Integrating the Epigenome to Identify Drivers of Hepatocellular Carcinoma

tRNA-derived small RNAs in human cancers: roles, mechanisms, and clinical application

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) are a new type of non-coding RNAs (ncRNAs) produced by the specific cleavage of precursor or mature tRNAs. tsRNAs are involved in various basic biological processes such as epigenetic, transcriptional, post-transcriptional, and translation regulation, thereby affecting the occurrence and development of various human diseases, including cancers. Recent studies have shown that tsRNAs play an important role in tumorigenesis by regulating biological behaviors such as malignant proliferation, invasion and metastasis, angiogenesis, immune response, tumor resistance, and tumor metabolism reprogramming. These may be new potential targets for tumor treatment. Furthermore, tsRNAs can exist abundantly and stably in various bodily fluids (e.g., blood, serum, and urine) in the form of free or encapsulated extracellular vesicles, thereby affecting intercellular communication in the tumor microenvironment (TME). Meanwhile, their abnormal expression is closely related to the clinicopathological features of tumor patients, such as tumor staging, lymph node metastasis, and poor prognosis of tumor patients; thus, tsRNAs can be served as a novel type of liquid biopsy biomarker. This review summarizes the discovery, production, and expression of tsRNAs and analyzes their molecular mechanisms in tumor development and potential applications in tumor therapy, which may provide new strategies for early diagnosis and targeted therapy of tumors.

Clinical significance of RNA methylation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a primary liver malignancy with high mortality rates and poor prognosis. Recent advances in high-throughput sequencing and bioinformatic technologies have greatly enhanced the understanding of the genetic and epigenetic changes in liver cancer. Among these changes, RNA methylation, the most prevalent internal RNA modification, has emerged as a significant contributor of the development and progression of HCC. Growing evidence has reported significantly abnormal levels of RNA methylation and dysregulation of RNA-methylation-related enzymes in HCC tissues and cell lines. These alterations in RNA methylation play a crucial role in the regulation of various genes and signaling pathways involved in HCC, thereby promoting tumor progression. Understanding the pathogenesis of RNA methylation in HCC would help in developing prognostic biomarkers and targeted therapies for HCC. Targeting RNA-methylation-related molecules has shown promising potential in the management of HCC, in terms of developing novel prognostic biomarkers and therapies for HCC. Exploring the clinical application of targeted RNA methylation may provide new insights and approaches for the management of HCC. Further research in this field is warranted to fully understand the functional roles and underlying mechanisms of RNA methylation in HCC. In this review, we described the multifaceted functional roles and potential mechanisms of RNA methylation in HCC. Moreover, the prospects of clinical application of targeted RNA methylation for HCC management are discussed, which may provide the basis for subsequent in-depth research on RNA methylation in HCC.

Hepatocellular carcinoma: molecular mechanism, targeted therapy, and biomarkers

Hepatocellular carcinoma (HCC) is a common malignancy and one of the leading causes of cancer-related death. The biological process of HCC is complex, with multiple factors leading to the broken of the balance of inactivation and activation of tumor suppressor genes and oncogenes, the abnormal activation of molecular signaling pathways, the differentiation of HCC cells, and the regulation of angiogenesis. Due to the insidious onset of HCC, at the time of first diagnosis, less than 30% of HCC patients are candidates for radical treatment. Systematic antitumor therapy is the hope for the treatment of patients with middle-advanced HCC. Despite the emergence of new systemic therapies, survival rates for advanced HCC patients remain low. The complex pathogenesis of HCC has inspired researchers to explore a variety of biomolecular targeted therapeutics targeting specific targets. Correct understanding of the molecular mechanism of HCC occurrence is key to seeking effective targeted therapy. Research on biomarkers for HCC treatment is also advancing. Here, we explore the molecular mechanism that are associated with HCC development, summarize targeted therapies for HCC, and discuss potential biomarkers that may drive therapies.

Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

Chronic liver diseases usually developed through stepwise pathological transitions under the persistent risk factors. The molecular changes during liver transitions are pivotal to improve liver diagnostics and therapeutics yet still remain elusive. Cumulative large-scale liver transcriptomic studies have been revealing molecular landscape of various liver conditions at bulk and single-cell resolution, however, neither single experiment nor databases enabled thorough investigations of transcriptomic dynamics along the progression of liver diseases. Here we establish GepLiver, a longitudinal and multidimensional liver expression atlas integrating expression profiles of 2469 human bulk tissues, 492 mouse samples, 409,775 single cells from 347 human samples and 27 liver cell lines spanning 16 liver phenotypes with uniformed processing and annotating methods. Using GepLiver, we have demonstrated dynamic changes of gene expression, cell abundance and crosstalk harboring meaningful biological associations. GepLiver can be applied to explore the evolving expression patterns and transcriptomic features for genes and cell types respectively among liver phenotypes, assisting the investigation of liver transcriptomic dynamics and informing biomarkers and targets for liver diseases.

Modeling cross-talk of RNA modification enzymes reveals tumor microenvironment-associated clinical significance and immunotherapy prediction in hepatobiliary malignancy

RNA modification includes four main types, N6-methyladenosine, N1-methyladenosine, alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing, involving 41 enzymes that serve as "writers", "readers" and "erasers". By collecting RNA modifying enzyme information in 1759 hepatobiliary malignancy (HBM) samples from 11 datasets, an RNA modification HBM Score (RH_score) was established based on unsupervised cluster analysis of RNA modification-associated differentially expressed genes (DEGs). We identified the imbalanced expression of 41 RNA modification enzymes in HBM, which was scientifically categorized into two groups: RH_Score high and RH_Score low. A high RH_Score was associated with a worse prognosis and more immature immune cells in the tumor microenvironment (TME), while a low RH_Score was associated with a better prognosis and more mature immune cells in the TME. Further analysis using single-cell databases showed that the high RH_Score was immune exhaustion in the TME. RH_Score was involved in transcriptional regulation and post-transcriptional events in HBM. Additionally, resistant and sensitive drugs were selected based on RNA modification, and anti-PD-L1 therapy responded better with low RH_Score. In conclusion, our study comprehensively analyzes RNA modification in HBM, which induces TME changes and transcriptional and posttranscriptional events, implying potential guiding significance in prognosis prediction and treatment options.

Identifying a novel cuproptosis-related necroptosis gene subtype-related signature for predicting the prognosis, tumor microenvironment, and immunotherapy of hepatocellular carcinoma

Background: Cuproptosis and necroptosis represent two distinct programmed cell death modalities implicated in neoplastic progression; however, the role of combining cuproptosis and necroptosis in hepatocellular carcinoma (HCC) remains to be elucidated. Methods: A total of 29 cuproptosis-related necroptosis genes (CRNGs) were identified, followed by an extensive analysis of their mutational characteristics, expression patterns, prognostic implications, and associations with the tumor microenvironment (TME). Subsequently, a CRNG subtype-related signature was developed, and its value of prognostic prediction, TME, and therapeutic responses in HCC were thoroughly investigated. Last, quantitative real-time PCR and Western blotting were employed for investigating the signature gene expression in 15 paired clinical tissue samples. Results: Two distinct CRNG subtypes were discerned, demonstrating associations between CRNG expression patterns, clinicopathological attributes, prognosis, and the TME. A CRNG subtype-related prognostic signature, subjected to external validation, was constructed, serving as an independent prognostic factor for HCC patients, indicating poor prognosis for high-risk individuals. Concurrently, the signature's correlations with an immune-suppressive TME, mutational features, stemness properties, immune checkpoint genes, chemoresistance-associated genes, and drug sensitivity were observed, signifying its utility in predicting treatment responses. Subsequently, highly accurate and clinically convenient nomograms were developed, and the signature genes were validated via quantitative real-time PCR and Western blotting, further substantiating the stability and dependability of the CRNG subtype-related prognostic signature. Conclusion: Overall, this investigation presented an extensive panorama of CRNGs and developed the CRNG subtype-related prognostic signature, which holds potential for implementation in personalized treatment strategies and prognostic forecasting for HCC patients.

