Abstract 1588: Identification of new signaling pathways between fibroblasts & tumor cells in pancreatic cancer
Bibliographic record
Abstract
Abstract We explore the unstudied role of nanoparticles (NPs), recently discovered secreted non-vesicular nanoparticles, in signaling between pre-cancer associated fibroblasts (preCAF), CAFs, and tumor cells. We generated two novel primary lines preCAF PFUM1 from a patient with high-grade intraductal papillary mucinous neoplasms and CAF FUM2 from a patient with pancreatic ductal adenocarcinoma, all tests performed between passages 2 and 3, fibroblast purity validated by RT-PCR and ACTA2 immunofluorescence. Small extracellular vesicles (sEVs), exomeres, and supermeres (the two main forms of NPs) were isolated by the ultracentrifugation method from PF-UM1 and F-UM2 with n=2-3 experiments. To validate the isolation, we used nanoparticle tracking, electron, and fluid-phase atomic force microscopy. Proteins were quantified by BCA assay. Liquid chromatography-mass spectrometry characterized the cargo from each fraction. Human cancer lines MIAPACA2 and SU8686 were treated with 10 μg of each fraction and cell proliferation was tested by phase-contrast images (Cytation 5), analyzed by Ilastik-based 1.4.0 machine-learning. We performed fluorescent Ki-67 and vimentin staining and quantified in QuPath 0.4.3. Non-parametric statistics were performed in Prism GraphPad. NPs constitute the major fraction of small particles released by fibroblasts, containing 80.5% (PFUM1) and 77.5% (FUM2) of the protein load by quantification. Mass spectrometry reveals enrichment of growth factors, epithelial-to-mesenchymal (EMT) transition, and metabolism-associated proteins in the NPs compared to sEVs. At 72 hours, cell proliferation for Su8686 reveals a proliferative effect for all fractions from both PFUM1 and FUM2 (19-63% increase compared to controls, p=0.049 to <0.0001). For MIAPACA2, only supermeres from PFUM1 and FUM2 consistently increased proliferation (9.5-35% increase, p=0.0051 to <0.0001). Ki-67 expression in MIAPACA2, increased by 9.6-23.0% following treatment by NPs (all p<0.0001) and by 2.9-9.2% with sEVs (p=0.011 to <0.0001). EMT was estimated by vimentin in MIAPACA2, as all preCAF fractions from PFUM1 reduced vimentin expression (p<0.001), while CAF FUM2 NPs increased vimentin expression (p<0.0001) while sEVs had no effect (p=0.075). In conclusion, the majority of pancreatic tumor-associated fibroblast small secretome is composed of NPs, exhibiting significant functional pro-tumoral effects. Citation Format: Ayman Al Shoukari, Maelle Batardiere, Nooshin Movahed, Camille beaussier, Jumanah Baig, Melissa gonzalez, Patricia Moraille, Eric Bonneil, Louise Rousseau, Simon turcotte, Kathleen Delgiorno, Marcus Tan, Anna Means, Elham Dianati Ajibisheh, Quoc-huy Trinh. Identification of new signaling pathways between fibroblasts & tumor cells in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1588.
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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) | 0.002 | 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".