Combination Chemotherapy and In vivo Modeling of BRCA-deficient, High-grade Serous Ovarian Cancer
Bibliographic record
Abstract
Ovarian cancer is the most fatal cancer in women with over 60% of patients succumbing to the disease. Mutations in a number of homologous recombination repair genes have been implicated in hereditary ovarian and breast cancer. Specifically, over half of ovarian cancer cases exhibit BRCA-deficiency by either germ line or somatic mutation, or epigenetic silencing. The importance of BRCA-deficiency is highlighted in its association with increased platinum sensitivity. Novel therapeutics such as PARP inhibitors have also been developed by exploiting the synthetic lethal phenotype of BRCA inactivation and PARP inhibition. However over 80% of patients still relapse with resistant disease. Therefore, strategies for more effective treatment are needed. The aim of this thesis was to investigate a chemotherapeutic ratiometric approach for treatment of ovarian cancer and provide a relevant pre-clinical model for evaluation of new therapeutic entities. The combination of carboplatin and olaparib resulted in profound synergism in BRCA-deficient high-grade serous ovarian cancer cell lines when carboplatin was administered at a higher molar ratio relative to olaparib. The combination achieved effective cytotoxicity by inducing greater DNA damage than either of the drugs alone. Synergism of carboplatin-olaparib combinations was also observed in a subset of BRCA-proficient cell lines, suggesting a potential for broader therapeutic applications. To further investigate the impact of BRCA status on therapeutic efficacy, a bioluminescent, BRCA-deficient xenograft model was developed. The model demonstrated characteristics resembling the disease clinically, including high disseminative tumor pattern, ascites production, and platinum sensitivity. Bioluminescent imaging as a means of non-invasion tumor monitoring correlated well with disease burden. Lastly, a systematic literature search identified potential limitations in utilization of bioluminescent imaging techniques in animal models. The correlation between bioluminescent signal and tumor burden is affected by many experimental aspects and it is difficult to identify a general limiting factor. Nonetheless, consideration must be given to methods of tumor measurement, heterogeneity of tumor cell population, and the location of the xenograft when developing the model. Overall, results presented herein provide encouraging data on the utilization of synergistic combinations and a valuable pre-clinical model for evaluation of such combinations for ovarian cancer treatment.
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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 | 0.001 |
| 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".