A novel approach for characterizing microsatellite instability in cancer cells

• Published in: PloS one 2013-05, Vol.8 (5), p.e63056
• Main Authors: Lu, Yuheng, Soong, T David, Elemento, Olivier
• Format: Article
• Language: English
• Subjects: Analysis; Biology; Biophysics; Biotechnology; Breast cancer; Cancer; Cancer cells; Cancer genetics; Colonic Neoplasms - diagnosis; Colonic Neoplasms - genetics; Colonic Neoplasms - metabolism; Colorectal cancer; Contraction; Datasets; Deoxyribonucleic acid; DNA; DNA Mismatch Repair; DNA repair; Gene expression; Genes; Genetic Markers; Genetic recombination; Genomes; Genomics; HCT116 Cells; Health aspects; High-Throughput Nucleotide Sequencing; Humans; INDEL Mutation; Medical diagnosis; Medical research; Medicine; Microsatellite Instability; Microsatellites; Mismatch repair; Molecular Diagnostic Techniques; Mutation; Physiology; Prostate cancer; Reliability; Repair; Sequence Analysis, DNA; Stability; Studies; Transcriptome; Tumor cell lines; Tumors
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0063056

Microsatellite instability (MSI) is characterized by the expansion or contraction of DNA repeat tracts as a consequence of DNA mismatch repair deficiency (MMRD). Accurate detection of MSI in cancer cells is important since MSI is associated with several cancer subtypes and can help inform therapeutic decisions. Although experimental assays have been developed to detect MSI, they typically depend on a small number of known microsatellite loci or mismatch repair genes and have limited reliability. Here, we report a novel genome-wide approach for MSI detection based on the global detection of insertions and deletions (indels) in microsatellites found in expressed genes. Our large-scale analyses of 20 cancer cell lines and 123 normal individuals revealed striking indel features associated with MSI: there is a significant increase of short microsatellite deletions in MSI samples compared to microsatellite stable (MSS) ones, suggesting a mechanistic bias of repair efficiency between insertions and deletions in normal human cells. By incorporating this observation into our MSI scoring metric, we show that our approach can correctly distinguish between MSI and MSS cancer cell lines. Moreover, when we applied this approach to primal tumor samples, our metric is also well consistent with diagnosed MSI status. Thus, our study offers new insight into DNA mismatch repair system, and also provides a novel MSI diagnosis method for clinical oncology with better reliability.