Potential long non-coding RNAs to be considered as biomarkers or therapeutic targets in gastric cancer

Abstract

Long non-coding RNAs are attracting the attention of researchers in many fields. These RNAs are longer than 200 nucleotides and do not encode any protein. A subset of them is reported to be strongly correlated with poor patient prognosis, suggesting a potential role in cancer progression (Esteller, 2011). Gastric cancer is one of the most common malignant tumors worldwide. Therefore, there is an urgent need to find genes which are helpful in the diagnosis, prognosis, and understanding of the molecular pathways of this cancer (Hajjari et al., 2013a). Finding novel molecular biomarkers of malignancy has been always important for clinical management. Like proteins, mRNAs, and miRNAs, lncRNAs show potentials as novel biomarkers and therapeutic targets in different cancer types (Zhang et al., 2013). However, there are a few reports on studying the relationship between gastric cancer progression and lncRNAs. Some useful clues for further researches seem necessary for deciphering the potential role of lncRNAs in gastric cancer. In this report, we present and highlight some evidences about the potential role of lncRNAs in gastric cancer based on the data indicated in Microarray databases. The results may give novel perspectives for further researches on the role of lncRNAs in gastric carcinogenesis. We used different databases including Oncomine, Gene Expression Atlas, Gene Expression Omnibus (GEO), and Array Express Databases to analyze the expression level of most recent cited and noted lncRNAs in studies on cancer progression (Niland et al., 2012; Zhang et al., 2013). The selected lncRNAs have been regarded as the most potential biomarkers in the studies on different cancer types (Zhang et al., 2013). The RNAs include H19, MALAT-1, HOTAIR, ANRIL, CRNDE, and MEG3. Some descriptions of these lncRNAs are presented below. Oncomine cancer microarray database was used to mine the lncRNA expression profile data according to the established methodology (Rhodes et al., 2007). Four publicly available datasets [Chen Gastric (Chen et al., 2003), DErrico Gastric (D'Errico et al., 2009), Wang Gastric (Wang et al., 2012), and Cho Gastric (Cho et al., 2011)] were inquired for our analysis. By using Oncomine and other microarray expression data accessible from GEO, Gene expression Atlas, and Array Express database, we found some significant differences of expression level for the lncRNAs. The datasets and clinopathological data of each study are presented in Table ​Table11. Table 1 Different datasets and their clinicopathological data used in the current study. Student's t-test was used for the differential expression analyses. Those which have significant differences (Fold change > 1.5, P-value < 0.01) between gastric cancer and normal tissues are brought in Table ​Table22. Table 2 Significant difference (Fold change > 1.5, P-value < 0.01) of the expression level of lncRNAs between gastric cancer types and normal tissues.