Alternative promoters in CpG depleted regions are prevalently associated with epigenetic misregulation of liver cancer transcriptomes

Transcriptional regulation is commonly governed by alternative promoters. However, the regulatory architecture in alternative and reference promoters, and how they differ, remains elusive. In 100 CAGE-seq libraries from hepatocellular carcinoma patients, here we annotate 4083 alternative promoters in 2926 multi-promoter genes, which are largely undetected in normal livers. These genes are enriched in oncogenic processes and predominantly show association with overall survival. Alternative promoters are narrow nucleosome depleted regions, CpG island depleted, and enriched for tissue-specific transcription factors. Globally tumors lose DNA methylation. We show hierarchical retention of intragenic DNA methylation with CG-poor regions rapidly losing methylation, while CG-rich regions retain it, a process mediated by differential SETD2, H3K36me3, DNMT3B, and TET1 binding. This mechanism is validated in SETD2 knockdown cells and SETD2-mutated patients. Selective DNA methylation loss in CG-poor regions makes the chromatin accessible for alternative transcription. We show alternative promoters can control tumor transcriptomes and their regulatory architecture.

Hydroxymethylation and Epigenetic Drugs: New Insights into the Diagnosis and Treatment in Epigenetics of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly lethal and heterogeneous malignancy with multiple genetic alternations and complex signaling pathways. The complexity and multifactorial nature of HCC pose a tremendous challenge regarding its diagnosis and treatment. Emerging evidence has indicated an important regulatory role of epigenetic modifications in HCC initiation and progression. Epigenetic modifications are stably heritable gene expression traits caused by changing the accessibility of chromatin structure and genetic activity without alteration in the DNA sequence and have been gradually recognized as a hallmark of cancer. In addition, accumulating data suggest a potential value of altered hydroxymethylation in epigenetic modifications and therapeutics targeting the epigenetically mediated regulation. As such, probing the epigenetic field in the era of precision oncology is a valid avenue for promoting the accuracy of early diagnosis and improving the oncological prognosis of HCC patients. This review focuses on the diagnostic performance and clinical utility of 5-hydroxymethylated cytosine, the primary intermediate product of the demethylation process, for early HCC diagnosis and discusses the promising applications of epigenetic-based therapeutic regimens for HCC.

Crosstalk between 5-methylcytosine and N6-methyladenosine machinery defines disease progression, therapeutic response and pharmacogenomic landscape in hepatocellular carcinoma

BACKGROUND

Accumulated evidence highlights the significance of the crosstalk between epigenetic and epitranscriptomic mechanisms, notably 5-methylcytosine (5mC) and N⁶-methyladenosine (m⁶A). Herein, we conducted a widespread analysis regarding the crosstalk between 5mC and m⁶A regulators in hepatocellular carcinoma (HCC).

METHODS

Pan-cancer genomic analysis of the crosstalk between 5mC and m⁶A regulators was presented at transcriptomic, genomic, epigenetic, and other multi-omics levels. Hub 5mC and m⁶A regulators were summarized to define an epigenetic and epitranscriptomic module eigengene (EME), which reflected both the pre- and post-transcriptional modifications.

RESULTS

5mC and m⁶A regulators interacted with one another at the multi-omic levels across pan-cancer, including HCC. The EME scoring system enabled to greatly optimize risk stratification and accurately predict HCC patients' clinical outcomes and progression. Additionally, the EME accurately predicted the responses to mainstream therapies (TACE and sorafenib) and immunotherapy as well as hyper-progression. In vitro, 5mC and m⁶A regulators cooperatively weakened apoptosis and facilitated proliferation, DNA damage repair, G2/M arrest, migration, invasion and epithelial-to-mesenchymal transition (EMT) in HCC cells. The EME scoring system was remarkably linked to potential extrinsic and intrinsic immune escape mechanisms, and the high EME might contribute to a reduced copy number gain/loss frequency. Finally, we determined potential therapeutic compounds and druggable targets (TUBB1 and P2RY4) for HCC patients with high EME.

CONCLUSIONS

Our findings suggest that HCC may result from a unique synergistic combination of 5mC-epigenetic mechanism mixed with m⁶A-epitranscriptomic mechanism, and their crosstalk defines therapeutic response and pharmacogenomic landscape.

Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives

Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments.

Epigenetics in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and has a high fatality rate. Genetic and epigenetic aberrations are commonly observed in HCC. The epigenetic processes include chromatin remodelling, histone alterations, DNA methylation, and noncoding RNA (ncRNA) expression and are connected with the progression and metastasis of HCC. Due to their potential reversibility, these epigenetic alterations are widely targeted for the development of biomarkers. In-depth understanding of the epigenetics of HCC is critical for developing rational clinical strategies that can provide a meaningful improvement in overall survival and prediction of therapeutic outcomes. In this article, we have summarised the epigenetic modifications involved in HCC progression and highlighted the potential biomarkers for diagnosis and drug development.

EIF2S2 is a novel independent prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly malignant disease with poor prognosis. It is urgent to find effective biomarkers. Eukaryotic Translation Initiation Factor 2 Subunit Beta (EIF2S2) is a subunit of heterotrimeric G protein EIF2, and its function is still unclear. We studied the role of EIF2S2 in the malignant progression of liver cancer and its relationship with immune infiltration.

Methods: Download the RNA expression and clinical information of EIF2S2 from the Cancer Genome Atlas (TCGA) database, analyze the relationship between the expression of EIF2S2 and the prognosis and clinicopathological characteristics of HCC, analyze the differential genes by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and tumor related immune infiltrating cells. The Protein expression level of EIF2S2 was obtained from Human Protein Atlas (HPA) databases. The relationship between EIF2S2 expression and immune infiltrates in HCC was analyzed on TIMER 2.0. The data processing analysis based on R language. Drug Sensitivity data from Genomics of Drug Sensitivity in Cancer (GDSC).

Results: EIF2S2 is highly expressed in HCC patients and is associated with poor prognosis. The expression of EIF2S2 was also correlated with age, clinical stage and pathological grade. Univariate and multivariate COX regression analysis showed that EIF2S2 was an independent risk factor for survival. The receiver operating characteristic (ROC) curve of EIF2S2 also confirmed the diagnostic value of EIF2S2 in HCC patients. Through GO and KEGG enrichment analysis, EIF2S2 expression was found to be closely related to some immune pathways. The expression of EIF2S2 was correlated with memory B cell, plasma B cell, CD8+ T cell, CD4+ resting memory T cell and the expression of some immune checkpoints, such as PDCD1, TIGIT and CTLA-4. It is also more sensitive to paclitaxel, sunitinib and other drugs.

Conclusion: This study shows that EIF2S2 can be used as a prognostic factor for HCC, which is closely related to immune infiltration and immune checkpoints, and may play a potential regulatory role in predicting drug sensitivity.

Integrative analysis of the characteristic of lipid metabolism-related genes for the prognostic prediction of hepatocellular carcinoma

BACKGROUND

Dysregulation of lipid metabolism is implicated in the progression of hepatocellular carcinoma (HCC). We therefore investigated the molecular characteristics of lipid-metabolism-related genes in HCC.

METHODS

Multi-dimensional bioinformatics analysis was conducted to comprehensively identify the lipid metabolism-related genes (LMRGs) from public databases, as well as the clinical information, immune features, and biological characteristics of HCC. The IMGR were then used to classify HCC into molecular phenotypes. Six lipid metabolism-related genes sets with the potential to predict the prognosis of HCC patients were identified.

RESULTS

A total of 770 HCC patients with complete clinical information and corresponding 776 LMRGs were downloaded from 3 databases. Univariate cox and non-negative matrix factorization analyses were used to classify HCC patients into 2 clusters. This molecular classification was associated with overall survival, clinical characteristics, and immune cells. The biological function of the differentially expressed LMRGs in the 2 clusters showed the genes associated with tumor-related metabolism pathways. A combination of multivariate/univariate cox regression and least absolute shrinkage and selection operator analyses were conducted to build a 6 LMRGs signature (6-IS) to predict the prognosis of HCC. The 6-IS signature was found to be an independent prognostic factor. Performance of the 6-IS prognostic signature was verified in a validation set and compared with an external data set. Results revealed the 6-IS signature could effectively predict the prognosis of patients with HCC.

CONCLUSIONS

This study provides new insights into the role of LMRG in the pathogenesis of HCC and presents a novel prognostic signature 6-IS monitoring the clinical course of HCC.

