Liquid biopsy for early detection of hepatocellular carcinoma

Preliminary Evaluation of Plasma circ_0009910, circ_0027478, and miR-1236-3p as Diagnostic and Prognostic Biomarkers in Hepatocellular Carcinoma

Circular RNAs (circRNAs) are increasingly recognized as significant regulators in multiple cancers, such as hepatocellular carcinoma (HCC), frequently affecting microRNA (miRNA) expression. The diagnostic and prognostic roles of circRNAs, specifically circ_0009910 and circ_0027478, in conjunction with miR-1236-3p, in HCC, have not yet been fully investigated. In this pilot study, we assessed the expression levels of circ_0009910, circ_0027478, and miR-1236-3p in plasma samples from 100 patients diagnosed with HCC and 50 healthy controls through reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR). The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis, and correlations with clinicopathological features were examined. Circ_0009910 and circ_0027478 exhibited significant upregulation in patients with HCC (p < 0.05), whereas miR-1236-3p demonstrated downregulation (p < 0.05). Circ_0009910 demonstrated significant diagnostic accuracy (area under the curve [AUC] = 0.90), effectively differentiating HCC from controls and showing a correlation with tumor size, metastasis, and alpha-fetoprotein (AFP) levels (p < 0.05). Both circ_0009910 and circ_0027478 exhibited a positive correlation with clinicopathological features, whereas miR-1236-3p demonstrated an inverse correlation. Logistic regression validated the diagnostic and prognostic capabilities of these biomarkers. The results indicate that circ_0009910, circ_0027478, and miR-1236-3p, in conjunction with AFP three, present a promising diagnostic and prognostic profile for HCC. Additional validation in larger cohorts is required to establish their clinical utility.

Discovery and validation of a novel dual-target blood test for the detection of hepatocellular carcinoma across stages from cirrhosis

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers. Early detection of HCC helps improve the patients' 5-year survival rate. Our goal was to identify superior methylation biomarkers to develop a methylation-specific quantitative PCR (MS‒qPCR) assay.

METHODS

A five-phase case-control study identified HCC methylation biomarkers via capture sequencing, TCGA/RNA-seq filtering, technical (MS-qPCR/Sanger) and biological (quadruplex MS-qPCR) validation. Methylated biomarkers were selected based on differential methylation expression using a tissue discovery cohort (43 HCC, 32 normal) and validated in plasma validation cohorts (Phase 1: 53 HCC, 52 cirrhosis, 20 benign, 50 healthy; Phase 2: 67 HCC, 81 cirrhosis). Then, the final assay's HCC detection performance was compared with existing blood-based surveillance methods.

RESULTS

Two methylated genes, OSR2 and TSPYL5, and a novel internal reference gene, SDF4, were identified and developed into an MS‒qPCR assay named Qliver. Qliver had an AUC of 0.955 (95% CI: 0.924-0.987) for distinguishing HCC patients from non-HCC patients in the Phase 1 plasma cohort, with a sensitivity of 88.68% (95% CI: 76.97%-95.73%) and a specificity of 89.34% (95% CI: 82.47%-94.20%), and 0.958 (95% CI: 0.927-0.989) for distinguishing HCC patients from cirrhosis patients in the Phase 2 plasma cohort, with a sensitivity of 88.06% (95% CI: 77.82%-94.70%) and a specificity of 92.59% (95% CI: 84.57%-97.23%). For the Phase 1 plus Plasma 2 cohort, Qliver had an AUC of at least 0.958 for detecting HCC in healthy individuals, cirrhosis patients and patients with benign liver diseases, which was superior to that of the GALAD score (AUC: 0.777 to 0.849). For BCLC stage 0 and A HCC patients, the sensitivity of Qliver ranged from 62.50% (95% CI: 24.49%-91.48%) to 72.73% (39.03%-93.98%), with a specificity of 90%. Overall, Qliver was superior to the AFP, AFP-L3, DCP and the GALAD score in terms of cirrhosis history, tumor stage, tumor size and tumor count.

CONCLUSIONS

Qliver demonstrated superior performance in detecting HCC compared with currently widely used blood biomarkers, suggesting its potential clinical benefit in HCC surveillance in high-risk populations.

The Current Role of Circulating Cell-Free DNA in the Management of Hepatocellular Carcinoma

Circulating cell-free DNA (cfDNA) has emerged as a compelling candidate of liquid biopsy markers for the diagnosis and prognosis of several cancers. We systematically reviewed data on the role of cfDNA markers in the diagnosis, prognosis and treatment of hepatocellular carcinoma (HCC). Early studies suggested that levels of circulating cfDNA, mitochondrial DNA and cfDNA integrity are higher in patients with HCC than chronic liver diseases. In subsequent studies, methylation changes in circulating tumor DNA (ctDNA) as well as cfDNA fragmentation patterns and circulating nucleosomes were found to offer high sensitivity (>60%) and excellent specificity (>90%) for HCC diagnosis. The predictive role of cfDNA markers and ctDNA has been assessed in a few studies including untreated patients with HCC providing promising results for prediction of survival. However, port-hepatectomy detection of cfDNA/ctDNA markers or copy number variation indicators of cfDNA seem to reflect minimum residual disease and thus a high risk for HCC recurrence. The same markers can be useful for prediction after transarterial chemoembolization, radiofrequency ablation, radiotherapy and even systemic therapies. In conclusion, cfDNA markers can be useful in HCC surveillance, improving early diagnosis rates, as well as for monitoring treatment effectiveness and minimal residual disease post-treatment.

