumors
