ArticleNature biotechnology2021
Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses.
Article in Nature biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 37 citations in OpenAlex.
- PrePPI - Structure-based Prediction of Protein-protein Interactomes and Networks.Journal of molecular biology · 2026Article
- Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks.Nature communications · 2026Article
- Pan-cancer inference and validation of hypermorphic, hypomorphic and neomorphic mutations.Nature genetics · 2026Article
- Network Analysis to Identify MicroRNAs Involved in Alzheimer's Disease and to Improve Drug Prioritization.Biomedicines · 2026Article
- MPAC: a computational framework for inferring pathway activities from multi-omic data.Bioinformatics (Oxford, England) · 2025Article
- TDP-43/ALKBH5-mediated mMedComm · 2025Article
- Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.Nature communications · 2024Article
- Pancancer network analysis reveals key master regulators for cancer invasiveness.Journal of translational medicine · 2023Article
- PrePPI: A Structure Informed Proteome-wide Database of Protein-Protein Interactions.Journal of molecular biology · 2023Article
- UHRF1 is a mediator of KRAS driven oncogenesis in lung adenocarcinoma.Nature communications · 2023Article
- The application of patient-derived organoid in the research of lung cancer.Cellular oncology (Dordrecht, Netherlands) · 2023Review
- Identifying prognostic subgroups of luminal-A breast cancer using deep autoencoders and gene expressions.PLoS computational biology · 2023Article
- Article
- Artificial intelligence, molecular subtyping, biomarkers, and precision oncology.Emerging topics in life sciences · 2021Review
- MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY.Current opinion in systems biology · 2021Article
- Network-based identification of key master regulators associated with an immune-silent cancer phenotype.Briefings in bioinformatics · 2021Article
- Article
- Mechanism-Centric Approaches for Biomarker Detection and Precision Therapeutics in Cancer.Frontiers in genetics · 2021Review
- Integrating 3D structural information into systems biology.The Journal of biological chemistryReview
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
Abstract
Tumor-specific elucidation of physical and functional oncoprotein interactions could improve tumorigenic mechanism characterization and therapeutic response prediction. Current interaction models and pathways, however, lack context specificity and are not oncoprotein specific. We introduce SigMaps as context-specific networks, comprising modulators, effectors and cognate binding-partners of a specific oncoprotein. SigMaps are reconstructed de novo by integrating diverse evidence sources-including protein structure, gene expression and mutational profiles-via the OncoSig machine learning framework. We first generated a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins that were experimentally validated in three-dimensional spheroid models and established uncharacterized crosstalk with RAB/RHO. To show that OncoSig is generalizable, we first inferred SigMaps for the ten most mutated human oncoproteins and then for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census. Taken together, these SigMaps show that the cell's regulatory and signaling architecture is highly tissue specific.
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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.