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Potential Role of NEU1 in Hepatocellular Carcinoma: A Study Based on Comprehensive Bioinformatical Analysis.

ABSTRACT: Background: Aberrant expression of NEU1 has been identified in many malignancies. Nevertheless, the clinical significance of NEU1 in hepatocellular carcinoma (HCC) has not been fully elucidated. Methods: In our study, multiple databases, including ONCOMINE, The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), Cancer Cell Line Encyclopedia (CCLE), Human Protein Atlas (HPA), Kaplan-Meier (KM) plotter, MethSurv, Gene Expression Profiling Interactive Analysis (GEPIA), and Metascape, etc., were utilized to investigate the expression, prognostic value, and function of NEU1 in HCC. Results: ONCOMINE, GEO, and TCGA analyses revealed that NEU1 was more highly expressed in HCC compared to normal tissues. Additionally, the mRNA and protein expression levels of NEU1 were increased in liver cancer cell lines and HCC tissues, respectively. Moreover, a trend toward increased NEU1 expression with advanced stage or grade was found. Furthermore, higher mRNA expression of NEU1 was found to be remarkably correlated with worse survival in HCC patients, and multivariate Cox analysis indicated that high mRNA expression of NEU1 was an independent prognostic factor for poor prognosis of HCC patients. Also, 21 methylated CpGs were found to be significantly related to HCC prognosis. Besides, functional enrichment analyses indicated that high NEU1 expression group had lower levels of B cells, CD8⁺ T cells, NK cells, and T helper cells, etc. than the low NEU1 expression group, and NEU1 may regulate a variety of tumor-related proteins and pathways, including lysosome, spliceosome, mTOR signaling pathway and so on. Conclusion: High expression level of NEU1 was positively correlated with unfavorable prognosis of HCC patients, which may be related to the regulation of cancer-associated pathways and the inhibition of immune function by NEU1. Thus, NEU1 could be used as a potential prognostic biomarker and target for HCC.

SUBMITTER: Wu Z

PROVIDER: S-EPMC8427823 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The aims of the present study were to examine the potential role of microRNA‑233‑3p (miR)‑223‑3p in the tumorigenesis of hepatocellular carcinoma (HCC), and to investigate its diagnostic accuracy and potential molecular mechanisms. The expression data of miR‑223‑3p in HCC were obtained from the Gene Expression Omnibus (GEO). Data for the precursor miR‑223 were obtained from The Cancer Genome Atlas (TCGA). The diagnostic role of miR‑223‑3p was identified by the receiver operating curve (ROC), and the diagnostic value of miR‑223‑3p in HCC was calculated from qualified reports in the literature. In addition, associated data from the GEO, TCGA and qualified experiments were pooled for comprehensive meta‑analysis. Genes, which intersected between online prediction databases, natural language processing and differentially expressed genes from TCGA were regarded as potential targets of miR‑223‑3p in HCC. The Gene Ontology enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes pathways of potential targets were performed using the Database for Annotation, Visualization and Integrated Discovery. The protein‑protein interactions were mapped using the Search Tool for the Retrieval of Interacting Genes. Among 15 qualified microarray data sets from GEO, seven showed that a significantly lower level of miR‑223‑3p was present in the HCC tissues, compared with that in non‑cancerous tissues (P<0.05). In addition, five GEO data sets revealed diagnostic values of miR‑223‑3p, with an area under the curve (AUC) of >0.80 (P<0.05). The diagnostic accuracy of the precursor miR‑223 in TCGA was also calculated (AUC=0.78, P<0.05). Similarly, the precursor miR‑223 showed a higher level of downregulation in HCC tissues, compared with that in healthy controls in TCGA (P<0.001). A summary ROC was also calculated as 0.89 (95% CI, 0.85‑0.91) in the meta‑analysis. A total of 72 potential targets were extracted, mainly involved in the terms 'microRNAs in cancer', 'ATP binding' and 'prostate cancer'. Five potential target genes were considered the hub genes of miR‑223‑3p in HCC, including checkpoint kinase 1, DNA methyltransferase 1, baculoviral IAP repeat containing 5, kinesin family member 23, and collagen, type I, α1. Based on TCGA, the hub genes were significantly upregulated in HCC (P<0.05). Collectively, these results showed that miR‑223‑3p may be crucial in HCC carcinogenesis showing high diagnostic accuracy, and may be mediated by several hub genes.

Project description:BackgroundHepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC.MethodsDeep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed.ResultsExpression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis.ConclusionsTranscriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

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:Background: Hepatocellular carcinoma (HCC) is a solid tumor with high recurrence rate and high mortality. It is crucial to discover available biomarkers to achieve early diagnosis and improve the prognosis. The effect of LSM4 in HCC still remains unrevealed. Our study is dedicated to exploring the expression of LSM4 in HCC, demonstrating its clinical significance and potential molecular mechanisms. Methods: Clinical information and LSM4 expression values of HCC were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Survival analysis and receiver operating characteristic (ROC) curve analysis were applied to evaluate the prognostic and diagnostic significance of LSM4. Calculating pooled standardized mean difference (SMD) and performing summary receiver operating characteristic (sROC) curve analysis to further determine its expression status and diagnostic significance. LSM4-related co-expressed genes (CEGs) were obtained and explored their clinical significance in HCC. LSM4-associated pathways were identified through Gene set enrichment analysis (GSEA). Results: Up-regulated LSM4 was detected in HCC tissues (SMD = 1.56, 95% CI: 1.29-1.84) and overexpressed LSM4 had excellent distinguishing ability (AUC = 0.91, 95% CI: 0.88-0.93). LSM4 was associated with clinical stage, tumor grade, and lymph node metastasis status (p < 0.05). Survival analysis showed that high LSM4 expression was related to poor overall survival (OS) of HCC patients. Cox regression analysis suggested that high LSM4 expression may be an independent risk factor for HCC. We obtained nine up-regulated CEGs of LSM4 in HCC tissues, and six CEGs had good prognostic and diagnostic significance. GSEA analysis showed that up-regulated LSM4 was closely related to the cell cycle, cell replication, focal adhesion, and several metabolism-associated pathways, including fatty acid metabolism. Conclusion: Overexpressed LSM4 may serve as a promising diagnostic and prognostic biomarker of HCC. Besides, LSM4 may play a synergistic effect with CEGs in promoting the growth and metastasis of HCC cells via regulating crucial pathways such as cell cycle, focal adhesion, and metabolism-associated pathways.

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Potential Role of NEU1 in Hepatocellular Carcinoma: A Study Based on Comprehensive Bioinformatical Analysis.

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