Expression pattern of PCAT1, PCAT2, and PCAT5 lncRNAs and their value as diagnostic biomarkers in patients with gastric cancer

Background: Gastric cancer (GC), is a complex multifactorial neoplasm with a high mortality and prevalence rate all over the world. Hence, it is necessary to identify the multiple pathways that are previously unknown and are involved in its initiation and progression. Recently, it has become clear that long non-coding RNAs (lncRNAs) play a crucial role in the onset and spread of cancer. The current study assessed the lncRNAs PCAT1, PCAT2, and PCAT5 expression in primary gastric tumors and adjacent noncancerous tissues.

Methods: 90 pairs of GC and adjacent noncancerous tissue samples were obtained. Total RNA was extracted, then cDNA was synthesized. Using quantitative reverse transcriptase PCR (qRT-PCR), PCAT1, PCAT2, and PCAT5 expression levels were evaluated. Using the SPSS statistical package, the correlation between clinicopathological characteristics and the expression of PCAT1, PCAT2, and PCAT5 was investigated. The diagnostic value of PCAT1, PCAT2, and PCAT5 in GC was assessed using the receiver operating characteristic (ROC) curve analysis.

Results: Compared to surrounding non-cancerous tissues, PCAT1, PCAT2, and PCAT5 were all significantly overexpressed in tumoral tissues (P = 0.001, P = 0.019, and P = 0.0001, respectively). PCAT5 expression was significantly associated with gender (P = 0.020), according to our research. The ROC curve's findings indicated that PCAT1, PCAT2, and PCAT5 may each function as poor diagnostic biomarkers, with respective AUC values of 64 %, 60 %, and 68 %, specificity values of 68 %, 60 %, and 76 %, and sensitivity values of 55 %, 72 %, and 52 %.

Conclusion: Our research suggested that PCAT1, PCAT2, and PCAT5 may be engaged in promoting and developing GC cells as a novel oncogene because of the increased expression of PCAT1, PCAT2 and PCAT5 in tumor tissues of GC patients. Additionally, PCAT1, PCAT2, and PCAT5 can be thought of as poor diagnostic biomarkers for GC case detection.