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Updated: Feb 23, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Analysis of somatic microsatellite indels identifies driver events in human tumors
Yosef E Maruvka1,2, Kent W Mouw3,4, Rosa Karlic5
1Massachusetts General Hospital Center for Cancer Research, Charlestown, Massachusetts, USA.
Abstract:
Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).
Insights
New tools accurately detect microsatellite (MS) indel mutations in cancer, revealing over 1,000 new mutations in cancer genes. These findings aid in distinguishing tumor types and identifying novel cancer drivers.
Area of Science:
- Genomics and Cancer Research
- Bioinformatics and Computational Biology
Background:
- Microsatellites (MSs) are repetitive DNA sequences prone to insertions/deletions (indels).
- Somatic MS indels' role in cancer is understudied due to detection challenges in short-read sequencing data.
Purpose of the Study:
- To develop accurate tools for detecting somatic MS indels in cancer.
- To identify genes with significantly frequent MS indels.
- To explore the utility of MS indels in tumor classification and driver identification.
Main Methods:
- Development of MSMuTect for somatic MS indel detection.
- Development of MSMutSig for identifying cancer genes with frequent MS indels.
- Application of MSMuTect to whole-exome sequencing data from 6,747 human tumors across 20 types.
Main Results:
- Identification of over 1,000 previously undescribed MS indels in cancer genes.
- Demonstration that MS indel patterns can distinguish microsatellite-stable from microsatellite-unstable tumors.
- Discovery of seven MS indel driver hotspots, including novel cancer drivers (ESRP1, PRDM2, DOCK3).
Conclusions:
- The developed tools enable accurate detection and analysis of somatic MS indels in cancer.
- MS indel analysis can improve tumor classification and identify novel cancer drivers.
- Somatic MS indels represent a significant, previously underappreciated factor in cancer development.
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