Preoperative window-of-opportunity (WOO) study of dacomitinib (Dac) in patients (Pts) with resectable oral cavity squamous cell carcinoma (OCC): Generation of a gene expression signature (DGS) as a predictor of Dac activity.
Bibliographic record
Abstract
6041 Background: Dac is a potent, irreversible oral pan-HER tyrosine kinase inhibitor (TKI) with activity demonstrated in a multi-center phase II trial as first-line treatment in pts with recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) (NCT01449201; Razak et al. Ann Oncol 2013). No predictive biomarkers currently exist for Dac. Methods: WOO is a single-center, investigator-initiated study which enrolled pts with untreated resectable OCC, ECOG 0-2, and adequate organ functions. Pts were randomized 2:1 to Dac 45 mg or placebo QD for 7-11 days prior to surgery. Pre- and post-treatment (surgical specimen) samples were collected. Study objectives: (1) to evaluate a gene expression signature as a predictor of response to Dac, (2) to assess Ki67 modulation by Dac on paired tumor samples. DGS generation and validation: Using pre- and post-treatment fresh tumor biopsies from 7 pts in the NCT01449201 study as a discovery set, DASL HT12 Illumina gene expression array was performed on RNA. Genes differentially expressed in two groups were identified: pre- vs. post-treatment samples and pts with short vs. long progression-free survival (< 10 weeks vs. > 10 weeks). Genes commonly deregulated in both groups defined the signature DGS. DGS was then applied to pre-treatment samples from the WOO study as a validation, blinded to clinical response. Euclidean distance was used for complete-linkage clustering. Results: 14 pts were enrolled in the WOO study with evaluable samples from 10 pts (Dac/Placebo 8:2; response: yes/no/unknown 4/5/1). In the discovery set, a signature of 47 commonly-deregulated genes was found to be capable of dividing patients as high- or low-expressers pre-treatment. Patients clustered as high-expressers were more likely to be good-responders after treatment (RR = 3.75, 95% C.I. 0.8-21.7). No difference was observed in pre- post-treatment Ki67 between pts on Dac or placebo, nor between responders and non-responders. Conclusions: DGS may identity a subgroup of SCCHN pts more likely to respond to Dac; further validation in other Dac-treated SCCHN pts is ongoing. Clinical trial information: NCT01116843.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".