The 44-kDa Pim-1 Kinase Phosphorylates BCRP/ABCG2 and Thereby Promotes Its Multimerization and Drug-resistant Activity in Human Prostate Cancer Cells
Bibliographic record
Abstract
We previously showed that the 44-kDa serine/threonine kinase Pim-1 (Pim-1L) can protect prostate cancer cells from apoptosis induced by chemotherapeutic drugs (Xie, Y., Xu, K., Dai, B., Guo, Z., Jiang, T., Chen, H., and Qiu, Y. (2006) Oncogene 25, 70-78). To further explore the mechanisms of Pim-1L-mediated resistance to chemotherapeutic drugs in prostate cancer cells, we employed a yeast two-hybrid screening to identify cellular proteins that were associated with Pim-1L, and we found the ABC transporter BCRP/ABCG2 as one of the potential interacting partners of Pim-1L. We also showed that the expression level of Pim-1L and BCRP was up-regulated in mitoxantrone and docetaxel-resistant prostate cancer cell lines. Pim-1L was co-localized with BCRP on the plasma membrane and induced phosphorylation of BCRP at threonine 362. Knocking-down Pim-1L expression in the drug-resistant prostate cancer cells abolished multimer formation of endogenous BCRP and resensitized the resistant cells to chemotherapeutic drugs suggesting that BCRP phosphorylation induced by Pim-1L was essential for its functionality. This is further corroborated by our finding that the plasma membrane localization and drug-resistant activity of BCRP were compromised by T362A mutation. Our data suggest that Pim-1L may protect prostate cancer cells from apoptosis, at least in part, through regulation of transmembrane drug efflux pump. These findings may provide a potential therapeutic approach by disrupting Pim-1 signaling to reverse BCRP-mediated multidrug resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".