ArticleNPJ precision oncology2021
Panels and models for accurate prediction of tumor mutation burden in tumor samples.
Article in NPJ precision oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Large-Scale Meta-Analysis Reveals Positive Feedback between Macrophages and T Cells That Sensitizes Tumors to Immunotherapy.Cancer research · 2024Pooled it
- Immune checkpoint knockout screen reveals TIGIT-CD155 interaction as a significant modulator of adapter CAR-T cell function in acute myeloid leukemia.Oncoimmunology · 2026Article
- Take Five: harmonization in personalized cancer vaccines for cancer immunotherapy.Experimental & molecular medicine · 2026Review
- Article
- Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.Molecular diagnosis & therapy · 2026Review
- Single-cell mutational burden distributions in birth-death processes.PLoS computational biology · 2025Article
- Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies.Vaccines · 2024Article
- Review
- The current state of molecular profiling in gastrointestinal malignancies.Biology direct · 2022Review
- Molecular Mechanisms of Resistance to Immune Checkpoint Inhibitors in Melanoma Treatment: An Update.Biomedicines · 2021Review
- Panels and models for accurate prediction of tumor mutation burden in tumor samples.NPJ precision oncology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.
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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.