Abstract 2148: Pre-clinical models recapitulating the spectrum of response of BRCA associated pancreatic cancer
Bibliographic record
Abstract
Abstract Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease, with the majority of patients diagnosed at an advanced stage. Comprehensive genomic analysis identified the homologous recombination deficiency (HRD) subgroup which is predominantly enriched in patients harboring germline BRCA1/2 mutations (glBRCA) and presents ~7% and up to 15% in selected high-risk populations. Tumors with HRD are susceptible to DNA-damaging agents and PARP inhibition. However, not all patients demonstrate a similar response, and a spectrum is observed. We analyzed the clinical outcome of ninety-one glBRCA PDAC patients treated at Sheba Medical Center. We identify three main subgroups of response spanning from ~25% patients refractory to first line platinum agents and ~9% patients with durable long-term response with no evidence of disease for over three years. The majority of the patients display a prolonged response to platinum and PARPi maintenance (>24 months) followed by acquired resistance. We generated patient derived xenograft (PDX) models and an ex-vivo culture system (EVOC) from naïve to treatment tissue and at clinical resistance. In vivo efficacy to platinum agents and PARPi demonstrates that these models recapitulate the specific clinical spectrum of response. We demonstrate the utility of both pre-clinical models in their ability to predict response to platinum-based agents and PARPi, with EVOC having a potential to assist in medical decisions while treating the patient. Whole genome sequencing of the tumors revealed that BRCA monoallelic tumors are associated with innate resistance while biallelic tumors reflect sensitivity to platinum agents and PARPi. In the acquired resistance models, the main identified mechanism of resistance was due to reversion mutations in 4/6 of samples. Whole genome analysis demonstrates high mutational and neo-antigen load in majority of the glBRCA tumors. In a preliminary study, we show the efficacy of anti PD1 in a novel humanized glBRCA PDAC PDX model. This extensive preclinical and clinical collection of BRCA associated PDAC, enables further understanding and investigation of this unique subtype in aim to develop alternative treatments to overcome resistance. Citation Format: Talia Golan, Chani Stossel, Maria Raitses-Gurevitch, Dikla Atias, Tamar Beller, Steven Gallinger, Raanan Berger. Pre-clinical models recapitulating the spectrum of response of BRCA associated pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2148.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".