Enabled homolog shown to be a potential biomarker and prognostic indicator for breast cancer by bioinformatics analysis
Bibliographic record
Abstract
BACKGROUND: Human enabled homolog (ENAH; also known as human ortholog of mammalian enabled, hMENA) is a member of the enabled/vasodilator-stimulated phosphor protein family that regulates fibroblast movement and nervous system development. The ENAH over-expression promotes breast cancer (BC) cell invasion and metastasis. METHODS: We studied ENAH mRNA expression in various tumors and normal tissues using the ONCOMINE database, and in an array of cancer cell lines using Cancer Cell Line Encyclopedia data. We also investigated the prognostic value of ENAH expression in patients with BC using Kaplan-Meier plots. RESULTS: Compared with normal tissues, ENAH expression levels were markedly elevated in BC. We identified a correlation between low ENAH and superior relapse-free survival (RFS) of patients with BC; specifically, those with ER(-), HER-2(+), Grade 3 and wild-type TP53 subtypes. Additionally, a correlation was detected between low ENAH and prolonged overall survival of patients with luminal B disease. CONCLUSION: ENAH is a potential biomarker and important prognostic factor in BC.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".