DNA methylation biomarkers for hepatocellular carcinoma

Measuring the differential expression of the major hypermethylated tumor suppressor genes in tissues of primary hepatocellular carcinoma

BACKGROUND

Hepatocarcinogenesis is a multifactorial process that arises from a integration of genetic and epigenetic anomalies leading to abnormal gene expression and function. It is difficult to characterize HCC with a single biomarker. Our study aimed at detecting the expression of a panel of 8 methylated genes (SOCS1, APC, Gadd45b, CDKN1B, P15, PAX6, STAT1 and MSH2) as regulatory factors among Egyptian patients with HCC.

METHODS

This study was conducted on HCC tissue samples of 30 Egyptian patients in comparison with their non-cancerous adjacent cirrhotic tissue as a control. Tissue samples were obtained from patients who have undergone living donor liver transplantation (LDLT) or liver resection at El Sahel Teaching Hospital (Cairo, Egypt). A special Custom designed PCR Arrays was used to analyze the expression profiles of chosen methylated genes associated with HCC.

RESULTS

Expression of SOCS1, APC, Gadd45b, CDKN1B, P15, PAX6, STAT1 and MSH2 were lower in the HCC tissue compared to the cirrhotic tissue (pvalue = 0.015, 0.081, 0.004, 0.027, 0.211, 0.015, 0.025 and 0.0001 respectively). 5 genes (SOCS1, APC, GAdd45b, CDKN1B, and MSH2) showed the ability to be used as diagnostic biomarkers for HCC with high sensitivity and specificity values at cut off values: 1.05, 1.17, 0.995, 0.546, and 0.125 respectively. As for the other 3 genes (P15, PAX6, STAT1), PAX6 gene has the highest sensitivity at a cut off value of 0.3364. A significant negative correlation was shown between alpha fetoprotein (AFP) and 5 of the studied genes (SOCS1, APC, Gadd45b, STAT1, and MSH2).

CONCLUSIONS

Expression of the selected hypermethylated genes (SOCS1, APC, Gadd45b, CDKN1B, P15, PAX6, STAT1 and MSH2) in HCC tissue samples was lower than adjacent tissue. Their role should be further studied to solve the mystery that surrounds the pathogenesis of HCC.

The association between tumour heterogeneity and immune evasion mechanisms in hepatocellular carcinoma and its clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. The emergence of combination therapy, atezolizumab (anti-PDL1, immune checkpoint inhibitor) and bevacizumab (anti-VEGF) has revolutionised the management of HCC. Despite this breakthrough, the best overall response rate with first-line systemic therapy is only about 30%, owing to intra-tumoural heterogeneity, complex tumour microenvironment and the lack of predictive biomarkers. Many groups have attempted to classify HCC based on the immune microenvironment and have consistently observed better outcomes in immunologically "hot" HCC. We summarised possible mechanisms of tumour immune evasion based on the latest literature and the rationale for combination/sequential therapy to improve treatment response. Lastly, we proposed future strategies and therapies to overcome HCC immune evasion to further improve treatment outcomes of HCC.

MethMarkerDB: a comprehensive cancer DNA methylation biomarker database

DNA methylation plays a crucial role in tumorigenesis and tumor progression, sparking substantial interest in the clinical applications of cancer DNA methylation biomarkers. Cancer-related whole-genome bisulfite sequencing (WGBS) data offers a promising approach to precisely identify these biomarkers with differentially methylated regions (DMRs). However, currently there is no dedicated resource for cancer DNA methylation biomarkers with WGBS data. Here, we developed a comprehensive cancer DNA methylation biomarker database (MethMarkerDB, https://methmarkerdb.hzau.edu.cn/), which integrated 658 WGBS datasets, incorporating 724 curated DNA methylation biomarker genes from 1425 PubMed published articles. Based on WGBS data, we documented 5.4 million DMRs from 13 common types of cancer as candidate DNA methylation biomarkers. We provided search and annotation functions for these DMRs with different resources, such as enhancers and SNPs, and developed diagnostic and prognostic models for further biomarker evaluation. With the database, we not only identified known DNA methylation biomarkers, but also identified 781 hypermethylated and 5245 hypomethylated pan-cancer DMRs, corresponding to 693 and 2172 genes, respectively. These novel potential pan-cancer DNA methylation biomarkers hold significant clinical translational value. We hope that MethMarkerDB will help identify novel cancer DNA methylation biomarkers and propel the clinical application of these biomarkers.

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection

Hepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSystem. Gene expression regulation was statistically significant. Gene network analysis identified four out of 70 HCC marker genes whose expression regulation by viral proteins may be associated with HCC: DNA-binding protein inhibitor ID - 1 (ID1), flap endonuclease 1 (FEN1), cyclin-dependent kinase inhibitor 2A (CDKN2A), and telomerase reverse transcriptase (TERT). It suggested the following viral protein effects in HCV/human protein heterocomplexes: HCV NS3(p70) protein activates human STAT3 and NOTC1; NS2-3(p23), NS5B(p68), NS1(E2), and core(p21) activate SETD2; NS5A inhibits SMYD3; and NS3 inhibits CCN2. Interestingly, NS3 and E1(gp32) activate c-Jun when it positively regulates CDKN2A and inhibit it when it represses TERT. The discovered regulatory mechanisms might be key areas of focus for creating medications and preventative therapies to decrease the likelihood of HCC development during HCV infection.

Changes in DNA methylation profile in liver tissue during progression of HCV-induced fibrosis to hepatocellular carcinoma

In this study we compared methylation levels of 27,578 CpG sites between paired samples of the tumor and surrounding liver tissues with various degrees of damage (fibrosis, cirrhosis) in HCV-induced hepatocellular carcinoma (HCC) patients, as well as between tumor and normal tissue in non-viral HCC patients, using GSE73003 and GSE37988 data from GEODataSets (https://www.ncbi.nlm.nih.gov/). A significantly lower number of differentially methylated sites (DMS) were found between HCC of non-viral etiology and normal liver tissue, as well as between HCC and fibrosis (32 and 40), than between HCC and cirrhosis (2450 and 2304, respectively, according to GSE73003 and GSE37988 datasets). As the pathological changes in the tissue surrounding the tumor progress, the ratio of hyper-/hypomethylated DMSs in the tumor decreases. Thus, in tumor tissues compared with normal/fibrosis/cirrhosis of the liver, 75/62.5/47.7 % (GSE73003) and 16 % (GSE37988) of CpG sites are hypermethylated, respectively. Persistent hypermethylation of the ZNF154 and ZNF540 genes, as well as CCL20 hypomethylation, were registered in tumor tissue in relation to both liver fibrosis and liver cirrhosis. Protein products of the EDG4, CCL20, GPR109A, and GRM8 genes, whose CpG sites are characterized by changes in DNA methylation level in tumor tissue in the setting of cirrhosis and fibrosis, belong to "Signaling by G-protein-coupled receptors (GPCRs)" category. However, changes in the methylation level of the "driver" genes for oncopathology (АРС, CDKN2B, GSTP1, ELF4, TERT, WT1) are registered in tumor tissue in the setting of liver cirrhosis but not fibrosis. Among the genes hypermethylated in tumor tissue in the setting of liver cirrhosis, the most represented biological pathways are developmental processes, cell-cell signaling, transcription regulation, Wnt-protein binding. Genes hypomethylated in liver tumor tissue in the setting of liver cirrhosis are related to olfactory signal transduction, neuroactive ligand-receptor interaction, keratinization, immune response, inhibition of serine proteases, and zinc metabolism. The genes hypermethylated in the tumor are located at the 7p15.2 locus in the HOXA cluster region, and the hypomethylated CpG sites occupy extended regions of the genome in the gene clusters of olfactory receptors (11p15.4), keratin and keratin-associated proteins (12q13.13, 17q21.2, and 21q22.11), epidermal differentiation complex (1q21.3), and immune system function loci 9p21.3 (IFNA, IFNB1, IFNW1 cluster) and 19q13.41-19q13.42 (KLK, SIGLEC, LILR, KIR clusters). Among the genes of fibrogenesis or DNA repair, cg14143055 (ADAMDEC1) is located in the binding region of the HOX gene family transcription factors (TFs), while cg05921699 (CD79A), cg06196379 (TREM1) and cg10990993 (MLH1) are located in the binding region of the ZNF protein family transcription factor (TF). Thus, the DNA methylation profile in the liver in HCV-induced HCC is unique and differs depending on the degree of surrounding tissue lesion - liver fibrosis or liver cirrhosis.

