Identification of Key Candidate Genes and Pathways for Relationship between Ovarian Cancer and Diabetes Mellitus Using Bioinformatical Analysis

Document Type : Research Articles


1 Department of Toxicology, Guilin Medical University School of Public Health, Guilin, China.

2 Department of Gynaecology and Obstetrics, Kailuan General Hospital, Tangshan, Hebei, China.

3 Department of Nutrition, School of Medicine, Jinan University, Guangzhou, Guangdong, China.

4 Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.


Ovarian cancer is one of the three major gynecologic cancers in the world. The aim of this study is to find the
relationship between ovarian cancer and diabetes mellitus by using the genetic screening technique. By GEO database
query and related online tools of analysis, we analyzed 185 cases of ovarian cancer and 10 control samples from
GSE26712, and a total of 379 different genes were identified, including 104 up-regulated genes and 275 down-regulated
genes. The up-regulated genes were mainly enriched in biological processes, including cell adhesion, transcription of
nucleic acid and biosynthesis, and negative regulation of cell metabolism. The down-regulated genes were enriched in
cell proliferation, migration, angiogenesis and macromolecular metabolism. Protein-protein interaction was analyzed
by network diagram and module synthesis analysis. The top ten hub genes (CDC20, H2AFX, ENO1, ACTB, ISG15,
KAT2B, HNRNPD, YWHAE, GJA1 and CAV1) were identified, which play important roles in critical signaling
pathways that regulate the process of oxidation-reduction reaction and carboxylic acid metabolism. CTD analysis
showed that the hub genes were involved in 1,128 distinct diseases (bonferroni-corrected P<0.05). Further analysis by
drawing the Kaplan-Meier survival curve indicated that CDC20 and ISG15 were statistically significant (P<0.05). In
conclusion, glycometabolism was related to ovarian cancer and genes and proteins in glycometabolism could serve as
potential targets in ovarian cancer treatment.


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