Chronic Inhibition of STAT3/STAT5 in Treatment-Resistant Human Breast Cancer Cell Subtypes: Convergence on the ROS/SUMO Pathway and Its Effects on xCT Expression and System xc- Activity
Bibliographic record
Abstract
Pharmacologically targeting activated STAT3 and/or STAT5 has been an active area of cancer research. The cystine/glutamate antiporter, system xc-, contributes to redox balance and export of intracellularly produced glutamate in response to up-regulated glutaminolysis in cancer cells. We have previously shown that blocking STAT3/5 using the small molecule inhibitor, SH-4-54, which targets the SH2 domains of both proteins, increases xCT expression, thereby increasing system xc- activity in human breast cancer cells. The current investigation demonstrates that chronic SH-4-54 administration, followed by clonal selection of treatment-resistant MDA-MB-231 and T47D breast cancer cells, elicits distinct subtype-dependent effects. xCT mRNA and protein levels, glutamate release, and cystine uptake are decreased relative to untreated passage-matched controls in triple-negative MDA-MB-231 cells, with the inverse occurring in estrogen-responsive T47D cells. This "ying-yang" effect is linked with a shifted balance between the phosphorylation status of STAT3 and STAT5, intracellular ROS levels, and STAT5 SUMOylation/de-SUMOylation. STAT5 emerged as a definitive negative regulator of xCT at the transcriptional level, while STAT3 activation is coupled with increased system xc- activity. We propose that careful classification of a patient's breast cancer subtype is central to effectively targeting STAT3/5 as a therapeutic means of treating breast cancer, particularly given that xCT is emerging as an important biomarker of aggressive cancers.
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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 | 0.000 | 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".