Regulation of pleiotropic physiological roles of nitric oxide signaling

Nitric Oxide (NO) is a highly diffusible, ubiquitous signaling molecule and a free radical that is naturally synthesized by our body. The pleiotropic effects of NO in biological systems are due to its reactivity with different molecules, such as molecular oxygen (O₂), superoxide anion, DNA, lipids, and proteins. There are several contradictory findings in the literature pertaining to its role in oncology. NO is a Janus-faced molecule shown to have both tumor promoting and tumoricidal effects, which depend on its concentration, duration of exposure, and location. A high concentration is shown to have cytotoxic effects by triggering apoptosis, and at a low concentration, NO promotes angiogenesis, metastasis, and tumor progression. Upregulated NO synthesis has been implicated as a causal factor in several pathophysiological conditions including cancer. This dichotomous effect makes it highly challenging to discover its true potential in cancer biology. Understanding the mechanisms by which NO acts in different cancers helps to develop NO based therapeutic strategies for cancer treatment. This review addresses the physiological role of this molecule, with a focus on its bimodal action in various types of cancers.

Activation of VIPR1 suppresses hepatocellular carcinoma progression by regulating arginine and pyrimidine metabolism

Background and aims: Vasoactive intestinal polypeptide type-I receptor (VIPR1) overexpression has been reported in numerous types of malignancies and utilized to develop novel target therapeutics and radiolabeled VIP analogue-based tumor imaging technology, but its role in liver carcinogenesis has not been explored. In the current study, we investigated the role of the VIP/VIPR1 signaling in controlling hepatocellular carcinoma (HCC) progression.

Approach and results: By analyzing clinical samples, we found the expression level of VIPR1 was downregulated in human HCC tissues, which was correlated with advanced clinical stages, tumor growth, recurrence, and poor outcomes of HCC clinically. In vitro and in vivo studies revealed that activation of VIPR1 by VIP markedly inhibited HCC growth and metastasis. Intriguingly, transcriptome sequencing analyses revealed that activation of VIPR1 by VIP regulated arginine biosynthesis. Mechanistical studies in cultured HCC cells demonstrated that VIP treatment partially restored the expression of arginine anabolic key enzyme argininosuccinate synthase (ASS1), and to some extent, inhibited de novo pyrimidine synthetic pathway by downregulating the activation of CAD (carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase). VIP treatment upregulated ASS1 and subsequently suppressed CAD phosphorylation in an mTOR/p70S6K signaling dependent manner. Clinically, we found human HCC samples were associated with downregulation of ASS1 but upregulation of CAD phosphorylation, and that VIPR1 levels positively correlated with ASS1 levels and serum levels of urea, the end product of the urea cycle and arginine metabolism in HCC.

Conclusions: Loss of VIPR1 expression in HCC facilitates CAD phosphorylation and tumor progression, and restoration of VIPR1 and treatment with the VIPR1 agonist may be a promising approach for HCC treatment.

Identification of aberrantly methylated differentially expressed genes and pro-tumorigenic role of KIF2C in melanoma

Background: Skin Cutaneous Melanoma (SKCM) is known as an aggressive malignant cancer, which could be directly derived from melanocytic nevi. However, the molecular mechanisms underlying the malignant transformation of melanocytes and melanoma tumor progression still remain unclear. Increasing research showed significant roles of epigenetic modifications, especially DNA methylation, in melanoma. This study focused on the identification and analysis of methylation-regulated differentially expressed genes (MeDEGs) between melanocytic nevus and malignant melanoma in genome-wide profiles.

Methods: The gene expression profiling datasets (GSE3189 and GSE114445) and gene methylation profiling datasets (GSE86355 and GSE120878) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified via GEO2R. MeDEGs were obtained by integrating the DEGs and DMGs. Then, a functional enrichment analysis of MeDEGs was performed. STRING and Cytoscape were used to describe the protein-protein interaction (PPI) network. Furthermore, survival analysis was implemented to select the prognostic hub genes. Next, we conducted gene set enrichment analysis (GSEA) of hub genes. To validate, SKCM cell culture and lentivirus infection was performed to reveal the expression and behavior pattern of KIF2C. Patients and specimens were collected and then immunohistochemistry (IHC) staining was conducted.

Results: We identified 237 hypomethylated, upregulated genes and 182 hypermethylated, downregulated genes. Hypomethylation-upregulated genes were enriched in biological processes of the oxidation-reduction process, cell proliferation, cell division, phosphorylation, extracellular matrix disassembly and protein sumoylation. Pathway enrichment showed selenocompound metabolism, small cell lung cancer and lysosome. Hypermethylation-downregulated genes were enriched in biological processes of positive regulation of transcription from RNA polymerase II promoter, cell adhesion, cell proliferation, positive regulation of transcription, DNA-templated and angiogenesis. The most significantly enriched pathways involved the transcriptional misregulation in cancer, circadian rhythm, tight junction, protein digestion and absorption and Hippo signaling pathway. After PPI establishment and survival analysis, seven prognostic hub genes were CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2, and FBL. Moreover, the most involved hallmarks obtained by GSEA were E2F targets, G2M checkpoint and mitotic spindle. Importantly, among the 7 hub genes, we found that down-regulated level of KIF2C expression significantly inhibited the proliferative ability of SKCM cells and suppressed the metastasis capacity of SKCM cells.

Conclusions: Our study identified potential aberrantly methylated-differentially expressed genes participating in the process of malignant transformation from nevus to melanoma tissues based on comprehensive genomic profiles. Transcription profiles of CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2, and FBL provided clues of aberrantly methylation-based biomarkers, which might improve the development of precision medicine. KIF2C plays a pro-tumorigenic role and potentially inhibited the proliferative ability in SKCM.

