STAT3 but Not HIF-1α Is Important in Mediating Hypoxia-Induced Chemoresistance in MDA-MB-231, a Triple Negative Breast Cancer Cell Line
Bibliographic record
Abstract
Hypoxia-induced chemoresistance (HICR) is a well-recognized phenomenon, and in many experimental models, hypoxia inducible factor-1α (HIF-1α) is believed to be a key player. We aimed to better understand the mechanism underlying HICR in a triple negative breast cancer cell line, MDA-MB-231, with a focus on the role of HIF-1α. In this context, the effect of hypoxia on the sensitivity of MDA-MB-231 cells to cisplatin and their stem-like features was evaluated and the role of HIF-1α in both phenomena was assessed. Our results showed that hypoxia significantly increased MDA-MB-231 resistance to cisplatin. Correlating with this, intracellular uptake of cisplatin was significantly reduced under hypoxia. Furthermore, the stem-like features of MDA-MB-231 cells increased as evidenced by the significant increases in the expression of ATP-binding cassette (ABC) drug transporters, the proportion of CD44+/CD24− cells, clonogenic survival and cisplatin chemoresistance. Under hypoxia, both the protein level and DNA binding of HIF-1α was dramatically increased. Surprisingly, siRNA knockdown of HIF-1α did not result in an appreciable change to HICR. Instead, signal transducer and activator of transcription 3 (STAT3) activation was found to be important. STAT3 activation may confer HICR by upregulating ABC transporters, particularly ABCC2 and ABCC6. This study has demonstrated that, in MDA-MB-231 cells, STAT3 rather than HIF-1α is important in mediating HICR to cisplatin.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".