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Abstract C028: GSK3β: a therapeutic target in KRAS mutant pancreatic cancers

2025· article· en· W4417207512 on OpenAlexaboutno aff
Muhammad Ayaz, Mohd Jamal Dar

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsnot available
Fundersnot available
KeywordsKRASPancreatic cancerSignal transductionKinaseCell growthCancerApoptosisPI3K/AKT/mTOR pathway

Abstract

fetched live from OpenAlex

Abstract Glycogen synthase kinase-3beta (GSK3β) is a multifunctional serine/threonine kinase seen at the convergence of several signaling cascades. GSK3β plays a central role in PI3K signaling and Wnt/beta-catenin signaling pathways, which are the key regulators of important biological functions like cell growth, survival, metabolism, epithelial–mesenchymal transition (EMT), cell proliferation and differentiation at various stages of embryonic and adult development. Accordingly, dysregulation of GSK3β has been linked to pathogenesis of cancer, diabetes, and several neurodegenerative disorders. Therefore, pharmacological interventions to inhibit GSK3β activity is an important therapeutic strategy to counter these abnormalities. Previously, we identified a highly selective, with a better pharmacokinetic profile pyrimidinylazaindole based small molecule inhibitor of GSK3β that showed potent growth inhibition in cell based and xenograft models of KRas mutant pancreatic cancers. Pertinently, this small molecule inhibitor was seen to induce apoptosis in a β-catenin and c-Myc dependent manner. Moreover, GSK3β inhibition decreased the nuclear activity of the NF-kB p65 in KRas mutated MiaPaCa-2 cells thereby impeding the cell survival and anti-apoptotic processes in these cells as well as in the xenograft model of pancreatic cancer. Since EMT driven chemoresistance remains one of the important factors involved in pancreatic cancer progression. Overcoming drug resistance in pancreatic cancer patients poses a prominent challenge, predominantly in cancers driven by K-RAS mutation. Here in this study, we have shown that small molecule inhibitor imapacts the EMT progresson in KRAS mutant pancreatic caners through mediating significant decreases in EMT markers like N Cadherins, and slug. No detectable levels of E-cadherin were seen, however, vimentin, ZEB and snail remained unchanged. While the recently FDA approved GSK3β inhibitor, elraglusib, inhibits both alpha and beta isoforms equally and shows relatively higher half maximal inhibitory concentration however, small mole identified in our study would prove a clinically-relevant choice for its higher potency, bioavailability, pharmacokinetic and drug like properties however further analysis. This study opens up new avenues for therapeutic treatment of mutant KRas-dependent human cancers through pharmacological inhibition of GSK3β. Citation Format: MIR OWAIS AYAZ, MOHD JAMAL DAR JAMAL. DAR. GSK3β: a therapeutic target in KRAS mutant pancreatic cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr C028.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.117
GPT teacher head0.488
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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