ERCC1 polymorphism in patients with locally advanced head and neck squamous cell carcinoma treated with concomitant chemoradiation: Prevalence and impact on treatment efficacy
Bibliographic record
Abstract
6032 Background: Excision repair cross-complementation group 1 (ERCC1) is a gene coding for the nucleotide excision repair complex. Its increased expression and polymorphism at codon 118 have been linked to poor response to chemotherapy or chemoradiation in several types of cancer. ERCC1 removes the cisplatin adducts on the DNA of cells and its polymorphism appears to be a marker of chemotherapeutic resistance to platinum-based therapy. Objectives: To determine the prevalence of the polymorphism of ERCC1 (codon 118) in patients with locally advanced HNSCC treated with concomitant platinum-based chemoradiation therapy with or without prior surgery, and its effect on eficacy evaluated by locoregional control, disease-free survival and overall survival. Methods: Prospective data on efficacy was available on 460 consecutive patients treated with concomitant chemoradiation in our institution with a minimal follow-up of 2 years. Of these, 230 fixed and paraffin embedded biopsies or surgical specimens were collected. DNA was extracted from specimens and polymorphism of codon 118 was determined using a PCR technique. All analysis were performed using Kaplan-Meier survival curves, Fisher's test for categorical data and log-rank statistics for failure times. Results: DNA extraction was successful in 222 patients. Polymorphism mapping was possible in 178 specimens. Genotypic distribution in the population was the following : AAT/AAT:40% (Gr1), AAC/AAT: 48%(Gr2), AAC/AAC: 12% (Gr3). At 3 years, evaluation of efficacy for Gr1, Gr2, and Gr3 was determined. Locoregional control was respectively 77%, 83%, and 67% (p = NS), DFS was 58%, 68% and 55% (p=NS), and OS was 70%, 69%, and 70% (p = NS). Conclusions: ERCC1 polymorphism did not have an impact in our population on response to chemoradiation therapy. It can be postulated that ERCC1 does not seem to discriminate patients for whom another treatment option should be sought for patients with locally advanced SCCHN. Further data will be presented at the meeting including a multivariate analysis using different markers tested in our laboratory (KRAS, MGMT methylation, etc). No significant financial relationships to disclose.
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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 | 0.002 |
| 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 | 0.000 | 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".