Downregulation of CYB5D2 is associated with breast cancer progression
Bibliographic record
Abstract
We report here that CYB5D2 is associated with tumor suppression function in breast cancer (BC). CYB5D2 expression was significantly reduced in tamoxifen resistant MCF7 cells and in MCF7 cell-derived xenografts treated with TAM. CYB5D2 overexpression induced apoptosis in MCF7 cells; CYB5D2 knockdown enhanced MCF7 cell proliferation. Using the TCGA and Curtis datasets within the Oncomine database, CYB5D2 mRNA expression was downregulated in primary BCs vs breast tissues and HER2-positive or triple negative BCs vs estrogen receptor (ER)-positive BCs. Using the TCGA and Metabric datasets (n = 817 and n = 2509) within cBioPortal, 660 and 4891 differentially expressed genes (DEGs) in relation to CYB5D2 were identified. These DEGs were enriched in pathways governing cell cycle progression, progesterone-derived oocyte maturation, oocyte-meiosis, estrogen-mediated S-phase entry, and DNA metabolism. CYB5D2 downregulation decreased overall survival (OS, p = 0.0408). A CYB5D2-derived 21-gene signature was constructed and robustly correlated with OS shortening (p = 5.72e-12), and independently predicted BC deaths (HR = 1.28; 95% CI 1.08-1.52; p = 0.004) once adjusting for known clinical factors. CYB5D2 reductions displayed relationship with mutations in PIK3CA, GATA3, MAP3K1, CDH1, TP53 and RB1. Impressively, 85% (560/659) of TP53 mutations occurred in the 21-gene signature-positive BC. Collectively, we provide the first evidence that CYB5D2 is a candidate tumor suppressor of 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 | 0.000 | 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) | 0.002 | 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".