Decreased NMIIA heavy chain phosphorylation at S1943 promotes mitoxantrone resistance by upregulating BCRP and N-cadherin expression in breast cancer cells
Bibliographic record
Abstract
Mitoxantrone (MX) is an effective treatment for breast cancer; however, high efflux of MX that is accomplished by breast cancer resistance protein (BCRP) leads to acquired multidrug resistance (MDR), reducing MX's therapeutic efficacy in breast cancer. Non-muscle myosin IIA (NMIIA) and its heavy phosphorylation at S1943 have been revealed to play key roles in tumor metastasis and progression, including in breast cancer; however, their molecular function in BCRP-mediated MDR in breast cancer remains unknown. In this study, we revealed that the expression of NMIIA heavy chain phosphorylation at S1943 was downregulated in BCRP-overexpressing breast cancer MCF-7/MX cells, and stable expression of NMIIA-S1943A mutant increased BCRP expression and promoted the resistance of MCF-7/MX cells to MX. Meanwhile, NMIIA S1943 phosphorylation induced by epidermal growth factor (EGF) was accompanied by the downregulation of BCRP in MCF-7/MX cells. Furthermore, stable expression of NMIIA-S1943A in MCF-7/MX cells resulted in upregulation of N-cadherin and the accumulation of β-catenin on the cell surface, which inhibited the nucleus translocation of β-catenin and Wnt/β-catenin-based proliferative signaling. EGF stimulation of MCF-7/MX cells showed the downregulation of N-cadherin and β-catenin. Our results suggest that decreased NMIIA heavy phosphorylation at S1943 increases BCRP expression and promotes MX resistance in breast cancer cells via upregulating N-cadherin expression.
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 | 0.000 |
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".