Abstract
Background
Gastric cancer (GC) is a major health problem and the third cause of cancer-induced deaths globally. Long non-coding RNAs (lncRNAs) are new cellular regulators in cancers whose contribution to GC carcinogenesis is still unknown to a large extent. This study aimed to investigate expression levels of bioinformatically ranked lncRNAs in GC tissues.
Methods
Using a bioinformatic approach, lncRNAs supposed to be involved in GC tumorigenesis were prioritized. Further, the top-ranked lncRNAs including HCG18, OIP5-AS1, FGD5-AS1, and LINC00657 were selected for experimental validation. Moreover, qPCR was used to validate bioinformatics findings in 35 GC and 35 paired adjacent normal gastric tissue samples (ANGTs). Receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) were generated to assess the diagnostic values of the lncRNAs.
Results
lncRNA-HCG18 showed to be the top-ranked lncRNA involved in GC, as identified by bioinformatics analysis. Additionally, HCG18, OIP5-AS1, FGD5-AS1, and LINC00657 expression levels significantly increased in GC tissue samples compared to ANGTs. The area under the curve (AUC) of HCG18, OIP5-AS1, FGD5-AS1, and LINC00657 were 0.80, 0.74, 0.73, and 0.71, respectively. Considering the findings, it was concluded that HCG18, OIP5-AS1, FGD5-AS1, and LINC00657 lncRNAs may contribute to GC tumorigenesis.
Conclusion
This study also found that the bioinformatic approach could be applied as an efficient approach to finding candidate lncRNAs relevant to GC progression.
Reduced expression of circRNA hsa_circ_0067582 in human gastric cancer and its potential diagnostic values