The Application of Liquid Biopsy Techniques in High-Risk Population for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system and has a 5-year overall survival rate of 14.1%. Many HCC patients are diagnosed at an advanced stage, and thus early screening is essential for reducing the mortality of HCC. In addition to commonly used detection indicators such as serum alpha-fetoprotein (AFP), lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) and abnormal prothrombin (protein induced by vitamin K absence II, PIVKA-II), liquid biopsy techniques have been demonstrated to have diagnostic value in HCC detection. Compared with invasive procedures, liquid biopsy can detect circulatory metabolites of malignant neoplasms. Liquid biopsy techniques can detect circulating tumor cells, circulating tumor DNA, circulating RNA and exosomes and have been used in the early screening, diagnosis and prognostic evaluation of HCC. This paper reviews the molecular biological characteristics and application of different liquid biopsy techniques, and aim to highlight promising biomarkers that may be feasible options for early-stage HCC evaluation to improve early screening in populations at high risk for HCC.

Comprehensive Analysis of Histone Modifications in Hepatocellular Carcinoma Reveals Different Subtypes and Key Prognostic Models

Histone modification, an important epigenetic mechanism, is related to the carcinogenesis of hepatocellular carcinoma (HCC). In three datasets, we screened 88 epigenetic-dysregulated PCGs (epi-PCGs) , which were significantly associated with HCC survival and could cluster HCC into three molecular subtypes. These subtypes were associated with prognosis, immunomodulatory alterations, and response to different treatment strategies. Based on 88 epi-PCGs in the TCGA training set, a risk prediction model composed of 4 epi-PCGs was established. The model was closely related to the clinicopathological features and showed a strong predictive ability in different clinical subgroups. In addition, the risk prediction model was an independent prognostic factor for patients with HCC. The significance of epi-PCGs in HCC is revealed by our data analysis.

Identification of Prognostic DNA Methylation Signatures in Lung Adenocarcinoma

Background

Increasing evidence exists of a link between DNA methylation and tumor immunotherapy. However, the impact of DNA methylation on the characteristics of the lung adenocarcinoma microenvironment and its effect on immunotherapy remain unclear.

Method

This study collected TCGA-LUAD related data sets (LUAD) to explore the characteristics and regulation of 20 DNA methylation-related genes. We further identified two DNA methylation subtypes by analysing the expression profiles of these 20 DNA methylation-related genes. Subsequently, the differences in immune cell infiltration (ICI) and the expression of immune-related signaling factors among different DNA methylation subtypes were explored, and the differentially expressed genes (DEGs) among different LUAD DNA methylation subtypes were identified. Using univariate Cox to screen differentially expressed genes meaningful for survival, a DNA methylation score (DMS) was constructed based on the weight of the first and second dimensions after dimensionality reduction by principal component analysis (PCA). Our study found that DMS can better evaluate the prognosis of lung adenocarcinoma.

Results

Based on DMS, LUAD samples were divided into two groups with high and low scores. The differences in clinical characteristics, tumor mutation load, and tumor immune cell infiltration between different DMS groups of LUAD were deeply explored, and the prediction ability of DMS for the benefit of immunotherapy was evaluated.

Conclusions

DMS is a valuable tool for predicting survival, clinicopathological features, and immunotherapeutic efficacy, which may help to promote personalized LUAD immunotherapy in the future.

Exploring epigenomic mechanisms of neural tube defects using multi-omics methods and data

Neural tube defects (NTDs) are a heterogeneous set of malformations attributed to disruption in normal neural tube closure during early embryogenesis. An in-depth understanding of NTD etiology and mechanisms remains elusive, however. Among the proposed mechanisms, epigenetic changes are thought to play an important role in the formation of NTDs. Epigenomics covers a wide spectrum of genomic DNA sequence modifications that can be investigated via high-throughput techniques. Recent advances in epigenomic technologies have enabled epigenetic studies of congenital malformations and facilitated the integration of big data into the understanding of NTDs. Herein, we review clinical epigenomic data that focuses on DNA methylation, histone modification, and miRNA alterations in human neural tissues, placental tissues, and leukocytes to explore potential mechanisms by which candidate genes affect human NTD pathogenesis. We discuss the links between epigenomics and gene regulatory mechanisms, and the effects of epigenetic alterations in human tissues on neural tube closure.

DNA hypermethylation modification promotes the development of hepatocellular carcinoma by depressing the tumor suppressor gene ZNF334

DNA methylation plays a pivotal role in the development and progression of tumors. However, studies focused on the dynamic changes of DNA methylation in the development of hepatocellular carcinoma (HCC) are rare. To systematically illustrate the dynamic DNA methylation alternation from premalignant to early-stage liver cancer with the same genetic background, this study enrolled 5 HBV-related patients preceded with liver cirrhosis, pathologically identified as early-stage HCC with dysplastic nodules. Liver fibrosis tissues, dysplastic nodules and early HCC tissues from these patients were used to measure DNA methylation. Here, we report significant differences in the DNA methylation spectrum among the three types of tissues. In the early stage of HCC, DNA hypermethylation of tumor suppressor genes is predominant. Additionally, DNA hypermethylation in the early stage of HCC changes the binding ability of transcription factor TP53 to the promoter of tumor suppressor gene ZNF334, and inhibits the expression of ZNF334 at the transcription level. Furthermore, through a series of in vivo and in vitro experiments, we have clarified the exacerbation effect of tumor suppressor gene ZNF334 deletion in the occurrence of HCC. Combined with clinical data, we found that the overall survival and relapse-free survival of patients with high ZNF334 expression are significantly longer. Thus, we partly elucidated a sequential alternation of DNA methylation modification during the occurrence of HCC, and clarified the biological function and regulatory mechanism of the tumor suppressor gene ZNF334, which is regulated by related DNA methylation sites. Our study provides a new target and clinical evidence for the early diagnosis and sheds light on the precise treatment of liver cancer.

A novel tRNA-derived fragment AS-tDR-007333 promotes the malignancy of NSCLC via the HSPB1/MED29 and ELK4/MED29 axes

Background

Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs. Recent studies suggest that tRFs participate in some pathological processes. However, the biological functions and mechanisms of tRFs in non-small cell lung cancer (NSCLC) are largely unknown.

Methods

Differentially expressed tRFs were identified by tRF and tiRNA sequencing using 9 pairs of pre- and post-operation plasma from patients with NSCLC. Quantitative real-time PCR (qRT-PCR) and fluorescence in situ hybridization (FISH) were used to determine the levels of tRF in tissues, plasma, and cells. Gain- and loss-of-function experiments were implemented to investigate the oncogenic effects of tRF on NSCLC cells in vitro and in vivo. Chromatin immunoprecipitation (ChIP), luciferase reporter, RNA pulldown, mass spectrum, RNA immunoprecipitation (RIP), Western blot, co-immunoprecipitation (Co-IP) assays, and rescue experiments were performed to explore the regulatory mechanisms of tRF in NSCLC.

Results

AS-tDR-007333 was an uncharacterized tRF and significantly up-regulated in NSCLC tissues, plasma, and cells. Clinically, AS-tDR-007333 overexpression could distinguish NSCLC patients from healthy controls and associated with poorer prognosis of NSCLC patients. Functionally, overexpression of AS-tDR-007333 enhanced proliferation and migration of NSCLC cells, whereas knockdown of AS-tDR-007333 resulted in opposite effects. Mechanistically, AS-tDR-007333 promoted the malignancy of NSCLC cells by activating MED29 through two distinct mechanisms. First, AS-tDR-007333 bound to and interacted with HSPB1, which activated MED29 expression by enhancing H3K4me1 and H3K27ac in MED29 promoter. Second, AS-tDR-007333 stimulated the expression of transcription factor ELK4, which bound to MED29 promoter and increased its transcription. Therapeutically, inhibition of AS-tDR-007333 suppressed NSCLC cell growth in vivo.

Conclusions

Our study identifies a new oncogenic tRF and uncovers a novel mechanism that AS-tDR-007333 promotes NSCLC malignancy through the HSPB1-MED29 and ELK4-MED29 axes. AS-tDR-007333 is a potential diagnostic or prognostic marker and therapeutic target for NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-022-01270-y.

