Abstract 3019: High throughput drug screening identified spleen tyrosine kinase as a novel therapeutic target in head and neck cancer with potent in vitro and in vivo activity
Bibliographic record
Abstract
Abstract Background and Significance: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, and survival remains poor highlighting the need for novel treatments for the treatment of HNSCC. High throughput drug screening has shown the potential to discover novel therapeutics in other cancers. Methods: Twenty-eight HNSCC cell lines, including 5 HPV-positive lines, were characterized with whole exome sequencing and copy number arrays and screened with 1505 potential anti-cancer agents on a robotic liquid handling platform at a single dose (4uM). The most potent hits were confirmed with 10-point dose response curves. Novel therapeutic targets were further investigated with mechanistic and xenograft studies. Results: Drug screening identified 10 agents with broad activity across our cell line panel. One of the most potent agents was ER27319 maleate, reported to be a spleen tyrosine kinase (Syk) inhibitor. We confirmed that this molecule inhibited Syk phosphorylation specifically at tyrosine residues 525/526. Additionally, ER27319 maleate as well as a more clinically relevant Syk inhibitor, Fostamatinib, were observed to significantly impaired cellular migration and invasion. Additionally, siRNA knockdown of Syk in HNSCC cells was found to decrease HNSCC cell line growth. Finally, inhibition of Syk was observed to control HNSCC tumour growth in vivo in cell line-derived xenografts. Conclusions: High throughput drug screening of HNSCC cell lines identified Syk as a novel target and confirmed potent in vitro and in vivo activity. Further preclinical evaluation is planned with a panel of patient-derived xenografts. Should these results yield significant activity, we will aim to repurpose approved Syk inhibitors to improve outcomes for patients suffering from HNSCC. Citation Format: Morgan Black, Laurie Ailles, Ren Sun, Alessandro Datti, Frederick Vizeacoumar, Nicole Pinto, Kara Ruicci, John Yoo, Kevin Fung, Danielle MacNeil, David A. Palma, Eric Winquist, Joe S. Mymryk, Paul C. Boutros, John W. Barrett, Anthony C. Nichols. High throughput drug screening identified spleen tyrosine kinase as a novel therapeutic target in head and neck cancer with potent in vitro and in vivo activity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3019.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".