Functional Characterization of Somatic Mutations in Cancer Using Network-based Inference of Protein Activity

Overview

Journal Nat Genet

Specialty Genetics

Date 2016 Jun 21

PMID 27322546

Citations 428

Authors

Mariano J Alvarez

Yao Shen

Federico M Giorgi

Alexander Lachmann

B Belinda Ding

B Hilda Ye

Andrea Califano

Affiliations

Soon will be listed here.

Abstract

Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given patient is crucial for developing personalized treatment plans. However, accurate inference of aberrant protein activity in biological samples is still challenging as genetic alterations are only partially predictive and direct measurements of protein activity are generally not feasible. To address this problem we introduce and experimentally validate a new algorithm, virtual inference of protein activity by enriched regulon analysis (VIPER), for accurate assessment of protein activity from gene expression data. We used VIPER to evaluate the functional relevance of genetic alterations in regulatory proteins across all samples in The Cancer Genome Atlas (TCGA). In addition to accurately infer aberrant protein activity induced by established mutations, we also identified a fraction of tumors with aberrant activity of druggable oncoproteins despite a lack of mutations, and vice versa. In vitro assays confirmed that VIPER-inferred protein activity outperformed mutational analysis in predicting sensitivity to targeted inhibitors.

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