Abstract 2879: Pre-clinical characterization of Dacomitinib, an irreversible pan-HER inhibitor, combined with radiation therapy in head and neck cancer models
Bibliographic record
Abstract
Abstract Introduction: Head and neck cancer is the 5th most common cancer worldwide; the majority of cases (>90%) are squamous cell carcinomas (SCCHNs). Despite advances in treatment, the 5-year overall survival rate for SCCHN patients still remains at ∼40-50%, underscoring the need to develop novel therapeutic strategies. EGFR is over-expressed in ∼90% of SCCHN cases, and is associated with tumor progression and poor prognosis. Dacomitinib (D), an irreversible pan-HER inhibitor, has demonstrated clinical potential in patients with non-small cell lung cancer, leading us to explore its therapeutic efficacy in SCCHN pre-clinical models, in combination with radiation therapy (RT), a curative modality for HNC management. Methods: The basal expression of EGFR family members was assessed via qRT-PCR in three SCCHN models (FaDu (human hypopharyngeal), UTSCC-8 & -42a (both laryngeal) squamous cancer, and NOE (normal oral epithelial) cell lines. MTS-based cell viability and clonogenic assays were performed with various concentrations of D, both alone and in combination with irradiation (IR). Inhibition of EGFR signalling by D was confirmed via immunoblotting. Cell cycle analysis was performed to assess mode of cytotoxicity. In vivo therapeutic studies were performed using FaDu xenografts in SCID mice; tumors were extracted post-treatment and examined for TUNEL, CD31, Ki67, and pEGFR via IHC. Results: EGFR was over-expressed in all three SCCHN, compared to the NOE cells. PF (50 nM) reduced FaDu cell viability by ∼25%, with an additive interaction being observed when D was combined with 2 Gy IR (∼36%). Similar trends were observed in the other two cell lines and also in the clonogenic assays. Immunoblotting confirmed a dose-dependent inhibition of EGFR signalling in D-treated SCCHN cells, along with downstream reduction of p-Erk, p-Akt, and p-mTOR expression. Cell cycle analyses showed ∼20% increase in the G0/G1 cell population in D-treated FaDu cells, and ∼10% increase in the sub-G cell population when D and IR were combined. Mice treated with the combination of D + IR exhibited a maximum tumor growth delay of ∼21 days, as compared to the IR only group, determined by time to tumor-plus-leg diameter of 14mm. Preliminary histological analysis of the extracted tumor tissue show ∼40% reduction in Ki67 staining in the PF + IR treated mice. The addition of D to IR appeared to be well-tolerated, with no change in body weight, or extent of alopecia. Conclusion: Dacomitinib effectively inhibited EGFR signalling in SCCHN models, leading to a reduction in cell viability and clonogenic survival in vitro, along with tumor growth delay in vivo. When D was combined with IR, there was an additive interaction, both in vitro and in vivo. Thus, D combined with RT may have a therapeutic benefit for patients with SCCHN. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2879. doi:1538-7445.AM2012-2879
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".