Abstract 2154: ERK/MAPK pathway inhibits tumorigenesis and cellular reprogramming of pancreatic cancer cells
Bibliographic record
Abstract
Abstract Reprogrammation of cancer cells into stem-like state is one the most important mechanisms implicated in tumor initiation, metastasis and resistance to chemotherapies. Acquisition of stem-like cell property is directly correlated with the level of activation of the ERK/MAPK pathway. Our study focuses on the implication of the downregulation of this pathway during the transition of pancreatic benign neoplasms to pancreatic ductal adenocarcinoma. This transformation is directly correlated with the acquisition of stem-like cells properties. Conversely, hyperactivation of the ERK pathway using phosphatase inhibitors abrogates the stem-like cell phenotype. We analyzed the variation of genes expression by microarrays analysis between cells obtained from pancreatic intraepithelial neoplasias and pancreatic cancer. These analyses implicate the expression of DUSPs and genes related to stem cell biology in tumor progression during pancreatic cancer. Citation Format: Benjamin le Calvé, Xavier Deschenes-Ximard, Filippos Kottakis, Véronique Bourdeau, Frédéric Lessard, Karine Moineau-Vallée, Emmanuelle Saint-Germain, Julien Fitamant, Rushika Miriam Perera, Nabeel Bardeesy, Gerardo Ferbeyre. ERK/MAPK pathway inhibits tumorigenesis and cellular reprogramming of pancreatic cancer cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2154. doi:10.1158/1538-7445.AM2015-2154
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".