<i>In vitro</i> Modeling of Human Pancreatic Duct Epithelial Cell Transformation Defines Gene Expression Changes Induced by K- <i>ras</i> Oncogenic Activation in Pancreatic Carcinogenesis
Bibliographic record
Abstract
Genetic analysis of pancreatic ductal adenocarcinomas and their putative precursor lesions, pancreatic intraepithelial neoplasias (PanIN), has shown a multistep molecular paradigm for duct cell carcinogenesis. Mutational activation or inactivation of the K-ras, p16(INK4A), Smad4, and p53 genes occur at progressive and high frequencies in these lesions. Oncogenic activation of the K-ras gene occurs in >90% of pancreatic ductal carcinoma and is found early in the PanIN-carcinoma sequence, but its functional roles remain poorly understood. We show here that the expression of K-ras(G12V) oncogene in a near diploid HPV16-E6E7 gene immortalized human pancreatic duct epithelial cell line originally derived from normal pancreas induced the formation of carcinoma in 50% of severe combined immunodeficient mice implanted with these cells. A tumor cell line established from one of these tumors formed ductal cancer when implanted orthotopically. These cells also showed increased activation of the mitogen-activated protein kinase, AKT, and nuclear factor-kappaB pathways. Microarray expression profiling studies identified 584 genes whose expression seemed specifically up-regulated by the K-ras oncogene expression. Forty-two of these genes have been reported previously as differentially overexpressed in pancreatic cancer cell lines or primary tumors. Real-time PCR confirmed the overexpression of a large number of these genes. Immunohistochemistry done on tissue microarrays constructed from PanIN and pancreatic cancer samples showed laminin beta3 overexpression starting in high-grade PanINs and occurring in >90% of pancreatic ductal carcinoma. The in vitro modeling of human pancreatic duct epithelial cell transformation may provide mechanistic insights on gene expression changes that occur during multistage pancreatic duct cell carcinogenesis.
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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) | 0.001 | 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".