C-Y Li1, G-Y Liang2, W-Z Yao1, J Sui1, X Shen1, Y-Q Zhang1, H Peng1, W-W Hong1, Y-C Ye3, Z-Y Zhang3, W-H Zhang3, L-H Yin1, Y-P Pu1. 1. Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, 87 Dingjiaqiao Street, Nanjing, 210009, Jiangsu, People's Republic of China. 2. Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, 87 Dingjiaqiao Street, Nanjing, 210009, Jiangsu, People's Republic of China. lianggeyu@163.com. 3. Gansu Wuwei Tumor Hospital, Wuwei, 733000, Gansu, People's Republic of China.
Abstract
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.
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 tumorTNM 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.
Authors: Ismael Riquelme; Oscar Tapia; Pamela Leal; Alejandra Sandoval; Matthew G Varga; Pablo Letelier; Kurt Buchegger; Carolina Bizama; Jaime A Espinoza; Richard M Peek; Juan Carlos Araya; Juan Carlos Roa Journal: Cell Oncol (Dordr) Date: 2015-10-12 Impact factor: 6.730
Authors: Tung On Yau; Chung Wah Wu; Ceen-Ming Tang; Yingxuan Chen; Jingyuan Fang; Yujuan Dong; Qiaoyi Liang; Simon Siu Man Ng; Francis Ka Leung Chan; Joseph Jao Yiu Sung; Jun Yu Journal: Oncotarget Date: 2016-01-12