Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization

• DOI: 10.3389/fcell.2021.631534
• Publication Date: 2021-04-12T06:51:47Z
• Authors: Lin Cui; Ping Wang; Dandan Ning; Jing Shao; Guiyuan Tan; Dajian Li; Xiaoling Zhong; Wanqi Mi; Chunlong Zhang; Shizhu Jin
• Keywords: Competing Endogenous RNA; Robustness

Gastric Cancer (GC) is a common cancer worldwide with high morbidity and mortality rate in Asia. Many prognostic signatures from genes non-coding RNA (ncRNA) levels have been identified by high-throughput expression profiling for GC. To date, there no reports on integrated optimization analysis based the GC global lncRNA-miRNA-mRNA network mechanism has not studied. In present work, specific regulatory (GCsLMM) was constructed ceRNA hypothesis combining miRNA-target interactions data of mine novel associated GC, we performed topological analysis, random walk restart algorithm, GCsLMM three levels, miRNA-, mRNA-, lncRNA-levels. We further obtained candidate calculating score analyzed robustness these combination strategy. The biological roles key were also explored. Finally, targeted PHF10 gene patterns independent datasets. findings this study will improve our understanding competing endogenous (ceRNA) mechanisms facilitate discovery biomarkers clinical guidelines.