MICROSATELLITE INSTABILITY PROFILING WITH MSISENSOR2 IN WHOLE-EXOME SEQUENCING DATA FROM HEALTHY CONTROLS AND COLORECTAL CANCER PATIENTS
Main Article Content
Authors
A.
Aitkulova
Center for Life sciences, National Laboratory Astana, Nazarbayev University, 010000, Astana, Kazakhstan
N.
Tynyshtykbayeva
Center for Life sciences, National Laboratory Astana, Nazarbayev University, 010000, Astana, Kazakhstan
A.
Daniyarov
Center for Life sciences, National Laboratory Astana, Nazarbayev University, 010000, Astana, Kazakhstan
A.
Akilzhanova
Center for Life sciences, National Laboratory Astana, Nazarbayev University, 010000, Astana, Kazakhstan
D.
Sarbassov
Center for Life sciences, National Laboratory Astana, Nazarbayev University, 010000, Astana, Kazakhstan
Abstract
Microsatellite instability (MSI) is a molecular phenotype linked to defects in DNA mismatch repair (MMR) and serves as a biomarker in colorectal cancer (CRC). Computational MSI assessment using next-generation sequencing data enables characterisation of microsatellite instability without a dedicated MSI assay. This study evaluated MSIsensor2 scores in blood-derived whole-exome sequencing (WES) data from healthy individuals and two CRC patients.
Whole-exome sequencing (WES) data from peripheral blood samples of 235 healthy Kazakh individuals were obtained from the DNA Biobank of the Laboratory of Genomic and Personalised Medicine, National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan. Blood-derived WES data from two patients with CRC, designated BR110 and BR114, were also analysed. Sequencing libraries were prepared using Illumina workflows and sequenced on the NovaSeq 6000 platform. MSIsensor2 was employed to assess MSI scores and quantify the number of unstable microsatellite loci detected. Relationships among MSI scores, locus coverage, and sequencing data volume were examined descriptively.
Of the 235 healthy individuals, 205 samples (87.2%) had MSI scores below 10%, while 30 samples (12.8%) had scores between 10% and 40% per study-specific classification. No sample exceeded 40%. The CRC-associated blood samples BR110 and BR114 demonstrated MSI scores of 5.43% and 7.81%, respectively. BR110 exhibited 10 unstable microsatellite sites among 184 covered sites, whereas BR114 had 26 among 333 covered sites. The higher score in BR114 corresponded with increased sequencing coverage and a greater number of evaluable loci. These findings indicate variability in computational MSI measurements across blood-derived WES datasets but do not establish tumour MSI status.
MSIsensor2 produced MSI-associated measurements from blood-derived WES data in both healthy individuals and patients with CRC. However, MSI scores from blood sequencing do not necessarily reflect tumour status; therefore, determining the clinical relevance of these findings requires investigation using tumour-derived material, established MSI reference assays, and a larger clinical cohort.
Keywords
Microsatellite instability, MSIsensor2, whole-exome sequencing, colorectal cancer, mismatch repair
Article Details
References
Boland CR, Thibodeau SN, Hamilton SR, et al. A National Cancer Institute Workshop on Microsatellite Instability for Cancer Detection and Familial Predisposition: Development of International Criteria for the Determination of Microsatellite Instability in Colorectal Cancer. Cancer Research. 1998;58(22):5248–5257. PubMed.
Sepulveda AR, Hamilton SR, Allegra CJ, et al. Molecular biomarkers for the evaluation of colorectal cancer: guideline from the American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology. Journal of Clinical Oncology. 2017;35(13):1453–1486. Crossref.
André T, Shiu KK, Kim TW, et al. Pembrolizumab in microsatellite-instability-high advanced colorectal cancer. New England Journal of Medicine. 2020;383:2207–2218. Crossref.
Takamatsu M, et al. Clinical predominance of whole-exome sequencing to evaluate microsatellite instability status. Cancer Science. 2023;114(7):2848–2859. Crossref.
Jia P, Yang X, Guo L, et al. MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability. Genomics, Proteomics & Bioinformatics. 2020;18(1):65–72. Crossref.
Niu-lab. MSIsensor2: Microsatellite instability detection for tumour-only sequencing data [Internet]. GitHub. Available from: URL.
Johansen AF, Kassentoft CG, Knudsen M, et al. Validation of computational determination of microsatellite status using whole exome sequencing data from colorectal cancer patients. BMC Cancer. 2019;19:971. Crossref.
Kautto EA, Bonneville R, Miya J, et al. Performance Evaluation for Rapid Detection of Pan-Cancer Microsatellite Instability with MANTIS. Oncotarget. 2017;8(5):7452–7463. Crossref.
Hause RJ, Pritchard CC, Shendure J, Salipante SJ. Classification and Characterization of Microsatellite Instability Across 18 Cancer Types. Nature Medicine. 2016;22:1342–1350. Crossref.
Middha S, Zhang L, Nafa K, et al. Reliable Pan-Cancer Microsatellite Instability Assessment by Using Targeted Next-Generation Sequencing Data. JCO Precision Oncology. 2017;1:1–17. Crossref.
Bonneville R, Krook MA, Kautto EA, et al. Landscape of Microsatellite Instability Across 39 Cancer Types. JCO Precision Oncology. 2017;1:1–15. Crossref.
Salipante SJ, Scroggins SM, Hampel HL, Turner EH, Pritchard CC. Detection of Mismatch Repair Deficiency and Microsatellite Instability in Colorectal Adenocarcinoma by Targeted Next-Generation Sequencing. The Journal of Molecular Diagnostics. 2018;20(1):1–11. Crossref.
Le DT, Durham JN, Smith KN, et al. Mismatch Repair Deficiency Predicts Response of Solid Tumors to PD-1 Blockade. Science. 2017;357(6349):409–413. Crossref.
Kang SY, Kim DG, Ahn S, Ha SY, Jang KT, Kim KM. Comparative Analysis of Microsatellite Instability by Next-Generation Sequencing, MSI PCR and MMR Immunohistochemistry in 1942 Solid Cancers. Pathology – Research and Practice. 2022;233:153874. Crossref.