scholarly journals Identification of Hub Genes in High-Grade Serous Ovarian Cancer Using Weighted Gene Co-Expression Network Analysis

2020 ◽  
Vol 26 ◽  
Author(s):  
Meijing Wu ◽  
Yue Sun ◽  
Jing Wu ◽  
Guoyan Liu
Keyword(s):  
Ovarian Cancer ◽  
Network Analysis ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Hub Genes

scholarly journals Integrated Weighted Gene Co-expression Network Analysis Reveals ALB Associated With Prognosis of High-grade Serous Ovarian Cancer

2021 ◽  
Author(s):  
Bo Wang ◽  
Shan Chao ◽  
Bo Guo
Keyword(s):  
Ovarian Cancer ◽  
Survival Analysis ◽  
Network Analysis ◽  
Single Gene ◽  
Enrichment Analysis ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Hub Genes ◽  
Hub Gene ◽  
Proteomic Data

Abstract Background: Ovarian cancer is the gynecologic tumor with the highest fatality rate, and high-grade serous ovarian cancer (HGSOC) is the most common and malignant type of ovarian cancer. One important reason for the poor prognosis of HGSOC is the lack of effective diagnostic and prognostic biomarkers. New biomarkers are necessary for improvement of treatment strategies and to ensure appropriate healthcare decisions.Methods: To construct the co-expression network of HGSOC samples, we applied weighted gene co-expression network analysis (WGCNA) to assess the proteomic data downloaded from Clinical Proteomic Tumor Analysis Consortium (CPTAC), and module-trait relationship was then analyzed and plotted in a heat map to choose key module associated with HGSOC. Enrichment analysis was performed on the genes in the key modules to explore the functional information in which these genes participate. Hub genes with high connectivity in key module were identified by Cytoscape software. Furthermore, the true hub gene was selected through survival analysis, followed by expression verification with transcriptome dataset from TCGA and GTEx. Finally, the potential biological functions of hub gene were analyzed via single-gene Gene Set Enrichment Analysis (GSEA).Results: After merging similar modules, a total of 9 modules were identified. Module-trait analysis revealed that the brown module (cor = 0.7) was significantly associated with HGSOC. The results of enrichment analysis of the genes in the brown module show that these genes were related to the functions of the extracellular matrix, the complement system and the blood system. Ten hub genes with the highest connectivity were selected by protein-protein interaction analysis. After survival analysis and expression verification of hub genes, only ALB was confirmed to be the true hub gene and positively correlated with HGSOC prognosis. Single gene GSEA revealed that ALB was associated with cell material degradation.Conclusion: We conducted the first gene co-expression analysis based on proteomic data from HGSOC samples, and found that ALB had prognostic value, which could be applied in the treatment of HGSOC in the future.

scholarly journals Characterization of Candidate Factors Associated With the Metastasis and Progression of High Grade Serous Ovarian Cancer

2021 ◽  
Author(s):  
Huiping Liu ◽  
Ling Zhou ◽  
Hongyan Cheng ◽  
Shang Wang ◽  
Wenqing Luan ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Primary Tumor ◽  
Gynecological Cancer ◽  
Wnt Signaling Pathway ◽  
The Cancer Genome Atlas ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Hub Genes ◽  
Bioinformatics Analyses ◽  
Factors Associated

Abstract Background. High grade serous ovarian cancer (HGSOC) is the highest cause of gynecological cancer-related mortality due to the extremely metastatic nature of this disease. The goal of this study is to explore and evaluate the profiles and characteristics of candidate factors associated with metastasis and progression of HGSOC.Methods. Transcriptomic data of HGSOC patients’ samples collected from the primary tumor and matched omental metastatic tumor were obtained from three independent studies in the NCBI GEO database. Genes significantly up-regulated and down-regulated were selected to evaluate the effects to prognosis and progression of ovarian cancer using data of ovarian cancer patients from The Cancer Genome Atlas (TCGA) database. Enrichment analysis for biological processes and pathways was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis. Furthermore, the hub genes immune landscapes were estimated by Tumor Immune Estimation Resource (TIMER) database.Results. 14 candidate genes included ADIPOQ, ALPK2, BARX1, CD37, CNR2, COL5A3, FABP4, FAP, GPR68, ITGBL1, MOXD1, PODNL1, SFRP2 and TRAF3IP3 were selected as up-regulated genes in metastatic tumors in every database while CADPS, GATA4, STAR and TSPAN8 were down-regulated. These 14 genes were significantly enriched for negative regulation of Wnt signaling pathway, fat cell differentiation, extracellular matrix organization. Finally, ALPK2, FAP, SFRP2 and GATA4, STAR, TSPAN8 were selected as hub genes that were found to be significantly associated with the survival and recurrence. All hub genes were correlated with several types of tumor microenvironmental cells infiltration significantly, especially for cancer associated fibroblasts and NK cells.Conclusions. This study indicates that screening for differentially expressed genes and pathways in HGSOC primary tumor and matched metastasis tumor using integrated bioinformatics analyses. In sum, we identify six hub genes correlated with the progression of HGSOC in our study, which might provide effective targets to predict prognosis and provide novel insights into immune-based therapy strategies of HGSOC well.

scholarly journals Sodium MRI with 3D-cones as a measure of tumour cellularity in high grade serous ovarian cancer

2019 ◽  
Vol 6 ◽  
pp. 156-162 ◽  
Author(s):  
Surrin S. Deen ◽  
Frank Riemer ◽  
Mary A. McLean ◽  
Andrew B. Gill ◽  
Joshua D. Kaggie ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Sodium Mri ◽  
Tumour Cellularity
Sign in / Sign up

Export Citation Format

Share Document