YONGHUI YU1,#, SONGHUI XU2,#, ERYONG ZHAO3,#, YONGSHUN DONG1, JINBIN CHEN1, BOQI RAO1, JIE ZENG4, LEI YANG1, JIACHUN LU1, FUMAN QIU1,4,*
BIOCELL, Vol.46, No.4, pp. 999-1011, 2022, DOI:10.32604/biocell.2022.017004
Abstract The outcomes of ovarian cancer are complicated and usually unfavorable due to their diagnoses at a late stage. Identifying the efficient prognostic biomarkers to improve the survival of ovarian cancer is urgently warranted. The survival-related pseudogenes retrieved from the Cancer Genome Atlas database were screened by univariate Cox regression analysis and further assessed by least absolute shrinkage and selection operator (LASSO) method. A risk score model based on the prognostic pseudogenes was also constructed. The pseudogene-mRNA regulatory networks were established using correlation analysis, and their potent roles in the ovarian cancer progression were uncovered by functional enrichment analysis. Lastly, ssGSEA… More >
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