Dataset Information

Sarcosine dehydrogenase as an immune infiltration-associated biomarker for the prognosis of hepatocellular carcinoma.

ABSTRACT: This study was aimed to investigate the prognostic value and clinical significance of sarcosine dehydrogenase (SARDH) in hepatocellular carcinoma (HCC) and to explore the underlying mechanisms. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), HPA and CPTAC databases were adopted to analyze the expression of SARDH mRNA and protein between normal liver tissue and HCC, and examine their relationship with clinicopathological features. Kaplan-Meier analysis, Cox regression, as well as nomogram were adopted to explore the prognostic value of SARDH in HCC. Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) together with Gene Set Enrichment Analysis (GSEA) were adopted to analyze the molecular mechanisms and biological functions of SARDH in HCC; while MethSurv, STRING, GeneMANIA, TIMER database data and single-sample gene set enrichment analysis (ssGSEA) algorithm were used for other bioinformatic analysis. Furthermore, immunohistochemistry was used to verify the expression of SARDH. Compared to normal liver tissue, SARDH expression was markedly lower in HCC. A lower SARDH expression was linked with Pathologic T stage (T3&T4), pathologic stage (Stage III&IV), and histologic grade (G3&4), which further indicates worse prognosis. Besides, results of bioinformatic analysis proved that SARDH expression was correlated with immune infiltration. In addition, SARDH hypermethylation was related to a poorer prognosis. SARDH expression was related to several key genes in the Ferroptosis pathway.

SUBMITTER: Xie H

PROVIDER: S-EPMC10751682 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Sarcosine dehydrogenase as an immune infiltration-associated biomarker for the prognosis of hepatocellular carcinoma.

Xie Haixiang H Yang Kejian K Qin Chongjiu C Zhou Xin X Liu Junqi J Nong Jusen J Luo Jianzhu J Wei Yongguang Y Hua Huasheng H Han Chuangye C Liao Xiwen X Yang Chengkun C Su Hao H Zhu Guangzhi G Ye Xinping X Peng Tao T

Journal of Cancer 20240101 1

This study was aimed to investigate the prognostic value and clinical significance of sarcosine dehydrogenase (SARDH) in hepatocellular carcinoma (HCC) and to explore the underlying mechanisms. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), HPA and CPTAC databases were adopted to analyze the expression of SARDH mRNA and protein between normal liver tissue and HCC, and examine their relationship with clinicopathological features. Kaplan-Meier analysis, Cox regression, as well as n ...[more]

PMID: 38164283

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Project description:ObjectiveThe morbidity of hepatocellular carcinoma (HCC) is increasing annually. The aim of this study is to investigate the molecular mechanisms of upregulated genes in HCC using bioinformatic methods, so as to identify new potential biological markers.MethodsThe Gene Expression Omnibus database (GEO database) was mined for HCC datasets, which were screened for hub genes and subjected to (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis. The hub genes were analyzed in terms of Receiver Operating Characteristic (ROC) and methylation levels. Validation of hub genes was completed through basic pathological alterations based on the protein and gene expression level of hub genes. The correlation of genes with immune infiltration in HCC was analyzed based on the database Timer 2.0, and the prognosis as well as survival of hub genes in HCC was analyzed using R studio software. Finally, we performed a gene combination drug analysis on the potential therapeutic targets in HCC.ResultsExpression-up-regulated genes were screened via differential analysis, which were mainly enriched in cell cycles and DNA replication pathways. Five hub genes, BRCA1 associated RING domain 1 (BARD1), Mismatch Repair Protein (MSH2), Recombinant H2A Histone Family, Member X (H2AFX), Recombinant H2A Histone Family, Member z (H2AFZ) and Chromosome 18 Open Reading Frame 54 (C18orf54) were identified using a Protein-Protein Interaction Networks (PPI). After a comprehensive analysis of ROC curves and methylation gene mutation sites, C18orf54 was localized followed by basic experiments, so as to verify the C18orf54 upregulated in HCC. Based on the online database Timer 2.0, the immune infiltration of C18orf54 gene in HCC was analyzed, which was found to be negatively correlated with CD4+ T cells and macrophages in HCC, meanwhile a further refinement of the immune checkpoint correlation analysis revealed that C18orf54 was mainly correlated with Hepatitis A virus cellular receptor 2 (HAVCR2), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Cytotoxic T lymphocyte associate protein-4 (CTLA4). The prognosis and survival of patients with HCC expressing C18orf54 were also analyzed, and it was found that such patients had a higher incidence of adjacent liver tissue inflammation, a higher child-Pugh grade score and a higher rate of residual tumor recurrence. Similarly, the prognosis was worse in the subset of patients with C18orf54. Finally, we performed a combined genetic analysis, which suggested that cyclosporine, quercetin, testosterone and calcitriol might be effective in reducing C18orf54 mRNA expression.ConclusionC18orf54 is involved in the immune infiltration and promotes the poor prognosis of HCC, which could be a candidate biomarker for HCC.

