scholarly journals Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation

2021 ◽  
Vol Volume 13 ◽  
pp. 707-721
Author(s):  
Yuzi Zhao ◽  
Jie Pi ◽  
Lihua Liu ◽  
Wenjie Yan ◽  
Shufang Ma ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Patients ◽  
Experimental Validation ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals Integrated Bioinformatics Analysis for Identification of the Hub Genes Linked with Prognosis of Ovarian Cancer Patients

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Xiaofeng Li ◽  
Qiu Wang ◽  
Zhicheng Wu ◽  
Jiantong Zheng ◽  
Ling Ji
Keyword(s):  
Ovarian Cancer ◽  
Survival Analysis ◽  
Cancer Patients ◽  
Differentially Expressed Genes ◽  
Early Stage ◽  
Central Carbon Metabolism ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Human Protein Atlas ◽  
Excessive Body Weight

Background. One of the most usual gynecological state of tumor is ovarian cancer and is a major reason of gynecological tumor-related global mortality rate. There have been multiple risk elements related to ovarian cancer like the background of past cases associated with breast cancer or ovarian cancer, or excessive body weight issues, case history of smoking, and untimely menstruation or menopause. Because of unclear expressions, more than 70% of the ovarian cancer patient cases are determined during the early stage. Material and Methods. GSE38666, GSE40595, and GSE66957 were the three microarray datasets which were analyzed using GEO2R for screening the differentially expressed genes. GO, Kyoto Encyclopedia of Genes, and protein expression studies were performed for analysis of hub genes. Then, survival analysis was performed for all the hub genes. Results. From the dataset, a total of 199 differentially expressed genes (DEGs) were identified. Through the KEGG pathway study, it was noted that the DEGs are mainly linked with the AGE-RAGE signaling pathway, central carbon metabolism, and human papillomavirus infection. The survival analysis showed 4 highly expressed hub genes COL4A1, SDC1, CDKN2A, and TOP2A which correlated with overall survival in ovarian cancer patients. Moreover, the expression of the 4 hub genes was validated by the GEPIA database and the Human Protein Atlas. Conclusion. The results have shown that all 4 hub genes were found to be upregulated in ovarian cancer tissues which predict poor prognosis in patients with ovarian cancer.

scholarly journals Abnormal methylation characteristics predict chemoresistance and poor prognosis in advanced high-grade serous ovarian cancer

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Li-yuan Feng ◽  
Bing-bing Yan ◽  
Yong-zhi Huang ◽  
Li Li
Keyword(s):  
Ovarian Cancer ◽  
Cancer Patients ◽  
Roc Analysis ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Chemotherapy Sensitivity ◽  
Kaplan Meier ◽  
Sensitivity Specificity

Abstract Background Primary or acquired chemoresistance is a key link in the high mortality rate of ovarian cancer. There is no reliable method to predict chemoresistance in ovarian cancer. We hypothesized that specific methylation characteristics could distinguish chemoresistant and chemosensitive ovarian cancer patients. Methods In this study, we used 450 K Infinium Methylation BeadChip to detect the different methylation CpGs between ovarian cancer patients. The differential methylation genes were analyzed by GO and KEGG Pathway bioinformatics analysis. The candidate CpGs were confirmed by pyrosequencing. The expression of abnormal methylation gene was identified by QRT-PCR and IHC. ROC analysis confirmed the ability to predict chemotherapy outcomes. Prognosis was evaluated using Kaplan–Meier. Results In advanced high-grade serous ovarian cancer, 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) remained hypermethylated in chemoresistant patients. The sensitivity, specificity and AUC of 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) methylation to predict chemotherapy sensitivity were 63.60–97.00%, 46.40–89.30% and 0.774–0.846. PFS of 6 candidate genes (ITGB6:cg21105318, cg07896068; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934) hypermethylation patients was significantly shorter. The expression of NCALD and LAMA3 in chemoresistant patients was lower than that of chemosensitive patients. Spearman analysis showed that NCALD and LAMA3 methylations were negatively correlated with their expression. Conclusions As a new biomarker of chemotherapy sensitivity, hypermethylation of NCALD and LAMA3 is associated with poor PFS in advanced high-grade serous ovarian cancer. In the future, further research on NCALD and LAMA3 will be needed to provide guidance for clinical stratification of demethylation therapy.

scholarly journals Identification of hub genes in key hallmarks of ovarian cancer via bioinformatics analysis

2021 ◽  
Vol 10 (2) ◽  
pp. 827-841
Author(s):  
Rongjia Su ◽  
Chengjuan Jin ◽  
Chengwen Jin ◽  
Menghua Kuang ◽  
Jiangdong Xiang
Keyword(s):  
Ovarian Cancer ◽  
Bioinformatics Analysis ◽  
Hub Genes

Immunoreactive score of Ep-CAM might predict survival in early ovarian cancer patients

2011 ◽  
Vol 71 (08) ◽  
Author(s):  
MJ Battista ◽  
J Steetskamp ◽  
N Mantai ◽  
S Gebhard ◽  
C Cotarelo ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Patients ◽  
Early Ovarian Cancer
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