Personalized treatment approaches in hepatocellular carcinoma

Personalized medicine is an emerging field that provides novel approaches to disease's early diagnosis, prevention, treatment, and prognosis based on the patient's criteria in gene expression, environmental factors, lifestyle, and diet. To date, hepatocellular carcinoma (HCC) is a significant global health burden, with an increasing incidence and significant death rates, despite advancements in surveillance, diagnosis, and therapeutic approaches. The majority of HCC lesions develop in patients with liver cirrhosis, carrying the risks of mortality associated with both the tumor burden and the cirrhosis. New therapeutic agents involving immune checkpoint inhibitors and targeted agents have been developed for sequential or concomitant application for advanced HCC but only a tiny percentage of patients benefit from each approach. Moreover, clinicians encounter difficulties determining the most appropriate regimen for each patient. This emphasizes the need for a personalized treatment approach. In other words, patients should no longer undergo treatment based on their tumor's histology but depending on the distinct molecular targets specific to their tumor biology. However, the utilization of precision medicine in managing HCC is still challenging. This review aims to discuss the role of personalized medicine in diagnosing, managing, and defining the prognosis of HCC. We also discuss the role of liquid biopsy and their clinical applications for immunotherapies in HCC. More clinical studies are still necessary to improve the precision of biomarkers used in the treatment decision for patients with HCC.

The current status and future directions of artificial intelligence in the prediction, diagnosis, and treatment of liver diseases

Early detection, accurate diagnosis, and effective treatment of liver diseases are of paramount importance for improving patient survival rates. However, traditional methods are frequently influenced by subjective factors and technical limitations. With the rapid progress of artificial intelligence (AI) technology, its applications in the medical field, particularly in the prediction, diagnosis, and treatment of liver diseases, have drawn increasing attention. This article offers a comprehensive review of the current applications of AI in hepatology. It elaborates on how AI is utilized to predict the progression of liver diseases, diagnose various liver conditions, and assist in formulating personalized treatment plans. The article emphasizes key advancements, including the application of machine learning and deep learning algorithms. Simultaneously, it addresses the challenges and limitations within this domain. Moreover, the article pinpoints future research directions. It underscores the necessity for large-scale datasets, robust algorithms, and ethical considerations in clinical practice, which is crucial for facilitating the effective integration of AI technology and enhancing the diagnostic and therapeutic capabilities of liver diseases.

The role of exosomal lncRNAs in acetaminophen-induced induced liver injury in SD rats

Background

Drug-induced liver injury (DILI) is a leading cause of drug development failures during clinical trials and post-market introduction. Current biomarkers, such as ALT and AST, lack the necessary specificity and sensitivity needed for accurate detection. Exosomes, which protect LncRNAs from RNase degradation, could provide reliable and easily accessible options for biomarkers.

Materials and methods

RNA-sequencing was used to identify differentially expressed LncRNAs (DE-LncRNAs), followed by isolation of LncRNAs from plasma exosomes in this study. Exosome characterization was conducted by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blot (WB). Bioinformatics analysis included functional enrichment and co-expression network analysis. Five rat models were established, and quantitative real-time PCR was used to verify the specificity and sensitivity of two candidate exosomal LncRNAs.

Results

The APAP-induced hepatocellular injury model was successfully established for RNA-sequencing, leading to the identification of several differentially expressed exosomal LncRNAs. Eight upregulated exosomal DE-LncRNAs were selected for validation. Among them, NONRATT018001.2 (p < 0.05) and MSTRG.73954.4 (p < 0.05) exhibited a more than 2-fold increase in expression levels. In hepatocellular injury and intrahepatic cholestasis models, both NONRATT018001.2 and MSTRG.73954.4 showed earlier increases compared to serum biomarkers ALT and AST. However, no histological changes were observed until the final time point. In the fatty liver model, NONRATT018001.2 and MSTRG.73954.4 increased earlier than ALT and AST at 21 days. By the 7th day, minor steatosis was evident in liver tissue, while the expression levels of the two candidate exosomal LncRNAs exceeded 2 and 4 times, respectively. In the hepatic fibrosis model, NONRATT018001.2 and MSTRG.73954.4 showed increases at every time point. By the 49th day, hepatocellular necrosis and fibrosis were observed in the liver tissue, with NONRATT018001.2 showing an increase of more than 8 times. The specificity of the identified exosomal DE-LncRNAs was verified using a myocardial injury model and they showed no significant differences between the case and control groups.

Conclusion

NONRATT018001.2 and MSTRG.73954.4 hold potential as biomarkers for distinguishing different types of organ injury induced by drugs, particularly enabling early prediction of liver injury. Further experiments, such as siRNA interference or gene knockout, are warranted to explore the underlying mechanisms of these LncRNAs.

