High GLP1R gene copy numbers associated with microsatellite instability for multiple cancers and with better survival probabilities for glioblastoma

While the Warburg effect is well-known and frequently studied, the molecular features that facilitate increased tumor cell glycolytic activity have yet to be extensively investigated. We hypothesized that amplification of genes encoding proteins related to glucose metabolism could be a mechanism to facilitate increased glycolysis. Thus, we applied a precision-guided copy number variation analysis approach to the GLP1R, AMFR, GCG, GPI, and ACTA1 genes across three different cancer types. Results indicated that higher CNs of GLP1R in glioblastoma were associated with better patient outcomes, while high CNs of GPI in lower-grade gliomas were associated with worse outcomes. Results also indicated that high microsatellite instability directly correlated with high CNs for most of the above indicated genes. These approaches to assessing tumor metabolism-related genes may lead to more accurate measures of patient risk and potential additional treatment options.

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Publication Details

Journal
Cell Cycle
Published
2024-10-17
DOI
https://doi.org/10.1080/15384101.2025.2485873
Citations
1
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.28
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article

High GLP1R gene copy numbers associated with microsatellite instability for multiple cancers and with better survival probabilities for glioblastoma

Rahul Jain, George Blanck, Mallika Varkhedi, Vayda R. Barker et al.
1 citations
Cell Cycle
Pancreatic and Hepatic Oncology Research
0.28
article

High GLP1R gene copy numbers associated with microsatellite instability for multiple cancers and with better survival probabilities for glioblastoma

Rahul Jain, George Blanck, Mallika Varkhedi, Vayda R. Barker, Tim Thomas, Michael T. Aboujaoude
article en
1 citations

Abstract

While the Warburg effect is well-known and frequently studied, the molecular features that facilitate increased tumor cell glycolytic activity have yet to be extensively investigated. We hypothesized that amplification of genes encoding proteins related to glucose metabolism could be a mechanism to facilitate increased glycolysis. Thus, we applied a precision-guided copy number variation analysis approach to the GLP1R, AMFR, GCG, GPI, and ACTA1 genes across three different cancer types. Results indicated that higher CNs of GLP1R in glioblastoma were associated with better patient outcomes, while high CNs of GPI in lower-grade gliomas were associated with worse outcomes. Results also indicated that high microsatellite instability directly correlated with high CNs for most of the above indicated genes. These approaches to assessing tumor metabolism-related genes may lead to more accurate measures of patient risk and potential additional treatment options.

Cell CycleVol. 23(17-20)
University of South Florida (US), Moffitt Cancer Center (US)
Openalex Percentile: Top 32%
Pancreatic and Hepatic Oncology Research
0.28
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