Dataset Information

Population bias in somatic measurement of microsatellite instability status.

ABSTRACT: Microsatellite instability (MSI) is a key secondary effect of a defective DNA mismatch repair mechanism resulting in incorrectly replicated microsatellites in many malignant tumors. Historically, MSI detection has been performed by fragment analysis (FA) on a panel of representative genomic markers. More recently, using next-generation sequencing (NGS) to analyze thousands of microsatellites has been shown to improve the robustness and sensitivity of MSI detection. However, NGS-based MSI tests can be prone to population biases if NGS results are aligned to a reference genome instead of patient-matched normal tissue. We observed an increased rate of false positives in patients of African ancestry with an NGS-based diagnostic for MSI status utilizing 7317 microsatellite loci. We then minimized this bias by training a modified calling model that utilized 2011 microsatellite loci. With these adjustments 100% (95% CI: 89.1% to 100%) of African ancestry patients in an independent validation test were called correctly using the updated model. This poses not only a significant technical improvement but also has an important clinical impact on directing immune checkpoint inhibitor therapy.

SUBMITTER: Saul M

PROVIDER: S-EPMC7476819 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Population bias in somatic measurement of microsatellite instability status.

Saul Michelle M Poorman Kelsey K Tae Hongseok H Vanderwalde Ari A Stafford Phillip P Spetzler David D Korn Wolfgang M WM Gatalica Zoran Z Swensen Jeff J

Cancer medicine 20200709 17

Microsatellite instability (MSI) is a key secondary effect of a defective DNA mismatch repair mechanism resulting in incorrectly replicated microsatellites in many malignant tumors. Historically, MSI detection has been performed by fragment analysis (FA) on a panel of representative genomic markers. More recently, using next-generation sequencing (NGS) to analyze thousands of microsatellites has been shown to improve the robustness and sensitivity of MSI detection. However, NGS-based MSI tests c ...[more]

PMID: 32644297

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Project description:Overexpression of TRIP13, a member of the AAA-ATPase family, is linked with various cancers, but its role in metastasis is unknown in colorectal cancer (CRC). In the current study, we investigated the role TRIP13 in experimental metastasis and its involvement in regulation of WNT/β-catenin and EGFR signaling pathways. Evaluation of formalin-fixed paraffin-embedded (FFPE) and frozen tissues of adenomas and CRCs, along with their corresponding normal samples, showed that TRIP13 was gradually increased in its phenotypic expression from adenoma to carcinoma and that its overexpression in CRCs was independent of patient's gender, age, race/ethnicity, pathologic stage, and p53 and microsatellite instability (MSI) status. Moreover, liver metastases of CRCs showed TRIP13 overexpression as compared to matched adjacent liver tissues, indicating the biological relevance of TRIP13 in CRC progression and metastasis. TRIP13 knockdown impeded colony formation, invasion, motility, and spheroid-forming capacity of CRC cells irrespective of their p53 and MSI status. Furthermore, xenograft studies demonstrated high expression of TRIP13 contributed to tumor growth and metastasis. Depletion of TRIP13 in CRC cells decreased metastasis and it was independent of the p53 and MSI status. Furthermore, TRIP13 interacted with a tyrosine kinase, FGFR4; this interaction could be essential for activation of the EGFR-AKT pathway. In addition, we demonstrated the involvement of TRIP13 in the Wnt signaling pathway and in the epithelial-mesenchymal transition. Cell-based assays revealed that miR-192 and PNPT1 regulate TRIP13 expression in CRC. Additionally, RNA sequencing of CRC cells with TRIP13 knockdown identified COL6A3, TREM2, SHC3, and KLK7 as downstream targets that may have functional relevance in TRIP13-mediated tumor growth and metastasis. In summary, our results demonstrated that TRIP13 promotes tumor growth and metastasis regardless of p53 and MSI status, and indicated that it is a target for therapy of CRC.

Project description:BACKGROUND:Clinical benefit from checkpoint inhibitors has been associated in a tumor-agnostic manner with two main tumor traits. The first is tumor antigenicity, which is typically measured by tumor mutation burden, microsatellite instability (MSI), or Mismatch Repair Deficiency using gene sequence platforms and/or immunohistochemistry. The second is the presence of a pre-existing adaptive immune response, typically measured by immunohistochemistry (e.g. single analyte PD-L1 expression) and/or gene expression signatures (e.g. tumor "inflamed" phenotype). These two traits have been shown to provide independent predictive information. Here we investigated the potential of using gene expression to predict tumor MSI, thus enabling the measurement of both tumor antigenicity and the level of tumor inflammation in a single assay, possibly reducing sample requirement, turn-around time, and overall cost. METHODS:Using The Cancer Genome Atlas RNA-seq datasets with the greatest MSI-H incidence, i.e. those from colon (n?=?208), stomach (n?=?269), and endometrial (n?=?241) cancers, we trained an algorithm to predict tumor MSI from under-expression of the mismatch repair genes MLH1, PMS2, MSH2, and MSH6 and from 10 additional genes with strong pan-cancer associations with tumor hypermutation. The algorithms were validated on the NanoString nCounter™ platform in independent cohorts of colorectal (n?=?52), endometrial (n?=?11), and neuroendocrine (n?=?4) tumors pre-characterized using the MMR immunohistochemistry assay. RESULTS:In the validation cohorts, the algorithm showed high prediction accuracy of tumor MSI status, with sensitivity of at least 88% attained at thresholds chosen to achieve 100% specificity. Furthermore, MSI status was compared to the Tumor Inflammation Signature (TIS), an analytically validated diagnostic assay which measures a suppressed adaptive immune response in the tumor and enriches for response to immune checkpoint blockade. TIS score was largely independent of MSI status, suggesting that measuring both parameters may identify more patients that would respond to immune checkpoint blockade than either assay alone. CONCLUSIONS:Development of a gene expression signature of MSI status raises the possibility of a combined diagnostic assay on a single platform which measures both tumor antigenicity and presence of a suppressed adaptive immune response. Such an assay would have significant advantages over multi-platform assays for both ease of use and turnaround time and could lead to a diagnostic test with improved clinical performance.

Dataset Information

Population bias in somatic measurement of microsatellite instability status.

Publications

Population bias in somatic measurement of microsatellite instability status.

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