ArticleNature communications2025
A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Molecular and Clinical Determinants of Targeted Therapy Treatment in Biliary Tract Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Machine Learning Algorithm for the Detection of Tumor Microsatellite Instability Based on Multiomics Biomarkers.JCO clinical cancer informatics · 2026Article
- Article
- Analysis of microsatellite instability intensity in single-cell resolution with scMnT reveals tumor heterogeneity in colorectal cancer.Briefings in bioinformatics · 2026Article
- Convergence of machine learning and genomics for precision oncology.Nature reviews. Cancer · 2026Review
- Reference-Free Microsatellite Instability Detection from Tumor Sequencing Using Intrasample Variability Modeling.Computational and structural biotechnology journal · 2026Article
- A Deep Learning-Based Approach for Explainable Microsatellite Instability Detection in Gastrointestinal Malignancies.Journal of imaging · 2025Article
- Prospective characterization of germline variants in patients with gliomas and glioneuronal tumors.Acta neuropathologica · 2025Article
- Lynch Syndrome and Somatic Mismatch Repair Variants in Pancreas Cancer.JAMA oncology · 2024Article
- Genome-wide loss of heterozygosity predicts aggressive, treatment-refractory behavior in pituitary neuroendocrine tumors.Acta neuropathologica · 2024Article
- Microsatellite Instability and Mismatch Repair Deficiency Define a Distinct Subset of Lung Cancers Characterized by Smoking Exposure, High Tumor Mutational Burden, and Recurrent Somatic MLH1 Inactivation.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2024Article
- Neoplasia risk in patients with Lynch syndrome treated with immune checkpoint blockade.Nature medicine · 2023Article
- Prevalence and Clinical Implications of Mismatch Repair-Proficient Colorectal Cancer in Patients With Lynch Syndrome.JCO precision oncology · 2023Article
- Clinical Importance of Clonal Hematopoiesis in Metastatic Gastrointestinal Tract Cancers.JAMA network open · 2023Article
- Comprehensive Molecular Characterization of Gallbladder Carcinoma and Potential Targets for Intervention.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Concurrent GermlineJCO precision oncology · 2022Article
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Authors and funding
18 authors.
Funding
Abstract
Microsatellite instability (MSI) is a critical phenotype of cancer genomes and an FDA-recognized biomarker that can guide treatment with immune checkpoint inhibitors. Previous work has demonstrated that next-generation sequencing data can be used to identify samples with MSI-high phenotype. However, low tumor purity, as frequently observed in routine clinical samples, poses a challenge to the sensitivity of existing algorithms. To overcome this critical issue, we developed MiMSI, an MSI classifier based on deep neural networks and trained using a dataset that included low tumor purity MSI cases in a multiple instance learning framework. On a challenging yet representative set of cases, MiMSI showed higher sensitivity (0.895) and auROC (0.971) than MSISensor (sensitivity: 0.67; auROC: 0.907), an open-source software previously validated for clinical use at our institution using MSK-IMPACT large panel targeted NGS data. In a separate, prospective cohort, MiMSI confirmed that it outperforms MSISensor in low purity cases (P = 8.244e-07).
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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.