ArticleMolecular systems biology2013
Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers.
Article in Molecular systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 170 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
170 citing papers in PubMed, 2 syntheses or guidelines pooled it, 296 citations in OpenAlex.
- Uncovering Oncogenic Mechanisms of Tumor Suppressor Genes in Breast Cancer Multi-Omics Data.International journal of molecular sciences · 2022Pooled it
- Computational Identification of Novel Stage-Specific Biomarkers in Colorectal Cancer Progression.PloS one · 2016Pooled it
- Impaired TGF-β signaling via AHNAK family mutations elicits an esophageal cancer subtype with sensitivities to genotoxic therapy and immunotherapy.Cancer immunology, immunotherapy : CII · 2024Trial
- PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- PICDGI: A framework for predicting cancer driver genes through dynamic gene-gene interaction modeling of single-cell data.PLoS computational biology · 2026Article
- Discovery of Supra-Bivalent GSK3β Inhibitory Peptides Containing an ATP-Mimetic Amino Acid.Journal of the American Chemical Society · 2026Article
- Identification of cancer mini-drivers by deciphering selective landscape in the cancer genome.Briefings in bioinformatics · 2026Article
- A multimodal framework for comprehensive driver variant prediction in cancer.Communications medicine · 2025Article
- A structural machine learning approach for rapid prediction of thermodynamically destabilizing tyrosine phosphorylations.Cell reports methods · 2025Article
- DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterations.Nature methods · 2025Article
- A core driver gene set identified based on geMER reveals its potential driver mechanism in pan-cancer.NPJ precision oncology · 2025Article
- Cancer gene identification through integrating causal prompting large language model with omics data-driven causal inference.Briefings in bioinformatics · 2025Article
- Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review).International journal of molecular medicine · 2025Review
- Proteogenomic Approaches for Diseasome Studies.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Characterization of cancer-driving nucleotides (CDNs) across genes, cancer types, and patients.eLife · 2024Article
- Multimodal multiobjective optimization with structural network control principles to optimize personalized drug targets for drug discovery of individual patients.Briefings in bioinformatics · 2024Article
- Rapid prediction of thermodynamically destabilizing tyrosine phosphorylations in cancers.bioRxiv : the preprint server for biology · 2024Article
- Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model.Nature communications · 2024Article
- Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome.NAR cancer · 2024Article
- Harmony of Protein Tags and Chimeric Molecules Empowers Targeted Protein Ubiquitination and Beyond.Cells · 2024Review
110 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Large-scale cancer genome sequencing has uncovered thousands of gene mutations, but distinguishing tumor driver genes from functionally neutral passenger mutations is a major challenge. We analyzed 800 cancer genomes of eight types to find single-nucleotide variants (SNVs) that precisely target phosphorylation machinery, important in cancer development and drug targeting. Assuming that cancer-related biological systems involve unexpectedly frequent mutations, we used novel algorithms to identify genes with significant phosphorylation-associated SNVs (pSNVs), phospho-mutated pathways, kinase networks, drug targets, and clinically correlated signaling modules. We highlight increased survival of patients with TP53 pSNVs, hierarchically organized cancer kinase modules, a novel pSNV in EGFR, and an immune-related network of pSNVs that correlates with prolonged survival in ovarian cancer. Our findings include multiple actionable cancer gene candidates (FLNB, GRM1, POU2F1), protein complexes (HCF1, ASF1), and kinases (PRKCZ). This study demonstrates new ways of interpreting cancer genomes and presents new leads for cancer research.
Indexed as
Identifiers
What OpenQuestion holds
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.