Cell of origin affects tumour development and phenotype in pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Objective Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumour thought to arise from ductal cells via pancreatic intraepithelial neoplasia (PanIN) precursor lesions. Modelling of different genetic events in mice suggests both ductal and acinar cells can give rise to PDAC. However, the impact of cellular context alone on tumour development and phenotype is unknown. Design We examined the contribution of cellular origin to PDAC development by inducing PDAC-associated mutations, Kras G12D expression and Trp53 loss, specifically in ductal cells ( Sox9CreER;Kras LSL-G12D ;Trp53 flox/flox (‘ Duct:KP cKO ’)) or acinar cells ( Ptf1a CreER ;Kras LSL-G12D ;Trp53 flox/flox (‘ Acinar:KP cKO ’)) in mice. We then performed a thorough analysis of the resulting histopathological changes. Results Both mouse models developed PDAC, but Duct:KP cKO mice developed PDAC earlier than Acinar:KP cKO mice. Tumour development was more rapid and associated with high-grade murine PanIN (mPanIN) lesions in Duct:KP cKO mice. In contrast, Acinar:KP cKO mice exhibited widespread metaplasia and low-grade as well as high-grade mPanINs with delayed progression to PDAC. Acinar-cell-derived tumours also had a higher prevalence of mucinous glandular features reminiscent of early mPanIN lesions. Conclusion These findings indicate that ductal cells are primed to form carcinoma in situ that become invasive PDAC in the presence of oncogenic Kras and Trp53 deletion, while acinar cells with the same mutations appear to require a prolonged period of transition or reprogramming to initiate PDAC. Our findings illustrate that PDAC can develop in multiple ways and the cellular context in which mutations are acquired has significant impact on precursor lesion initiation, disease progression and tumour phenotype.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".