ARRDC3 as a Diagnostic and Prognostic Biomarker for Epithelial Ovarian Cancer Based on Data Mining
Authors Chen Y, Tian D, Chen X, Tang Z, Li K, Huang Z, Fu Y, Feng Y, Yang Z
Received 19 January 2021
Accepted for publication 22 February 2021
Published 22 March 2021 Volume 2021:14 Pages 967—981
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Scott Fraser
Yanli Chen,1– 3 Dan Tian,1 Xiaoqi Chen,1 Zhi Tang,1 Kuina Li,1 Zhijiong Huang,1 Yong Fu,4 Yanying Feng,4 Zhijun Yang1,3
1Department of Gynecologic Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China; 2Department of Obstetrics and Gynecology, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, People’s Republic of China; 3Key Laboratory of High-Incidence-Tumor Prevention & Treatment (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, People’s Republic of China; 4Department of Cardiopulmonary Center, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China
Correspondence: Zhijun Yang
Guangxi Medical University Cancer Hospital, No.71 Hedi Road, Nanning, 530021, Guangxi, People’s Republic of China
Email [email protected]
Cardiopulmonary Center, Guangxi Medical University Cancer Hospital, No. 71 Hedi Road, Nanning, 530021, People’s Republic of China
Email [email protected]
Purpose: The dysregulation of arrestin domain containing 3 (ARRDC3) has an important effect on oncogenesis and tumor progression in many cancers, including renal cell carcinoma and breast cancer. However, the role of ARRDC3 in ovarian cancer (OC) has not been reported.
Methods: The present study explored the diagnostic and prognostic roles of ARRDC3 in ovarian cancer using GEPIA, ONCOMINE, GEO, and Kaplan–Meier Plotter databases for training and validation. Then, we conducted a stratified analysis for clinicopathological factors using Kaplan–Meier Plotter and GEPIA databases. To further explore the mechanisms, we also used the MIST database to visualize the protein–protein interaction network of ARRDC3 associated with OC. The gene–gene interaction network was visualized by GeneMANIA plugin in Cytoscape 3.8.0 software, and the associated co-expression genes of ARRDC3 were analyzed by the cBioPortal database. The 100 top co-expression genes chosen for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used by the DAVID website.
Results: A significant difference in ARRDC3 mRNA expression was found between OC and normal ovary tissues. ARRDC3 could potentially be implicated in the diagnosis of OC. A high ARRDC3 mRNA expression level was associated with poor overall survival and progression-free survival. However, no significance was reported in respect to post progression survival. Except for histology, which had no prognostic value for PPS in stratified analysis, stratified analysis of other factors had prognostic value for OS, PFS, and PPS. Interestingly, we found a positive correlation between ARRDC3 expression and CD8+ T cells, macrophages, neutrophils, and dendritic cells, indicating that ARRDC3 might be associated with immune infiltration of these immune cells. Co-expression genes enrichment analysis found that they were involved in the Renin-angiotensin system pathway.
Conclusion: Differentially expressed ARRDC3 might be a potential prognostic and diagnostic marker in Ovarian Cancer.
Keywords: biomarker, diagnosis, prognosis, ovarian neoplasms
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