Discovery of prognostic and predictive tissue biomarkers in patients with resectable esophageal cancer.
Bibliographic record
Abstract
45 Background: Patients with operable esophageal adenocarcinoma have a poor prognosis (median survival <2 years). We aimed to discover novel prognostic and predictive biomarkers to be validated as tools for patient selection for optimal neo-adjuvant therapy. Methods: Protein levels of XPF, MUS81, Cyclins A, B1, D1 and E, and Ki67 were assessed by retrospective immunohistochemical analysis of baseline tumor biopsy samples from 3 groups of patients with operable esophageal adenocarcinoma: surgery alone (N=54), 2 cycles of cisplatin-fluorouracil chemotherapy followed by surgery (N=46), and 2 cycles of oxaliplatin-fluorouracil chemotherapy (N=38). Expression of 48,803 genes was studied by Illumina HT-12 chip array followed by functional pathway analysis in oxaliplatin-treated patients before and after chemotherapy (N=38). Results were tested for association with pathological response (Mandard regression grading) (Chi-square test), disease free survival (DFS) and overall survival (OS) (Wilcoxon test). Results: High Ki67 protein levels were associated with worse OS (P=0.034; N=93). None of the markers were predictive of clinical endpoints following cisplatin chemotherapy. In oxaliplatin-treated patients (N=38), functional pathway analysis revealed associations between overexpression of cell cycle/DNA repair genes at baseline and worse clinical outcomes. Expression of 15 DNA repair (DNAR) genes was associated with DFS, and 16 DNAR genes with OS. Expression of 21 DNAR genes significantly increased after chemotherapy. Gene expression associations were validated at the protein level: high MUS81 at baseline predicted poor DFS (P=0.036) and poor OS (P=0.015) following oxaliplatin therapy; high XPF expression was associated with lack of pathological response (P=0.032); high Cyclin B1 predicted poor DFS (P=0.017). XPF protein levels increased following oxaliplatin (P=0.001, paired t-test). Conclusions: By confirmation of mRNA findings at the protein level, XPF, MUS81, and Cyclin B1 have been discovered as predictive biomarkers for response to oxaliplatin chemotherapy that merit prospective validation as tools for patient selection. Funded by Oxford NIHR Biomedical Research Centre and ECMC.
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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 | 0.000 | 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".