Clinical significance of glycogen synthase kinase 3 (GSK-3) expression and tumor budding grade in colorectal cancer: Implications for targeted therapy
Bibliographic record
Abstract
Glycogen synthase kinase 3 (GSK-3) has been proposed as a novel cancer target due to its regulating role in both tumor and immune cells. However, the connection between GSK-3 and immunoevasive contexture, including tumor budding (TB) has not been previously examined. Methods: we investigated the expression levels of total GSK-3 as well as its isoforms (GSK-3β and GSK-3α) and examined their potential correlation with TB grade and the programmed cell death-ligand 1 (PD-L1) in colorectal cancer (CRC) tumor samples. Additionally, we compared the efficacy of GSK-3-inhibition with PD-1/PD-L1 blockade in humanized patient-derived (PDXs) xenografts models of high-grade TB CRC. we show that high-grade (BD3) TB CRC is associated with elevated expression levels of total GSK-3, specifically the GSK-3β isoform, along with increased expression of PD-L1 in tumor cells. Moreover, we define an improved risk stratification of CRC patients based on the presence of GSK-3+/PD-L1+/BD3 tumors, which are associated with a worse prognosis. Significantly, in contrast to the PD-L1/PD-1 blockade approach, the inhibition GSK-3 demonstrated a remarkable enhancement in the antitumor response. This was achieved through the reduction of tumor buds via necrosis and apoptosis pathways, along with a notable increase of activated tumor-infiltrating CD8+ T cells, NK cells, and CD4- CD8- T cells. our study provides compelling evidence for the clinical significance of GSK-3 expression and TB grade in risk stratification of CRC patients. Moreover, our findings strongly support GSK-3 inhibition as an effective therapy specifically targeting high-grade TB in CRC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".