Dataset Information

Potential Role and Clinical Value of PPP2CA in Hepatocellular Carcinoma

ABSTRACT:

Background and Aims

Protein phosphatase 2A (PP2A) is associated with many cancers. This study aimed to clarify whether PPP2CA, which encodes the alpha isoform of the catalytic subunit of PP2A, plays a role in hepatocellular carcinoma (HCC) and to identify the potential underlying molecular pathways.

Methods

Based on bioinformatics, public databases and our in-house RNA-Seq database, we analyzed the clinical value and molecular mechanism of PPP2CA in HCC.

Results

Data were analyzed from 2,545 patients with HCC and 1,993 controls without HCC indexed in The Cancer Genome Atlas database, the Gene Expression Omnibus database and our in-house RNA-Seq database. PPP2CA expression was significantly higher in HCC tissue than in non-cancerous tissues (standardized mean difference: 0.69, 95% confidence interval [CI]: 0.50–0.89). PPP2CA expression was able to differentiate HCC from non-HCC, with an area under the summary receiver operator characteristic curve of 0.79 (95% CI: 0.75–0.83). Immunohistochemistry of tissue sections confirmed that PPP2CA protein was up-regulated in HCC tissues. High PPP2CA expression in HCC patients was associated with shorter overall, progression-free and disease-free survival. Potential molecular pathways through which PPP2CA may be involved in HCC were determined using miRWalk 2.0 as well as analysis of Gene Ontology categories, Kyoto Encyclopedia of Genes and Genomes pathways, and protein-protein interaction networks.

Conclusions

PPP2CA is up-regulated in HCC and higher expression correlates with worse prognosis. PPP2CA shows potential as a diagnostic marker for HCC. Future studies should examine whether PPP2CA contributes to HCC through the candidate microRNAs, pathways and hub genes identified in this study.

SUBMITTER: Yang C

PROVIDER: S-EPMC8516843 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Overexpression of Golgi membrane protein 1 (GOLM1) is closely associated with hepatocellular carcinoma (HCC) vascular invasion. How GOLM1 may be involved in angiogenesis in HCC remains unclear. We explored how GOLM1 promotes angiogenesis in HCC and potential prognostic value. Expression levels of GOLM1 in HCC patients and healthy controls were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) between HCC patients and controls were compared. GOLM1 was knocked out in the HCC cell line, and RNA sequencing and DEG expression analysis were performed compared with control cells. Based on TCGA data and cell line RNA sequencing data, DEGs affected by a high expression of GOLM1 were identified. Subsequently, enrichment analysis was performed to explore the functions and pathways of the DEGs affected by a high expression of GOLM1. A relevant network analysis was built. Cox regression, genomic variance analysis scores, minimum absolute shrinkage and selection operator regression, and random forest regression models were applied to determine the best prognostic model and validated using the GSE54236 dataset from the Gene Expression Omnibus (GEO). We determined the effect of GOLM1 expression on immune cell infiltration in liver cancer. GOLM1 was overexpressed in HCC tissues compared with controls, and its level correlated with tumor purity and prognosis. 400 DEGs affected by highly expressed GOLM1 were identified in TCGA and cell line RNA sequencing data. Enrichment analysis revealed that these DEGs may be related to biological processes of oxidative stress and angiogenesis and involved in the VEGF signaling pathway and protein processing in endoplasmic reticulum. We predicted a comprehensive regulatory network in which GOLM1 activated VEGF signaling to promote HCC angiogenesis. GOLM1 may interact with E2F1 and IGF2BP3 to promote angiogenesis. GOLM1 overexpression was associated with greater immune cell infiltration. A random forest regression model was the best prognostic model. Our study reveals a potential molecular mechanism of GOLM1 in promoting HCC. We developed two prognostic models based on DEG associated with GOLM1 overexpression to help stratify HCC prognosis and improve individualized treatment.

