Multidrug Resistance-Associated Protein 2 Expression Is Upregulated by Adenosine 5’-Triphosphate in Colorectal Cancer Cells and Enhances Their Survival to Chemotherapeutic Drugs
Bibliographic record
Abstract
Extracellular adenosine 5'-triphosphate (ATP) is a signaling molecule that induces a plethora of effects ranging from the regulation of cell proliferation to modulation of cancerous cell behavior. In colorectal cancer, ATP was reported to stimulate epithelial cell proliferation and possibly promote resistance to anti-cancer treatments. However, the exact role of this danger-signaling molecule on cancerous intestinal epithelial cells (IECs) in response to chemotherapeutic agents remains unknown. To address how ATP may influence the response of cancerous IECs to chemotherapeutic agents, we used Caco-2 cells, which display enterocyte-like features, to determine the effect of ATP on the expression of multidrug resistance-associated protein 2 (MRP2). Gene and protein expression were determined by quantitative real-time PCR (qRT-PCR) and Western blotting. Resistance to etoposide, cisplatin and doxorubicin was determined by MTT assays in response to ATP stimulation of Caco-2 cells and in cells for which MRP2 expression was down-regulated by shRNA. ATP increased the expression of MRP2 at both the mRNA and protein levels. MRP2 expression involved an ATP-dependent stimulation of the MEK/ERK signaling pathway that was associated with an increase in relative resistance of Caco-2 cells to etoposide. Abolition of MRP2 expression using shRNA significantly reduced the protective effect of MRP2 toward etoposide as well as to cisplatin and doxorubicin. This study describes the mechanism by which ATP may contribute to the chemoresistance of cancerous IECs in colorectal cancer. Given the heterogeneity of colorectal adenocarcinoma responses to anti-cancer drugs, these findings call for further study to understand the role of P2 receptors in cancer drug therapy and to develop novel therapies aimed at regulating P2 receptor activity.
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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 | 0.000 |
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 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".