RIPK3 expression as a potential predictive and prognostic marker in metastatic colon cancer
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer is one of the primary causes of cancer-related deaths and 5-fluorouracil (5-FU) therapy remains the cornerstone of treatment in these patients. Resistance to 5-FU represents a major obstacle; therefore, finding new predictive and prognostic markers is crucial for improvement of patient outcomes. Recently a new type of programmed cell death was discovered-necroptosis, which depends on receptor interacting protein 3 (RIPK3). Preclinical data showed that necroptotic cell death is an important effector mechanism of 5-FU-mediated anticancer activity. PURPOSE: To investigate the predictive and prognostic performance of RIPK3 expression in primary tumors. METHODS: Colon cancer patients (n=74) with metastatic stage were included in this retrospective study and all were treated with first-line 5-FU based chemotherapy. Immunohistochemical staining was performed. RESULTS: The progression free survival for the low expression group of RIPK3 was 5.6 months (95% CI, 4.4-6.8) vs 8.4 months (95% CI, 6.4-10.3) of the group with high expression (p=0.02). Moreover, patients with high expression of RIPK3 were associated with lower risk of disease progression HR 0.61 (95% CI, 0.38-0.97; p=0.044). Patients with high expression levels of RIPK3 also had significantly longer mean overall survival (OS) of 29.3 months (95% CI, 20.8-37.8) as compared with those with low expression: 18.5 months (95% CI, 15.06-21.9) (p= 0.036). In addition, univariate analysis showed that high level of RIPK3 expression was associated with a longer OS HR 0.59 (95% CI, 0.35-0.98; p=0.044). CONCLUSIONS: This study suggests that expression of RIPK3 in primary tumors of metastatic colon cancer patients should be further investigated for its potential as a promising predictive and prognostic marker.
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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 | 0.000 |
| 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) | 0.002 | 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".