Patient-specific modeling of stroma-mediated chemoresistance of pancreatic cancer using a three-dimensional organoid-fibroblast co-culture system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cancer-associated fibroblasts (CAFs) are considered to play a fundamental role in pancreatic ductal adenocarcinoma (PDAC) progression and chemoresistance. Patient-derived organoids have demonstrated great potential as tumor avatars for drug response prediction in PDAC, yet they disregard the influence of stromal components on chemosensitivity. METHODS: We established direct three-dimensional (3D) co-cultures of primary PDAC organoids and patient-matched CAFs to investigate the effect of the fibroblastic compartment on sensitivity to gemcitabine, 5-fluorouracil and paclitaxel treatments using an image-based drug assay. Single-cell RNA sequencing was performed for three organoid/CAF pairs in mono- and co-culture to uncover transcriptional changes induced by tumor-stroma interaction. RESULTS: Upon co-culture with CAFs, we observed increased proliferation and reduced chemotherapy-induced cell death of PDAC organoids. Single-cell RNA sequencing data evidenced induction of a pro-inflammatory phenotype in CAFs in co-cultures. Organoids showed increased expression of genes associated with epithelial-to-mesenchymal transition (EMT) in co-cultures and several potential receptor-ligand interactions related to EMT were identified, supporting a key role of CAF-driven induction of EMT in PDAC chemoresistance. CONCLUSIONS: Our results demonstrate the potential of personalized PDAC co-cultures models not only for drug response profiling but also for unraveling the molecular mechanisms involved in the chemoresistance-supporting role of the tumor stroma.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it