Abstract A058: Primary cancer-associated fibroblasts alter tumor organoid chemosensitivity through epigenetic regulation
Bibliographic record
Abstract
Abstract Pancreatic adenocarcinoma (PDAC) is the 3rd leading cause of cancer-related deaths in Canada with a 5-year survival rate at ∼12%. A major cause of this poor survival rate is the inefficiency of current treatments. Only 20% of patients are eligible for surgical resection while the other 80% are treated with chemotherapies (nab-paclitaxel, Gemcitabine, FOLFIRINOX) having limited efficacy. This resistance is due to the PDAC tumour microenvironment (TME), including cancer-associated fibroblasts (CAFs). Numerous studies show CAFs and the TME affect tumour growth, chemoresistance and metastasis, but the mechanisms underlying the effects are unknown. Epigenetic mechanisms, including DNA methylation and histone modifications, link environmental factors to altered gene expression. Genes encoding epigenetic mediators are often mutated or over-expressed in PDAC, but a role in resistance has yet to be defined. We hypothesize that epigenetic reprogramming occurs in pancreatic cancer cells in response to secreted factors from CAFs leading to increased therapy resistance. Methods: Most work to date on PDAC resistance has been performed with immortalized cell lines and in two dimensions. Therefore, to test our hypothesis, we established patient-derived organoids (PDO) and CAFs obtained from endoscopic ultrasound (EUS). Clinical data was obtained through the DERIVE (Determination of Response to Therapy in Individual Patients) database. To examine the effects of CAFs on PDOs, we obtained conditioned media (CM) from four, early passage CAFs, grown 48 hours in culture. Organoid media was supplemented 1:1 with CAF-CM and six PDOs grown in this media for up to 14 days. PDO growth and the response to gemcitabine, FOLFIRINOX or radiation was monitored using an Incucyte system. To identify changes in the epigenome and how this reflects changes in gene expression, DNA methylation arrays and ATAC-Seq was performed before and after treatment with CAF-CM and aligned to RNA-seq analysis on RNA isolated at the same time point. Results: Exposure of PDOs to CAF-CM resulted in altered phenotypes and molecular profiles of PDOs in a patient-specific fashion. Increased resistance to chemotherapy (Gemcitabine) and radiotherapy was observed in multiple PDOs. Changes in DNA methylation and chromatin accessibility was aligned with transcriptomic data and identified known and novel pathways linked to chemoresistance. Metabolomic and cytokine analysis on CAFs-CM identified differential enrichment of metabolites linked to epigenetic mediators. We are currently determining if these factors secreted by the CAFs promote chemo and radio-resistance. Conclusions: This study shows the importance in integrating TME components when examining novel therapeutic options. In addition, we show (1) CAFs secrete factors that enhance therapeutic resistance in PDOs and (2) these changes likely involve altered epigenetic reprogramming. Future experiments will identify the epigenetic factors that can be targeted to counteract chemoresistance. Citation Format: Emilie Jaune-Pons, Zachary Klassen, Joana Ribeiro Pinto, Maria Nica, Nadeem Hussain, Michael Sey, Ken Leslie, Matthew Cecchini, Crystal Engelage, Danielle Porplycia, Stephen Welch, Brian Yan, Christopher Pin. Primary cancer-associated fibroblasts alter tumor organoid chemosensitivity through epigenetic regulation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A058.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".