Identifying the mRNAs associated with Bladder cancer recurrence

Autor: Zhang Zhihui, Dayin Chen, Zhenguo Luo, Hui-Feng Cao, Junjuan Yu, Liang Cheng
Rok vydání: 2020
Předmět:
Collagen Type IV
Male
Oncology
Cancer Research
medicine.medical_specialty
Multivariate statistics
Urinary Bladder
Datasets as Topic
Down-Regulation
Biology
Collagen Type I
Disease-Free Survival
Internal medicine
Protein Interaction Mapping
Biomarkers
Tumor
Genetics
medicine
Humans
Gene Regulatory Networks
0501 psychology and cognitive sciences
Protein Interaction Maps
RNA
Messenger
KEGG
Gene
Oligonucleotide Array Sequence Analysis
0505 law
Bladder cancer
Proportional hazards model
Microarray analysis techniques
Gene Expression Profiling
05 social sciences
General Medicine
Prognosis
medicine.disease
Up-Regulation
Gene Expression Regulation
Neoplastic
Urinary Bladder Neoplasms
Ppi network
050501 criminology
Female
Neoplasm Recurrence
Local
Toxicogenomics
Collagen Type V
050104 developmental & child psychology
Zdroj: Cancer Biomarkers. 28:429-437
ISSN: 1875-8592
1574-0153
DOI: 10.3233/cbm-190617
Popis: Objective To identify the mRNAs associated with bladder cancer (BC) recurrence. Methods The transcription profile of GSE31684 including 39 recurrent BC tumor samples and 54 non-recurrent BC tumor samples as well as transcription profile of GSE13507 including 36 recurrent BC tumor samples and 67 non-recurrent BC tumor samples were downlaoded from the Gene Expression Omnibus. Then, the differentially expressed genes (DEGs) were identified using linear models for microarray data (limma) and the intersections of DEGs from the two datasets were further screened. The weighed gene co-expression network analysis (WGCNA) was used to screen the modules related to BC recurrence. Protein-protein interaction (PPI) network analysis was used to analyze the genes interaction. Their functions were predicted by Gene Ontology and KEGG pathway enrichment. Moreover, The Comparative Toxicogenomics Database 2017 update (CTD) was used to search the BC related pathway. The univariate cox regression analysis was used to identify DEGs associated to the recurrence. Kaplan-Meier plots were used to illustrate recurrence free survival time (RFS). Results A total of 692 intersections DEGs were screened. WGCNA showed that 7 modules (2279 genes) were stable in both the datasets. A total of 169 intersection DEGs were mapped to the 7 modules. There existed 149 interaction relationships among 81 proteins (18 down-regulated and 63 up-regulated DEGs) in the PPI network. Two KEGG pathways including Focal adhesion and ECM-receptor interaction were enriched which were also found in the CTD. The univariate cox regression analysis showed that 3 DEGs (COL4A1, COL1A2 and COL5A1) were significant related to the prognosis. Multivariate cox regression analysis revealed that pathologic_N (N0-N1 vs N2-N3, p= 0.033) were independent prognostic factors for overall survival in patients with BC. Conclusion COL4A1, COL1A2 and COL5A1 could be associated with BC recurrence.
Databáze: OpenAIRE
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