ArticleNature medicine2022
Systematic pan-cancer analysis of mutation-treatment interactions using large real-world clinicogenomics data.
Article in Nature medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- Leveraging tumor dynamics to discover mutations influencing progression and treatment response for precision oncology.Genome medicine · 2026Article
- Network resilience of the human interactome to pan-cancer mutations reveals conserved pathway vulnerabilities.iScience · 2026Article
- Prognostic pan-cancer and single-cancer models: A large-scale analysis using a real-world clinico-genomic database.PloS one · 2026Article
- Learning Patient Similarity from Genomics for Precision Oncology.medRxiv : the preprint server for health sciences · 2025Article
- Collaborative AI for precision neurorehabilitation: a roadmap.Journal of neuroengineering and rehabilitation · 2025Review
- Mutations in tumor signaling, metastases, and synthetic lethality establish distinct patterns.PLoS computational biology · 2025Article
- Pan-cancer analysis shapes the understanding of cancer biology and medicine.Cancer communications (London, England) · 2025Review
- Precision treatment in breast cancer: Leveraging genetic interactions.Clinical and translational medicine · 2025Article
- DiffInvex identifies evolutionary shifts in driver gene repertoires during tumorigenesis and chemotherapy.Nature communications · 2025Article
- A multi-task domain-adapted model to predict chemotherapy response from mutations in recurrently altered cancer genes.iScience · 2025Article
- Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence.Nature cancer · 2025Article
- Article
- Characterizing mutation-treatment effects using clinico-genomics data of 78,287 patients with 20 types of cancers.Nature communications · 2024Article
- Article
- Automated Electronic Health Record Data Extraction and Curation Using ExtractEHR.JCO clinical cancer informatics · 2024Article
- Pan-cancer analysis of the immunological and oncogenic roles of ATAD2 with verification in papillary thyroid carcinoma.Scientific reports · 2024Article
- Real-world experience with circulating tumor DNA in cerebrospinal fluid from patients with central nervous system tumors.Acta neuropathologica communications · 2024Article
- Article
- Co-occurring Mutations in Different Genes Can Fuel Oncogenic Signaling and Serve as Metastatic Tumor Markers.bioRxiv : the preprint server for biology · 2024Article
- From algorithms to action: improving patient care requires causality.BMC medical informatics and decision making · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying the effectiveness of different cancer therapies in patients with specific tumor mutations is critical for improving patient outcomes and advancing precision medicine. Here we perform a large-scale computational analysis of 40,903 US patients with cancer who have detailed mutation profiles, treatment sequences and outcomes derived from electronic health records. We systematically identify 458 mutations that predict the survival of patients on specific immunotherapies, chemotherapy agents or targeted therapies across eight common cancer types. We further characterize mutation-mutation interactions that impact the outcomes of targeted therapies. This work demonstrates how computational analysis of large real-world data generates insights, hypotheses and resources to enable precision oncology.
Indexed as
Identifiers
35773542What 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.