Abstract 3507: STAT3beta suppresses tumorigenesis via modulating the phosphorylation dynamics and transcription activity of STAT3alpha in esophageal squamous cell carcinoma
Bibliographic record
Abstract
Abstract While the oncogenic role of STAT3 is well-documented, a number of studies have described that STAT3 carries tumor suppressor functions. We hypothesized that the relative abundance of STAT3α and STAT3β, the two STAT3 isoforms, dictate its exact functional roles in cancer cells. Using Western blots and a cohort of esophageal squamous cell carcinoma (ESCC)(n=91), we found that STAT3β significantly correlated with a shorter survival (P=0.030), whereas phospho-STAT3α-Tyr705 and total STAT3 did not carry significant prognostic value. Correlating with these observations, STAT3β significantly suppressed the oncogenic effects of STAT3α in ESCC cell lines in a soft-agar clonogenic assay. Interestingly, while STAT3β suppressed the transcriptional activity of STAT3α, it enhanced the phosphorylation of STAT3α-Tyr705 and its nuclear translocation. STAT3β also prolonged the phosphorylation of STAT3α-Tyr705 and increased its cytoplasmic localization following cytokine stimulation. Furthermore, the substantial increase in phospho-STAT3α-Tyr705 in this setting was related to STAT3β-mediated inhibition of dephosphorylation. Taken together, our findings have highlighted the tumor suppressor roles of STAT3β via its interactions with STAT3α at different levels. Our data also strongly suggests that, an accurate interpretation of the oncogenic activity of STAT3α in tumors based on the detection of nuclear STAT3 or phospho-STAT3-Tyr705 requires the knowledge of the STAT3β expression status. Citation Format: Haifeng Zhang, Raymond Lai, Enmin Li, Liyan Xu. STAT3beta suppresses tumorigenesis via modulating the phosphorylation dynamics and transcription activity of STAT3alpha in esophageal squamous cell carcinoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3507. doi:10.1158/1538-7445.AM2014-3507
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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 | 0.001 | 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".