The Expression and Role Analysis of Methylation-Regulated Differentially Expressed Gene UBE2C in Pan-Cancer, Especially for HGSOC

Simple Summary

DNA methylation has attracted a great deal of scientific interest as an early biomarker and potential therapeutic target. HGSOC result in high mortality due to the absence of reliable biomarkers for early diagnosis and prognosis. In this study, we performed an integrated bioinformatic analysis and found that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with advanced cancer stages and poor prognoses. Meantime, this finding was also confirmed in pan-cancer analysis. Furthermore, the experimental validation of the expression and role of UBE2C was performed on HGSOC tissues and cancer cell lines. Importantly, demethylation could upregulate the expression of UBE2C. Taken together, methylation-regulated UBE2C may be a novel biomarker for diagnosis and prognosis, not only for ovarian cancer but a variety of cancers.

Abstract

High-grade serous ovarian cancer (HGSOC) is the most fatal gynecological malignant tumor. DNA methylation is associated with the occurrence and development of a variety of tumor types, including HGSOC. However, the signatures regarding DNA methylation changes for HGSOC diagnosis and prognosis are less explored. Here, we screened differentially methylated genes and differentially expressed genes in HGSOC through the GEO database. We identified that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with more advanced cancer stages and poor prognoses. Additionally, the pan-cancer analysis showed that UBE2C was overexpressed and hypomethylation in almost all cancer types and was related to poor prognoses for various cancers. Next, we established a risk or prognosis model related to UBE2C methylation sites and screened out the three sites (cg03969725, cg02838589, and cg00242976). Furthermore, we experimentally validated the overexpression of UBE2C in HGSOC clinical samples and ovarian cell lines using quantitative real-time PCR, Western blot, and immunohistochemistry. Importantly, we discovered that ovarian cancer cell lines had lower DNA methylation levels of UBE2C than IOSE-80 cells (normal ovarian epithelial cell line) by bisulfite sequencing PCR. Consistently, treatment with 5-Azacytidine (a methylation inhibitor) was able to restore the expression of UBE2C. Taken together, our study may help us to understand the underlying molecular mechanism of UBE2C in pan-cancer tumorigenesis; it may be a useful biomarker for diagnosis, treatment, and monitoring, not only of ovarian cancer but a variety of cancers.

Combined screening analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

BACKGROUND

Methylation plays an important role in hepatocellular carcinoma (HCC) by altering the expression of key genes. The aim of this study was to screen the aberrantly methylated-differentially expressed genes (DEGs) in HCC and elucidate their underlying molecular mechanism.

METHODS

Gene expression microarrays (GSE101685) and gene methylation microarrays (GSE44909) were selected. DEGs and differentially methylated genes (DMGs) were screened. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the Database for Annotation, Visualization, and Integrated discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to analyze the functional protein-protein interaction (PPI) network. Molecular Complex Detection (MCODE) analysis was performed using the Cytoscape software. Hub genes were verified in The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 80 hypomethylation-high expression genes (Hypo-HGs) were identified. Pathway enrichment analysis showed DNA replication, cell cycle, viral carcinogenesis, and the spliceosome. The top 5 hub genes were minichromosome maintenance complex component 3 (MCM3), checkpoint kinase 1 (CHEK1), kinesin family member 11 (KIF11), PDZ binding kinase (PBK), and Rac GTPase activating protein 1 (RACGAP1). In addition, 189 hypermethylation-low expression genes (Hyper-LGs) were identified. Pathway enrichment analysis indicated enrichment in metabolic pathways, drug metabolism-other enzymes, and chemical carcinogenesis. The top 5 hub genes were leukocyte immunoglobulin like receptor B2 (LILRB2), formyl peptide receptor 1 (FPR1), S100 calcium binding protein A9 (S100A9), S100 calcium binding protein A8 (S100A8), and myeloid cell nuclear differentiation antigen (MNDA). The methylation status and mRNA expression of MCM3, CHEK1, KIF11, PBK, and S100A9 were consistent in the TCGA database and significantly correlated with the prognosis of patients.

CONCLUSIONS

Combined screening of aberrantly methylated-DEGs based on bioinformatic analysis may provide new clues for elucidating the epigenetic mechanism in HCC. Hub genes, including MCM3, CHEK1, KIF11, PBK, and S100A9, may serve as biomarkers for the precise diagnosis of HCC.

Maternal Choline Supplementation and High-Fat Feeding Interact to Influence DNA Methylation in Offspring in a Time-Specific Manner

Maternal methyl donor supplementation during pregnancy has demonstrated lasting influence on offspring DNA methylation. However, it is unknown whether an adverse postnatal environment, such as high-fat (HF) feeding, overrides the influence of prenatal methyl donor supplementation on offspring epigenome. In this study, we examined whether maternal supplementation of choline (CS), a methyl donor, interacts with prenatal and postnatal HF feeding to alter global and site-specific DNA methylation in offspring. We fed wild-type C57BL/6J mouse dams a HF diet with or without CS throughout gestation. After weaning, the offspring were exposed to HF feeding for 6 weeks resembling a continued obesogenic environment. Our results suggest that maternal CS under the HF condition (HFCS) increased global DNA methylation and DNA methyltransferase 1 (Dnmt1) expression in both fetal liver and brain. However, during the postnatal period, HFCS offspring demonstrated lower global DNA methylation and Dnmt1 expression was unaltered in both the liver and visceral adipose tissue. Site-specific DNA methylation analysis during both fetal and postnatal periods demonstrated that HFCS offspring had higher methylation of CpGs in the promoter of Srebf1, a key mediator of de novo lipogenesis. In conclusion, the influence of maternal CS on offspring DNA methylation is specific to HF feeding status during prenatal and postnatal periods. Without continued CS during the postnatal period, global DNA methylation enhanced by prenatal CS in the offspring was overridden by postnatal HF feeding.

The effect of key DNA methylation in different regions on gene expression in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cancer with high morbidity and mortality. As we all know, the alteration of DNA methylation has a crucial impact on the occurrence of HCC. However, the mechanism of the effect of DNA methylation in different regions on gene expression is still unclear. Here, by computing and analyzing the distribution of differential methylation in 12 different regions in HCC tissues and adjacent normal tissues, not only the hypermethylation of CpG islands and global hypomethylation were found, but also a stable distribution pattern of differential methylation in HCC was found. Then the correlations between DNA methylations in different regions and gene expressions were calculated, and the diversity of correlations in different regions was determined. The key genes of differential methylation and differential expression related to the survival of HCC patients were obtained by using Cox regression analysis, a four-gene prognostic risk scoring model was constructed, and the prognostic performance was well verified. The regions of the differentially methylated CpG sites corresponding to the four key genes were located and their influences on the expression were analyzed. The results indicate that the promoter, first exon, 5'UTR, sixth exon, N_Shore, and S_Shore hypomethylation promotes the expression of key oncogenes, which together lead to the occurrence of HCC. These results might help to study the role of DNA methylation in HCC and provide potential biomarkers for the diagnosis of HCC.

Identification of prostate cancer specific methylation biomarkers from a multi-cancer analysis

Background

Detecting prostate cancer at a non-aggressive stage is the main goal of prostate cancer screening. DNA methylation has been widely used as biomarkers for cancer diagnosis and prognosis, however, with low clinical translation rate. By taking advantage of multi-cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we aimed to identify prostate cancer specific biomarkers which can separate between non-aggressive and aggressive prostate cancer based on DNA methylation patterns.

