Pepsinogen C expression–related lncRNA/circRNA/mRNA profile and its co-mediated ceRNA network in gastric cancer

Abstract Background The expression of pepsinogen C (PGC) is considered an ideal negative biomarker of gastric cancer, but its pathological mechanisms remain unclear. This study aims to analyze competing endogenous RNA (ceRNA) networks related to PGC expression at a post-transcriptional level and build an experimental basis for studying the role of PGC in the progression of gastric cancer. Materials and methods RNA sequencing technology was used to detect the differential expression profiles of PGC-related long non-coding (lnc)RNAs, circular (circ)RNAs, and mRNAs. The online database, STRING, was used to construct protein–protein interaction (PPI) networks of differentially expressed (DE) mRNAs. A ggcorrplot R package and online database were used to construct DElncRNAs/DEcircRNAs co-mediated PGC expression–related ceRNA networks. In vivo and in vitro validations were performed using quantitative reverse transcription–PCR. Results RNA sequencing found 637 DEmRNAs, 698 DElncRNAs, and 38 DEcircRNAs. The PPI network of PGC expression–related mRNAs consisted of 503 nodes and 1179 edges. CFH, PPARG, and MUC6 directly interacted with PGC. Enrichment analysis suggested that DEmRNAs were mainly enriched in cancer-related pathways. Eleven DElncRNAs, 13 circRNAs, and 35 miRNA–mRNA pairs were used to construct ceRNA networks co-mediated by DElncRNAs and DEcircRNAs that were PGC expression–related. The network directly related to PGC was as follows: SNHG16/hsa_circ_0008197–hsa-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p–PGC. Quantitative reverse transcriptase PCR validation results showed that PGC, PPARG, SNHG16, and hsa_circ_0008197 were differentially expressed in gastric cancer cells and tissues: PGC positively correlated with PPARG (r = 0.276, P = 0.009), SNHG16 (r = 0.35, P = 0.002), and hsa_circ_0008197 (r = 0.346, P = 0.005). Conclusion PGC-related DElncRNAs and DEcircRNAs co-mediated complicated ceRNA networks to regulate PGC expression, thus affecting the occurrence and development of gastric cancer at a post-transcriptional level. Of these, the network directly associated with PGC expression was a SNHG16/hsa_circ_0008197–mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p – PGC axis. This study may form a foundation for the subsequent exploration of the possible regulatory mechanisms of PGC in gastric cancer.