Accurate and highly interpretable prediction of gene expression from histone modifications

Background

Histone Mark Modifications (HMs) are crucial actors in gene regulation, as they actively remodel chromatin to modulate transcriptional activity: aberrant combinatorial patterns of HMs have been connected with several diseases, including cancer. HMs are, however, reversible modifications: understanding their role in disease would allow the design of ‘epigenetic drugs’ for specific, non-invasive treatments. Standard statistical techniques were not entirely successful in extracting representative features from raw HM signals over gene locations. On the other hand, deep learning approaches allow for effective automatic feature extraction, but at the expense of model interpretation.

Results

Here, we propose ShallowChrome, a novel computational pipeline to model transcriptional regulation via HMs in both an accurate and interpretable way. We attain state-of-the-art results on the binary classification of gene transcriptional states over 56 cell-types from the REMC database, largely outperforming recent deep learning approaches. We interpret our models by extracting insightful gene-specific regulative patterns, and we analyse them for the specific case of the PAX5 gene over three differentiated blood cell lines. Finally, we compare the patterns we obtained with the characteristic emission patterns of ChromHMM, and show that ShallowChrome is able to coherently rank groups of chromatin states w.r.t. their transcriptional activity.

Conclusions

In this work we demonstrate that it is possible to model HM-modulated gene expression regulation in a highly accurate, yet interpretable way. Our feature extraction algorithm leverages on data downstream the identification of enriched regions to retrieve gene-wise, statistically significant and dynamically located features for each HM. These features are highly predictive of gene transcriptional state, and allow for accurate modeling by computationally efficient logistic regression models. These models allow a direct inspection and a rigorous interpretation, helping to formulate quantifiable hypotheses.

Interferon drives HCV scarring of the epigenome and creates targetable vulnerabilities following viral clearance

BACKGROUND AND AIMS

Chronic HCV infection is a leading etiologic driver of cirrhosis and ultimately HCC. Of the approximately 71 million individuals chronically infected with HCV, 10%-20% are expected to develop severe liver complications in their lifetime. Epigenetic mechanisms including DNA methylation and histone modifications become profoundly disrupted in disease processes including liver disease.

APPROACH AND RESULTS

To understand how HCV infection influences the epigenome and whether these events remain as "scars" following cure of chronic HCV infection, we mapped genome-wide DNA methylation, four key regulatory histone modifications (H3K4me3, H3K4me1, H3K27ac, and H3K27me3), and open chromatin in parental and HCV-infected immortalized hepatocytes and the Huh7.5 HCC cell line, along with DNA methylation and gene-expression analyses following elimination of HCV in these models through treatment with interferon-α (IFN-α) or a direct-acting antiviral (DAA). Our data demonstrate that HCV infection profoundly affects the epigenome (particularly enhancers); HCV shares epigenetic targets with interferon-α targets; and an overwhelming majority of epigenetic changes induced by HCV remain as "scars" on the epigenome following viral cure. Similar findings are observed in primary human patient samples cured of chronic HCV infection. Supplementation of IFN-α/DAA antiviral regimens with DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine synergizes in reverting aberrant DNA methylation induced by HCV. Finally, both HCV-infected and cured cells displayed a blunted immune response, demonstrating a functional effect of epigenetic scarring.

CONCLUSIONS

Integration of epigenetic and transcriptional data elucidate key gene deregulation events driven by HCV infection and how this may underpin the long-term elevated risk for HCC in patients cured of HCV due to epigenome scarring.

Pt(II)-NHC Complex Induces ROS-ERS-Related DAMP Balance to Harness Immunogenic Cell Death in Hepatocellular Carcinoma

Immunogenic cell death (ICD) can engage a specific immune response and establish a long-term immunity in hepatocellular carcinoma (HCC). Herein, we design and synthesize a series of Pt(II)-N-heterocyclic carbene (Pt(II)-NHC) complexes derived from 4,5-diarylimidazole, which show strong anticancer activities in vitro. Among them, 2c displays much higher anticancer activities than cisplatin and other Pt(II)-NHC complexes, especially in HCC cancer cells. In addition, we find that 2c is a type II ICD inducer, which can successfully induce endoplasmic reticulum stress (ERS) accompanied by reactive oxygen species (ROS) generation and finally lead to the release of damage-associated molecular patterns (DAMPs) in HCC cells. Importantly, 2c shows a great anti-HCC potential in a vaccination mouse model and leads to the in vivo immune cell activation in the CCl4-induced liver injury model.

5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma

Simple Summary

To identify the prognostic significance of 5mC-related lncRNAs in colon adenocarcinoma (COAD), we examined the expression levels and mutations of 21 5mC-regulated genes of COAD in TCGA. We also identified lncRNAs associated with 5mC regulatory genes using Pearson correlation analysis. After the least absolute shrinkage and selection operator (Lasso) Cox regression, the risk signature of 4 5mC-related lncRNAs was selected. Next, the risk signature’s predictive efficacy was proven. Moreover, the biological mechanism and potential immunotherapeutic response of this risk signature were identified. Collectively, we constructed the 5mC-related lncRNA risk signature, which could provide a novel prognostic prediction of COAD patients.

Abstract

Globally, colon adenocarcinoma (COAD) is one of the most frequent types of malignant tumors. About 40~50% of patients with advanced colon adenocarcinoma die from recurrence and metastasis. Long non-coding RNAs (lncRNAs) and 5-methylcytosine (5mC) regulatory genes have been demonstrated to involve in the progression and prognosis of COAD. The goal of this study was to explore the biological characteristics and potential predictive value of 5mC-related lncRNA signature in COAD. In this research, The Cancer Genome Atlas (TCGA) was utilized to obtain the expression of genes and somatic mutations in COAD, and Pearson correlation analysis was used to select lncRNAs involved in 5mC-regulated genes. Furthermore, we applied univariate Cox regression and Lasso Cox regression to construct 5mC-related lncRNA signature. Then Kaplan–Meier survival analysis, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and a nomogram were performed to estimate the prognostic effect of the risk signature. GSEA was utilized to predict downstream access of the risk signature. Finally, the immune characteristics and immunotherapeutic signatures targeting this risk signature were analyzed. In the results, we obtained 1652 5mC-related lncRNAs by Pearson correlation analysis in the TCGA database. Next, we selected a risk signature that comprised 4 5mC-related lncRNAs by univariate and Lasso Cox regression. The prognostic value of the risk signature was proven. Finally, the biological mechanism and potential immunotherapeutic response of the risk signature were identified. Collectively, we constructed the 5mC-related lncRNA risk signature, which could provide a novel prognostic prediction of COAD patients.

Prognostic Biomarker DDOST and Its Correlation With Immune Infiltrates in Hepatocellular Carcinoma

Background: Dolichyl-diphosphooligosaccharide–protein glycosyltransferase non-catalytic subunit (DDOST) is an important enzyme in the process of high-mannose oligosaccharide transferring in cells. Increasing DDOST expression is associated with impairing liver function and the increase of hepatic fibrosis degrees, hence exacerbating the liver injury. However, the relation between DDOST and hepatocellular carcinoma (HCC) has not been revealed yet.

Method: In this study, we evaluated the prognostic value of DDOST in HCC based on data from The Cancer Genome Atlas (TCGA) database. The relationship between DDOST expression and clinical-pathologic features was evaluated by logistic regression, the Wilcoxon signed-rank test, and Kruskal–Wallis test. Prognosis-related factors of HCC including DDOST were evaluated by univariate and multivariate Cox regression and the Kaplan–Meier method. DDOST-related key pathways were identified by gene set enrichment analysis (GSEA). The correlations between DDOST and cancer immune infiltrates were investigated by the single-sample gene set enrichment analysis (ssGSEA) of TCGA data.

Results: High DDOST expression was associated with poorer overall survival and disease-specific survival of HCC patients. GSEA suggested that DDOST is closely correlated with cell cycle and immune response via the PPAR signaling pathway. ssGSEA indicated that DDOST expression was positively correlated with the infiltrating levels of Th2 cells and negatively correlated with the infiltration levels of cytotoxic cells.

Conclusion: All those findings indicated that DDOST was correlated with prognosis and immune infiltration in HCC.