Results

We performed a comparison analysis of DNA methylation status between normal prostate tissues and prostate adenocarcinoma (PRAD) samples at different Gleason stages. The candidate biomarkers were selected by excluding the biomarkers existing in multiple cancers (pan-cancer) and requiring significant difference between PRAD and other urinary samples. By least absolute shrinkage and selection operator (LASSO) selection, 8 biomarkers (cg04633600, cg05219445, cg05796128, cg10834205, cg16736826, cg23523811, cg23881697, cg24755931) were identified and in-silico validated by model constructions. First, all 8 biomarkers could separate PRAD at different stages (Gleason 6 vs. Gleason 3 + 4: AUC = 0.63; Gleason 6 vs. Gleason 4 + 3 and 8–10: AUC = 0.87). Second, 5 biomarkers (cg04633600, cg05796128, cg23523811, cg23881697, cg24755931) effectively detected PRAD from normal prostate tissues (AUC ranged from 0.88 to 0.92). Last, 6 biomarkers (cg04633600, cg05219445, cg05796128, cg23523811, cg23881697, cg24755931) completely distinguished PRAD with other urinary samples (AUC = 1).

Conclusions

Our study identified and in-silico validated a panel of prostate cancer specific DNA methylation biomarkers with diagnosis value.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04416-w.

Downregulated Expression of CLEC9A as Novel Biomarkers for Lung Adenocarcinoma

Purpose

Abnormal CLEC9A expression is concerned with carcinogenesis. However, the role of CLEC9A in lung adenocarcinoma (LUAD) remains unknown. The goal of this study was to reveal the role of CLEC9A in LUAD based on bioinformatics and cellular functional experiments.

Materials and methods

Data available from The Cancer Genome Atlas (TCGA) were employed to study CLEC9A expression and mutations in LUAD. Expression and alterations of CLEC9A were analyzed using UALCAN and cBioPortal, respectively. Kaplan-Meier analysis was used to analyze the effect of CLEC9A on the survival of LUAD. Protein-protein interaction (PPI) network was built using GeneMANIA analysis. The similar genes of CLEC9A were obtained using GEPIA analysis, while co-expression genes correlated with CLEC9A were identified using LinkedOmics analysis. The effects of CLEC9A expression on immune cell infiltration was assessed. The effect of CLEC9A on the proliferation, apoptosis, cell cycle distribution, and invasion of human LUAD cells was detected in the LUAD cell line.

Results

CLEC9A was downregulated and the CLEC9A gene was often altered in LUAD. The survival of LUAD patients was correlated with the expression level of CLEC9A. The similar genes of CLEC9A were linked to functional networks involving positive regulation of interleukin-12 production, plasma membrane and CD40 receptor binding, primary immunodeficiency, intestinal immune network for IgA production, and cell adhesion molecules pathways. Cell cycle, apoptosis, EMT, and RAS/MAPK were significantly enriched pathways in positive and negative correlation genes with CLEC9A. A difference in the immune infiltration level of immune cell between the high and low CLEC9A expression groups was observed. Somatic cell copy number alternations (CNAs) of the CLEC9A, including arm-level gain and arm-level deletion, observably changed the infiltration levels of B cells, CD4+ T cells, macrophages, and neutrophils in LUAD. Except for LAG3, the expression of CD274, CTLA4, PDCD1, and TIGIT was positively correlated with the expression level of CLEC9A. After transfection, overexpression and knockdown of CLEC9A could affect the proliferation, apoptosis, cell cycle distribution, and invasion of LUAD cells.

Conclusion

CLEC9A is associated with prognosis and tumor immune microenvironment of LUAD, suggesting that CLEC9A may be considered as a novel biomarker for LUAD.

The Relevance of SOCS1 Methylation and Epigenetic Therapy in Diverse Cell Populations of Hepatocellular Carcinoma

The suppressor of cytokine signaling 1 (SOCS1) is a tumor suppressor gene found to be hypermethylated in cancers. It is involved in the oncogenic transformation of cirrhotic liver tissues. Here, we investigated the clinical relevance of SOCS1 methylation and modulation upon epigenetic therapy in diverse cellular populations of hepatocellular carcinoma (HCC). HCC clinical specimens were evaluated for SOCS1 methylation and mRNA expression. The effect of 5-Azacytidine (5-AZA), a demethylation agent, was assessed in different subtypes of HCC cells. We demonstrated that the presence of SOCS1 methylation was significantly higher in HCC compared to peri-HCC and non-tumoral tissues (52% vs. 13% vs. 14%, respectively, p < 0.001). In vitro treatment with a non-toxic concentration of 5-AZA significantly reduced DNMT1 protein expression for stromal subtype lines (83%, 73%, and 79%, for HLE, HLF, and JHH6, respectively, p < 0.01) compared to cancer stem cell (CSC) lines (17% and 10%, for HepG2 and Huh7, respectively), with the strongest reduction in non-tumoral IHH cells (93%, p < 0.001). 5-AZA modulated the SOCS1 expression in different extents among the cells. It was restored in CSC HCC HepG2 and Huh7 more efficiently than sorafenib. This study indicated the relevance of SOCS1 methylation in HCC and how cellular heterogeneity influences the response to epigenetic therapy.

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

Epigenetic Changes Affecting the Development of Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma is a life-threatening disease. Despite many efforts to understand the exact pathogenesis and the signaling pathways involved in its formation, treatment remains unsatisfactory. Currently, an important function in the development of neoplastic diseases and treatment effects is attributed to changes taking place at the epigenetic level. Epigenetic studies revealed modified methylation patterns in HCC, dysfunction of enzymes engaged in the DNA methylation process, the aberrant function of non-coding RNAs, and a set of histone modifications that influence gene expression. The aim of this review is to summarize the current knowledge on the role of epigenetics in the formation of hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) remains a serious oncologic issue with still a dismal prognosis. So far, no key molecular mechanism that underlies its pathogenesis has been identified. Recently, by specific molecular approaches, many genetic and epigenetic changes arising during HCC pathogenesis were detected. Epigenetic studies revealed modified methylation patterns in HCC tumors, dysfunction of enzymes engaged in the DNA methylation process, and a set of histone modifications that influence gene expression. HCC cells are also influenced by the disrupted function of non-coding RNAs, such as micro RNAs and long non-coding RNAs. Moreover, a role of liver cancer stem cells in HCC development is becoming evident. The reversibility of epigenetic changes offers the possibility of influencing them and regulating their undesirable effects. All these data can be used not only to identify new therapeutic targets but also to predict treatment response. This review focuses on epigenetic changes in hepatocellular carcinoma and their possible implications in HCC therapy.

Methylation degree of metalloproteinase inhibitor RECK gene: Links to RECK protein level and hepatocellular carcinoma in chronic HCV infection patients

The RECK gene, a tumor suppressor gene, inhibits angiogenesis, invasion, and tumor metastasis. Epigenetic regulation of the RECK gene constitutes a potent approach to the molecular basis of liver malignancy. This study aims to evaluate the promoter methylation status of the RECK gene and its serum level in patients with hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) and the potential association of RECK gene methylation with clinical criteria of HCC. One hundred and fifty-five subjects were included (healthy control [55], chronic HCV patients [55], HCV-related HCC patients [45]). The methylation status of the RECK gene promoter and serum RECK level were investigated by methylation-specific PCR and enzyme-linked immunosorbent assay techniques, respectively. RECK gene promoter hypermethylation was recorded in 46.7% of HCC patients, and 10.9% of HCV patients, but not in control subjects (0%). It was related to RECK protein level, varices, edema, ascites, lymph node metastasis, vascular invasion, and the largest diameter of focal lesions. Meanwhile, it was not associated with focal lesion number nor distant metastasis of HCC. In conclusion, RECK gene promoter hypermethylation is linked to HCV genotype-4-related HCC. Moreover, different degrees of RECK gene promoter methylation are associated with serum RECK level, lymph node metastasis, and vascular invasion, which could prove its pathogenic role in hepatocarcinogenesis in chronic HCV-infected patients.

