Bibliographic record
Abstract
Transcription factors represent the crucial role of controlling gene transcription in cancer development and progression. However, their functions in gastric cancer have not been thoroughly characterized. For this study, we comprehensively evaluated the correlation between infiltration patterns of tumor microenvironment (TME) cells and TFs expression in the cohort of stomach adenocarcinoma (STAD) from TCGA database. We integrally explored differential expression panel and prognostic value of candidate TFs in TCGA-STAD cohort. Notably, we found a key transcription factor named HEYL, which its expression level was correlated with stromal component transformation of TME. HEYL was regularly high expressed in gastric cancer and correlated with patients' poor prognosis. Knockdown of HEYL prominently abrogated the tendency of cell proliferation, migration, and progression in gastric cancer. Consistently, overexpression of HEYL strikingly accelerated the gastric carcinoma development through activating oncogenic signaling pathways and transcriptional activation of cadherin 11 (CDH11). Our findings not only identified the close relationship between TFs and TME phenotype, but also emphasized the crucial importance of TFs, especially HEYL, which could be identified as a candidate biomarker to evaluate prognostic risk and therapeutic effect in gastric cancer.
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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 | 0.004 |
| 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 | 0.001 |
| 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".