Abstract 3133: In vitro modeling of human pancreatic duct epithelial cell transformation
Bibliographic record
Abstract
Abstract Background: Pancreatic cancer is the fifth most common cause of cancer death in North America and has an overall 5-year survival rate of less than 5%. Over 90% of tumours are ductal carcinoma (PDAC), which putatively arise from the pancreatic ducts. In PDAC, KRAS oncogene activation occurs in approximately 90% of cases, while SMAD4 tumour suppressor gene inactivation occurs in around 55% of cases. We hypothesize that introduction of multiple genetic aberrations into pancreatic epithelial cells derived from normal ducts may provide a dynamic model to study pancreatic duct cell carcinogenesis. Materials and Methods: We have isolated another cell line from the H6c7 immortalized near normal pancreatic duct epithelial (HPDE) cell line called TβR. TβR cells were generated by growing the H6c7 cells in progressively increasing concentrations of TGF-β and are resistant to growth inhibition by TGFβ. Overexpression of KRASG12V in TβR gave rise to TβR-KRAS cells. Results: Spectral karyotypic analysis of TβR cells revealed paradiploidy but with the loss of one copy of chromosome 18, on which the Smad4 gene resides. Q-PCR and Western blot confirmed the lost of Smad4 expression in this cell line. TβR cells demonstrated increased invasiveness as compared to the parental H6c7 cell line, and this is further enhanced in TβR-KRAS cells. The TGF-β-Smad4 signaling pathway was disrupted in both the TβR and TβR-KRAS cell lines. This resulted in the loss of responsiveness to TGF-β and the repressed expression of Smad4 responsive genes. The subcutaneous injection of the TβR-KRAS induced in tumor growth in SCID mice. Conclusion: The complete loss of Smad4 expression cooperates with KRASG12V oncogene to induce tumorigenicity in H6c7 cells. This provides a dynamic in vitro model to study the gene expression changes that characterize the key molecular events that occur during pancreatic ductal carcinogenesis. (Supported by the Canadian Institutes of Health Research grant MOP-49585) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3133.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".