Role of Nitric Oxide in Gene Expression Regulation during Cancer: Epigenetic Modifications and Non-Coding RNAs

Nitric oxide (NO) has been identified and described as a dual mediator in cancer according to dose-, time- and compartment-dependent NO generation. The present review addresses the different epigenetic mechanisms, such as histone modifications and non-coding RNAs (ncRNAs), miRNA and lncRNA, which regulate directly or indirectly nitric oxide synthase (NOS) expression and NO production, impacting all hallmarks of the oncogenic process. Among lncRNA, HEIH and UCA1 develop their oncogenic functions by inhibiting their target miRNAs and consequently reversing the inhibition of NOS and promoting tumor proliferation. The connection between miRNAs and NO is also involved in two important features in cancer, such as the tumor microenvironment that includes key cellular components such as tumor-associated macrophages (TAMs), cancer associated fibroblasts (CAFs) and cancer stem cells (CSCs).

Identification of Methylation-Regulated Differentially Expressed Genes and Related Pathways in Hepatocellular Carcinoma: A Study Based on TCGA Database and Bioinformatics Analysis

Background

In recent years, DNA methylation modification has been shown to be a critical mechanism in the field of epigenetics.

Methods

Hepatocellular carcinoma (HCC) data were obtained from The Cancer Genome Atlas project, including RNA expression profiles, Illumina Human Methylation 450K BeadChip data, clinical information, and pathological features. Then, differentially expressed genes (DEGs) and differentially methylated genes were identified using R software. Methylation-regulated DEGs (MeDEGs) were further analyzed using Spearman’s correlation analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database and ClueGO in Cytoscape software. Kaplan–Meier survival analysis explored the relationship between methylation, expression of MeDEGs, and survival time. Gene set enrichment analysis (GSEA) was conducted to predict the function of prognosis-related MeDEGs.

Results

A total of nine up-regulated and 72 down-regulated MeDEGs were identified. GO and KEGG pathway analyses results indicated that multiple cancer-related terms were enriched. Kaplan–Meier survival analysis showed that the methylation status of four MeDEGs (CTF1, FZD8, PDK4, and ZNF334) was negatively associated with overall survival. Moreover, the methylation status of CDF1 and PDK4 was identified as an independent prognostic factor. According to GSEA, hypermethylation of prognosis-related MeDEGs was enriched in pathways that included “Spliceosome”, “Cell cycle”, “RNA degradation”, “RNA polymerase”, “DNA replication”, “Mismatch repair”, “Base excision repair”, “Nucleotide excision repair”, “Homologous recombination”, “Protein export”, and “Pyrimidine metabolism”.

Conclusions

Aberrant DNA methylation plays a critical role in malignant progression of HCC. Prognosis-related MeDEGs identified in this research may be potential biomarkers and targets in diagnosis and treatment.

Estrogen Receptor-α Suppresses Liver Carcinogenesis and Establishes Sex-Specific Gene Expression

Estrogen protects females from hepatocellular carcinoma (HCC). To determine whether this protection is mediated by classic estrogen receptors, we tested HCC susceptibility in estrogen receptor-deficient mice. In contrast to a previous study, we found that diethylnitrosamine induces hepatocarcinogenesis to a significantly greater extent when females lack Esr1, which encodes Estrogen Receptor-α. Relative to wild-type littermates, Esr1 knockout females developed 9-fold more tumors. Deficiency of Esr2, which encodes Estrogen Receptor-β, did not affect liver carcinogenesis in females. Using microarrays and QPCR to examine estrogen receptor effects on hepatic gene expression patterns, we found that germline Esr1 deficiency resulted in the masculinization of gene expression in the female liver. Six of the most dysregulated genes have previously been implicated in HCC. In contrast, Esr1 deletion specifically in hepatocytes of Esr1 conditional null female mice (in which Cre was expressed from the albumin promoter) resulted in the maintenance of female-specific liver gene expression. Wild-type adult females lacking ovarian estrogen due to ovariectomy, which is known to make females susceptible to HCC, also maintained female-specific expression in the liver of females. These studies indicate that Esr1 mediates liver cancer risk, and its control of sex-specific liver gene expression involves cells other than hepatocytes.

Gene networks and transcriptional regulators associated with liver cancer development and progression

BACKGROUND

Treatment options for hepatocellular carcinoma (HCC) are limited, and overall survival is poor. Despite the high frequency of this malignoma, its basic disease mechanisms are poorly understood. Therefore, the aim of this study was to use different methodological approaches and combine the results to improve our knowledge on the development and progression of HCC.

METHODS

Twenty-three HCC samples were characterized by histological, morphometric and cytogenetic analyses, as well as comparative genomic hybridization (aCGH) and genome-wide gene expression followed by a bioinformatic search for potential transcriptional regulators and master regulatory molecules of gene networks.

RESULTS

Histological evaluation revealed low, intermediate and high-grade HCCs, and gene expression analysis split them into two main sets: GE1-HCC and GE2-HCC, with a low and high proliferation gene expression signature, respectively. Array-based comparative genomic hybridization demonstrated a high level of chromosomal instability, with recurrent chromosomal gains of 1q, 6p, 7q, 8q, 11q, 17q, 19p/q and 20q in both HCC groups and losses of 1p, 4q, 6q, 13q and 18q characteristic for GE2-HCC. Gene expression and bioinformatics analyses revealed that different genes and gene regulatory networks underlie the distinct biological features observed in GE1-HCC and GE2-HCC. Besides previously reported dysregulated genes, the current study identified new candidate genes with a putative role in liver cancer, e.g. C1orf35, PAFAH1B3, ZNF219 and others.

CONCLUSION

Analysis of our findings, in accordance with the available published data, argues in favour of the notion that the activated E2F1 signalling pathway, which can be responsible for both inappropriate cell proliferation and initial chromosomal instability, plays a pivotal role in HCC development and progression. A dedifferentiation switch that manifests in exaggerated gene expression changes might be due to turning on transcriptional co-regulators with broad impact on gene expression, e.g. POU2F1 (OCT1) and NFY, as a response to accumulating cell stress during malignant development. Our findings point towards the necessity of different approaches for the treatment of HCC forms with low and high proliferation signatures and provide new candidates for developing appropriate HCC therapies.

