ArticleNature genetics2016
Functional characterization of somatic mutations in cancer using network-based inference of protein activity.
Article in Nature genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 592 papers, 2 of them syntheses that pooled it.
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Who cites it
592 citing papers in PubMed, 2 syntheses or guidelines pooled it, 1,038 citations in OpenAlex.
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- A comprehensive transcriptional reference for severity and progression in spinal cord injury reveals novel translational biomarker genes.Journal of translational medicine · 2025Pooled it
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- Single-cell transcriptomics reveals transcriptional reprogramming and microenvironmental remodeling in ectopic ACTH/CRH-secreting pheochromocytomas.Journal of translational medicine · 2026Article
- Complex assembly and activity states as multifaceted protein attributes explaining phenotypic variability.Molecular systems biology · 2026Article
- KDM6A loss enhances oxidative phosphorylation uncovering tissue-level convergent evolution.The EMBO journal · 2026Article
- Epithelial to mesenchymal transition and M2 macrophages drive aggressiveness in murine and human sarcomatoid urothelial carcinoma.bioRxiv : the preprint server for biology · 2026Article
- Functional proteomic and phosphoproteomic profiling of routine FFPE CNS tumor tissue complements genomic and epigenomic characterization.Acta neuropathologica · 2026Article
- Combined BET bromodomain and DNA methyltransferase inhibition targets critical survival pathways in transdifferentiated prostate cancer.JCI insight · 2026Article
- Systems biology framework for the rational design of operational conditions for in vitro/in vivo translation of tissue models.Science advances · 2026Article
- Single-cell multi-omic profiling of heterogeneous PROCRiScience · 2026Article
- Conserved signaling pathways and transcriptional regulators drive ovarian aging across species.Poultry science · 2026Article
- RAISE quantifies RNA binding protein activity via transcriptomic profiling.Nature communications · 2026Article
- Integrated analysis of single-cell transcriptome identifies a glial-neurovascular signaling trajectory in brain repair after ischemia.Biology direct · 2026Article
- A transcription factor regulatory atlas for activity inference and perturbation prediction.Nucleic acids research · 2026Article
- Benchmarking methods for inferring single-cell transcription factor activity using large-scale perturbation sequencing data.Briefings in bioinformatics · 2026Article
- Developmental and MAPK-responsive transcription factors regulate distinct malignant cell states and associated genetic dependencies in pancreatic cancer.Nature genetics · 2026Article
- Pancreatic adenocarcinoma comprises six universally coexisting cell states.Nature genetics · 2026Article
532 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.