Abstract 5833: Senescence is a central response to chemotherapy in ovarian cancer
Bibliographic record
Abstract
Abstract High-grade serous ovarian carcinoma (HGSOC) commonly responds to initial therapy, but this response is rarely durable. Understanding the cell fate decisions taken by HGSOC cells in response to treatment could guide new therapeutic opportunities. Here, we find that more than 90% of tissue-derived primary HGSOC cultures, reflecting the original disease, retain the capacity to undergo stress-induced cellular senescence and primarily undergo therapy-induced senescence (TIS) in response to first-line carboplatin/taxol chemotherapy. HGSOC-TIS displays senescence-associated hallmarks, including a stable proliferation arrest, increased p16INK4A expression, persistent DNA damage, an inflammatory secretome, and senolytic sensitivity, suggesting new avenues for selective pharmacological manipulation of these cells. Comparison of pre- and post-chemotherapy patient HGSOC tissue samples revealed changes in physio-pathological senescence biomarkers supporting the occurrence of post-treatment TIS. Whether cell senescence induced by cancer therapy is beneficial or detrimental to treatment outcomes remains unknown. We find that patients with stronger TIS biomarkers in post-chemotherapy tissues have a more favorale 5-year survival, suggesting that the induction of senescence in HGSOC cells accounts, at least in part, for beneficial responses to treatment. Given that HGSOC cells almost universally retain the capacity to undergo senescence and that senescence appears beneficial in this context, senescence-centric therapeutic avenues should be further explored. Citation Format: Michael Skulimowski, Llilians Calvo-Gonzales, Shuofei Cheng, Isabelle Clément, Lise Portelance, Yu Zhan, Euridice Carmona, Manon de Ladurantaye, Julie Lafontaine, Kurosh Rahimi, Diane Provencher, Anne-Marie Mes-Masson, Francis Rodier. Senescence is a central response to chemotherapy in ovarian cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5833.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".