A Panel of Emerging EMT Genes Identified in Malignant Mesothelioma
Bibliographic record
Abstract
Abstract Malignant mesothelioma (MESO) is a highly aggressive cancer with poor prognosis. Epithelial-mesenchymal transition (EMT) is a critical process in malignancies involved in tumor angiogenesis, progression, invasion and metastasis, immunosuppressive microenvironment and therapy resistance. However, there is a lack of specific biomarkers to identify EMT in MESO. Biphasic MESO with dual phenotypes could be an optimal model to study EMT process. Using a powerful EMTome to investigate EMT gene signature, we identified a panel of EMT genes COL5A2, ITGAV, SPARC and ACTA2 in MESO. In combination with TCGA database, Timer2.0 and other resources, we observed that overexpression of these emerging genes is positively correlated with immunosuppressive infiltration, and an unfavorable factor to patient survival in MESO. The expression of these genes was confirmed in our patients and human cell lines. Our findings suggest that these genes may be novel targets for therapeutics and prognosis in MESO and other types of cancers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".