Identification of molecular marker associated with ovarian cancer prognosis using bioinformatics analysis and experiments

• Published in: Journal of cellular physiology Vol. 234; no. 7; pp. 11023 - 11036
• Main Authors: Zheng, Ming‐Jun, Li, Xiao, Hu, Yue‐Xin, Dong, Hui, Gou, Rui, Nie, Xin, Liu, Qing, Ying‐Ying, Hao, Liu, Juan‐Juan, Lin, Bei
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.07.2019
• Subjects: Annotations; Apoptosis; Bioinformatics; Biological activity; Biomarkers, Tumor; Blood coagulation; Cancer; Cell cycle; Cell proliferation; Computational Biology; Databases, Genetic; DEG; Diagnosis; Differentiation (biology); Encyclopedias; Female; Gene expression; Gene Expression Regulation, Neoplastic; Genes; Genomes; GEO database; Humans; Immunohistochemistry; Medical prognosis; Metabolism; Middle Aged; Molecular modelling; Neoplasm Proteins - genetics; Neoplasm Proteins - metabolism; Ovarian cancer; Ovarian Neoplasms - metabolism; Ovarian Neoplasms - pathology; p53 Protein; Pathogenesis; Phosphoserine; Phosphoserine aminotransferase; Prognosis; Proteins; PSAT1; Rap1 protein; Reproductive system; Risk analysis; Risk factors; Signal transduction; Signaling; Survival; Survival analysis; Transcriptome; Tumors; Tyrosine; Wnt protein; GEO database; immunohistochemistry; PSAT1; ovarian cancer; DEG; bioinformatics

Background Ovarian cancer is one of the three major malignant tumors of the female reproductive system, and the mortality associated with ovarian cancer ranks first among gynecologic malignant tumors. The pathogenesis of ovarian cancer is not yet clearly defined but elucidating this process would be...