Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

The complex role of immune cells in antigen presentation and regulation of T-cell responses in hepatocellular carcinoma: progress, challenges, and future directions

Hepatocellular carcinoma (HCC) is a prevalent form of liver cancer that poses significant challenges regarding morbidity and mortality rates. In the context of HCC, immune cells play a vital role, especially concerning the presentation of antigens. This review explores the intricate interactions among immune cells within HCC, focusing on their functions in antigen presentation and the modulation of T-cell responses. We begin by summarizing the strategies that HCC uses to escape immune recognition, emphasizing the delicate equilibrium between immune surveillance and evasion. Next, we investigate the specific functions of various types of immune cells, including dendritic cells, natural killer (NK) cells, and CD8+ T cells, in the process of antigen presentation. We also examine the impact of immune checkpoints, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and the pathways involving programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1), on antigen presentation, while taking into account the clinical significance of checkpoint inhibitors. The review further emphasizes the importance of immune-based therapies, including cancer vaccines and CAR-T cell therapy, in improving antigen presentation. In conclusion, we encapsulate the latest advancements in research, propose future avenues for exploration, and stress the importance of innovative technologies and customized treatment strategies. By thoroughly analyzing the interactions of immune cells throughout the antigen presentation process in HCC, this review provides an up-to-date perspective on the field, setting the stage for new therapeutic approaches.

Metabolomics in viral hepatitis: advances and review

Viral hepatitis is a major worldwide public health issue, affecting hundreds of millions of people and causing substantial morbidity and mortality. The majority of the worldwide burden of viral hepatitis is caused by five biologically unrelated hepatotropic viruses: hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis D virus (HDV), and hepatitis E virus (HEV). Metabolomics is an emerging technology that uses qualitative and quantitative analysis of easily accessible samples to provide information of the metabolic levels of biological systems and changes in metabolic and related regulatory pathways. Alterations in glucose, lipid, and amino acid levels are involved in glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway, and amino acid metabolism. These changes in metabolites and metabolic pathways are associated with the pathogenesis and medication mechanism of viral hepatitis and related diseases. Additionally, differential metabolites can be utilized as biomarkers for diagnosis, prognosis, and therapeutic responses. In this review, we present a thorough overview of developments in metabolomics for viral hepatitis.

Metabolomics and network analysis uncovered profound inflammation-associated alterations in hepatitis B virus-related cirrhosis patients with early hepatocellular carcinoma

Patients with hepatitis B virus (HBV)-related liver cirrhosis (LC) are at high risk for hepatocellular carcinoma (HCC). Limitations in the early detection of HCC give rise to poor survival in this high-risk population. Here, we performed comprehensive metabolomics on health individuals and HBV-related LC patients with and without early HCC. Compared to non-HCC patients (N = 108) and health controls (N = 80), we found that patients with early HCC (N = 224) exhibited a specific plasma metabolome map dominated by lipid alterations, including lysophosphatidylcholines, lysophosphatidic acids and bile acids. Pathway and function network analyses indicated that these metabolite alterations were closely associated with inflammation responses. Using multivariate regression and machine learning approaches, we identified a five-metabolite combination that showed significant performances in differentiating early-HCC from non-HCC than α-fetoprotein (area under the curve values, 0.981 versus 0.613). At metabolomic levels, this work provides additional insights of metabolic dysfunction related to HCC progressions and demonstrates the plasma metabolites might be measured to identify early HCC in patients with HBV-related LC.

Metabolome and transcriptome integration reveals metabolic profile of hepatocellular carcinoma

BACKGROUND AND AIM

Accumulated evidence highlights the role of metabolites in cancer diagnosis. However, the diagnosis of hepatocellular carcinoma (HCC), especially its early diagnosis, is still very difficult. The main purposes of the study are to explore the comprehensive characteristic metabolites of HCC through an integrated nontargeted metabolomics and transcriptomics approach and evaluate the diagnostic value of some metabolic changes in HCC.

