Caspase-4 Has Potential Utility as a Colorectal Tissue Biomarker for Dysplasia and Early-Stage Cancer
Bibliographic record
Abstract
Background and Aims: Colorectal cancer (CRC) is the second most deadly cancer globally. The rapidly rising incidence rate of CRC, coupled with increased diagnoses in individuals <50 years, indicates that early detection of CRC, and those at an increased risk of CRC development, is paramount to improve the survival rates of these patients. Here, we profile caspase-4 expression across 2 distinct CRC development pathways, sporadic CRC (sCRC) and inflammatory bowel disease-associated CRC (IBD-CRC), to examine its utility as a novel biomarker for CRC risk and diagnosis. Methods: Tissue samples from patients with CRC, colonic polyps, IBD-CRC, and sCRC were assessed by immunohistochemistry for caspase-4 expression in epithelial and stromal compartments. RNAseq expression data for caspase-4 in CRC and normal tissue samples were mined from online databases. Results: Epithelial caspase-4 expression is selectively elevated in CRC tumor tissue compared to adjacent normal tissue, where it is not expressed. In the sCRC pathway, caspase-4 is expressed in the epithelial and stromal tissue of all histological subtypes of colonic polyps, with a significant increase in epithelial expression from low-grade dysplasia to high-grade dysplasia progression. For the IBD-CRC pathway, caspase-4 epithelial expression was specifically upregulated in dysplastic and neoplastic tissue of IBD-CRC but was not expressed in normal or inflamed tissue. Conclusion: This study demonstrates that epithelial caspase-4 is selectively expressed in colon tissue during the development of dysplasia. As such, epithelial caspase-4 represents a promising novel tissue biomarker for CRC risk and diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".