A new apoptosis inhibitor, CIAPIN1 (cytokine-induced apoptosis inhibitor 1), mediates multidrug resistance in leukemia cells by regulating MDR-1, Bcl-2, and Bax
Bibliographic record
Abstract
We investigated the role of cytokine-induced apoptosis inhibitor 1 (CIAPIN1), a newly identified apoptosis inhibitor, in leukemia cell multidrug resistance (MDR) and its possible underlying mechanisms. CIAPIN1 was found to be overexpressed at the mRNA and protein levels in the vincristine-induced multidrug-resistant leukemia cell line HL-60/VCR, compared with HL-60, its parental cell line. In this study, we transfected HL-60 with a eukaryotic expression vector of CIAPIN1. In vitro drug sensitivity assays suggested that HL-60-CIAPIN1 cells conferred resistance to both P-glycoprotein (P-gp)-related and -unrelated drugs. Blocking CIAPIN1 expression in HL-60/VCR cells by CIAPIN1-specific small interfering RNA increased the cells' sensitivity to various chemotherapeutic drugs. Flow cytometry results suggested that CIAPIN1 expression could suppress adriamycin-induced apoptosis, accompanied by a decreased accumulation and increased release of adriamycin. Semiquantitative RT-PCR, Western blot analysis, and luciferase reporter assays suggested that CIAPIN1 could significantly upregulate the expression of MDR-1 and Bcl-2, the transcription of the MDR-1 gene, as well as downregulate the expression of Bax. Additionally, the inhibition of CIAPIN1 expression by RNA interference or P-gp inhibitor could partially reverse CIAPIN1-mediated MDR. Taken together, our findings suggest that downregulating CIAPIN1 could sensitize leukemia cells to chemotherapeutic drugs by downregulating MDR-1 and Bcl-2 and by upregulating Bax, yet not altering either glutathione-S-transferase activity or intracellular glutathione content in leukemia cells. Further study of CIAPIN1's function may reveal more of the mechanisms of leukemia MDR and result in the development of strategies to treat leukemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".