METHODS

Dysregulated metabolites and pathways in HCC were identified by nontargeted metabolomics analysis of 72 pairs of matched liver tissues, including HCC tissue (HCT) and adjacent noncancerous tissue (ANT). Meanwhile, to ensure the reliability of the results, metabolic enzymes were quantified at the mRNA level by RNA sequencing. To facilitate the utilization of this information, a diagnostic model was developed based on binary logistic regression using 63 HCC serum samples collected from the aforementioned 72 patients and 40 noncancer serum samples.

RESULTS

The results showed that 267 metabolites were significantly altered in HCT. These differential metabolites binding to related differential metabolic enzyme genes were enriched in 14 metabolic pathways. And combination of 5-oxoproline, taurocholenate sulfate, and maltose could be used as a novel candidate early serum diagnostic marker for HCC.

CONCLUSIONS

We profiled the metabolic features of HCC and found global biochemical pathway aberration. The diagnostic potential of differential metabolites found in serum tissues, further validated in liver samples, showed that 5-oxoproline, taurocholenate sulfate, and maltose combination had a high accuracy for hepatocellular carcinoma detection, especially for alpha fetoprotein negative patients.

Cellular, Molecular and Proteomic Characteristics of Early Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers. Early detection/diagnosis is vital for the prognosis of HCC, whereas diagnosis at late stages is associated with very low survival rate. Early diagnosis is based on 6-month surveillance of the patient and the use of at least two imaging modalities. The aim of this study was to investigate diagnostic markers for the detection of early HCC based on proteome analysis, microRNAs (miRNAs) and circulating tumor cells (CTCs) in the blood of patients with cirrhosis or early or advanced HCC. We studied 89 patients with HCC, of whom 33 had early HCC and 28 were cirrhotic. CTCs were detected by real-time quantitative reverse transcription PCR and immunofluorescence using the markers epithelial cell adhesion molecule (EPCAM), vimentin, alpha fetoprotein (aFP) and surface major vault protein (sMVP). Expression of the five most common HCC-involved miRNAs (miR-122, miR-200a, miR-200b, miR-221, miR-222) was examined in serum using quantitative real time PCR (qRT-PCR). Finally, patient serum was analyzed via whole proteome analysis (LC/MS). Of 53 patients with advanced HCC, 27 (51%) had detectable CTCs. Among these, 10/27 (37%) presented evidence of mesenchymal or intermediate stage cells (vimentin and/or sMVP positive). Moreover, 5/17 (29%) patients with early HCC and 2/28 (7%) cirrhotic patients had detectable CTCs. Patients with early or advanced HCC exhibited a significant increase in miR-200b when compared to cirrhotic patients. Our proteome analysis indicated that early HCC patients present a significant upregulation of APOA2, APOC3 proteins when compared to cirrhotic patients. When taken in combination, this covers the 100% of the patients with early HCC. miR-200b, APOA2 and APOC3 proteins are sensitive markers and can be potentially useful in combination for the early diagnosis of HCC.

Identification of Downregulated Exosome-Associated Gene ENPP1 as a Novel Lipid Metabolism and Immune-Associated Biomarker for Hepatocellular Carcinoma

Exosome plays an important role in the occurrence and development of tumors, such as hepatocellular carcinoma (LIHC). However, the functions and mechanisms of exosome-associated molecules in LIHC are still underexplored. Here, we investigated the role of the exosome-related gene ENPP1 in LIHC. Comprehensive bioinformatics from multiple databases revealed that ENPP1 was significantly downregulated in LIHC tissues. The patients with downregulated ENPP1 displayed a poor prognosis. Immunohistochemistry (IHC) was used to further confirm the downregulated ENPP1 in LIHC tissues. In addition, the coexpression network of ENPP1 was also explored to understand its roles in the underlying signaling pathways, including fatty acid degradation and the PPAR signaling pathway. Simultaneously, GSEA analysis indicated the potential roles of ENPP1 in the lipid metabolism-associated signaling pathways in the pathogenesis of LIHC, including fatty acid metabolism, fatty acid synthesis, and so on. Finally, immunological analysis indicated that ENPP1 might also be involved in multiple immune-related features, including immunoinhibitors, immunostimulators, and chemokines. Taken together, these findings could enhance our understanding of ENPP1 in LIHC pathogenesis and immune response and provide a new target for ENPP1-related immunotherapy in clinical treatment.

