A New Strategy to Identify ceRNA-Based CCDC144NL-AS1/SERPINE1 Regulatory Axis as a Novel Prognostic Biomarker for Stomach Adenocarcinoma via High Throughput Transcriptome Data Mining and Computational Verification

Abstract

Stomach adenocarcinoma (STAD) is one of the most malignant cancers that endanger human health. There is growing evidence that competitive endogenous RNA (ceRNA) regulatory networks play an important role in various human tumors. However, the complexity and behavioral characteristics of the ceRNA network in STAD are still unclear. In this study, we constructed a ceRNA regulatory network to identify the potential prognostic biomarkers associated with STAD. The expression profile of lncRNA, miRNA, and mRNA was downloaded from The Cancer Genome Atlas (TCGA). After performing bioinformatics analysis, the CCDC144NL-AS1/hsa-miR-145-5p/SERPINE1 ceRNA network associated to STAD prognosis of STAD was obtained. The CCDC144NL-AS1/SERPINE1 axis in the ceRNA network was identified by correlation analysis and considered as a clinical prognosis model by Cox regression analysis. In addition, methylation analysis indicated that the abnormal upregulation of CCDC144NL-AS1/SERPINE1 axis might be related to the aberrant methylation of some sites, and immune infiltration analysis suggested that CCDC144NL-AS1/SERPINE1 axis probably influences the alteration of tumor immune microenvironment and the occurrence and development of STAD. In particular, the CCDC144NL-AS1/SERPINE1 axis based on the ceRNA network constructed in the present study might be an important novel factor correlating with the diagnosis and prognosis of STAD.

Data mining combines bioinformatics discover immunoinfiltration-related gene SERPINE1 as a biomarker for diagnosis and prognosis of stomach adenocarcinoma

“…In recent years, bioinformatics research related to transcriptomic studies and high-throughput sequencing have led to the discovery of more and more genes involved in driving. A few studies have found a novel prognostic biomarker for STAD by high throughput transcriptome data mining 5 . The tumor microenvironment (TME) refers to the non-cancerous cells and components that are presented in the tumor, including the molecules they produce and release.…”

Competing endogenous RNA networks reveal long non-coding RNAs as potential prognostic biomarkers in gastric cancer: A systematic review and meta-analysis

“…Besides, according to the information of multivariate survival analysis, the pooled HRs with 95% CI was calculated. Four studies (23,(27)(28)(29) with clear basis of HR examination were considered for pooled examination of multivariate reports. Furthermore, lncRNAs which were reported at least three times according to the univariate or multivariate survival analysis were meta-analized.…”

“…Among the included studies in the current meta-analysis, three (22,24,29) and two (19,23) studies introduced CCDC144NL-AS1 and LINC01094 as prognostic biomarkers in GC, respectively. As mentioned above, three ceRNA network studies reported CCDC144NL-AS1 as prognostic biomarker in GC.…”

“…Higher expression of 57 and lower expression of 13 lncRNAs were associated with shorter OS. Studies with multivariate analysis reported four lncRNAs with clear basis of HR including LINC01094, CCDC144NL-AS1, LINC00205, and MAGI2-AS3 (23,(27)(28)(29). The pooled HRs for univariate reports was 1.01 (95% CI 1.01-1.02, p-value<0.001, Figure 2).…”

“…Forest plots of these lncRNAs have been presented (Figure 4a and 4b). HR: hazard ratio, lncRNA: long non-coding RNA CI: confidence interval Three ceRNA network studies have reported prognostic effects of CCDC144NL-AS1 based on three univariate and one multivariate analyses (22,24,29). On the other hand, LINC01094 was reported according to two studies based on two univariate and one multivariate analyses (19,23).…”