ArticleNPJ genomic medicine2018
Mutation load estimation model as a predictor of the response to cancer immunotherapy.
Article in NPJ genomic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrated genomic analysis identifies a genetic mutation model predicting response to immune checkpoint inhibitors in melanoma.Cancer medicine · 2020Pooled it
- Tumor mutation burden and circulating tumor DNA in combined CTLA-4 and PD-1 antibody therapy in metastatic melanoma - results of a prospective biomarker study.Journal for immunotherapy of cancer · 2019Trial
- Trial
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- Exploring a mutation-based signature to predict the benefits of immune checkpoint inhibitors in oncogene-addicted subsets of non-small cell lung cancer: a retrospective study.Respiratory research · 2025Article
- Calcium ion-binding genes can predict tumor mutation burden and immune checkpoint blockade response in a pan-cancer model.Discover oncology · 2025Article
- Comprehensive analysis of the immunological implication and prognostic value of MEAK7 in non-small cell lung cancer.Translational cancer research · 2025Article
- Molecular principles underlying aggressive cancers.Signal transduction and targeted therapy · 2025Review
- Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer.Biology direct · 2024Article
- Article
- TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapy.Briefings in bioinformatics · 2024Article
- Checkpoint Inhibitors in Acute Myeloid Leukemia.Biomedicines · 2023Review
- Surveillance of cfDNA Hot Spot Mutations in NSCLC Patients during Disease Progression.International journal of molecular sciences · 2023Article
- Synthetic enforcement of STING signaling in cancer cells appropriates the immune microenvironment for checkpoint inhibitor therapy.Science advances · 2023Article
- Review
- Data-driven design of targeted gene panels for estimating immunotherapy biomarkers.Communications biology · 2022Article
- Multi-Level Analysis and Identification of Tumor Mutational Burden Genes across Cancer Types.Genes · 2022Article
- Prediction of biomarkers and therapeutic combinations for anti-PD-1 immunotherapy using the global gene network association.Nature communications · 2022Article
- Main Strategies for the Identification of Neoantigens.Cancers · 2020Review
- Novel immune subtypes of lung adenocarcinoma identified through bioinformatic analysis.FEBS open bio · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The determination of the mutation load, a total number of nonsynonymous point mutations, by whole-exome sequencing was shown to be useful in predicting the treatment responses to cancer immunotherapy. However, this technique is expensive and time-consuming, which hampers its application in clinical practice. Therefore, the objective of this study was to construct a mutation load estimation model for lung adenocarcinoma, using a small set of genes, as a predictor of the immunotherapy treatment response. Using the somatic mutation data downloaded from The Cancer Genome Atlas (TCGA) database, a computational framework was developed. The estimation model consisted of only 24 genes, used to estimate the mutation load in the independent validation cohort precisely (
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Registered trials
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