ArticleCell systems2019
CHASMplus Reveals the Scope of Somatic Missense Mutations Driving Human Cancers.
Article in Cell systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.
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
90 citing papers in PubMed, 133 citations in OpenAlex.
- Comprehensive Somatic Profiling of Gastroenteropancreatic Neuroendocrine Neoplasms.Endocrine oncology (Bristol, England) · 2026Article
- Identifying multigenic modules under selection in the tumor genome.Bioinformatics (Oxford, England) · 2026Article
- Comprehensive Bioinformatic Characterization of CD70, CD80, and TIGIT as Diagnostic, Prognostic, and Immune Biomarkers in Pan-Cancer.Current issues in molecular biology · 2026Article
- Convergent Evolution in Tumor Genomes Targets Functional Domains.bioRxiv : the preprint server for biology · 2026Article
- plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Article
- Gene duplication is associated with gene diversification and potential neofunctionalization in lung cancer evolution.Genome research · 2026Article
- An interpretable molecular framework for predicting cancer driver missense mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Mutations altering the DNA binding domains of the human RAD52 protein exert distinct effects on homologous recombination repair in Saccharomyces cerevisiae.G3 (Bethesda, Md.) · 2026Article
- Interpreting the functional impact of genetic variants: The need for context qualifiers.American journal of human genetics · 2026Review
- Classification of driver and passenger mutations in different cancer types using deep neural networks.Bioinformatics advances · 2026Article
- The Cancer Epitope Database and Analysis Resource (CEDAR): current capabilities and future directions.Frontiers in oncology · 2026Review
- Article
- Cancer mutations in RAD51 and its paralogues.PloS one · 2026Article
- A Co-essentiality Network of Cancer Driver Genes Better Prioritizes Anticancer Drugs.Genomics, proteomics & bioinformatics · 2025Article
- Passenger mutations link cellular origin and transcriptional identity in human lung adenocarcinomas.Nature genetics · 2025Article
- Integrative analysis of genomic and transcriptomic data informs precancer progression in the pancreas.bioRxiv : the preprint server for biology · 2025Article
- AI cancer driver mutation predictions are valid in real-world data.Nature communications · 2025Article
- Cancer histone mutations impact protein binding and DNA repair with possible links to genomic instability.Nucleic acids research · 2025Article
- Comprehensive Analysis of Human Colorectal Cancers Harboring Polymerase Epsilon Mutations.International journal of molecular sciences · 2025Article
30 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 sequencing studies of patient cohorts have statistically implicated many genes driving cancer growth and progression, and their identification has yielded substantial translational impact. However, a remaining challenge is to increase the resolution of driver prediction from the level of genes to mutations because mutation-level predictions are more closely aligned with the goal of precision cancer medicine. Here, we present CHASMplus, a computational method that is uniquely capable of identifying driver missense mutations, including those specific to a cancer type, as evidenced by significantly superior performance on diverse benchmarks. Applied to 8,657 tumor samples across 32 cancer types in The Cancer Genome Atlas (TCGA), CHASMplus identifies over 4,000 unique driver missense mutations in 240 genes, supporting a prominent role for rare driver mutations. We show which TCGA cancer types are likely to yield discovery of new driver missense mutations by additional sequencing, which has important implications for public policy.
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.