Integrating the Epigenome and Transcriptome of Hepatocellular Carcinoma to Identify Systematic Enhancer Aberrations and Establish an Aberrant Enhancer-Related Prognostic Signature

Recently, emerging evidence has indicated that aberrant enhancers, especially super-enhancers, play pivotal roles in the transcriptional reprogramming of multiple cancers, including hepatocellular carcinoma (HCC). In this study, we performed integrative analyses of ChIP-seq, RNA-seq, and whole-genome bisulfite sequencing (WGBS) data to identify intergenic differentially expressed enhancers (DEEs) and genic differentially methylated enhancers (DMEs), along with their associated differentially expressed genes (DEE/DME-DEGs), both of which were also identified in independent cohorts and further confirmed by HiC data. Functional enrichment and prognostic model construction were conducted to explore the functions and clinical significance of the identified enhancer aberrations. We identified a total of 2,051 aberrant enhancer-associated DEGs (AE-DEGs), which were highly concurrent in multiple HCC datasets. The enrichment results indicated the significant overrepresentations of crucial biological processes and pathways implicated in cancer among these AE-DEGs. A six AE-DEG-based prognostic signature, whose ability to predict the overall survival of HCC was superior to that of both clinical phenotypes and previously published similar prognostic signatures, was established and validated in TCGA-LIHC and ICGC-LIRI cohorts, respectively. In summary, our integrative analysis depicted a landscape of aberrant enhancers and associated transcriptional dysregulation in HCC and established an aberrant enhancer-derived prognostic signature with excellent predictive accuracy, which might be beneficial for the future development of epigenetic therapy for HCC.

Simultaneous Mapping of Enhancers and Enhancer Rearrangements with Paired-End H3K27ac ChIP-seq

We describe a protocol for H3K27ac ChIP paired-end sequencing and computational analysis of rearrangements. Our approach can be used to simultaneously map enhancers and their activity and to identify structural variations at enhancers. Since changes in enhancer activity and new enhancer translocations both play a major role in tumor initiation, progression, and response to therapy, this approach holds promise to uncover some of the mechanisms behind these processes.

Identification and Validation of a Novel Six-Gene Expression Signature for Predicting Hepatocellular Carcinoma Prognosis

Background

Hepatocellular carcinoma (HCC) is a highly lethal disease. Effective prognostic tools to guide clinical decision-making for HCC patients are lacking.

Objective

We aimed to establish a robust prognostic model based on differentially expressed genes (DEGs) in HCC.

Methods

Using datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Genome Consortium (ICGC), DEGs between HCC tissues and adjacent normal tissues were identified. Using TCGA dataset as the training cohort, we applied the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analyses to identify a multi-gene expression signature. Proportional hazard assumptions and multicollinearity among covariates were evaluated while building the model. The ICGC cohort was used for validation. The Pearson test was used to evaluate the correlation between tumor mutational burden and risk score. Through single-sample gene set enrichment analysis, we investigated the role of signature genes in the HCC microenvironment.

Results

A total of 274 DEGs were identified, and a six-DEG prognostic model was developed. Patients were stratified into low- or high-risk groups based on risk scoring by the model. Kaplan-Meier analysis revealed significant differences in overall survival and progression-free interval. Through univariate and multivariate Cox analyses, the model proved to be an independent prognostic factor compared to other clinic-pathological parameters. Time-dependent receiver operating characteristic curve analysis revealed satisfactory prediction of overall survival, but not progression-free interval. Functional enrichment analysis showed that cancer-related pathways were enriched, while immune infiltration analyses differed between the two risk groups. The risk score did not correlate with levels of PD-1, PD-L1, CTLA4, or tumor mutational burden.

Conclusions

We propose a six-gene expression signature that could help to determine HCC patient prognosis. These genes may serve as biomarkers in HCC and support personalized disease management.

Comprehensive clinicopathologic study of alpha fetoprotein-expression in a large cohort of patients with hepatocellular carcinoma

Alpha fetoprotein (AFP) is the most widely used diagnostic and prognostic serum biomarker for hepatocellular carcinoma (HCC). Despite its wide clinical use, a systematic clinicopathologic study comparing AFP expression in HCC in situ with serum AFP concentrations has not yet been conducted. To analyze AFP expression in a large cohort of patients by immunohistochemistry, we employed a comprehensive tissue microarray with 871 different HCCs of overall 561 patients. AFP immunoreactivity was detected in only about 20% of HCC core biopsies, whereas 48.9% of the patients displayed increased serum values (>12 ng/mL). Immunostaining of whole tumor slides revealed that lack of detectable immunoreactivity in core biopsies in a subgroup of patients with elevated AFP serum concentrations is due to heterogeneous intratumoral AFP expression. Serum AFP concentrations and AFP expression in situ were moderately correlated (Spearman's rank correlation coefficient .53, P = 1.2e - 13). High AFP expression detected in serum (>227.3 ng/mL) or in situ predicted unfavorable prognosis and was associated with vascular invasion, higher tumor grade and macrotrabecular-massive tumor subtype. Multivariate and ROC curve analysis demonstrated that high AFP concentrations in serum is an independent prognostic parameter and represents the more robust prognostic predictor in comparison to AFP immunostaining of core biopsies. The previously published vessels encapsulating tumor clusters (VETC) pattern turned out as an additional, statistically independent prognostic parameter. AFP-positivity was associated with increased tumor cell apoptosis, but not with increased vascular densities. Additionally, AFP-positive tumors displayed increased proliferation rates, urea cycle dysregulation and signs of genomic instability, which may constitute the basis for their increased aggressiveness.

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma

DNA methylation is a key transcription regulator, whose aberration was ubiquitous and important in most cancers including hepatocellular carcinoma (HCC). Whole-genome bisulfite sequencing (WGBS) was conducted for comparison of DNA methylation in tumor and adjacent tissues from 33 HCC patients, accompanying RNA-seq to determine differentially methylated region-associated, differentially expressed genes (DMR-DEGs), which were independently replicated in the TCGA-LIHC cohort and experimentally validated via 5-aza-2-deoxycytidine (5-azadC) demethylation. A total of 9,867,700 CpG sites showed significantly differential methylation in HCC. Integrations of mRNA-seq, histone ChIP-seq, and WGBS data identified 611 high-confidence DMR-DEGs. Enrichment analysis demonstrated activation of multiple molecular pathways related to cell cycle and DNA repair, accompanying repression of several critical metabolism pathways such as tyrosine and monocarboxylic acid metabolism. In TCGA-LIHC, we replicated about 53% of identified DMR-DEGs and highlighted the prognostic significance of combinations of methylation and expression of nine DMR-DEGs, which were more efficient prognostic biomarkers than considering either type of data alone. Finally, we validated 22/23 (95.7%) DMR-DEGs in 5-azadC-treated LO2 and/or HepG2 cells. In conclusion, integration of epigenome and transcriptome data depicted activation of multiple pivotal cell cycle-related pathways and repression of several metabolic pathways triggered by aberrant DNA methylation of promoters and enhancers in HCC.

Identification of novel key molecular signatures in the pathogenesis of experimental diabetic retinopathy

Deep mining of the molecular mechanisms underlying diabetic retinopathy (DR) is critical for the development of novel therapeutic targets. This study aimed to identify key molecular signatures involved in experimental DR on the basis of integrated bioinformatics analysis. Four datasets consisting of 37 retinal samples were downloaded from the National Center of Biotechnology Information Gene Expression Omnibus. After batch-effect adjustment, bioinformatics tools such as Networkanalyst, Enrichr, STRING, and Metascape were used to evaluate the differentially expressed genes (DEGs), perform enrichment analysis, and construct protein-protein interaction networks. The hub genes were identified using Cytoscape software. The DEGs of interest from the meta-analysis were confirmed by quantitative reverse transcription-polymerase chain reaction in diabetic rats and a high-glucose-treated retinal cell model, respectively. A total of 743 DEGs related to lens differentiation, insulin resistance, and high-density lipoprotein (HDL) cholesterol metabolism were obtained using the meta-analysis. Alterations of dynamic gene expression in the chloride ion channel, retinol metabolism, and fatty acid metabolism were involved in the course of DR in rats. Importantly, H3K27m3 modifications regulated the expression of most DEGs at the early stage of DR. Using an integrated bioinformatics approach, novel molecular signatures were obtained for different stages of DR progression, and the findings may represent distinct therapeutic strategies for DR patients.

