Dataset Information

Targeted next-generation sequencing-based detection of microsatellite instability in colorectal carcinomas.

ABSTRACT: In the present study, we developed a computational method and panel markers to assess microsatellite instability (MSI) using a targeted next-generation sequencing (NGS) platform and compared the performance of our computational method, mSILICO, with that of mSINGS to detect MSI in CRCs. We evaluated 13 CRC cell lines, 84 fresh and 119 formalin-fixed CRC tissues (including 61 MSI-high CRCs and 155 microsatellite-stable CRCs) and tested the classification performance of the two methods on 23, 230, and 3,154 microsatellite markers. For the fresh tissue and cell line samples, mSILICO showed a sensitivity of 100% and a specificity of 100%, regardless of the number of panel markers, whereas for the formalin-fixed tissue samples, mSILICO exhibited a sensitivity of up to 100% and a specificity of up to 100% with three differently sized panels ranging from 23 to 3154. These results were similar to those of mSINGS. With the application of mSILICO, the small panel of 23 markers had a sensitivity of ?95% and a specificity of 100% in cell lines/fresh tissues and formalin-fixed tissues of CRC. In conclusion, we developed a new computational method and microsatellite marker panels for the determination of MSI that does not require paired normal tissues. A small panel could be integrated into the targeted NGS panel for the concurrent analysis of single nucleotide variations and MSI.

SUBMITTER: Lee Y

PROVIDER: S-EPMC7850495 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Targeted next-generation sequencing-based detection of microsatellite instability in colorectal carcinomas.

Lee Yunbeom Y Lee Ji Ae JA Park Hye Eun HE Han Hyojun H Kim Yuhnam Y Bae Jeong Mo JM Kim Jung Ho JH Cho Nam-Yun NY Kim Hwang-Phill HP Kim Tae-You TY Kang Gyeong Hoon GH

PloS one 20210201 2

In the present study, we developed a computational method and panel markers to assess microsatellite instability (MSI) using a targeted next-generation sequencing (NGS) platform and compared the performance of our computational method, mSILICO, with that of mSINGS to detect MSI in CRCs. We evaluated 13 CRC cell lines, 84 fresh and 119 formalin-fixed CRC tissues (including 61 MSI-high CRCs and 155 microsatellite-stable CRCs) and tested the classification performance of the two methods on 23, 230, ...[more]

PMID: 33524032

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Project description:BackgroundDNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue.MethodsScikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity.ResultsDeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910-0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823-0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types. Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital.

Project description:BackgroundMismatch repair (MMR)/microsatellite instability (MSI) and tumor mutational burden (TMB) are independent biomarkers that complement each other for predicting immune checkpoint inhibitors (ICIs) efficacy. Here we aim to establish a strategy that integrates MSI and TMB determination for colorectal cancer (CRC) in one single assay.MethodsSurgical or biopsy specimens retrospectively collected from CRC patients were subjected to NGS analysis. Immunohistochemistry (IHC) and polymerase chain reaction (PCR) were also used to determine MMR/MSI for those having enough tissues. The NGS-MSI method was validated against IHC and PCR. The MSI-high (MSI-H) or microsatellite stable (MSS) groups were further stratified based on tumor mutational burden, followed by validation using the The Cancer Genome Atlas (TCGA) CRC dataset. Immune microenvironment was evaluated for each subgroup be profiling the expression of immune signatures.ResultsTissues from 430 CRC patients were analyzed using a 381-gene NGS panel. Alterations in KRAS, NRAS, BRAF, and HER2 occurred at a significantly higher incidence among MSI-H tumors than in MSS patients (83.6% vs. 58.4%, p = 0.0003). A subset comprising 98 tumors were tested for MSI/MMR using all three techniques, where NGS proved to be 99.0 and 93.9% concordant with PCR and IHC, respectively. Four of the 7 IHC-PCR discordant cases had low TMB (1.1-8.1 muts/Mb) and were confirmed to have been misdiagnosed by IHC. Intriguingly, 4 of the 66 MSS tumors (as determined by NGS) were defined as TMB-high (TMB-H) using a cut-off of 29 mut/Mb. Likewise, 15 of the 456 MSS tumors in the TCGA CRC cohort were also TMB-H with a cut-off of 9 muts/Mb. Expression of immune signatures across subgroups (MSS-TMB-H, MSI-H-TMB-H, and MSS-TMB-L) confirmed that the microenvironment of the MSS-TMB-H tumors was similar to that of the MSI-H-TMB-H tumors, but significantly more immune-responsive than that of the MSS-TMB-L tumors, indicating that MSI combined with TMB may be more precise than MSI alone for immune microenvironment prediction.ConclusionThis study demonstrated that NGS panel-based method is both robust and tissue-efficient for comprehensive molecular diagnosis of CRC. It also underscores the importance of combining MSI and TMB information for discerning patients with different microenvironment.

Dataset Information

Targeted next-generation sequencing-based detection of microsatellite instability in colorectal carcinomas.

Publications

Targeted next-generation sequencing-based detection of microsatellite instability in colorectal carcinomas.

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