Circulating tumor DNA and its role in detection, prognosis and therapeutics of hepatocellular carcinoma

The epigenetic basis of hepatocellular carcinoma - mechanisms and potential directions for biomarkers and therapeutics

Hepatocellular carcinoma (HCC) is the sixth leading cancer worldwide and has complex pathogenesis due to its heterogeneity, along with poor prognoses. Diagnosis is often late as current screening methods have limited sensitivity for early HCC. Moreover, current treatment regimens for intermediate-to-advanced HCC have high resistance rates, no robust predictive biomarkers, and limited survival benefits. A deeper understanding of the molecular biology of HCC may enhance tumor characterization and targeting of key carcinogenic signatures. The epigenetic landscape of HCC includes complex hallmarks of 1) global DNA hypomethylation of oncogenes and hypermethylation of tumor suppressors; 2) histone modifications, altering chromatin accessibility to upregulate oncogene expression, and/or suppress tumor suppressor gene expression; 3) genome-wide rearrangement of chromatin loops facilitating distal enhancer-promoter oncogenic interactions; and 4) RNA regulation via translational repression by microRNAs (miRNAs) and RNA modifications. Additionally, it is useful to consider etiology-specific epigenetic aberrancies, especially in viral hepatitis and metabolic dysfunction-associated steatotic liver disease (MASLD), which are the main risk factors of HCC. This article comprehensively explores the epigenetic signatures in HCC, highlighting their potential as biomarkers and therapeutic targets. Additionally, we examine how etiology-specific epigenetic patterns and the integration of epigenetic therapies with immunotherapy could advance personalized HCC treatment strategies.

Innovative Strategies in the Diagnosis and Treatment of Liver Cirrhosis and Associated Syndromes

Liver cirrhosis continues to be a major global health issue, contributing to high morbidity and mortality due to its progressive nature and associated complications. This review explores recent advancements in the diagnosis and treatment of liver cirrhosis and its related syndromes. Non-invasive diagnostic tools, such as elastography and serum biomarkers, have significantly improved early detection, reducing the need for liver biopsies. Advanced imaging techniques, including MRI and CT, further enhance diagnostic accuracy. In parallel, molecular and genomic research is providing new insights into the pathogenesis of the disease, paving the way for precision medicine. On the treatment front, pharmacological innovations, such as antifibrotic agents and targeted therapies, show promise in slowing disease progression. Endoscopic interventions like variceal banding are improving the management of complications, while advancements in liver transplantation and artificial liver support systems offer life-saving alternatives. Regenerative medicine, particularly stem cell therapy and tissue engineering, is emerging as a promising strategy for liver repair. Managing cirrhosis-related syndromes, including portal hypertension, ascites, hepatic encephalopathy, and hepatorenal syndrome, now involves evolving therapeutic approaches such as transjugular intrahepatic portosystemic shunt (TIPS) and novel pharmacotherapies. Prognostic scoring systems like the MELD and Child-Pugh are being refined with new biomarkers for better risk stratification. The future of cirrhosis care will likely involve the integration of artificial intelligence and machine learning for early diagnosis and personalized treatments, alongside emerging therapies currently under investigation. Despite these advancements, challenges such as costs, accessibility, and healthcare disparities remain barriers to widespread adoption. This review highlights the importance of incorporating innovative diagnostic and therapeutic strategies into clinical practice to improve the outcomes for patients with liver cirrhosis and its complications.

Evaluation of PDZD11 in hepatocellular carcinoma: prognostic value and diagnostic potential in combination with AFP

Background

Hepatocellular carcinoma (HCC) is the most prevalent liver cancer, with a 5-year survival rate below 20% and an average survival time of 3-6 months. Identifying new biomarkers is crucial for early diagnosis and prognosis. The function of PDZ domain protein 11 (PDZD11) in HCC remains unclear.

Methods

In this study, PDZD11 was investigated as a potential biomarker for HCC using bioinformatic analysis of the TCGA and ICGC datasets. Furthermore, we assessed the potential of serum PDZD11 as a clinical diagnostic marker by enrolling a cohort comprising 78 HCC patients and 62 healthy controls (HC) using the ELISA analysis and combining its expression with common tumor markers.

Results

Our research found significantly higher PDZD11 mRNA expression in HCC tissues compared to tumor-adjacent tissues (p < 0.001), which was associated with lower overall survival (OS) rates (p < 0.01). Multivariate evaluation methods established PDZD11 as a standalone predictor of prognosis. A nomogram incorporating PDZD11 expression and clinicopathological factors predicted OS rates for HCC patients over various years. Patients with HCC exhibited notably elevated serum PDZD11 levels compared to HC, with these levels rising further in advanced disease stages and deteriorating performance status (PS). ROC analysis showed high diagnostic accuracy when PDZD11 is combined with AFP (AUC = 0.958).

