RESUMO
Gastric cancer (GC) is a prominent public health issue and ranks as the third most prevalent cause of cancer-related mortality on a global scale. The role of long non-coding RNAs (lncRNAs) in cancer is not yet fully understood, particularly in relation to GC development. The objective of this study was to examine the expression levels of lncRNAs in GC tissues using a bioinformatics-based ranking approach. A bioinformatics methodology was employed to prioritize lncRNAs that are hypothesized to play a role in GC tumorigenesis. Moreover, a selection was made for experimental validation of the highest-ranked lncRNAs, which include HCG18, OIP5-AS1, FGD5-AS1, and NORAD. Additionally, quantitative real-time polymerase chain reaction (qRT-PCR) was employed to confirm the results obtained from bioinformatics analysis in a total of 35 GC samples and their corresponding adjacent non-tumoral samples. Receiver operating characteristic (ROC) curves and the corresponding area under the ROC curve (AUC) were utilized to evaluate the diagnostic efficacy of the lncRNAs. The bioinformatics analysis revealed that the lncRNA HCG18 is the highest-ranked lncRNA associated with GC. Furthermore, the expression levels of HCG18, OIP5-AS1, FGD5-AS1, and NORAD were found to be significantly elevated in GC samples when compared to adjacent non-tumoral samples. The calculated values for the AUC of HCG18, OIP5-AS1, FGD5-AS1, and NORAD were 0.80, 0.74, 0.73, and 0.71, respectively. The results of the study indicate that the lncRNAs HCG18, OIP5-AS1, FGD5-AS1, and NORAD may play a role in the development of GC. Additionally, the present study revealed that utilizing bioinformatic techniques can prove to be a highly effective strategy in identifying potential lncRNAs pertinent to the progression of GC.