Tracking Down the Epigenetic Footprint of HCV-Induced Hepatocarcinogenesis

Hepatitis C virus (HCV) is a major cause of death and morbidity globally and is a leading cause of hepatocellular carcinoma (HCC). Incidence of HCV infections, as well as HCV-related liver diseases, are increasing. Although now, with new direct acting antivirals (DAAs) therapy available, HCV is a curable cancer-associated infectious agent, HCC prevalence is expected to continue to rise because HCC risk still persists after HCV cure. Understanding the factors that lead from HCV infection to HCC pre- and post-cure may open-up opportunities to novel strategies for HCC prevention. Herein, we provide an overview of the reported evidence for the induction of alterations in the transcriptome of host cells via epigenetic dysregulation by HCV infection and describe recent reports linking the residual risk for HCC post-cure with a persistent HCV-induced epigenetic signature. Specifically, we discuss the contribution of the epigenetic changes identified following HCV infection to HCC risk pre- and post-cure, the molecular pathways that are epigenetically altered, the downstream effects on expression of cancer-related genes, the identification of targets to prevent or revert this cancer-inducing epigenetic signature, and the potential contribution of these studies to early prognosis and prevention of HCC as an approach for reducing HCC-related mortality.

Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis.

Methods

A bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003).

Results

Firstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes, MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 which played key roles in HCC. The results of multiple verification methods indicated that the 11 hub genes had highly diagnostic efficiencies to distinguish tumors from normal tissues. Lastly, the methylation changes of gene CDC20, TOP2A, TK1, FEN1 in HCC samples had statistical significance (P-value < 0.05).

Conclusion

MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, the cell cycle and mitotic pathway might played vital roles in the progression of HCC.

circRNA circ_102049 Implicates in Pancreatic Ductal Adenocarcinoma Progression through Activating CD80 by Targeting miR-455-3p

Emerging evidence has shown that circular RNAs (circRNAs) and DNA methylation play important roles in the causation and progression of cancers. However, the roles of circRNAs and abnormal methylation genes in the tumorigenesis of pancreatic ductal adenocarcinoma (PDAC) are still largely unknown. Expression profiles of circRNA, gene methylation, and mRNA were downloaded from the GEO database, and differentially expressed genes were obtained via GEO2R, and a ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Inflammation-associated genes were collected from the GeneCards database. Then, functional enrichment analysis and protein-protein interaction (PPI) networks of inflammation-associated methylated expressed genes were investigated using Metascape and STRING databases, respectively, and visualized in Cytoscape. Hub genes of PPI networks were identified using the NetworkAnalyzer plugin. Also, we analyzed the methylation, protein expression levels, and prognostic value of hub genes in PDAC patients through the UALCAN, Human Protein Atlas (HPA), and Kaplan-Meier plotter databases, respectively. The circRNA_102049/miR-455-3p/CD80 axis was identified by the ceRNA network and hub genes. In vitro and in vivo experiments were performed to evaluate the functions of circRNA_102049. The regulatory mechanisms of circRNA_102049 and miR-455-3p were explored by RT-PCR, western blot, and dual-luciferase assays. In the present study, twelve hub genes (STAT1, CCND1, KRAS, CD80, ICAM1, ESR1, RAF1, RPS6KA2, KDM6B, TNRC6A, FOSB, and DNM1) were determined from the PPI networks. Additionally, the circRNA_102049 was upregulated in PDAC cell lines. Functionally, the knockdown of circRNA_102049 by siRNAs inhibited cell growth, inflammatory factors, and migratory and invasive potential and promoted cell apoptosis. Mechanistically, circRNA_102049 functioned as a sponge of miR-455-3p and partially reversed the effect of miR-455-3p and consequently upregulated CD80 expression. Our findings showed that circRNA_102049 and methylated hub genes play an important role in the proliferation, apoptosis, migration, invasion, and inflammatory response of PDAC, which might be selected as a promising prognostic marker and therapeutic target for PDAC.

Identification of Key Pathways and Genes in Obesity Using Bioinformatics Analysis and Molecular Docking Studies

Obesity is an excess accumulation of body fat. Its progression rate has remained high in recent years. Therefore, the aim of this study was to diagnose important differentially expressed genes (DEGs) associated in its development, which may be used as novel biomarkers or potential therapeutic targets for obesity. The gene expression profile of E-MTAB-6728 was downloaded from the database. After screening DEGs in each ArrayExpress dataset, we further used the robust rank aggregation method to diagnose 876 significant DEGs including 438 up regulated and 438 down regulated genes. Functional enrichment analysis was performed. These DEGs were shown to be significantly enriched in different obesity related pathways and GO functions. Then protein-protein interaction network, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. The module analysis was performed based on the whole PPI network. We finally filtered out STAT3, CORO1C, SERPINH1, MVP, ITGB5, PCM1, SIRT1, EEF1G, PTEN and RPS2 hub genes. Hub genes were validated by ICH analysis, receiver operating curve (ROC) analysis and RT-PCR. Finally a molecular docking study was performed to find small drug molecules. The robust DEGs linked with the development of obesity were screened through the expression profile, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for obesity.

A prognostic nomogram for lung adenocarcinoma based on immune-infiltrating Treg-related genes: from bench to bedside

Background

Accumulating evidence suggests that lymphocyte infiltration in the tumor microenvironment is positively correlated with tumorigenesis and development, while the role of Tregs (regulatory T cells) has been controversial. Therefore, we attempted to discover the possible value of Tregs for lung adenocarcinoma (LUAD).

Methods

The gene-sequencing data of LUAD were applied from three Gene Expression Omnibus (GEO) datasets—GSE10072, GSE32863 and GSE43458; the corresponding fractions of tumor-infiltrating immune cells were extracted from the CIBERSORTx portal. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis were conducted to identify the significant module and candidate genes related to Tregs. The role of candidate genes in LUAD was further verified using data from The Cancer Genome Atlas (TCGA) database. Finally, we constructed a nomogram model to predict the prognosis of LUAD by plotting Kaplan-Meier (K-M), receiver operating characteristic (ROC) and calibration curves, which elucidated the performance of the nomogram.

Results

In total, 10,047 genes in 333 samples (196 tumor and 137 normal samples) from the GEO database were included. By WGCNA and PPI analysis, we identified a significant black module and 36 candidate genes related to Treg. Next, the candidate genes were verified using TCGA data by Cox regression analysis to screen 13 hub genes that stratified LUAD patients into low- or high-risk groups. Low-risk patients showed a significantly longer overall survival (OS) than high-risk patients (3-year OS: 70.2% vs. 35.2%; 5-year OS: 36.6% vs. 0; P=1.651E-09), and the areas under the ROC curves (AUCs) showed good (3-year AUC: 0.733; 5-year AUC: 0.777). Next, we constructed a survival nomogram combining the hub genes and clinical parameters; the low-risk patients still showed a favorable prognosis compared with that of the high-risk patients (P=7.073E-13), and the AUCs were better (3-year AUC: 0.763; 5-year AUC: 0.873).

Conclusions

We revealed the role of immune-infiltrating Treg-related genes in LUAD and constructed a prognostic nomogram, which may help clinicians make optimal therapeutic decisions and help patients obtain better outcomes.

