A Prospective Tumour Marker for Breast Cancer: YWHAB and Its Role in Promoting Oncogenic Phenotypes
Bibliographic record
Abstract
Background: YWHAB (14-3-3 Beta) was found in the secretome of miR-526b and miR-655 overexpressed breast cancer (BRCA) cell lines. The potential of YWHAB as a therapeutic target or biomarker for BRCA is investigated here. Methods: After YWHAB was knocked down with siRNA, BRCA cell lines were used for in vitro assays (proliferation, migration, epithelial-to-mesenchymal transition). In silico analysis and in situ validation with BRCA plasma and biopsy tissues were used to test YWHAB’s biomarker potential. Results: YWHAB RNA and protein expression are elevated in aggressive BRCA cell lines, and the knockdown of YWHAB inhibited cell migration, proliferation, and EMT in all subtypes of tumour cell lines. YWHAB expression is significantly higher in BRCA biopsy tissue and blood plasma compared to control tissues and benign plasmas. YWHAB is expressed in all hormonal subtypes of BRCA tumours and has shown increased expression in advanced tumour stages. Its high expression is linked to poor patient survival. YWHAB is a sensitivity tumour marker (AUC of 0.7340, p = 0.0012) but is not a promising blood biomarker. Nevertheless, combined with pri-miR-526b, YWHAB mRNA expression shows potential as a BRCA blood biomarker (AUC of 0.711, p = 0.032), which must be validated in a larger sample set. Conclusion: We elucidate the novel role of YWHAB as a therapeutic target in BRCA, given that its inhibition mitigated aggressive phenotypes across all tumour subtypes, including triple-negative breast cancer. Furthermore, YWHAB emerges as a potential tumour marker, exhibiting high expression in metastatic BRCA and correlating with poor patient survival; however, it is not a sensitive blood biomarker. Keywords: breast cancer, microRNA, miRNA, miR-526b, miR-655, YWHAB, 14-3-3 Beta, biomarker, migration, epithelial to mesenchymal transition, proliferation
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".