ArticleScientific reports2023
A large-scale functional analysis of genes expressed differentially in insulin secreting MIN6 sublines with high versus mildly reduced glucose-responsiveness.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- DOCK10 Regulates Insulin Hypersecretion in Insulinoma and Serves as a Diagnostic and Therapeutic Target.Cellular and molecular gastroenterology and hepatology · 2026Article
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8 authors at 1 institution in 1 country.
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Abstract
Molecular mechanisms of glucose-stimulated insulin secretion (GSIS) from pancreatic β-cells are not fully understood. GSIS deteriorations are believed to underlie the pathogenesis of type 2 diabetes mellitus. By comparing transcript levels of 3 insulin secreting MIN6 cell sublines with strong glucose-responsiveness and 3 with mildly reduced responsiveness, we identified 630 differentially expressed genes. Using our recently developed system based on recombinase-mediated cassette exchange, we conducted large-scale generation of stable clones overexpressing such genes in the doxycycline-regulated manner. We found that overexpressions of 18, out of 83, genes altered GSIS. Sox11 ((sex determining region Y)-box 11) was selected to confirm its roles in regulating insulin secretion, and the gene was subjected to shRNA-mediated suppression. While Sox11 overexpression decreased GSIS, its suppression increased GSIS, confirming the role of Sox11 as a negative regulator of insulin secretion. Furthermore, metabolic experiments using radiolabelled glucose showed Sox11 to participate in regulating glucose metabolism. Our data suggested that overexpression screening is a feasible option for systemic functional testing to identify important genes in GSIS.
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