ITGB1 Drives Hepatocellular Carcinoma Progression by Modulating Cell Cycle Process Through PXN/YWHAZ/AKT Pathways

Integrin β1 (ITGB1), which acts as an extracellular matrix (ECM) receptor, has gained increasing attention as a therapeutic target for the treatment of hepatocellular carcinoma (HCC). However, the underpinning mechanism of how ITGB1 drives HCC progression remains elusive. In this study, we first found that ITGB1 expression was significantly higher in HCC tissues than in normal controls by bioinformatics analysis. Furthermore, bioinformatics analysis revealed that paxillin (PXN) and 14-3-3 protein zeta (YWHAZ) are the molecules participating in ITGB1-regulated HCC tumor cell cycle progression. Indeed, immunohistochemistry (IHC) revealed that ITGB1, paxillin, and YWHAZ were strongly upregulated in paired HCC tissue compared with adjacent normal tissues. Notably, the inhibition of ITGB1 expression by small interfering RNA (siRNA) resulted in the downregulated expression of PXN and YWHAZ in primary HCC cells, as assessed by western blot and immunostaining. In addition, ITGB1 knockdown markedly impaired the aggressive behavior of HCC tumor cells and delayed cell cycle progression as determined by cell migration assay, drug-resistance analysis, colony formation assay, quantitative real-time polymerase chain reaction (qRT-PCR), and cell cycle analysis as well as cell viability measurements. More importantly, we proved that xenograft ITGB1^high tumors grew more rapidly than ITGB1^low tumors. Altogether, our study showed that the ITGB1/PXN/YWHAZ/protein kinase B (AKT) axis enhances HCC progression by accelerating the cell cycle process, which offers a promising approach to halt HCC tumor growth.

HDNA methylation data-based molecular subtype classification related to the prognosis of patients with hepatocellular carcinoma

Background

DNA methylation is a common chemical modification of DNA in the carcinogenesis of hepatocellular carcinoma (HCC).

Methods

In this bioinformatics analysis, 348 liver cancer samples were collected from the Cancer Genome Atlas (TCGA) database to analyse specific DNA methylation sites that affect the prognosis of HCC patients.

Results

10,699 CpG sites (CpGs) that were significantly related to the prognosis of patients were clustered into 7 subgroups, and the samples of each subgroup were significantly different in various clinical pathological data. In addition, by calculating the level of methylation sites in each subgroup, 119 methylation sites (corresponding to 105 genes) were selected as specific methylation sites within the subgroups. Moreover, genes in the corresponding promoter regions in which the above specific methylation sites were located were subjected to signalling pathway enrichment analysis, and it was discovered that these genes were enriched in the biological pathways that were reported to be closely correlated with HCC. Additionally, the transcription factor enrichment analysis revealed that these genes were mainly enriched in the transcription factor KROX. A naive Bayesian classification model was used to construct a prognostic model for HCC, and the training and test data sets were used for independent verification and testing.

Conclusion

This classification method can well reflect the heterogeneity of HCC samples and help to develop personalized treatment and accurately predict the prognosis of patients.

Prognostic implications of aberrantly expressed methylation‑driven genes in hepatocellular carcinoma: A study based on The Cancer Genome Atlas

RNA‑Sequencing and methylation data for hepatocellular carcinoma (HCC) were downloaded from The Cancer Genome Atlas (TCGA). The aberrantly expressed methylation‑driven genes in HCC and normal tissues were identified using the Limma package and the MethylMix algorithm. The Database for Annotation, Visualization and Integrated Discovery and ConsensusPathDB were used for Gene Ontology (GO) enrichment and pathway analysis. Univariate and multivariate Cox regression analyses were used to construct a prognostic risk model of HCC. Survival curve and receiver operating characteristic (ROC) curves were applied to evaluate the clinical utility of the risk model. A total of 238 methylation‑driven genes were successfully identified from cancer and normal tissues. GO enrichment analysis indicated that these genes functioned in the extracellular space, interfering with lipid metabolism in hepatocytes and regulating adaptive immune responses. In total, 14 relevant pathways were identified. The following prognostic risk model was generated: Risk score=CALML3 (degree of methylation) x (‑4.860) + CCNI2 x (2.071) + TNFRSF12A x (‑3.369) + IFITM1 x (1.203) + ENPP7P13 x (‑1.366) + DDT x (2.139) + RASAL2‑AS1 x (‑1.384) + ANKRD22 x (‑3.215). The median risk score (0.970) derived from this model was set as cutoff value for assigning patients to high‑ or low‑risk group. The 5‑year survival rate was 35.8% [95% confidence interval (CI)=27.1‑47.4%] in the high‑risk group and 61.7% (95% CI=51.4‑74.2%) in the low‑risk group (P<0.0001). The ROC curve showed an area under the curve of 0.742, indicating that this model is appropriate for predicting the survival rate of patients. Furthermore, the methylation and expression levels of two key genes, tumor necrosis factor superfamily member 12A and D‑dopachrome decarboxylase, were significantly associated with prognosis and were correlated with cg00510447, cg26808293, cg11060661 and cg16132339 methylation. In conclusion, a prognostic risk model for HCC is proposed based on the bioinformatic analysis of methylation‑driven genes. The findings of the present study may improve understanding of the pathogenesis and prognosis of HCC.

Development and validation of a CIMP-associated prognostic model for hepatocellular carcinoma

Background

CpG island methylator phenotype (CIMP), a common biological phenomenon characterized by a subset of concurrently methylated genes, can have an influence on the progression of multiple cancers. However, the potential mechanism of CIMP in hepatocarcinogenesis and its clinical relevance remains only partially understood.

Methods: We used a methylation array from the cancer genome atlas (TCGA) to stratify HCC patients into different CIMP subtypes, and evaluated their correlation with clinical characteristics. In addition, mutation, CNV, and transcriptome profiles were also utilized to evaluate the distinctive genomic patterns correlated with CIMP. Finally, a CIMP-associated prognostic model (CPM) was trained and validated using four independent datasets.

Findings

A subgroup of patients was identified as having CIMP-H, which was associated with worse OS and DFS. Gene enrichment analysis indicated that the terms “liver cancer with EPCAM up”, “tumor invasiveness up”, “methyltransferase complex”, and “translational initiation” were enriched in CIMP-H subgroup. Notably, somatic mutation analysis indicated that CIMP-H patients presented with a higher mutation burden of BRD4, DDIAS and NOX1. Moreover, four CPM associated genes could significantly categorize patients into low- and high-risk groups in the training dataset and another 3 independent validation datasets. Finally, a nomogram incorporating a classifier based on four mRNAs, pathological M stage and CIMP status was established, which showed a favorable discriminating ability and might contribute to clinical decision-making for HCC.

Interpretation

Our work highlights the potential clinical application value of CPM in predicting the overall survival of HCC patients and the mechanisms underlying the role of CIMP in hepatocarcinogenesis.

Fund

This work was supported by the State Key Project on Infectious Diseases of China (2018ZX10723204-003), the National Nature Science Foundation of China (Nos. 81874065, 81500565, 81874149, 81572427, and 81401997), the Hepato-Biliary-Pancreatic Malignant Tumor Investigation Fund of Chen Xiao-ping Foundation for the Development of Science and Technology of Hubei Province (CXPJJH11800001-2018356).

