Analysis of Gene Expression in Bladder Cancer: Possible Involvement of Mitosis and Complement and Coagulation Cascades Signaling Pathway
Bibliographic record
Abstract
This study focused on identifying bladder cancer (BC)-associated genes, transcription factors (TFs), and microRNAs (miRNAs). Two microarray data sets GSE37815 and GSE40355 were utilized to screen common differentially expressed genes (DEGs) associated with BC. Then, functional enrichment analysis was performed for elucidating the involved functions of DEGs. Subsequently, the protein–protein interaction (PPI) network and submodule of PPI network were analyzed. Finally, the regulation relationships of TF–DEGs and miRNA–DEGs were obtained to construct miRNA–target–TF regulatory network. DEGs were identified across BC and normal bladder tissues samples. Functional enrichment analysis results showed that most upregulated DEGs were closely associated with the Gene Ontology function of “mitotic spindle assembly checkpoint” and pathway of “Cell cycle,” whereas most downregulated DEGs were significantly associated with “Complement and coagulation cascades” pathway (e.g., A2M and F13A1) and “Ras signaling pathway” (e.g., GNG11). DEGs such as F13A1 and A2M were highlighted in the PPI network and Submodule 1. In addition, three centromere-associated CENPK, CENPF, and CENPO were enriched in Submodule 2. Moreover, miR-519d had high degree in the regulatory network and CENPO was predicted to be one target of miR-519d. The upregulated CENPK, CENPF, and CENPO, and downregulated A2M, F13A1, and GNG11 might contribute to the progression of BC. In addition, the downregulated miR-519d might lead to the development of BC by upregulating the expression of CENPO. However, future investigation of those findings should be needed.
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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 | 0.002 |
| 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".