Overexpression of Ubiquitin-Conjugating Enzyme E2C Is Associated with Worsened Prognosis in Prostate Cancer.
Xiaobo WuXingbo LongChenkai MaYin Celeste CheukMengbo HuJimeng HuHaowen JiangPublished in: International journal of molecular sciences (2022)
To evaluate the role of ubiquitin-conjugating enzyme E2C (UBE2C) in prostate cancer (PCa) progression and prognosis, the TCGA and our PCa tissue microarray cohort were included in the study. Weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization were used to cluster patients and to screen genes that play a vital role in PCa progression (hub gene). Immunohistochemistry staining was used to evaluate the protein level of UBE2C in prostatic tissues. Through WGCNA, we found a gene co-expression module (named the purple module) that is strongly associated with the Gleason score, pathologic T stage, and biochemical recurrent status. Genes in the purple module are enriched in cell cycle and P53 signaling and help us to cluster patients into two groups with distinctive biochemical recurrent survival rates and TP53 mutation statuses. Further analysis showed UBE2C served as a hub gene in the purple module. The expression of UBE2C in PCa was significantly higher than that in paracancerous tissues and was remarkably associated with pathologic grade, Gleason score, and prognosis in PCa patients. To conclude, UBE2C is a PCa-progress-related gene and a biomarker for PCa patients. Therapy targeting UBE2C may serve as a promising treatment of PCa in the future.
Keyphrases
- prostate cancer
- end stage renal disease
- newly diagnosed
- ejection fraction
- genome wide
- chronic kidney disease
- cell cycle
- poor prognosis
- prognostic factors
- radical prostatectomy
- peritoneal dialysis
- gene expression
- squamous cell carcinoma
- radiation therapy
- stem cells
- genome wide identification
- small molecule
- computed tomography
- patient reported outcomes
- lymph node
- drug delivery
- patient reported
- cancer therapy
- replacement therapy
- bioinformatics analysis