Prognostic effect of DNA methylation of BTG2 gene in Chinese hepatocellular carcinoma
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ABSTRACT:
SUBMITTER: Ma J
PROVIDER: S-EPMC10979207 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
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Project description:Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and high mortality worldwide. DNA methylation, one of the most common epigenetic changes, might serve a vital regulatory role in cancer. Methods: To identify categories based on DNA methylation data, consensus clustering was employed. The risk signature was yielded by systematic bioinformatics analyses based on the remarkably methylated CpG sites of cluster 1. Kaplan-Meier analysis, variable regression analysis, and ROC curve analysis were further conducted to validate the prognosis predictive ability of risk signature. Gene set enrichment analysis (GSEA) was performed for functional annotation. To uncover the context of tumor immune microenvironment (TIME) of HCC, we employed the ssGSEA algorithm and CIBERSORT method and performed TIMER database exploration and single-cell RNA sequencing analysis. Additionally, quantitative real-time polymerase chain reaction was employed to determine the LRRC41 expression and preliminarily explore the latent role of LRRC41 in prognostic prediction. Finally, mutation data were analyzed by employing the "maftools" package to delineate the tumor mutation burden (TMB). Results: HCC samples were assigned into seven subtypes with different overall survival and methylation levels based on 5'-cytosine-phosphate-guanine-3' (CpG) sites. The risk prognostic signature including two candidate genes (LRRC41 and KIAA1429) exhibited robust prognostic predictive accuracy, which was validated in the external testing cohort. Then, the risk score was significantly correlated with the TIME and immune checkpoint blockade (ICB)-related genes. Besides, a prognostic nomogram based on the risk score and clinical stage presented powerful prognostic ability. Additionally, LRRC41 with prognostic value was corroborated to be closely associated with TIME characterization in both expression and methylation levels. Subsequently, the correlation regulatory network uncovered the potential targets of LRRC41 and KIAA1429. Finally, the methylation level of KIAA1429 was correlated with gene mutation status. Conclusion: In summary, this is the first to identify HCC samples into distinct clusters according to DNA methylation and yield the CpG-based prognostic signature and quantitative nomogram to precisely predict prognosis. And the pivotal player of DNA methylation of genes in the TIME and TMB status was explored, contributing to clinical decision-making and personalized prognosis monitoring of HCC.
| S-EPMC8187884 | biostudies-literature
Project description:Growing evidence has revealed the crucial role of epigenetics in tumor progression and immune response. However, the molecular subtypes and their microenvironment characterization mediated by DNA methylation regulators in hepatocellular carcinoma remain little known. In this study, we comprehensively integrated the transcriptome profiling of twenty DNA methylation regulators in hepatocellular carcinoma. Consensus clustering was used to identify distinct methylation regulator-related molecular subtypes. The prognostic DMS signature was constructed using principal components analysis. Most regulators experienced a low genomic variation, but we found a remarkably difference in mRNA expression of these regulators between normal and tumor tissues. Three distinct methylation regulator-related molecular subtypes were successfully identified according to the expression of 20 regulators, which had substantially different biological characteristics and prognosis. The classic carcinogenic pathways and stromal activity including TGF-beta, p53 and WNT signaling pathway were significantly activated in subtype B, leading to a survival inferiority in subtype B compared to other two subtypes. Further analysis demonstrated the constructed DMS signature was an independent predictive biomarker in patient prognosis. Two anti-checkpoint immunotherapy cohorts demonstrated patients with high DMS presented significantly improved treatment advantages and enhanced responses especially the survival prolonged. Generally, the high DMS groups improved more than 15% clinical response to immunotherapy than low DMS groups. In conclusion, this study identified three DNA methylation regulator-related subtypes with distinct clinical, molecular and biological characteristics, and constructed a prognostic and immunotherapeutic relevant gene signature. It might help to promote individualized immunotherapy for hepatocellular carcinoma from the perspective DNA methylation regulators.
| S-EPMC9271297 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression.MethodsTranscriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively.ResultsThree methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications.ConclusionThrough bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.