Project description:Objective: This study aimed to validate FANCI as a potential marker for both prognosis and therapy in liver hepatocellular carcinoma. Method: FANCI expression data were acquired from GEPIA, HPA, TCGA, and GEO databases. The impact of clinicopathological features was analyzed by UALCAN. The prognosis of Liver Hepatocellular Carcinoma (LIHC) patients with highly expressed FANCI was constructed utilizing Kaplan-Meier Plotter. GEO2R was employed to identify differentially expressed genes (DEGs). Metascape was used to analyze functional pathways correlations. Protein-Protein interaction (PPI) networks were generated by Cytoscape. Furthermore, molecular complex detection (MCODE) was utilized to recognize Hub genes, which were selected to establish a prognostic model. Lastly, the relationship between FANCI and immune cell infiltration in LIHC was examined. Results: Compared to adjacent tissues, FANCI expression levels were significantly higher in LIHC tissues and were positively correlated to the cancer grade, stage, and prior hepatitis B virus (HBV) infection. High expression of FANCI was found to be associated with poor prognosis in LIHC (HR=1.89, p<0.001). DEGs that were positively correlated with FANCI were involved in various processes, including the cell cycle, VEGF pathway, immune system processes, and biogenesis of ribonucleoproteins. MCM10, TPX2, PRC1, and KIF11 were identified as key genes closely related to FANCI and poor prognosis. A reliable five-variable prognostic model was constructed with strong predictive capability. Lastly, a positive correlation was observed between FANCI expression and tumor-infiltration levels of CD8+ T cells, B cells, regulatory T (Tregs), CD4+ T helper 2 (Th2), and macrophage M2 cells. Conclusion: FANCI may hold promise as a potential biomarker for predicting prognostic outcomes, and a valuable therapeutic target for LIHC patients, with a focus on anti-proliferation, anti-chemoresistance, and combination with immunotherapy.

Project description:Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and its prognosis remains unsatisfactory. The identification of new and effective markers is helpful for better predicting the prognosis of patients with HCC and for conducting individualized management. The oncogene Aurora kinase A (AURKA) is involved in a variety of tumors; however, its role in liver cancer is poorly understood. The aim of this study was to establish AURKA-related gene signatures for predicting the prognosis of patients with HCC. Methods: We first analyzed the expression of AURKA in liver cancer and its prognostic significance in different data sets. Subsequently, we selected genes with prognostic value related to AURKA and constructed a gene signature based on them. The predictive ability of the gene signature was tested using the HCC cohort development and verification data sets. A nomogram was constructed by integrating the risk score and clinicopathological characteristics. Finally, the influence of the gene signature on the immune microenvironment in HCC was comprehensively analyzed. Results: We found that AURKA was highly expressed in HCC, and it exhibited prognostic value. We selected eight AURKA-related genes with prognostic value through the protein-protein interaction network and successfully constructed a gene signature. The nine-gene signature could effectively stratify the risk of patients with HCC and demonstrated a good ability in predicting survival. The nomogram showed good discrimination and consistency of risk scores. In addition, the high-risk group showed a higher percentage of immune cell infiltration (i.e., macrophages, myeloid dendritic cells, neutrophils, and CD4+T cells). Moreover, the immune checkpoints SIGLEC15, TIGIT, CD274, HAVCR2, and PDCD1LG2 were also higher in the high-risk group versus the low-risk group. Conclusions: This gene signature may be useful prognostic markers and therapeutic targets in patients with HCC.

Dataset Information

Sarcosine dehydrogenase as an immune infiltration-associated biomarker for the prognosis of hepatocellular carcinoma.

Publications

Sarcosine dehydrogenase as an immune infiltration-associated biomarker for the prognosis of hepatocellular carcinoma.

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