Dataset Information

Mosaic analysis and tumor induction in zebrafish by microsatellite instability-mediated stochastic gene expression.

ABSTRACT: Mosaic analysis, in which two or more populations of cells with differing genotypes are studied in a single animal, is a powerful approach to study developmental mechanisms and gene function in vivo. Over recent years, several genetic methods have been developed to achieve mosaicism in zebrafish, but despite their advances, limitations remain and different approaches and further refinements are warranted. Here, we describe an alternative approach for creating somatic mosaicism in zebrafish that relies on the instability of microsatellite sequences during replication. We placed the coding sequences of various marker proteins downstream of a microsatellite and out-of-frame; in vivo frameshifting into the proper reading frame results in expression of the protein in random individual cells that are surrounded by wild-type cells. We optimized this approach for the binary Gal4-UAS expression system by generating a driver line and effector lines that stochastically express Gal4-VP16 or UAS:H2A-EGFP and self-maintaining UAS:H2A-EGFP-Kaloop, respectively. To demonstrate the utility of this system, we stochastically expressed a constitutively active form of the human oncogene H-RAS and show the occurrence of hyperpigmentation and sporadic tumors within 5 days. Our data demonstrate that inducing somatic mosaicism through microsatellite instability can be a valuable approach for mosaic analysis and tumor induction in Danio rerio.

SUBMITTER: Koole W

PROVIDER: S-EPMC4073281 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Mosaic analysis and tumor induction in zebrafish by microsatellite instability-mediated stochastic gene expression.

Koole Wouter W Tijsterman Marcel M

Disease models & mechanisms 20140130 7

Mosaic analysis, in which two or more populations of cells with differing genotypes are studied in a single animal, is a powerful approach to study developmental mechanisms and gene function in vivo. Over recent years, several genetic methods have been developed to achieve mosaicism in zebrafish, but despite their advances, limitations remain and different approaches and further refinements are warranted. Here, we describe an alternative approach for creating somatic mosaicism in zebrafish that ...[more]

PMID: 24487406

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Project description:BackgroundClinical 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.MethodsUsing 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.ResultsIn 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.ConclusionsDevelopment 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

Mosaic analysis and tumor induction in zebrafish by microsatellite instability-mediated stochastic gene expression.

Publications

Mosaic analysis and tumor induction in zebrafish by microsatellite instability-mediated stochastic gene expression.

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