Functional characterization of somatic mutations in cancer using network-based inference of protein activity.
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.
Department of Systems Biology, Columbia University, New York, New York, USA.|DarwinHealth Inc., New York, New York, USA.
Mariano J
MJ
Alvarez
Department of Systems Biology, Columbia University, New York, New York, USA.|DarwinHealth Inc., New York, New York, USA.
Yao
Y
Shen
Department of Systems Biology, Columbia University, New York, New York, USA.
Federico M
FM
Giorgi
Department of Systems Biology, Columbia University, New York, New York, USA.
Alexander
A
Lachmann
Department of Cell Biology, Albert Einstein College of Medicine, New York, New York, USA.
B Belinda
BB
Ding
Department of Cell Biology, Albert Einstein College of Medicine, New York, New York, USA.
B Hilda
BH
Ye
Department of Systems Biology, Columbia University, New York, New York, USA.|Department of Biomedical Informatics, Columbia University, New York, New York, USA.|Department of Biochemistry &Molecular Biophysics, Columbia University, New York, New York, USA.|Institute for Cancer Genetics, Columbia University, New York, New York, USA.|Motor Neuron Center, Columbia University, New York, New York, USA.|Columbia Initiative in Stem Cells, Columbia University, New York, USA.
Andrea
A
Califano
D000465:Algorithms; D000970:Antineoplastic Agents / Q000494:pharmacology; D019295:Computational Biology / Q000379:methods*; D062313:Databases, Pharmaceutical; D030562:Databases, Protein; D015972:Gene Expression Regulation, Neoplastic / Q000187:drug effects; D053263:Gene Regulatory Networks; D006801:Humans; D009154:Mutation / Q000235:genetics*; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism*; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics* / Q000378:metabolism*; D060066:Protein Interaction Maps / Q000187:drug effects; D017434:Protein Structure, Tertiary
D000970:Antineoplastic Agents; D009363:Neoplasm Proteins