Communications of the ACM
Technique Pinpoints the 'partners in Crime' of Cancer Genes
Researchers at Stanford University have devised an algorithm to churn through piles of existing data to identify and target backup biological pathways often used by cancers.
Credit: Steve Fisch
Researchers at Stanford University have developed an algorithm to sift through vast datasets and identify genetic pathways for cancer.
The team taught the computer an "if this, then that" concept to help identify pairs of genes with co-dependent expression levels, and then applied their method to data in the Cancer Genome Atlas to detect situations in which genes were either more highly expressed in the presence of particular cancer-associated mutations than when the mutation was absent, or genes that were seldom or never deleted in the presence of the mutation.
The researchers addressed 12 different types of cancers and more than 3,000 cancer-associated mutations to specify thousands of new complementary genes that could be amenable to drug therapy.
They found 17 out of 89 potential synthetic lethal partners for an established leukemia-associated mutation are likely to be susceptible to drugs that are either already clinically available or are under development.
From Stanford University
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Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA
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