Downregulation of the Unfolded Protein Response Links Metformin Treatment to Good Clinical Outcomes in Colorectal Cancer Patients
Bibliographic record
Abstract
Type 2 diabetes is a risk factor for colorectal cancer (CRC) development and progression. However, metformin-treated diabetic CRC patients tend to have better clinical outcomes than those managed by other means. To better characterize the molecular underpinnings of metformin’s protective effects, we performed a targeted transcriptomic analysis of primary CRC tissue samples (n = 272). A supervised learning algorithm pinpointed molecular features that discriminate between metformin-treated and diet-controlled diabetic CRC samples, as well as those that discriminated between non-diabetic samples based on their five-year overall survival status. Our results show downregulation of TMEM132 in metformin-treated samples (p = 0.05) and non-diabetics with good clinical outcomes (p = 0.05) relative to diet-controlled and non-diabetics with poor survival, respectively. Furthermore, upregulation of SCNN1A is observed in metformin-treated samples (p = 0.04) and non-diabetics with good clinical outcomes (p = 0.01) relative to diet-controlled samples and those with poor clinical outcomes, respectively. We also show that the antiapoptotic protein sFas is downregulated in metformin-treated samples relative to diet-controlled samples (p = 0.005). These findings suggest a role for the unfolded protein response in mediating metformin-related CRC-protective effects by enhancing apoptosis and suggest the investigation of these proteins as targets for novel CRC therapies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".