Global DNA 5hmC and CK195hmC+ Contents: A Promising Biomarker for Predicting Prognosis in Small Hepatocellular Carcinoma

Background: 5-Hydroxymethylcytosine (5hmC) with dynamic existence possesses multiple regulatory functions. Whereas, 5hmC’s impact on small hepatocellular carcinoma (SHCC) remains unclear. The present work focused on characterizing 5hmC content within SHCC and assessing the possibility of using global genomic 5hmC level as the predicative factor of clinical outcome. Methods: This study applied ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in measuring 5mC, 5fC and 5hmC contents. In addition, immunohistochemistry (IHC) was adopted to measure CK19 and 5hmC contents. Results: Research showed 5mC, 5hmC, and 5fC contents from global genomics of SHCC reduced extensively compared with healthy samples (p < 0.001). Moreover, SHCC was associated with lymph node metastasis (LNM). Greater 5mC and 5hmC levels were observed in non-metastasis group compared with the metastasis group (p < 0.001). Correlation analysis between the HBV DNA level and 5mC, 5fC and 5hmC levels exhibited that HBV DNA was associated with 5mC, 5hmC, and 5fC content reduction, which was verified in the cytological experiments. Moreover, 5hmC content had a negative correlation with the expression level of CK19 in SHCC. The decrease in 5hmC and CK19 containing 5hmC positive cell (called CK19^5hmC+) should be ascribed to the bad prognosis among SHCC patients. Conclusions: The contents of 5hmC and CK19^5hmC+ of genomic DNA might be adopted for predicting SHCC survival as an important biomarker.

Landscape analysis of lncRNAs shows that DDX11-AS1 promotes cell-cycle progression in liver cancer through the PARP1/p53 axis

Although long non-coding RNAs (lncRNAs) play important roles in tumorigenesis, the underlying mechanisms are unclear. Transcriptomic analysis of 33 hepatocellular carcinoma (HCC) samples revealed that the most enriched pathway for differentially expressed genes was related to the cell cycle process, where DDX11-AS1 is the most significant lncRNA. Upregulation of DDX11-AS1 expression through demethylation was significantly associated with a poor prognosis. Further mechanistic studies revealed that DDX11-AS1 promoted the growth of HCC by interacting with PARP1 through attenuating its binding to p53, leading to downregulated expression of p53 for inhibiting the transcription of downstream genes such as p21. Knockdown of DDX11-AS1 expression in xenograft mice using anti-DDX11-AS1 oligonucleotide suppressed liver tumor proliferation. These findings indicate that DDX11-AS1 plays a role in the development of liver cancer by affecting the cell cycle.

Overexpression of anillin is related to poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Anillin (ANLN) is required for tumor growth. It has been proven that knockdown of ANLN effectively reduces the occurrence of hepatocellular carcinoma (HCC) in transgenic mice. However, the functional role of ANLN in HCC patients remains to be elucidated.

METHODS

Both microarray and TCGA project were used for the analyses of ANLN expression and regulation in HCC. The effect of ANLN on proliferation and cell cycle was detected by CCK-8, colony formation assay and flow cytometry. ANLN expression was measured by immunohistochemistry. Correlation between ANLN expression and clinicopathological features was assessed by Pearson Chi-square test and 5-year overall survival after liver resection was evaluated by Kaplan-Meier method.

RESULTS

Increased copy number, decreased methylation levels in the CpG island and upregulated histone hypermethylation of ANLN were found in HCC. Knockdown of ANLN inhibited proliferation and induced G2/M phase arrest in SMMC-7721 cells. ANLN was mainly expressed in the nucleus and showed significantly higher expression levels in cancerous tissues than those in paired adjacent tissues. Moreover, nuclear ANLN expression levels in HCC metastases were significantly higher than those in primary HCC. The results of Cox proportional hazards regression model suggested that ANLN nuclear expression in HCC was an independent risk factor for poor 5-year overall survival of patients after liver resection.

CONCLUSIONS

ANLN is a potential therapeutic target for HCC. Patients with nuclear ANLN overexpression in HCC tissue may need adjuvant therapy after liver resection.

Periostin deficiency reduces diethylnitrosamine-induced liver cancer in mice by decreasing hepatic stellate cell activation and cancer cell proliferation

Periostin is a critical extracellular regulator in the pathogenesis of liver disorders such as hepatosteatosis, non-alcoholic steatohepatitis, inflammation, and fibrosis. Periostin is also involved in the progression of hepatocellular carcinoma (HCC). However, the molecular mechanisms of periostin in hepatic stellate cell (HSC) activation and tumor cell proliferation in the pathogenesis of HCC remain largely unknown. We demonstrate that periostin is markedly upregulated in diethylnitrosamine (DEN)-induced mouse HCC tissues and that periostin knockout impairs DEN-induced HCC development. Periostin is predominantly derived from activated HSCs and periostin deficiency in HSCs impairs HSC activation and inhibits HSC-promoted HCC cell proliferation in vitro and tumor growth in vivo. Mechanistically, periostin promotes HSC activation through the integrin-FAK-STAT3-periostin pathway and augments HCC cell proliferation by activating ERK. There are positive correlations between periostin and HSC activation and cell proliferation in HCC clinical samples. Collectively, our findings demonstrate that HSC-derived periostin promotes HCC development by enhancing HSC activation through an autocrine periostin-integrin-FAK-STAT3-periostin circuit and by augmenting HCC cell proliferation via the ERK pathway in a paracrine manner. Thus, periostin is a multifaceted extracellular regulator in the development of HCC. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer

BACKGROUND

Despite using prognostic algorithms and standard surveillance guidelines, 17% of patients initially diagnosed with low risk clear cell renal cell carcinoma (ccRCC) ultimately relapse and die of recurrent disease, indicating additional molecular parameters are needed for improved prognosis.

RESULTS

To address the gap in ccRCC prognostication in the lower risk population, we performed a genome-wide analysis for methylation signatures capable of distinguishing recurrent and non-recurrent ccRCCs within the subgroup classified as 'low risk' by the Mayo Clinic Stage, Size, Grade, and Necrosis score (SSIGN 0-3). This approach revealed that recurrent patients have globally hypermethylated tumors and differ in methylation significantly at 5929 CpGs. Differentially methylated CpGs (DMCpGs) were enriched in regulatory regions and genes modulating cell growth and invasion. A subset of DMCpGs stratified low SSIGN groups into high and low risk of recurrence in independent data sets, indicating that DNA methylation enhances the prognostic power of the SSIGN score.

CONCLUSIONS

This study reports a global DNA hypermethylation in tumors of recurrent ccRCC patients. Furthermore, DMCpGs were capable of discriminating between aggressive and less aggressive tumors, in addition to SSIGN score. Therefore, DNA methylation presents itself as a potentially strong biomarker to further improve prognostic power in patients with low risk SSIGN score (0-3).

Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy closely related to metabolic reprogramming. We investigated how CTNNB1 mutation regulates the HCC metabolic phenotype and thus affects the prognosis of HCC. We obtained the mRNA expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA), the International Cancer Genomics Consortium (ICGC) and the Gene Expression Omnibus database (GSE14520 and GSE116174). We conducted gene set enrichment analysis on HCC patients with and without mutant CTNNB1 through TCGA dataset. The Kaplan‐Meier analysis and univariate Cox regression analysis assisted in screening metabolic genes related to prognosis, and the prognosis model was constructed using the Lasso and multivariate Cox regression analysis. The prognostic model showed good prediction performance in both the training cohort (TCGA) and the validation cohorts (ICGC, GSE14520, GSE116174), and the high‐risk group presented obviously poorer overall survival compared with low‐risk group. Cox regression analysis indicated that the risk score can be used as an independent predictor for the overall survival of HCC. The immune infiltration in different risk groups was also evaluated in this study to explore underlying mechanisms. This study is also the first to describe an metabolic prognostic model associated with CTNNB1 mutations and could be implemented for determining the prognoses of individual patients in clinical practice.

Epigenetics in hepatocellular carcinoma development and therapy: The tip of the iceberg

Hepatocellular carcinoma (HCC) is a deadly tumour whose causative agents are generally well known, but whose pathogenesis remains poorly understood. Nevertheless, key genetic alterations are emerging from a heterogeneous molecular landscape, providing information on the tumorigenic process from initiation to progression. Among these molecular alterations, those that affect epigenetic processes are increasingly recognised as contributing to carcinogenesis from preneoplastic stages. The epigenetic machinery regulates gene expression through intertwined and partially characterised circuits involving chromatin remodelers, covalent DNA and histone modifications, and dedicated proteins reading these modifications. In this review, we summarise recent findings on HCC epigenetics, focusing mainly on changes in DNA and histone modifications and their carcinogenic implications. We also discuss the potential drugs that target epigenetic mechanisms for HCC treatment, either alone or in combination with current therapies, including immunotherapies.

