Mouse Models for Pancreatic Ductal Adenocarcinoma are Affected by the cre-driver Used to Promote KRASG12D Activation
Bibliographic record
Abstract
Background & Aims The fundamental biology of pancreatic ductal adenocarcinoma has been greatly impacted by the characterization of genetically engineered mouse models that allow temporal and spatial activation of oncogenic KRAS (KRAS G12D ). One of the most commonly used models involves targeted insertion of a cre -recombinase into the Ptf1a gene. However, this approach disrupts the Ptf1a gene, resulting in haploinsufficiency that likely affects sensitivity to oncogenic KRAS (KRAS G12D ). This study aims to determine if Ptf1a haploinsufficiency affected the acinar cell response to KRAS G12D before and after induction of pancreatic injury. Methods We performed morphological and molecular analysis of 3 genetically engineered mouse models that express a tamoxifen-inducible cre -recombinase to activate Kras G12D in acinar cells of the pancreas. The cre-recombinase was targeted to the acinar-specific transcription factor genes, Ptf1a or Mist1/Bhlha15 , or expressed within a BAC-derived Elastase transgene. Histological and RNA-seq analyses were used to delineate differences between the models. Results Up to 2 months after tamoxifen induction of KRAS G12D , morphological changes were negligible. However, induction of pancreatic injury by cerulein resulted in widespread PanIN lesions in Ptf1a creERT pancreata within 7 days and maintained for at least 5 weeks post-injury, which was not seen in the models with 2 functional Ptf1a alleles. RNA-sequencing analysis prior to injury induction suggested Ptf1a creERT and Mist1 creERT mice have unique profiles of gene expression that predict a differential response to injury. Multiplex analysis of pancreatic tissue confirmed different inflammatory responses between the models. Conclusions These findings suggest Ptf1a haploinsufficiency in Ptf1a creERT mouse models promotes KRAS G12D priming of genes for promotion of pancreatic ductal adenocarcinoma.
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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) | 0.001 | 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".