Prognostic Risk Model and Tumor Immune Environment Modulation of m5C-Related LncRNAs in Pancreatic Ductal Adenocarcinoma

Abstract

RNA methylation modification is a key process in epigenetics that regulates posttranscriptional gene expression. With advances in next-generation sequencing technology, 5-methylcytosine (m5C) modification has also been found in multiple RNAs. Long non-coding RNAs (lncRNAs) were proved to have a key role in cancer progression and closely related to the tumor immune microenvironment. Thus, based on the PDAC patients’ clinical information and genetic transcriptome data from the TCGA database, we performed a detailed bioinformatic analysis to establish a m5C-related lncRNA prognostic risk model for PDAC patients and discovered the relationship between the risk model and PDAC immune microenvironment. Pearson correlation coefficient analysis was applied to conduct a m5C regulatory gene and m5C-related lncRNA co-expression network. Expression of m5C-related lncRNAs screened by univariate regression analysis with prognostic value showed a significant difference between pancreatic cancer and normal tissues. The least absolute shrinkage and selection operator (LASSO) Cox regression method was applied to determine an 8-m5C-related lncRNA prognostic risk model. We used principal component analysis to indicate that the risk model could distinguish all the samples clearly. The clinical nomogram also accurately predicted 1-, 1.5-, 2-, and 3-year survival time among PDAC patients. Additionally, this risk model was validated in the entire group and sub-test groups using KM analysis and ROC analysis. Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the survival of PDAC patients. Furthermore, the association between the risk model and tumor immune microenvironment was evaluated via the ESTIMATE R package and CIBERSORT method. Consequently, the results indicated that immune cells were associated with m5C-related lncRNA risk model scores and had different distribution in the high- and low-risk groups. Based on all these analyses, the m5C-related lncRNA risk model could be a reliable prognostic tool and therapeutic target for PDAC patients.

The Value of m5C-Related lncRNAs in the Prognostic Assessment and Immunotherapy of Stomach Adenocarcinoma

“…What roles do m5C-related lncRNAs play in the TME? In pancreatic ductal adenocarcinoma, m5C-related lncRNAs have been reported to induce polarisation or infiltration of M2 phenotype macrophages [ 26 ]. In this research, we investigated the relationship between m5C-related lncRNAs and tumor immune cell infiltration in STAD.…”

“…Thirteen m5C methylation-regulated genes have been described in the published study, namely, YBX1, ALYREF, DNMT1, NSUN4, TRDMT1, TET2, NSUN7, NSUN6, NSUN5, NSUN3, NSUN2, DNMT3A, and DNMT3B [ 26 ]. The expression matrix of the 13 m5C methylation-regulated genes was obtained from RNA-seq transcriptome data.…”

5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas

“…lncRNA H19 modified by m5C methylation promotes hepatocarcinogenesis and progression through recruitment of oncoprotein G3BP1 ( 55 ). Recently, deep bioinformatics mining of high-throughput data revealed that m5c-related lncRNAs have potential effects on immune infiltration and can be used as multiple tumor prognostic markers and therapeutic targets ( 56 , 57 ). To our knowledge, this is the first exploration of m5C-related lncRNAs in LGG, yielding the prognostic biomarkers LINC00265, CIRBP-AS1, GDNF-AS1 and ZBTB20-AS4.…”

Emerging Role of Epigenetic Alterations as Biomarkers and Novel Targets for Treatments in Pancreatic Ductal Adenocarcinoma

“…Epigenetic variation predicts the risk of tumor development and growth, and the DNA methylome in PDAC is significantly altered from healthy controls, with several protein coding genes and long non-coding genes being potential prognostic biomarkers [36,37]. In addition, long non-coding RNAs (lncRNAs) and microRNA expression profiles may help prognosticate patients [38,39]. For one, microRNA-192 is epigenetically downregulated in PDAC via promoter methylation, where higher expression caused better overall survival, together with in vitro data suggesting an inverse correlation with EMT markers and less favorable growth patterns [40].…”