Epigenome-wide DNA methylation profiling of portal vein tumor thrombosis (PVTT) tissues in hepatocellular carcinoma patients

Aberrant methylation is a hallmark of hepatocellular carcinoma and plays an important role in tumor initiation and progression. However, the epigenome-wide methylation patterns of portal vein tumor thrombosis (PVTTs) have not been fully explored. Here, we performed epigenome-wide DNA methylation of adjacent normal tissues (ANTs), paired tumor tissues and paired PVTTs using an Infinium HumanMethylation450 array (n = 11) and conducted the Sequenom EpiTYPER assays to confirm the aberrantly methylated genes. MTS and apoptosis assay were used to assess the synergistic effect of two drugs on the HCC cell lines. We found the mean global methylation levels of HCC tissues and PVTTs were significantly lower than ANTs (P < 0.01). A total of 864 differentially methylated CpG sites annotated in 532 genes were identified between HCC tissues and paired PVTTs (|mean methylation difference|>10%, P < 0.005). The pathway analysis based on hypermethylated genes in PVTT tissues was interestingly enriched in regulation of actin cytoskeleton pathway (P = 4.48E−5). We found 23 genes whose methylation levels were gradually alternated in HCC tissues and PVTTs. Aberrant methylation status of TNFRSF10A, ZC3H3 and SLC9A3R2 were confirmed in a validation cohort (n = 48). The functional experiments demonstrated the combination of decitabine (DAC) and tumor necrosis factor-related apoptosis-inducing ligand (rh-TRAIL) could synergistically suppress the proliferation and induce apoptosis in SK-Hep-1 and Huh7 cell lines. Together, our findings indicated that DNA methylation plays an important role in the PVTT formation through regulating the metastasis-related pathways. The combination of DAC and rh-TRAIL might be a promising treatment strategy for HCC.

Landscape of active enhancers developed de novo in cirrhosis and conserved in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) patients always have a background of cirrhosis. Aberrant epigenetic changes in cirrhosis provide a conductive environment for HCC tumorigenesis. Active enhancers (AEs) are essential for epigenetic regulation and play an important role in cell development and the progression of many diseases. However, the role of AEs in the progression from cirrhosis to HCC remains unclear. We systemically constructed a landscape of AEs that developed de novo in cirrhosis and were conserved in HCC, referred to as CL-HCC AEs. We observed significant upregulation of these CL-HCC AE-associated genes in cirrhosis and HCC, with no other epigenetic changes. Enrichment analysis of these CL-HCC AE-associated genes revealed enrichment in both hepatocyte-intrinsic tumorigenesis and tumor immune response, which might contribute to HCC tumorigenesis. Analysis of the diagnostic ability of these CL-HCC AE-associated genes provided a five-gene (THBS4, OLFML2B, CDKN3, GABRE, and HDAC11) diagnostic biomarker for HCC. Molecular subtype (MS) identification based on the CL-HCC AE-associated genes identified 3 MSs. Samples representing the 3 MSs showed differences in CL-HCC AE-associated gene expression levels, prognosis, copy number variation (CNV)/mutation frequencies, functional pathways, tumor microenvironment (TME) cell subtypes, immunotherapy responses and putative drug responses. We also found that the BET bromodomain inhibitor JQ1 downregulated the expression of CL-HCC AE-associated genes. Collectively, our results suggest that CL-HCC AEs and their associated genes contribute to HCC tumorigenesis and evolution, and could be used to distinguish the different landscapes of HCC and help explore the mechanism, classification, prediction, and precision therapy of HCC.

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma

Currently, an increasing number of studies suggest that long non-coding RNAs (lncRNAs) and methylation-regulated lncRNAs play a critical role in the pathogenesis of various cancers including hepatocellular carcinoma (HCC). Therefore, methylated differentially expressed lncRNAs (MDELs) may be critical biomarkers of HCC. In this study, 63 MDELs were identified by screening The Cancer Genome Atlas (TCGA) HCC lncRNAs expression data set and lncRNAs methylation data set. Based on univariate and multivariate survival analysis, four MDELs (AC025016.1, LINC01164, LINC01183 and LINC01269) were selected to construct the survival prognosis prediction model. Through the PI formula, the study indicates that our new prediction model performed well and is superior to the traditional staging method. At the same time, compared with the previous prediction models reported in the literature, the results of time-dependent receiver operating characteristic (ROC) curve analysis show that our 4-MDELs model predicted overall survival (OS) stability and provided better prognosis. In addition, we also applied the prognostic model to Cancer Cell Line Encyclopedia (CCLE) cell lines and classified different hepatoma cell lines through the model to evaluate the sensitivity of different hepatoma cell lines to different drugs. In conclusion, we have established a new risk scoring system to predict the prognosis, which may have a very important guiding significance for the individualized treatment of HCC patients.

Comprehensive analysis of 5-hydroxymethylcytosine in zw10 kinetochore protein as a promising biomarker for screening and diagnosis of early colorectal cancer

BACKGROUND

As a new epigenetic biomarker, 5-hydroxymethylcytosine (5hmC) is broadly involved in various diseases including cancers. However, the function and diagnostic performance of 5hmC in colorectal cancer (CRC) remain unclear.

RESULTS

High-throughput sequencing was used to profile 5hmC levels in adjacent normal colon, advanced adenomas, and CRC. The expression and 5hmC levels in zw10 kinetochore protein (ZW10) were significantly increased in the tissues and blood samples for patients with advanced adenoma and CRC, and were much higher in the early stages of CRC (I and II). The receiver operating characteristic analysis had potential diagnostic value for CRC. The area under the curve (AUC) of ZW10 5hmC levels in tissue samples of CRC was 0.901. In blood samples, the AUC was 0.748 for CRC. In addition, the ZW10 5hmC level had much higher diagnostic performance in early stages of CRC (AUC = 0.857) than it did in advanced stages (AUC = 0.594). Compared with FHC cell, ZW10 expression in HT29 cell was significantly increased. The ZW10 knockdown could inhibit cell proliferation and the ZW10 overexpression could promote cell proliferation in HT-29 cell. Furthermore, ZW10 knockdown inhibited AKT and mTOR phosphorylation, and ZW10 overexpression promoted AKT and mTOR phosphorylation.

CONCLUSIONS

The ZW10 5hmC level may serve as an effective epigenetic biomarker for minimally invasive screening and diagnosis of CRC, and it has higher diagnostic performance in early stages of CRC than it does in advanced stages. In addition, ZW10 could regulate CRC progression through the AKT-mTOR signaling.

Sex-biased genetic programs in liver metabolism and liver fibrosis are controlled by EZH1 and EZH2

Sex differences in the incidence and progression of many liver diseases, including liver fibrosis and hepatocellular carcinoma, are associated with sex-biased hepatic expression of hundreds of genes. This sexual dimorphism is largely determined by the sex-specific pattern of pituitary growth hormone secretion, which controls a transcriptional regulatory network operative in the context of sex-biased and growth hormone-regulated chromatin states. Histone H3K27-trimethylation yields a major sex-biased repressive chromatin mark deposited at many strongly female-biased genes in male mouse liver, but not at male-biased genes in female liver, and is catalyzed by polycomb repressive complex-2 through its homologous catalytic subunits, Ezh1 and Ezh2. Here, we used Ezh1-knockout mice with a hepatocyte-specific knockout of Ezh2 to investigate the sex bias of liver H3K27-trimethylation and its functional role in regulating sex-differences in the liver. Combined hepatic Ezh1/Ezh2 deficiency led to a significant loss of sex-biased gene expression, particularly in male liver, where many female-biased genes were increased in expression while male-biased genes showed decreased expression. The associated loss of H3K27me3 marks, and increases in the active enhancer marks H3K27ac and H3K4me1, were also more pronounced in male liver. Further, Ezh1/Ezh2 deficiency in male liver, and to a lesser extent in female liver, led to up regulation of many genes linked to liver fibrosis and liver cancer, which may contribute to the observed liver pathologies and the increased sensitivity of these mice to hepatotoxin exposure. Thus, Ezh1/Ezh2-catalyzed H3K27-trimethyation regulates sex-dependent genetic programs in liver metabolism and liver fibrosis through its sex-dependent effects on the epigenome, and may thereby determine the sex-bias in liver disease susceptibility.

