ArticleFrontiers in oncology2022
Improved NGS-based detection of microsatellite instability using tumor-only data.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Histomolecular Features of a Rare Subtype of Pleomorphic Adenoma Characterised by Abundant Lymphoid Stroma and HMGA2 Rearrangements.Head and neck pathology · 2025Article
- Non-invasive colorectal cancer screening methods: focusing on diagnostic genetic and epigenetic markers.Cancer cell international · 2025Review
- Real-World Evaluation of Microsatellite Instability Detection via Targeted NGS Panels in Routine Molecular Diagnostics.International journal of molecular sciences · 2025Article
- NGS coverage accurately predictsFrontiers in oncology · 2025Article
- Comparative Analysis of Next-Generation Sequencing and Immunohistochemistry in MSI/MMR Testing.Turk patoloji dergisi · 2025Article
- A Panel-Based Mutational Signature of Mismatch Repair Deficiency is Associated With Durable Response to Pembrolizumab in Metastatic Castration-Resistant Prostate Cancer.Clinical genitourinary cancer · 2024Article
- A Bioinformatics Toolkit for Next-Generation Sequencing in Clinical Oncology.Current issues in molecular biology · 2023Review
- Mismatch repair deficiency testing in Lynch syndrome-associated urothelial tumors.Frontiers in oncology · 2023Article
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Authors and funding
20 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microsatellite instability (MSI) is a molecular signature of mismatch repair deficiency (dMMR), a predictive marker of immune checkpoint inhibitor therapy response. Despite its recognized pan-cancer value, most methods only support detection of this signature in colorectal cancer. In addition to the tissue-specific differences that impact the sensitivity of MSI detection in other tissues, the performance of most methods is also affected by patient ethnicity, tumor content, and other sample-specific properties. These limitations are particularly important when only tumor samples are available and restrict the performance and adoption of MSI testing. Here we introduce MSIdetect, a novel solution for NGS-based MSI detection. MSIdetect models the impact of indel burden and tumor content on read coverage at a set of homopolymer regions that we found are minimally impacted by sample-specific factors. We validated MSIdetect in 139 Formalin-Fixed Paraffin-Embedded (FFPE) clinical samples from colorectal and endometrial cancer as well as other more challenging tumor types, such as glioma or sebaceous adenoma or carcinoma. Based on analysis of these samples, MSIdetect displays 100% specificity and 96.3% sensitivity. Limit of detection analysis supports that MSIdetect is sensitive even in samples with relatively low tumor content and limited microsatellite instability. Finally, the results obtained using MSIdetect in tumor-only data correlate well (R=0.988) with what is obtained using tumor-normal matched pairs, demonstrating that the solution addresses the challenges posed by MSI detection from tumor-only data. The accuracy of MSI detection by MSIdetect in different cancer types coupled with the flexibility afforded by NGS-based testing will support the adoption of MSI testing in the clinical setting and increase the number of patients identified that are likely to benefit from immune checkpoint inhibitor therapy.
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