| S-EPMC10830715 | biostudies-literature
Project description:Hepatocellular Carcinoma (HCC) is one of the most common cancers in the world and it is often associated with poor prognosis. Liver transplantation and resection are two currently available curative therapies. However, most patients cannot be treated with such therapies due to late diagnosis. This underscores the urgent need to identify potential markers that ensure early diagnosis of HCC. As more evidences are suggesting that epigenetic changes contribute hepatocarcinogenesis, DNA methylation was poised as one promising biomarker. Indeed, genome wide profiling reveals that aberrant methylation is frequent event in HCC. Many studies showed that differentially methylated genes and CpG island methylator phenotype (CIMP) status in HCC were associated with clinicopathological data. Some commonly studied hypermethylated genes include p16, SOCS1, GSTP1 and CDH1. In addition, studies have also revealed that methylation markers could be detected in patient blood samples and associated with poor prognosis of the disease. Undeniably, increasing number of methylation markers are being discovered through high throughput genome wide data in recent years. Proper and systematic validation of these candidate markers in prospective cohort is required so that their actual prognostication and surveillance value could be accurately determined. It is hope that in near future, methylation marker could be translate into clinical use, where patients at risk could be diagnosed early and that the progression of disease could be more correctly assessed.
| S-EPMC4022334 | biostudies-other
Project description:BackgroundAberrant methylation of DNA is a key driver of hepatocellular carcinoma (HCC). In this study, we sought to integrate four cohorts profile datasets to identify such abnormally methylated genes and pathways associated with HCC.MethodsTo this end, we downloaded microarray datasets examining gene expression (GSE84402, GSE46408) and gene methylation (GSE73003, GSE57956) from the GEO database. Abnormally methylated differentially expressed genes (DEGs) were sorted and pathways were analyzed. The String database was then used to perform enrichment and functional analysis of identified pathways and genes. Cytoscape software was used to create a protein-protein interaction network, and MCODE was used for module analysis. Finally, overall survival analysis of hub genes was performed by the OncoLnc online tool.ResultsIn total, we identified 19 hypomethylated highly expressed genes and 14 hypermethylated lowly expressed genes at the screening step, and finally found six mostly changed hub genes including MAD2L1, CDC20, CCNB1, CCND1, AR and ESR1. Pathway analysis showed that aberrantly methylated-DEGs mainly associated with the cell cycle process, p53 signaling, and MAPK signaling in HCC. After validation in TCGA database, the methylation and expression status of hub genes was significantly altered and same with our results. Patients with high expression of MAD2L1, CDC20 and CCNB1 and low expression of CCND1, AR, and ESR1 was associated with shorter overall survival.ConclusionsTaken together, we have identified novel aberrantly methylated genes and pathways linked to HCC, potentially offering novel insights into the molecular mechanisms governing HCC progression and serving as novel biomarkers for precision diagnosis and disease treatment.
| S-EPMC6142709 | biostudies-literature
Project description:In this study, we performed a comprehensively analysis of gene expression and DNA methylation data to establish diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC). Methods: We collected gene expression and DNA methylation datasets for over 1,200 clinical samples. Integrated analyses of RNA-sequencing and DNA methylation data were performed to identify DNA methylation-driven genes. These genes were utilized in univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to build a prognostic model. Recurrence and diagnostic models for HCC were also constructed using the same genes. Results: A total of 123 DNA methylation-driven genes were identified. Two of these genes (SPP1 and LCAT) were chosen to construct the prognostic model. The high-risk group showed a markedly unfavorable prognosis compared to the low-risk group in both training (HR = 2.81; P < 0.001) and validation (HR = 3.06; P < 0.001) datasets. Multivariate Cox regression analysis indicated the prognostic model to be an independent predictor of prognosis (P < 0.05). Also, the recurrence model successfully distinguished the HCC recurrence rate between the high-risk and low-risk groups in both training (HR = 2.22; P < 0.001) and validation (HR = 2; P < 0.01) datasets. The two diagnostic models provided high accuracy for distinguishing HCC from normal samples and dysplastic nodules in the training and validation datasets, respectively. Conclusions: We identified and validated prognostic, recurrence, and diagnostic models that were constructed using two DNA methylation-driven genes in HCC. The results obtained by integrating multidimensional genomic data offer novel research directions for HCC biomarkers and new possibilities for individualized treatment of patients with HCC.