Discovery and validation of methylated-differentially expressed genes in Helicobacter pylori-induced gastric cancer

DNA methylation has an important role in Helicobacter pylori (H. pylori)-induced gastric cancer (GC) processes and development. The aim of this study was to search genome-scale epigenetic modifications for studying pathogenesis of H. pylori-induced GC, and to find factors and powerful signature related to survival and prognosis. In this study, we conducted a comprehensive analysis of DNA methylation and gene expression profiles in the Gene Expression Omnibus (GEO), to identified differentially expressed genes (DEGs) and differentially methylated genes (DMGs). Functional enrichment analysis of the screened genes was performed, and a protein-protein interaction network was constructed. The TCGA DNA methylation databases and 55 H. pylori-infected GC cases of GEO RNA sequencing (GSE62254) were utilized for prognostic value validation of hub genes. Finally, a prognosis-related risk signature was identified by a series of bioinformatics analysis for H. pylori-induced GC patients. Totally, 161 DMGs were identified. Pathway analysis showed that all MDEGs mainly associated with Ras signaling pathway, renal cell carcinoma, mitogen-activated protein kinase signaling pathway. Five hub genes including CACNB2, GNB4, GRIN2A, MEF2C, and PREX1 were screened as independent prognostic factors in H. pylori-induced GC patients. Two-gene (CACNB2 and MEF2C) risk signature was constructed for predicting the overall survival of H. pylori-induced GC patients. Our study indicated possible MDEGs and pathways in H. pylori-induced GC by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of H. pylori-induced GC. Hub genes might serve as aberrantly methylation-based biomarkers for clinical diagnostic and prognostic evaluation of H. pylori-induced GC.

Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA-Seq data

Endometrial cancer is highly malignant and has a poor prognosis in the advanced stage, thus, prediction of its prognosis is important. DNA methylation has rapidly gained clinical attention as a biomarker for diagnostic, prognostic and predictive purposes in various cancers. In present study, differentially methylated positions and differentially expressed genes were identified according to DNA methylation and RNA-Seq data. Functional analyses and interaction network were performed to identify hub genes, and overall survival analysis of hub genes were validated. The top genes were evaluated by immunohistochemical staining of endometrial cancer tissues. The gene function was evaluated by cell growth curve after knockdown CDC20 and CCNA2 of endometrial cancer cell line. A total of 329 hypomethylated highly expressed genes and 359 hypermethylated lowly expressed genes were identified, and four hub genes were obtained according to the interaction network. Patients with low expression of CDC20 and CCNA2 showed better overall survival. The results also were demonstrated by the immunohistochemical staining. Cell growth curve also demonstrated that knockdown CDC20 and CCNA2 can suppress the cell proliferation. We have identified two aberrantly methylated genes, CDC20 and CCNA2 as novel biomarkers for precision diagnosis in EC.

Transcriptome Analysis Revealed a Highly Connected Gene Module Associated With Cirrhosis to Hepatocellular Carcinoma Development

Introduction

Cirrhosis is one of the most important risk factors for development of hepatocellular carcinoma (HCC). Recent studies have shown that removal or well control of the underlying cause could reduce but not eliminate the risk of HCC. Therefore, it is important to elucidate the molecular mechanisms that drive the progression of cirrhosis to HCC.

Materials and Methods

Microarray datasets incorporating cirrhosis and HCC subjects were identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were determined by GEO2R software. Functional enrichment analysis was performed by the clusterProfiler package in R. Liver carcinogenesis-related networks and modules were established using STRING database and MCODE plug-in, respectively, which were visualized with Cytoscape software. The ability of modular gene signatures to discriminate cirrhosis from HCC was assessed by hierarchical clustering, principal component analysis (PCA), and receiver operating characteristic (ROC) curve. Association of top modular genes and HCC grades or prognosis was analyzed with the UALCAN web-tool. Protein expression and distribution of top modular genes were analyzed using the Human Protein Atlas database.

Results

Four microarray datasets were retrieved from GEO database. Compared with cirrhotic livers, 125 upregulated and 252 downregulated genes in HCC tissues were found. These DEGs constituted a liver carcinogenesis-related network with 272 nodes and 2954 edges, with 65 nodes being highly connected and formed a liver carcinogenesis-related module. The modular genes were significantly involved in several KEGG pathways, such as “cell cycle,” “DNA replication,” “p53 signaling pathway,” “mismatch repair,” “base excision repair,” etc. These identified modular gene signatures could robustly discriminate cirrhosis from HCC in the validation dataset. In contrast, the expression pattern of the modular genes was consistent between cirrhotic and normal livers. The top modular genes TOP2A, CDC20, PRC1, CCNB2, and NUSAP1 were associated with HCC onset, progression, and prognosis, and exhibited higher expression in HCC compared with normal livers in the HPA database.

Conclusion

Our study revealed a highly connected module associated with liver carcinogenesis on a cirrhotic background, which may provide deeper understanding of the genetic alterations involved in the transition from cirrhosis to HCC, and offer valuable variables for screening and surveillance of HCC in high-risk patients with cirrhosis.

Identification of DNA methylation-driven genes in esophageal squamous cell carcinoma: a study based on The Cancer Genome Atlas

Background

Aberrant DNA methylations are significantly associated with esophageal squamous cell carcinoma (ESCC). In this study, we aimed to investigate the DNA methylation-driven genes in ESCC by integrative bioinformatics analysis.

Methods

Data of DNA methylation and transcriptome profiling were downloaded from TCGA database. DNA methylation-driven genes were obtained by methylmix R package. David database and ConsensusPathDB were used to perform gene ontology (GO) analysis and pathway analysis, respectively. Survival R package was used to analyze overall survival analysis of methylation-driven genes.

Results

Totally 26 DNA methylation-driven genes were identified by the methylmix, which were enriched in molecular function of DNA binding and transcription factor activity. Then, ABCD1, SLC5A10, SPIN3, ZNF69, and ZNF608 were recognized as significant independent prognostic biomarkers from 26 methylation-driven genes. Additionally, a further integrative survival analysis, which combined methylation and gene expression data, was identified that ABCD1, CCDC8, FBXO17 were significantly associated with patients’ survival. Also, multiple aberrant methylation sites were found to be correlated with gene expression.

Conclusion

In summary, we studied the DNA methylation-driven genes in ESCC by bioinformatics analysis, offering better understand of molecular mechanisms of ESCC and providing potential biomarkers precision treatment and prognosis detection.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0770-9) contains supplementary material, which is available to authorized users.

Molecular mechanisms in the pathogenesis of N-nitrosodimethylamine induced hepatic fibrosis

Hepatic fibrosis is marked by excessive synthesis and deposition of connective tissue proteins, especially interstitial collagens in the extracellular matrix of the liver. It is a result of an abnormal wound healing in response to chronic liver injury from various causes such as ethanol, viruses, toxins, drugs, or cholestasis. The chronic stimuli involved in the initiation of fibrosis leads to oxidative stress and generation of reactive oxygen species that serve as mediators of molecular events involved in the pathogenesis of hepatic fibrosis. These processes lead to cellular injury and initiate inflammatory responses releasing a variety of cytokines and growth factors that trigger activation and transformation of resting hepatic stellate cells into myofibroblast like cells, which in turn start excessive synthesis of connective tissue proteins, especially collagens. Uncontrolled and extensive fibrosis results in distortion of lobular architecture of the liver leading to nodular formation and cirrhosis. The perpetual injury and regeneration process could also results in genomic aberrations and mutations that lead to the development of hepatocellular carcinoma. This review covers most aspects of the molecular mechanisms involved in the pathogenesis of hepatic fibrosis with special emphasize on N-Nitrosodimethylamine (NDMA; Dimethylnitorsmaine, DMN) as the inducing agent.