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Li C.-Y.,Nanjing Southeast University | Liang G.-Y.,Nanjing Southeast University | Yao W.-Z.,Nanjing Southeast University | Sui J.,Nanjing Southeast University | And 9 more authors.
Clinical and Translational Oncology | Year: 2016

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. © 2016 Federación de Sociedades Españolas de Oncología (FESEO) Source


Li C.,Nanjing Southeast University | Liang G.,Nanjing Southeast University | Yao W.,Nanjing Southeast University | Sui J.,Nanjing Southeast University | And 8 more authors.
Oncology Reports | Year: 2016

Gastric cancer (GC) is one of the most lethal malignancies worldwide. To reduce its high mortality, sensitive and specific biomarkers for early detection are urgently needed. Recent studies have reported that tumor-specific long non-coding RNAs (lncRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In the present study, lncRNA and mRNA expression profiling of GC specimens and their paired adjacent non-cancerous tissues was performed. Differentially expressed lncRNAs and mRNAs were identified through microarray analysis. The function of differential mRNA was determined by gene ontology and pathway analysis and the functions of lncRNAs were studied by constructing a co-expression network to find the relationships with corresponding mRNAs. We connected the co-expression network, mRNA functions, and the results of the microarray profile differential expression and selected 14 significantly differentially expressed key lncRNAs and 21 key mRNAs. Quantitative RT-PCR (qRT-PCR) was conducted to verify these key RNAs in 50 newly diagnosed GC patients. The data showed that RP5-919F19, CTD-2541M15 and UCA1 was significantly higher expressed. AP000459, LOC101928316, RP11-167N4 and LINC01071 expression was significantly lower in 30 advanced GC tumor tissues than adjacent nontumor tissues P<0.05. Then, we further validated the above significant differential expression candidate lncRNAs in 20 early stage GC patients. Results showed that CTD-2541M15 and UCA1 were significantly higher expressed, AP000459, LINC01071 and MEG3 expression was significantly lower in 20 early stage GC patient tumor tissues than adjacent non-tumor tissues (P<0.05). In addition, expression of these lncRNAs shows gradual upward trend from early stage GC to advanced GC. Furthermore, conditional logistic regression analysis revealed the aberrant expression of CTD-2541M15, UCA1 and MEG3 closely linked with GC. There is a set of differentially expressed lncRNAs in GC which may be associated with the progression and development of GC. The differential expression profiles of lncRNAs in GC may be promising biomarkers for the early detection and early screening of high-risk populations. Source


Li C.-Y.,Nanjing Southeast University | Liang G.-Y.,Nanjing Southeast University | Yao W.-Z.,Nanjing Southeast University | Sui J.,Nanjing Southeast University | And 9 more authors.
International Journal of Oncology | Year: 2016

Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05). The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis. Source

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