Hepatocellular Carcinoma Surveillance Strategies: Major Guidelines and Screening Advances

BACKGROUND/OBJECTIVES

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, with prognosis and treatment outcomes that are significantly influenced by the stage at diagnosis. Early detection through regular surveillance is crucial for improving patient outcomes, especially in high-risk groups such as those with cirrhosis or chronic hepatitis B. Geographic variations in HCC risk factors, including viral hepatitis and non-alcoholic fatty liver disease (NAFLD), have led to the development of different international surveillance guidelines. This review aims to compare and evaluate the surveillance strategies proposed by the Asian Pacific Association for the Study of the Liver (APASL), the American Association for the Study of Liver Diseases (AASLD), and the European Association for the Study of the Liver and European Organization for Research and Treatment of Cancer (EASL-EORTC).

METHODS

The review examined and compared major international guidelines on HCC surveillance, focusing on patient selection, imaging modalities, and the integration of biomarkers. We also explored recent advancements in screening techniques, including artificial intelligence and emerging biomarkers, to identify future directions for improving surveillance strategies.

RESULTS

Our analysis identified key differences in the guidelines, particularly in imaging modality preferences and the use of biomarkers for early detection. While all guidelines place emphasis on high-risk populations, the inclusion criteria and surveillance intervals vary. Additionally, novel technologies such as artificial intelligence show potential to enhance the accuracy and efficiency of HCC detection.

CONCLUSIONS

This review highlights the need to harmonize the international guidelines, particularly in regard to patients with non-cirrhotic NAFLD who remain under-represented in current surveillance protocols. Future research should focus on integrating emerging technologies and biomarkers to improve early detection and overall patient outcomes.

Extracellular Vesicle microRNA: A Promising Biomarker and Therapeutic Target for Respiratory Diseases

Respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, lung cancer, and coronavirus pneumonia, present a major global health challenge. Current diagnostic and therapeutic options for these diseases are limited, necessitating the urgent development of novel biomarkers and therapeutic strategies. In recent years, microRNAs (miRNAs) within extracellular vesicles (EVs) have received considerable attention due to their crucial role in intercellular communication and disease progression. EVs are membrane-bound structures released by cells into the extracellular environment, encapsulating a variety of biomolecules such as DNA, RNA, lipids, and proteins. Specifically, miRNAs within EVs, known as EV-miRNAs, facilitate intercellular communication by regulating gene expression. The expression levels of these miRNAs can reflect distinct disease states and significantly influence immune cell function, chronic airway inflammation, airway remodeling, cell proliferation, angiogenesis, epithelial-mesenchymal transition, and other pathological processes. Consequently, EV-miRNAs have a profound impact on the onset, progression, and therapeutic responses of respiratory diseases, with great potential for disease management. Synthesizing the current understanding of EV-miRNAs in respiratory diseases such as COPD, asthma, lung cancer, and novel coronavirus pneumonia, this review aims to explore the potential of EV-miRNAs as biomarkers and therapeutic targets and examine their prospects in the diagnosis and treatment of these respiratory diseases.

Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma

This review comprehensively explores the complex interplay between extracellular vesicles (ECVs)/exosomes and circadian rhythms, with a focus on the role of this interaction in hepatocellular carcinoma (HCC). Exosomes are nanovesicles derived from cells that facilitate intercellular communication by transporting bioactive molecules such as proteins, lipids, and RNA/DNA species. ECVs are implicated in a range of diseases, where they play crucial roles in signaling between cells and their surrounding environment. In the setting of cancer, ECVs are known to influence cancer initiation and progression. The scope of this review extends to all cancer types, synthesizing existing knowledge on the various roles of ECVs. A unique aspect of this review is the emphasis on the circadian-controlled release and composition of exosomes, highlighting their potential as biomarkers for early cancer detection and monitoring metastasis. We also discuss how circadian rhythms affect multiple cancer-related pathways, proposing that disruptions in the circadian clock can alter tumor development and treatment response. Additionally, this review delves into the influence of circadian clock components on ECV biogenesis and their impact on reshaping the tumor microenvironment, a key component driving HCC progression. Finally, we address the potential clinical applications of ECVs, particularly their use as diagnostic tools and drug delivery vehicles, while considering the challenges associated with clinical implementation.

Genetic screening of liver cancer: State of the art

Liver cancer, primarily hepatocellular carcinoma, remains a global health challenge with rising incidence and limited therapeutic options. Genetic factors play a pivotal role in the development and progression of liver cancer. This state-of-the-art paper provides a comprehensive review of the current landscape of genetic screening strategies for liver cancer. We discuss the genetic underpinnings of liver cancer, emphasizing the critical role of risk-associated genetic variants, somatic mutations, and epigenetic alterations. We also explore the intricate interplay between environmental factors and genetics, highlighting how genetic screening can aid in risk stratification and early detection via using liquid biopsy, and advancements in high-throughput sequencing technologies. By synthesizing the latest research findings, we aim to provide a comprehensive overview of the state-of-the-art genetic screening methods for liver cancer, shedding light on their potential to revolutionize early detection, risk assessment, and targeted therapies in the fight against this devastating disease.