Enhancer-associated regulatory network and gene signature based on transcriptome and methylation data to predict the survival of patients with lung adenocarcinoma

Accumulating evidence has proved that aberrant methylation of enhancers plays regulatory roles in gene expression for various cancers including lung adenocarcinoma (LUAD). In this study, the transcriptome and methylation data of The Cancer Genome Atlas (TCGA)-LUAD cohort were comprehensively analyzed with a five-step Enhancer Linking by Methylation/Expression Relationships (ELMER) process. Step 1: 131,371 distal (2 kb upstream from the transcription start site) probes were obtained. Step 2: 10,665 distal hypomethylated probes were identified in an unsupervised mode with the get.diff.meth function. Step 3: 699 probe-gene pairs with negative correlations were screened using the get.pair function in an unsupervised mode. Step 4: After mapping with probes, 768 motifs were obtained and 24 of them were enriched. Step 5: 127 transcription factors (TFs) with differential expressions and negative correlations with methylation levels were screened, which were corresponding to 21 motifs. After the ELMER process, a prognostic “TFs-motifs-genes” regulatory network was constructed. The Least absolute shrinkage and selection operator (LASSO) and Stepwise regression analyses were further applied to identify variables in the TCGA-LUAD cohort and an eight-gene signature was constructed for calculating the risk score. The risk score was verified in two independent validation cohorts. The area under curve values of receiver operating characteristic curves predicting 1-, 3-, and 5-years survival ranged from 0.633 to 0.764. With the increase of the risk scores, both the survival statuses and clinical traits showed a worse tendency. There were significant differences in the degrees of immune cell infiltration, TMB values, and TIDE scores between the high-risk and low-risk groups. Finally, a better-performing prognostic nomogram was integrated with the risk score and other clinical traits. In short, this multi-omics analysis demonstrated the application of ELMER in analyzing enhancer-associated regulatory network in LUAD, which provided promising strategies for epigenetic therapy and prognostic biomarkers.

Nucleic acid biomarkers to assess graft injury after liver transplantation

Many risk factors and complications impact the success of liver transplantation, such as ischaemia-reperfusion injury, acute rejection, and primary graft dysfunction. Molecular biomarkers have the potential to accurately diagnose, predict, and monitor injury progression or organ failure. There is a critical opportunity for reliable and non-invasive biomarkers to reduce the organ shortage by enabling i) the assessment of donor organ quality, ii) the monitoring of short- and long-term graft function, and iii) the prediction of acute and chronic disease development. To date, no established molecular biomarkers have been used to guide clinical decision-making in transplantation. In this review, we outline the recent advances in cell-free nucleic acid biomarkers for monitoring graft injury in liver transplant recipients. Prior work in this area can be divided into two categories: biomarker discovery and validation studies. Circulating nucleic acids (CNAs) can be found in the extracellular environment pertaining to different biological fluids such as bile, blood, urine, and perfusate. CNAs that are packaged into extracellular vesicles may facilitate intercellular and interorgan communication. Thus, decoding their biological function, cellular origins and molecular composition is imperative for diagnosing causes of graft injury, guiding immunosuppression and improving overall patient survival. Herein, we discuss the most promising molecular biomarkers, their state of development, and the critical aspects of study design in biomarker research for early detection of post-transplant liver injury. Future advances in biomarker studies are expected to personalise post-transplant therapy, leading to improved patient care and outcomes.