Mining of RNA Methylation-Related Genes and Elucidation of Their Molecular Biology in Gallbladder Carcinoma

Abstract

Gallbladder carcinoma (GBC), which has high invasion and metastasis risks, remains the most common biliary tract malignancy. Surgical resection for GBC is the only effective treatment, but most patients miss the opportunity for curative surgery because of a lack of timely diagnosis. The aim of this study was to identify and verify early candidate diagnostic and prognostic RNA methylation related genes for GBC via integrated transcriptome bioinformatics analysis. Lists of GBC-related genes and methylation-related genes were collected from public databases to screen differentially expressed genes (DEGs) by using the limma package and the RobustRankAggreg (RRA) package. The core genes were collected with batch effects corrected by the RRA algorithm through protein interaction network analysis, signaling pathway enrichment analysis and gene ranking. Four modules obtained from four public microarray datasets were found to be related to GBC, and FGA, F2, HAO1, CFH, PIPOX, ITIH4, GNMT, MAT1A, MTHFD1, HPX, CTH, EPHX2, HSD17B6, AKR1C4, CFHR3, ENNP1, and NAT2 were revealed to be potential hub genes involved in methylation-related pathways and bile metabolism-related pathways. Among these, FGA, CFH, F2, HPX, and PIPOX were predicted to be methylated genes in GBC, but POPIX had no modification sites for RNA methylation. Furthermore, survival analysis of TCGA (the Cancer Genome Atlas) database showed that six genes among the hub genes, FGA, CFH, ENPP1, CFHR3, ITIH4, and NAT2, were highly expressed and significantly correlated with worse prognosis. Gene correlation analysis revealed that the FGA was positively correlated with the ENPP1, NAT2, and CFHR3, while CFH was positively correlated with the NAT2, CFHR3, and FGA. In addition, the results of immunohistochemistry (IHC) showed that the expressions of FGA, F2, CFH, PIPOX, ITIH4, GNMT, MAT1A, MTHFD1, HPX, CFHR3, NAT2, and ENPP1 were higher in GBC tissues than that in control tissues. In conclusion, two genes, FGA and CFH, were identified as RNA methylation-related genes also involved in bile metabolism in GBC, which may be novel biomarkers to early diagnose and evaluate prognosis for GBC.

Keywords: RNA methylation; bile metabolism; bioinformatics; biomarkers; differentially expressed genes; gallbladder carcinoma.

Figure 1

Workflow chart of mining of RNA methylation-related genes in gallbladder carcinoma.

Figure 2

Collection of differentially expressed genes (DEGs) in GBC. (A) Venn diagram of four RNA microarray datasets (GSE45001, GSE31370, GSE26566, and GSE76633). (B) heat map of differentially expressed genes. Each column represents one dataset and each row represents one gene. Green represents a lower expression level, red represents higher expression levels, and white represents that there is no different expression amongst the genes. The number in each rectangle represents the normalized gene expression level.

Figure 3

Functional enrichment analysis. (A) co-expression of the DEGs. (B) the DEGs enriched pathway analysis.

Figure 4

Annotation of core genes. (A) volcano plots for DECs in GBC based on the four microarray datasets from GEO. (B) the levels of methylation of hub genes between the control and GBC cases from TCGA database.

Figure 5

Survival analysis of the core genes in GBC patients through TCGA database. (A) survival analysis of FGA. (B) survival analysis of CFH. (C) survival analysis of ENPP1. (D) survival analysis of CFHR3. (E) survival analysis of ITIH4. (F) survival analysis of NAT2.

Figure 6

The correlation coefficients among 17 core genes from the TCGA CHOL dataset. (A) the details of correlation coefficients by Pearson statistical analysis among 17 core genes. (B) the genes positively correlated with FGA and CFH.

Figure 7

Immunohistochemistry of FGA, F2, CFH, PIPOX, ITIH4, GNMT, MAT1A, MTHFD1, HPX, CTH, CFHR3, ENNP1, and NAT2 in clinical GBC and control specimens.