A novel cuproptosis-related gene prognostic signature in colon adenocarcinoma
Bibliographic record
Abstract
Cuproptosis is the latest cell death type caused by enhanced mitochondrial-dependent energy metabolism. This study plans to establish a survival prognosis model for colon adenocarcinoma (COAD) patients based on cuproptosis-related genes (CRGs). We investigated the genetic alterations of CRGs in COAD based on The Cancer Genome Atlas database and validated in the GSE41328 dataset. Our results showed that LIPT1, PDHA1, GLS, and CDKN2A had significantly higher expression in COAD tissues than in normal tissues, while FDX1, DLD, and MTF1 had significantly lower expression in COAD tissues than in normal tissues (|(log2(fold change))| > 2, p < 0.05). DLD (hazard ratio (HR): 0.658; 95% confidence interval (CI): 0.445, 0.974; p = 0.037) and CDKN2A (HR: 1.785; 95% CI: 1.200, 2.654; p = 0.004) expressions were linked with overall survival throughout a log-rank test. CRG prognostic scores exhibited an area under the curve of 0.737, 0.646, and 0.633 at 1, 3, and 5 years. Patients with a high-risk factor suffered from poor prognosis (HR = 1.514; 95% CI: 1.022, 2.243; p = 0.0386). An independent validation dataset (GSE41328 ( N = 20)) confirmed the above results. The CRGs’ signature may be used as a prognostic predictor for COAD patients, providing unique insights into anticancer therapy.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".