Bioinformatic Analysis Identified Potentially Prognostic Long Noncoding RNAs and MicroRNAs for Gastric Cancer

• Published in: BioMed research international Vol. 2021; pp. 6683136 - 14
• Main Authors: Guo, Jiao, Liu, Yongda, Zhao, Ping
• Format: Journal Article
• Language: English
• Published: United States Hindawi 10.12.2021; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Analysis; Antigens; Atrophy; Biomarkers; Cancer; Care and treatment; Computational biology; Computational Biology - methods; Cyclic GMP; Diagnosis; Diagnostic Tests, Routine - methods; Female; Gastric cancer; Genes; Genomes; Health aspects; Humans; Kaplan-Meier Estimate; Male; MAP kinase; Medical prognosis; Metastases; MicroRNAs; MicroRNAs - genetics; Middle Aged; miRNA; Multivariate Analysis; Non-coding RNA; Ontology; Pathogenesis; Prognosis; Regression analysis; RNA; RNA, Long Noncoding - genetics; Signal Transduction - genetics; Software; Statistical analysis; Stomach cancer; Stomach Neoplasms - genetics; Stomach Neoplasms - pathology; Tumors; China
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2021/6683136

Gastric cancer (GC) is the fifth most common malignant tumor in the world. The present study was performed to discover the potential diagnostic and therapeutic long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) of GC. Data used in this study to identify differentially expressed lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) were obtained from 187 GC tissues and 32 adjacent nontumor tissues. The total clinical data on GC included 187 cases. The above data were from the TCGA database. RStudio/Bioconductor software was used to conduct univariate analysis, the least absolute shrinkage and selection operator (LASSO) Cox, and multivariate Cox proportional risk regression for the DElncRNAs and DEmiRNAs. Clinical information was analyzed through univariate and multivariate Cox analysis. Results: five lncRNAs (AC007785.3, AC079385.3, LINC00392, LINC01729, and U95743.1) and two miRNAs (hsa-miR-3174, hsa-miR-605) were proven to be independent prognostic indicators of GC. Results of the Kaplan-Meier survival analysis showed that AC007785.3, AC079385.3, LINC01729, miR-3174, and miR-605 were significantly correlated with OS of GC. The target genes of AC079385.3, miR-3174, and miR-605 were obtained and clustered mainly on MAPK and cGMP-PKG signaling pathways. The clinical data showed that age and clinicopathologic stage were correlated with the prognosis of GC. Furthermore, AC007785.3 was associated with metastasis of GC, and miR-3174 was associated with the primary tumor condition of GC. We identified three lncRNAs (AC007785.3, AC079385.3, LINC01729), two miRNAs (miR-3174, miR-605), and clinical factors related to the pathogenesis and prognosis of GC. Our predicted results provide a possible entry point for the study of prognostic markers for GC.