IL15RA and SMAD3 Genetic Variants Predict Overall Survival in Metastatic Colorectal Cancer Patients Treated with FOLFIRI Therapy: A New Paradigm
Bibliographic record
Abstract
A new paradigm in cancer chemotherapy derives from the interaction between chemotherapeutics, including irinotecan and 5-fluorouracil (5-FU), and the immune system. The patient’s immune response can modulate chemotherapy effectiveness, and, on the other hand, chemotherapeutic agents can foster tumor cell immunogenicity. On these grounds, the analysis of the cancer patients’ immunogenetic characteristics and their effect on survival after chemotherapy represent a new frontier. This study aims to identify genetic determinants in the immuno-related pathways predictive of overall survival (OS) after FOLFIRI (irinotecan, 5-FU, leucovorin) therapy. Two independent cohorts comprising a total of 335 patients with metastatic colorectal cancer (mCRC) homogeneously treated with first-line FOLFIRI were included in the study. The prognostic effect of 192 tagging genetic polymorphisms in 34 immune-related genes was evaluated using the bead array technology. The IL15RA rs7910212-C allele was associated with worse OS in both discovery (HR: 1.57, p = 0.0327, Bootstrap p-value = 0.0280) and replication (HR: 1.71, p = 0.0411) cohorts. Conversely, SMAD3 rs7179840-C allele was associated with better OS in both discovery (HR: 0.65, p = 0.0202, Bootstrap p-value = 0.0203) and replication (HR: 0.61, p = 0.0216) cohorts. A genetic prognostic score was generated integrating IL15RA-rs7910212 and SMAD3-rs7179840 markers with inflammation-related prognostic polymorphisms we previously identified in the same study population (i.e., PXR [NR1I2]-rs1054190, VDR-rs7299460). The calculated genetic score successfully discriminated patients with different survival probabilities (p < 0.0001 log-rank test). These findings provide new insight on the prognostic value of genetic determinants, such as IL15RA and SMAD3 markers, and could offer a new decision tool to improve the clinical management of patients with mCRC receiving FOLFIRI.
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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) | 0.001 | 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".