Functional characterization of somatic mutations in cancer using network-based inference of protein activity

Mariano J. Alvarez, Yao Shen, Federico M. Giorgi, Alexander Lachmann, B. Belinda Ding, B. Hilda Ye, Andrea Califano

Research output: Contribution to journalArticle

108 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)838-847
Number of pages10
JournalNature Genetics
Volume48
Issue number8
DOIs
StatePublished - Aug 1 2016

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Mutation
Neoplasms
Proteins
Oncogene Proteins
Regulon
Atlases
Carcinogenesis
Genome
Gene Expression
Therapeutics

ASJC Scopus subject areas

  • Genetics

Cite this

Alvarez, M. J., Shen, Y., Giorgi, F. M., Lachmann, A., Ding, B. B., Ye, B. H., & Califano, A. (2016). Functional characterization of somatic mutations in cancer using network-based inference of protein activity. Nature Genetics, 48(8), 838-847. https://doi.org/10.1038/ng.3593

Functional characterization of somatic mutations in cancer using network-based inference of protein activity. / Alvarez, Mariano J.; Shen, Yao; Giorgi, Federico M.; Lachmann, Alexander; Ding, B. Belinda; Ye, B. Hilda; Califano, Andrea.

In: Nature Genetics, Vol. 48, No. 8, 01.08.2016, p. 838-847.

Research output: Contribution to journalArticle

Alvarez, MJ, Shen, Y, Giorgi, FM, Lachmann, A, Ding, BB, Ye, BH & Califano, A 2016, 'Functional characterization of somatic mutations in cancer using network-based inference of protein activity', Nature Genetics, vol. 48, no. 8, pp. 838-847. https://doi.org/10.1038/ng.3593
Alvarez, Mariano J. ; Shen, Yao ; Giorgi, Federico M. ; Lachmann, Alexander ; Ding, B. Belinda ; Ye, B. Hilda ; Califano, Andrea. / Functional characterization of somatic mutations in cancer using network-based inference of protein activity. In: Nature Genetics. 2016 ; Vol. 48, No. 8. pp. 838-847.
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