Phosphorylation of STAT1 serine 727 enhances platinum resistance in uterine serous carcinoma
Bibliographic record
Abstract
Uterine serous carcinoma (USC) is a highly aggressive histological subtype of endometrial cancers harboring highly metastatic and chemoresistant features. Our previous study showed that STAT1 is highly expressed in USC and acts as a key molecule that is positively correlated with tumor progression, but it remains unclear whether STAT1 is relevant to the malicious chemorefractory nature of USC. In the present study, we investigated the regulatory role of STAT1 toward platinum-cytotoxicity in USC. STAT1 suppression sensitized USC cells to increase cisplatin-mediated apoptosis (p < 0.001). Furthermore, phosphorylation of STAT1 was prominently observed on serine-727 (pSTAT1-Ser727), but not on tyrosine-701, in the nucleus of USC cells treated with cisplatin. Mechanistically, the inhibition of pSTAT1-Ser727 by dominant-negative plasmid elevated cisplatin-mediated apoptosis by increasing intracellular accumulation of cisplatin through upregulation of CTR1 expression. TBB has an inhibitory effect on casein kinase 2 (CK2), which phosphorylate STAT1 at serine residues. Sequential treatment with TBB and cisplatin on USC cells greatly reduced nuclear pSTAT1-Ser727, enhanced intracellular accumulation of cisplatin, and subsequently increased apoptosis. Tumor load was significantly reduced by combination therapy of TBB and cisplatin in in vivo xenograft models (p < 0.001). Our results collectively suggest that pSTAT1-Ser727 may play a key role in platinum resistance as well as tumor progression in USC. Thus, targeting the STAT1 pathway via CK2 inhibitor can be a novel method for attenuating the chemorefractory nature of USC.
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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) | 0.001 | 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".