Improved Progression-Free Survival in Irinotecan-Treated Metastatic Colorectal Cancer Patients Carrying the HNF1A Coding Variant p.I27L
Bibliographic record
Abstract
Hepatocyte nuclear factor 1-alpha (HNF1A) is a liver-enriched transcription factor that plays a key role in many aspects of hepatic function including detoxification processes. We examined whether HNF1A polymorphisms are associated with clinical outcomes in two independent cohorts combining 417 European ancestry patients with metastatic colorectal cancer (mCRC) treated with irinotecan-based chemotherapy. The intronic rs2244608A>G marker was predictive of an improved progression-free survival with a trend in the Canadian cohort and reaching significance in the Italian cohort, with hazard ratios (HR) of 0.74 and 0.72, P = 0.076 and 0.038, respectively. A strong association between rs2244608A>G and improved PFS was found in the combined analysis of both cohorts (HR = 0.72; P = 0.002). Consistent with an altered HNF1A function, mCRC carriers of the rs2244608G minor allele displayed enhanced drug exposure by 45% (P = 0.032) compared to non-carriers. In Caucasians, rs2244608A>G is in strong linkage with the coding variant rs1169288c.79A>C (HNF1A p.I27L). In healthy donors, we observed an altered hepatic (ABCC1, P = 0.009, ABCC2, P = 0.048 and CYP3A5, P = 0.001; n = 89) and intestinal (TOP1, P = 0.004; n = 75) gene expression associated with the rs1169288C allele. In addition, the rs1169288C polymorphism could significantly increase the ABCC1 promoter activity by 27% (P = 0.008) and 15% (P = 0.041) in the human kidney HEK293 and the human liver HepG2 cell lines, respectively. Our findings suggest that the HNF1A rs2244608, or the tightly linked functional coding variant p.I27L, might be a potential prognostic marker with irinotecan-based regimens.
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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 | 0.000 |
| 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) | 0.001 | 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".