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Abstract NT-118: SEQUENTIAL THERAPEUTIC TARGETING OF OVARIAN CANCER HARBORING DYSFUNCTIONAL BRCA1

2019· article· en· W3167506735 on OpenAlexaff
Tahira Baloch, Roy Kessous, David Octeau, Liron Kogan, Ido Laskov, Michael Witcher, Walter H. Gotlieb, Amber Yasmeen

Bibliographic record

VenueClinical Cancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsOvarian cancerOlaparibChemotherapyMedicineCancer researchCisplatinPaclitaxelDebulkingCancerOncologyPARP inhibitorCarboplatinDoxorubicinInternal medicineBiologyPoly ADP ribose polymerase

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Ovarian cancer is the most lethal gynecologic cancer. High grade serous ovarian cancer (HGSC) is the most common and deadly histological subtype. The current standard treatment protocol involves primary debulking surgery followed by platinum-based combination chemotherapy. PARP inhibitors(PARPi) are the first approved personalized treatments used in BRCA1-mutated recurrent ovarian cancer patients and have shown promising clinical results. Previously published data in collaboration with Dr. Witcher's lab, we described a significant reduction in PARP1 protein levels in patients after giving standard carboplatinum-paclitaxel chemotherapy that is effecting the clinical efficacy of PARP inhibitors in clinical trials. PARP inhibitors are currently administered after standard chemotherapy, when PARP levels are the lowest which was clearly shown in the previous published paper. Applying novel strategy and following the sequence of administration, giving PARP inhibitors first followed by standard chemotherapy might improve response rates. This study aims to evaluate this strategy (in vitro) in the pre-clinical models. METHODS: BRCA1 mutated (UWB1.287, SNU-251), epigenetically silenced (OVCAR8), and wild-type BRCA1 (OVCAR3, SKOV3, A2780P & A2780R) cell lines were exposed to clinically relevant doses of PARPi, either followed by standard chemotherapy, or the inverse sequence. Therapeutic efficacy was assessed using colony formation assay. Apoptotic index was evaluated by cell cycle analysis and apoptotic assays using flow cytometry. Western Blotting was used to detect the levels of relevant apoptotic and cell cycle proteins. RESULTS: Exposure to PARPi prior to standard chemotherapy sensitized BRCA1 mutated or epigenetically silenced BRCA1 cell lines to lower doses of Cisplatin (CP) or Paclitaxel (PT). Similarly, pre-treatment with PARPi prior to chemotherapy induced apoptosis more effectively in the same cell lines. Similar results were observed in BRCA1 wild-type cell lines and cell lines in which BRCA1 functionality was restored. CONCLUSION: Pre-treatment of cell lines with PARPi followed by standard chemotherapy is more efficient (in vitro) in inhibiting growth and inducing apoptosis than the present sequence of chemotherapy followed by PARPi. Citation Format: Tahira Baloch, Roy Kessous, David Octeau , Liron Kogan, Ido Laskov, Michael Witcher, Walter H. Gotlieb and Amber Yasmeen. SEQUENTIAL THERAPEUTIC TARGETING OF OVARIAN CANCER HARBORING DYSFUNCTIONAL BRCA1 [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr NT-118.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.299
GPT teacher head0.544
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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