Project description:BackgroundGlycine-N-acyltransferase-like 1 (GLYATL1), which is involved in the detoxification of endogenous and exogenous acyl-CoA, promotes glutamine metabolism in xenobiotic metabolism. Recent evidence suggests an association between GLYATL1 and tumors. However, there are few comprehensive analyses of GLYATL1 in cancers. We evaluated the expression and prognostic value of GLYATL1 and explored the mechanism underlying the association between GLYATL1 and cancers.MethodsGLYATL1 mRNA expression across cancers was investigated in the Oncomine database and confirmed in the UALCAN and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Next, its prognostic value in different cancers was revealed by PrognoScan and Kaplan-Meier plotter. According to clinicopathologic features, we conducted a subgroup analysis of the prognosis of GLYATL1 in a cohort of hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) and the GSE116174 dataset. We further investigated the GLYATL1 promoter methylation profile in HCC. Next, a protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Finally, we utilized gene set enrichment analysis (GSEA) to identify significantly enriched pathways and confirmed their associations using the Tumor Immune Estimation Resource (TIMER) and GEPIA databases.ResultsGLYATL1 is downregulated in many cancers and indicates a poor prognosis. Specifically, low GLYATL1 expression was associated with short overall survival (OS) in HCC patients. Interestingly, GLYATL1 expression was associated with poor OS in stage I-II HCC patients and was revealed as an independent prognostic factor. The promoter methylation level of GLYATL1 in HCC tissue was significantly higher than that in normal liver tissue. The PPI network suggested that GLYATL1 is co-expressed with ten genes, including CNGA3 and GNB5. GSEA revealed that GLYATL1 is predominantly negatively enriched in xenobiotic metabolism, and the gene association analysis in TIMER and GEPIA showed a significantly negative association between the expression of GLYATL1 and the expression of most genes involved in mitochondrial glutamine metabolism, including SLC1A5 and SLC1A11.ConclusionsOur study is the first to shed light on the expression and prognostic value of GLYATL1 in cancers and provide a potential regulatory mechanism underlying HCC development.

Project description:As one of the members of the kinesin family, the role and potential mechanism of kinesin family member C1 (KIFC1) in the development of liver hepatocellular carcinoma (LIHC), especially in the immune infiltration, have not been fully elucidated. In this study, multiple databases and immunohistochemistry were employed to analyze the role and molecular mechanism including the immune infiltration of KIFC1 in LIHC. Generally, KIFC1 mRNA expression was overexpressed in LIHC tissues than normal tissues, and its protein was also highly expressed in the LIHC. KIFC1 mRNA expression was correlated with tumor grade and TNM staging, which was negatively correlated with overall survival and disease-free survival. Moreover, univariable and multivariate Cox analysis revealed that upregulated KIFC1 mRNA is an independent prognostic factor for LIHC. The KIFC1 promoter methylation level was negatively associated with KIFC1 mRNA expression and advanced stages and grade in LIHC. The different methylation sites of KIFC1 had a different effect on the prognosis of LIHC. Specifically, the KIFC1 mRNA expression level showed intense correlation with tumor immunity, such as tumor-infiltrating immune cells and immune scores as well as multiple immune-related genes. Moreover, KIFC1 co-expressed with some immune checkpoints and related to the responses to immune checkpoint blockade (ICB) and chemotherapies. Significant GO analysis showed that genes correlated with KIFC1 served as catalytic activity, acting on DNA, tubulin binding, histone binding, ATPase activity, and protein serine/threonine kinase activity. KEGG pathway analysis showed that these genes related to KIFC1 are mainly enriched in signal pathways such as cell cycle, spliceosome, pyrimidine metabolism, and RNA transport. Conclusively, KIFC1 was upregulated and displayed a prognostic value in LIHC. Moreover, KIFC1 may be involved in the LIHC progression partially through immune evasion and serve as a predictor of ICB therapies and chemotherapies.