53BP1 mediates sensitivity to chemotherapy and is associated with poor clinical outcomes in high-grade serous ovarian cancer
Bibliographic record
Abstract
ABSTRACT High-grade serous ovarian cancer (HGSOC) remains the most lethal gynecological malignancy in North American women. At a cellular level, the current first-line chemotherapies cause DNA-damage and activate the DNA damage response signalling cascade. Here we explore the role of 53BP1, a central mediator of the DNA damage response, in HGSOC chemotherapy outcomes. Tissue 53BP1 protein levels were quantified in two independent HGSOC cohorts, the COEUR validation cohort (n = 173) and CHUM cohort (n = 56). Univariate and multivariate analyses showed that high nuclear 53BP1 levels in ovarian cancer cells were strongly associated with poor disease-specific survival in both cohorts. High 53BP1 was associated with poor progression-free survival (PFS) in the COEUR cohort, and trended towards poor PFS in the CHUM cohort. These findings were validated by whole-tumour TP53BP1 mRNA of the TCGA Firehose Legacy cohort (n = 591) in which high TP53BP1 mRNA levels were associated with poor overall survival on multivariate analysis. In HGSOC cell lines, 53BP1 levels were positively correlated with resistance to carboplatin using colony formation assay, and depletion of 53BP1 sensitized resistant cell lines to genotoxic therapies. These results suggest that 53BP1 is associated with poor prognosis in HGSOC and may mediate this relationship by modulating cellular sensitivity to chemotherapy. Statement of translational relevance Current first-line chemotherapies in ovarian cancer cause DNA damage and activate the DNA damage response, culminating in the taking of cell fate decisions. 53BP1 is a central mediator in this signalling cascade, where it is involved at multiple levels: signal amplification, recruitment of effectors, DNA repair pathway choice, and cell cycle regulation. However, its role in ovarian cancer treatment outcomes remains unknown. In this study, we found that 53BP1 correlated with poor clinical outcomes in three ovarian cancer patient cohorts and mediated carboplatin sensitivity in ovarian cancer cells. These results reveal 53BP1 and the DNA damage response as important actors in ovarian cancer treatment response. Though further studies are necessary to gain a more complete understanding of their involvement in clinical outcomes, they appear as promising candidates for potential therapeutic targeting in ovarian cancer.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".