Evaluation of potential predictive markers of efficacy of dacomitinib in patients (pts) with recurrent/metastatic SCCHN from a phase II trial.
Bibliographic record
Abstract
6041 Background: Dacomitinib is an irreversible pan-HER TKI with preclinical (EGFRvIII+ cell lines, SCCHN xenografts) and clinical activity (phase II recurrent/metastatic SCCHN; Razak et al, Ann Oncol 2012). However, little is known about predictive markers of efficacy related to EGFR signalling in this setting. Methods: Of69 pts treated with 1st-line dacomitinib in a phase II trial for recurrent/metastatic SCCHN, 48 pts had archival tumor specimens obtained before treatment and 13 had paired biopsies (days 0 and 7 of therapy, FFPE and snap frozen). EGFRvIII and PTEN (IHC), HPV genotyping and human genomic mutations (Sequenom OncoCarta Panel – 19 genes, 238 mutations) were evaluated on archival tissue. IHC expression of AKT, CC3, EGFR, ERK, HER2, HER3, MET, Ki67, pAKT, pEGFR, pERK, pHER2 and pMET was evaluated in paired specimens. The presence/absence or expression level of these markers was correlated with response (RR)/clinical benefit (CB), PFS and OS. Results: In pts with archival tissue, no statistically significant difference was found in RR/CB or PFS based on HPV, EGFRvIII, PTEN or presence of mutation. There was a trend to increased OS in HPV+ pts (HR 0.47, 95% CI 0.21–1.07, P=0.068). In paired biopsies, some expression variation was seen for cytoplasm AKT, membrane EGFR, nuclear ERK and pAKT. There was no correlation between basal expression of these markers and RR/CB or PFS. Variations in ratio to baseline of EGFR, pAKT, pERK and MET were qualitatively associated with RR/CB. No statistically significant correlations could be established for PFS, but there were interesting qualitative variations in the levels of expression of some molecules, eg, EGFR, pAKT. Conclusions: No predictive efficacy marker was identified. It cannot be determined if increased OS in HPV+ cases is due to prognostic or predictive effects. Paired biopsies demonstrated that dacomitinib was associated with variation in expression of multiple elements in signalling pathways linked to EGFR. Given the small number of paired biopsies, and large amount of data generated, descriptive study of cases is required. Further data will be presented at the meeting. Clinical trial information: 00768664.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".