| S-EPMC6831284 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents.
| S-EPMC7456968 | biostudies-literature
Project description:BackgroundN6-methyladenosine (m6A) RNA methylation is the most prevalent modification of mammalian RNA, and it is associated with tumorigenesis and cancer progression. Its regulation is mediated via m6A-related regulators, including "erasers," "readers," and "writers". The present study evaluated the expression profile, risk signature and prognostic value of 13 m6A regulators in hepatocellular carcinoma (HCC) using different datasets, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and clinical samples.MethodsWe used 374 HCC samples derived from the TCGA database, 569 HCC samples from 2 GEO datasets, and clinical tumour and nontumour tissues derived from 60 patients with HCC who underwent surgery in Xinqiao Hospital Chongqing to assess the gene expression profiles and prognostic values of m6A-related regulators in HCC.ResultsEight of 13 core m6A-related regulators were overexpressed in all databases, including TCGA, GSE, clinical tumour and nontumour tissues of HCC. Two clusters (Cluster 1 and Cluster 2) were identified via consensus clustering. Cluster 2 was associated with poorer prognosis, higher tumour grade, higher AFP levels, and worse outcome compared to Cluster 1, which indicates that these m6A-related regulators are highly correlated with HCC malignancy. We performed survival analyses using the Log rank tests and a Cox regression model. Gene enrichment analysis was used to detect the related KEGG and GO pathways. We derived a prognostic risk signature using five selected m6A-related regulators.ConclusionOur work suggested that m6A-related regulators might be key participants in the tumour progression of HCC and potential biomarkers with prognostic value.
| S-EPMC7966299 | biostudies-literature
Project description: Not available
| S-DIXA-D-1150 | biostudies-other
Project description:BackgroundAlcohol is a well-known risk factor for hepatocellular carcinoma (HCC), but the mechanisms underlying the alcohol-related hepatocarcinogenesis are still poorly understood. Alcohol alters the provision of methyl groups within the hepatic one-carbon metabolism, possibly inducing aberrant DNA methylation. Whether specific pathways are epigenetically regulated in alcohol-associated HCC is, however, unknown. The aim of the present study was to investigate the genome-wide promoter DNA methylation and gene expression profiles in non-viral, alcohol-associated HCC. From eight HCC patients undergoing curative surgery, array-based DNA methylation and gene expression data of all annotated genes were analyzed by comparing HCC tissue and homologous cancer-free liver tissue.ResultsAfter merging the DNA methylation with gene expression data, we identified 159 hypermethylated-repressed, 30 hypomethylated-induced, 49 hypermethylated-induced, and 56 hypomethylated-repressed genes. Notably, promoter DNA methylation emerged as a novel regulatory mechanism for the transcriptional repression of genes controlling the retinol metabolism (ADH1A, ADH1B, ADH6, CYP3A43, CYP4A22, RDH16), iron homeostasis (HAMP), one-carbon metabolism (SHMT1), and genes with a putative, newly identified function as tumor suppressors (FAM107A, IGFALS, MT1G, MT1H, RNF180).ConclusionsA genome-wide DNA methylation approach merged with array-based gene expression profiles allowed identifying a number of novel, epigenetically regulated candidate tumor-suppressor genes in alcohol-associated hepatocarcinogenesis. Retinol metabolism genes and SHMT1 are also epigenetically regulated through promoter DNA methylation in alcohol-associated HCC. Due to the reversibility of epigenetic mechanisms by environmental/nutritional factors, these findings may open up to novel interventional strategies for hepatocarcinogenesis prevention in HCC related to alcohol, a modifiable dietary component.
| S-EPMC4419480 | biostudies-literature