Abstract 278: Investigating the functional role of cancer-associated fibroblasts in the emergence of drug-tolerant persisters in ovarian cancer
Bibliographic record
Abstract
Abstract Chemoresistance remains a major clinical challenge for the treatment of high-grade serous ovarian cancer (HGSC), the most lethal gynecologic malignancy. The majority of patients who initially respond to first-line platinum/taxane-based chemotherapy eventually relapse with chemoresistant disease, leading to poor survival outcomes. It is increasingly recognized that cancer cells can enter a reversible drug-tolerant persister (DTP) state through non-genetic mechanisms to evade chemotherapy-induced cytotoxicity prior to the development of chemoresistance. However, how environmental signals and extracellular factors from the tumor microenvironment drive the process remains poorly understood. Cancer-associated fibroblasts (CAFs) are a functionally heterogeneous population of activated fibroblasts. CAFs play a critical role in shaping the tumor microenvironment and tumor behaviors, including promoting tumor growth and mediating therapy resistance. Here, we demonstrated that HGSC cell lines co-cultured with patient-derived FAP-high CAFs, a subpopulation of CAFs previously identified in our lab to be tumor-promoting, significantly increase the formation of DTPs upon prolonged carboplatin treatment compared to the mono-cultured condition. Interestingly, the extracellular matrix (ECM) organization signature is enriched in FAP-high CAFs compared to their FAP-low counterparts, and we found that ECM deposited by FAP-high CAFs also facilitates the emergence of DTPs in HGSC cells. Future work will focus on elucidating the mechanisms by which FAP-high CAFs and the associated ECM promote DTP formation in HGSC cells through transcriptomic and proteomic profiling. This will aid the identification of potential therapeutic vulnerabilities to target cancer cells in the DTP state in FAP-high HGSC patients. Citation Format: Angel S. Ng, Ngoc Bui, Laurie Ailles. Investigating the functional role of cancer-associated fibroblasts in the emergence of drug-tolerant persisters in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 278.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".