Screening And Analysis Of Long Chain Non - Coding RNA Associated With Gastric Cancer

Objective: According to the latest cancer statistics in China, gastric cancer(GC) is the second most common malignant primary cancer and also the second most cause of cancer-related death. Quite a lot of patients are still diagnosed at an advanced stage in spite of the significant improvements in its diagnosis and treatment during recent years. These patients often miss the chance of radical resection, and the rate of relapse and metastasis remain high even if they receive radical surgery, postoperative adjuvant radiotherapy, chemotherapy, molecular-target therapy and biological therapy. The 5-year survival rate of patients with advanced GC is only 30%- 50%, probably because GC is a highly heterogeneous disease with complicated signaling pathways. The genetic dysregulation of many proto-oncogenes and tumor suppressor genes is thought to be an indispensable factor in the pathogenesis of GC. In the past few decades, not only the functions and mechanisms of small non-coding RNAs, especially that of mi RNAs have been fully understood, but also the newfound long non-coding RNAs(lnc RNAs) have been discovered play an important role in a variety of human diseases including GC. As the rapid development of gene chip and next generation sequencing, GC associated biomarkers have been constantly discovered. However most studies only focus on the single biomarker that can’t guarantee the accuracy in the diagnosis and prediction of GC. In this study, we performed GC associated lnc RNAs profile via the Human Lnc RNA Microarray, and choose some valuable lnc RNAs for the further validation and preliminary analysis of their clinical significance, so as to complete the "GC associated molecular biomarkers signature" applied to establish the diagnostic and predictive patterns of GC.Methods: We investigated the expression patterns of lnc RNAs and m RNAs in GC tumor samples(T) relative to those of matched adjacent non-tumor tissues(N) of five GC patients with GC family history. Differential expression profiles of lnc RNAs in GC were established. Three lnc RNAs with potential functions were choosed by searching the literatures. The expression levels of them in 72 GC tissues and GC cell lines were determined using quantitative real-time polymerase chain reaction. GO analysis and Pathway analysis were performed on differential expressed m RNAs. We have also analyzed the association between the expression levels of TUG1 and clinical pathology factors of GC patients as well as the prognostic values in order to find its clinical significance.Results: 3107 lnc RNAs were significantly differentially expressed in GC tumor tissues compared with adjacent non-tumor tissues via the screening of the Lnc RNA microarray. Up-regulated and down-regulated over two-fold were 1300 and 1807, respectively. Up-regulated and down-regulated over ten-fold were 50 and 482, respectively. Combining the analysis of literature, three valuable lnc RNAs: TUG1, HOTAIRM1, SNHG12 were validated by q RT-PCR in 72 clinical GC tumor tissues and their paired adjacent non-tumor tissues as well as GC cell lines. The results of q RT-PCR were consistent with the microarray data. According to the GO analysis of differentially expressed m RNAs, there were 1898 up-regulated and 1256 down-regulated m RNAs assigned to molecular function, 1976 up-regulated and 1349 down-regulated m RNAs assigned to cellular component, 1846 up-regulated and 1223 down-regulated m RNAs assigned to molecular function. In addition, we identified 47 up-regulated pathways and 12 down-regulated pathways through KEGG Pathway analysis. Compared with that in adjacent non-tumor tissues, the expression level of TUG1 in GC tumor tissues was significantly higher. The high expression level of TUG1 was also correlated with tumor invasion depth(P=0.002), lymph node metastasis(P=0.034), distant metastasis(P=0.029), TNM stage(P=0.008) and cancer embolus in vessels(P=0.045). The Cox’s proportional-hazard model for multivariate analysis revealed that TUG1 expression(P=0.031), together with lymph node metastasis(P<0.001), distant metastasis(P=0.002), TNM stage(P=0.039) and cancer embolus in vessels(P<0.001) were independently unfavorable prognostic factors for the overall survival of GC patients.Conclusion: We successfully established differentially expressed profiles of lnc RNAs in GC by lnc RNA microarray. The preliminary validation of several lnc RNAs using q RT-PCR also supported the results of the gene chip. Among them, TUG1 was significantly up-regulated in GC tumor tissues and associated with clinical pathology factors as well as prognosis of GC patients. Thus, TUG1 is more likely to be a new member of "GC associated molecular biomarkers signature" to play an important role in clinical.