Sex-differences in the expression of genes in liver have a direct impact on liver diseases whose incidence and severity is sex-biased, and is controlled by hormones that regulate chemical alterations to histone proteins used to package chromosomal DNA. However, a direct demonstration of the functional importance of such sex differences in histone protein modifications has been elusive. Here, we address this question using a mouse model deficient in two enzymes, Ezh1/Ezh2, which generate the histone repressive mark H3K27me3. Remarkably, although H3K27me3 marks are formed by Ezh1/Ezh2 throughout the genome, loss of liver Ezh1/Ezh2 preferentially disrupts the control of sex-biased genes, with expression increasing in male mouse liver for many female-biased genes and decreasing for many male-biased genes. Sex-biased H3K27me3 repressive marks were abolished, and there was a gain of active histone marks at gene enhancers. We also found increased expression of many genes associated with liver fibrosis and hepatocellular carcinoma, which may help explain the increased sensitivity of Ezh1/Ezh2-deficient livers to hepatotoxic chemicals whose exposure may lead to sex differences in liver disease incidence and susceptibility. Thus, our findings highlight the potential role of sex differences in histone modifications catalyzed by Ezh1/Ezh2 in widespread sex differences in liver diseases.

Hydroxymethylation and tumors: can 5-hydroxymethylation be used as a marker for tumor diagnosis and treatment?

5-Methylcytosine (5mC) is considered as a common epigenetic modification that plays an important role in the regulation of gene expression. At the same time, 5-hydroxymethylcytosine (5hmC) has been found as an emerging modification of cytosine bases of recent years. Unlike 5mC, global 5hmC levels vary from tissues that have differential distribution both in mammalian tissues and in the genome. DNA hydroxymethylation is the process that 5mC oxidates into 5hmC with the catalysis of TET (ten-eleven translocation) enzymes. It is an essential option of DNA demethylation, which modulates gene expression by adjusting the DNA methylation level. Various factors can regulate the demethylation of DNA, such as environmental toxins and mental stress. In this review, we summarize the progress in the formation of 5hmC, and obtaining 5hmC in a cell-free DNA sample presents multiple advantages and challenges for the subject. Furthermore, the clinical potential for 5hmC modification in dealing with cancer early diagnosis, prognostic evaluation, and prediction of therapeutic effect is also mentioned.

Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis

The molecular mechanisms underlying hepatocellular carcinoma (HCC) progression remain largely undefined. Here, we identified 176 commonly upregulated genes in HCC tissues based on three Gene Expression Omnibus datasets and The Cancer Genome Atlas (TCGA) cohort. We integrated survival and methylation analyses to further obtain 12 upregulated genes for validation. These genes were overexpressed in HCC tissues at the transcription and protein levels, and increased mRNA levels were related to higher tumor grades and cancer stages. The expression of all markers was negatively associated with overall and disease-free survival in HCC patients. Most of these hub genes can promote HCC proliferation and/or metastasis. These 12 hub genes were also overexpressed and had strong prognostic value in many other cancer types. Methylation and gene copy number analyses indicated that the upregulation of these hub genes was probably due to hypomethylation or increased gene copy numbers. Further, the methylation levels of three genes, KPNA2, MCM3, and LRRC1, were associated with HCC clinical features. Moreover, the levels of most hub genes were related to immune cell infiltration in HCC microenvironments. Finally, we identified three upregulated genes (KPNA2, TARBP1, and RNASEH2A) that could comprehensively and accurately provide diagnostic and prognostic value for HCC patients.

A four-methylated mRNA signature-based risk score system predicts survival in patients with hepatocellular carcinoma

Evidence suggests that altered DNA methylation plays a causative role in the pathogenesis of various cancers, including hepatocellular carcinoma (HCC). Thus, methylated differently expressed genes (MDEGs) could potentially serve as biomarkers and therapeutic targets in HCC. In the present study, screening four genomics profiling datasets (GSE62232, GSE84402, GSE73003 and GSE57956) enabled us to identify a total of 148 MDEGs. A signature was then established based on the top four MDEGs (BRCA1, CAD, CDC20 and RBM8A). Taking clinical variables into consideration, we constructed a risk score system consisting of the four-MDEG signature and the patients' clinical features, which was predictive of prognosis in HCC. The prognostic value of the HCC risk score system was confirmed using TCGA HCC samples. The scores were then used to construct a nomogram, performance of which was evaluated using Harrel's concordance index (C-index) and a calibration curve. The signature-based nomogram for prediction of overall survival in HCC patients exhibited good performance and was superior to traditional staging systems (C-index: 0.676 vs 0.629, P< 0.05). We have thus established a novel risk score system that is predictive of prognosis and is a potentially useful guide for personalized treatment of HCC patients.

A FITM1-Related Methylation Signature Predicts the Prognosis of Patients With Non-Viral Hepatocellular Carcinoma

Although great progress has been made in treatment against hepatitis virus infection, the prognosis of hepatocellular carcinoma (HCC) remains unsatisfied. Therefore, there is an unmet need to explore biomarkers or prognostic models for monitoring non-viral hepatocellular carcinoma. Accumulating evidence indicates that DNA methylation participates in carcinogenesis of malignancies. In the present study, we analyzed 101 non-viral HCC patients from TCGA database to figure out methylation-driven genes (MDGs) that might get involved in non-viral HCC pathogenesis using MethyMix algorithm. Then we picked out 8 key genes out of 137 MDGs that could affect the overall survival (OS) of both methylation and expression level. Using PCA, Uni-variate, Multi-variate, and LASSO cox regression analyses, we confirmed the potential prognostic value of these eight epigenetic genes. Ultimately, combined with immunohistochemistry (IHC), ROC, OS, and GSEA analyses, fat storage-inducing transmembrane protein1 (FITM1) was identified as a novel tumor suppressor gene in non-viral HCC and an applicable FITM1-methylation-based signature was built in a training set and validated in a testing set. Briefly, our work provides several potential biomarkers, especially FITM1, as well as a new method for disease surveillance and treatment strategy development.

DNA methylation of individual repetitive elements in hepatitis C virus infection-induced hepatocellular carcinoma

Background

The two most common repetitive elements (REs) in humans, long interspersed nuclear element-1 (LINE-1) and Alu element (Alu), have been linked to various cancers. Hepatitis C virus (HCV) may cause hepatocellular carcinoma (HCC) by suppressing host defenses, through DNA methylation that controls the mobilization of REs. We aimed to investigate the role of RE methylation in HCV-induced HCC (HCV-HCC).

Results

We studied methylation of over 30,000 locus-specific REs across the genome in HCC, cirrhotic, and healthy liver tissues obtained by surgical resection. Relative to normal liver tissue, we observed the largest number of differentially methylated REs in HCV-HCC followed by alcohol-induced HCC (EtOH-HCC). After excluding EtOH-HCC-associated RE methylation (FDR < 0.001) and those unable to be validated in The Cancer Genome Atlas (TCGA), we identified 13 hypomethylated REs (11 LINE-1 and 2 Alu) and 2 hypermethylated REs (1 LINE-1 and 1 Alu) in HCV-HCC (FDR < 0.001). A majority of these REs were located in non-coding regions, preferentially enriched with chromatin repressive marks H3K27me3, and positively associated with gene expression (median correlation r = 0.32 across REs). We further constructed an HCV-HCC RE methylation score that distinguished HCV-HCC (lowest score), HCV-cirrhosis, and normal liver (highest score) in a dose-responsive manner (p for trend < 0.001). HCV-cirrhosis had a lower score than EtOH-cirrhosis (p = 0.038) and HCV-HCC had a lower score than EtOH-HCC in TCGA (p = 0.024).

Conclusions

Our findings indicate that HCV infection is associated with loss of DNA methylation in specific REs, which could implicate molecular mechanisms in liver cancer development. If our findings are validated in larger sample sizes, methylation of these REs may be useful as an early detection biomarker for HCV-HCC and/or a target for prevention of HCC in HCV-positive individuals.

Electronic supplementary material

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