Resumen de Identification and functional characterization of microRNAs reveal a potential role in gastric cancer progression

C.-Y. Li, G.-Y. Liang, W.-Z. Yao, J. Sui, X. Shen, Y.-Q. Zhang, H. Peng, W.-W. Hong, Y.-C. Ye, Z.-Y. Zhang, W.-H. Zhang, L.-H. Yin, Y.-P. Pu

• Purpose To investigate the potential candidate microRNA (miRNA) biomarkers for the clinical diagnosis, classification, and prognosis of gastric cancer (GC).

  Methods We use bioinformatics overlapping subclasses analysis to find the tumor grade and lymphatic metastasis-related GC specific miRNAs from the Cancer Genome Atlas (TCGA) database. Then, we further investigated these GC specific miRNAs distributions in different GC clinical features and their correlations overall survival on the basis of GC patients’ information and their related RNA sequencing profile from TCGA. Finally, we randomly selected some of key miRNAs use qRT-PCR to confirm the reliability and validity.

  Results 22 GC specific key miRNAs were identified (Fold-change >2, P < 0.05), 11 of them were discriminatively expressed with tumor size, grade, TNM stage and lymphatic metastasis (P < 0.05). In addition, nine miRNAs (miR-196b-5p, miR-135b-5p, miR-183-5p, miR-182-5p, miR-133a-3p, miR-486-5p, miR-144-5p, miR-129-5p and miR-145-5p) were found to be significantly associated with overall survival (log-rank P < 0.05). Finally, four key miRNAs (miR-183-5p, miR-486-5p, miR-30c-2-3p and miR-133a-3p) were randomly selected to validation and their expression levels in 53 newly diagnosed GC patients by qRT-PCR. Results showed that the fold-changes between TCGA and qRT-PCR were 100 % in agreement. We also found miR-183-5p and miR-486-5p were significantly correlated with tumor TNM stage (P < 0.05), and miR-30c-2-3p and miR-133a-3p were associated with tumor differentiation degree and lymph-node metastasis (P < 0.05). These verified miRNAs clinically relevant, and the bioinformatics analysis results were almost the same.

  Conclusion These key miRNAs may functions as potential candidate biomarkers for the clinical diagnosis, classification and prognosis for GC.