Abstract A61: FAK activity sustains intrinsic and acquired ovarian cancer resistance to platinum chemotherapy
Bibliographic record
Abstract
Abstract Gene copy number alterations, tumor cell stemness, and development of platinum chemotherapy resistance contribute to high-grade serous ovarian cancer (HGSOC) recurrence. Stemness phenotypes involving Wnt-beta-catenin, aldehyde dehydrogenase activities, intrinsic platinum resistance, and tumorsphere formation are here associated with spontaneous genetic gains in KRAS, MYC, and FAK (KMF) genes, in a new aggressive murine model of ovarian cancer. Noncanonical signaling via FAK sustained KMF and human tumorsphere proliferation as well as resistance to cisplatin cytotoxicity. Platinum-resistant tumorspheres can acquire a dependence on FAK for growth. Accordingly, increased FAK tyrosine phosphorylation was observed within HGSOC patient tumors surviving neoadjuvant chemotherapy. Combining a FAK inhibitor with platinum overcame chemoresistance, triggering tumor cell apoptosis. FAK transcriptomic analyses across knockout and reconstituted cells identified 135 genes elevated by a FAK activity-dependent, beta-catenin, and Myc signaling axis including pluripotency and DNA repair genes. Identified target increases in HGSOC tumors may reflect oncogenic FAK signaling. Citation Format: Carlos J. Díaz Osterman, Duygu Ozmadenci, Elizabeth G. Kleinschmidt, Kristin N. Taylor, Allison M. Barrie, Shulin Jiang, Lisa M. Bean, Florian J. Sulzmaier, Jian Li, Xiao Lei Chen, Guo Fu, Marjaana Ojalill, Pekka Rappu, Jyrki Heino, Adam A. Mark, Guorong Xu, Kathleen M. Fisch, David T. Weaver, Jonathan A. Pachter, Balázs Győrffy, Michael T. McHale, Denise C. Connolly, Alfredo Molinolo, Dwayne G. Stupack, David D. Schlaepfer. FAK activity sustains intrinsic and acquired ovarian cancer resistance to platinum chemotherapy [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A61.
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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 | 0.000 |
| 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".