Conclusion

PDZD11 is more sensitive than AFP in assessing HCC prognosis. In conclusion, PDZD11 is a promising supplementary biomarker for HCC diagnosis and prognosis alongside AFP.

Geographic and Viral Etiology Patterns of TERT Promoter and CTNNB1 Exon 3 Mutations in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and a leading cause of cancer-related mortality worldwide. Genetic alterations play a critical role in hepatocarcinogenesis, with mutations in the telomerase reverse transcriptase promoter (TERTp) and CTNNB1 exon 3 representing two of the most frequently reported somatic events in HCC. However, the frequency and distribution of these mutations vary across geographic regions and viral etiologies, particularly hepatitis B virus (HBV) and hepatitis C virus (HCV). This study aimed to assess the global distribution and etiological associations of TERTp and CTNNB1 exon 3 mutations in HCC through a comprehensive literature review. Our analysis, encompassing over 4000 HCC cases, revealed that TERTp mutations were present in 49.2% of tumors, with C228T being the predominant variant (93.3% among mutated cases). A striking contrast was observed between viral etiologies: TERTp mutations were detected in 31.6% of HBV-related HCCs, compared to 66.2% in HCV-related cases. CTNNB1 exon 3 mutations were identified in 23.1% of HCCs, showing a similar association with viral etiology, being more common in HCV-related cases (30.7%) than in HBV-related tumors (12.8%). Geographically, both mutations exhibited comparable patterns, with higher frequencies in Europe, Japan, and the USA, while lower rates were observed in China, Taiwan, and South Korea. Our findings underscore the distinct molecular profiles of HCC according to viral etiology and geographic origin, highlighting the need for region- and etiology-specific approaches to HCC prevention, diagnosis, and targeted therapy.

Diagnostic accuracy of methylated SEPT9 for primary liver cancer: a systematic review and meta-analysis

Background

Primary live cancer (PLC), including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). This meta-analysis was conducted to evaluate the diagnostic efficacy of blood methylated septin 9 gene (mSEPT9) for PLC and to analyze its performance across various subgroups.

Methods

We conducted a comprehensive search across PubMed, the Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI), covering research up to May 10, 2024. The pooled sensitivity, specificity, diagnostic odds ratios, and area under the summary receiver operating characteristic (AUC) were calculated for the diagnostic performance of mSEPT9 for PLC. The quality of the studies was assessed using the QUADAS-2 tool, and the meta-analysis was performed using Stata16.0 software.

Results

Ten articles with 2,182 participants were included in the meta-analysis. The pooled sensitivity of mSEPT9 for detecting primary liver cancer was 0.51 (95% confidence interval [CI]: 0.37-0.65), and the pooled specificity was 0.93 (95% CI: 0.78-0.98). The pooled diagnostic odds ratio was 13 (95% CI: -58), and the area under the Summary Receiver Operator Characteristic Curve was 0.75 (95% CI: 0.71-0.79). Subgroup analyses showed that ICC, case-control studies, qPCR and Asian populations had higher specificities (0.99 [95% CI: 0.97-1.00], 0.93 [95% CI: 0.91-0.95], 0.90 [95% CI: 0.88-0.92] and 0.94 [95% CI: 0.92-0.96], respectively) and diagnostic odds ratios (62.04 [95% CI: 6.53-589.53], 17.62 [95% CI: 4.03-76.99], 13.03 [95% CI: 2.01-84.63] and 14.19 [95% CI: 2.42-83.11], respectively) compared to hepatocellular carcinoma, cohort Study, and Euramerican populations.

Conclusions

This study confirmed that mSEPT9 in blood has high specificity and moderate sensitivity for detecting primary liver cancer. The diagnostic performance of mSEPT9 varied across different subgroups, limiting its use as an independent screening tool and necessitating its use in conjunction with other methods for confirmatory diagnostics.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42024549669.

Raman Spectroscopy and Exosome-Based Machine Learning Predicts the Efficacy of Neoadjuvant Therapy for HER2-Positive Breast Cancer

Early prediction of the neoadjuvant therapy efficacy for HER2-positive breast cancer is crucial for personalizing treatment and enhancing patient outcomes. Exosomes, which play a role in tumor development and treatment response, are emerging as potential biomarkers for cancer diagnosis and efficacy prediction. Despite their promise, current exosome detection and isolation methods are cumbersome and time-consuming and often yield limited purity and quantity. In this study, we employed Raman spectroscopy to analyze the molecular changes in exosomes from the sera of HER2-positive breast cancer patients before and after two cycles of neoadjuvant therapy. Utilizing machine learning techniques (PCA, LDA, and SVM), we developed a predictive model with an AUC value exceeding 0.89. Additionally, we introduced an innovative HER2-positive exosome capture and detection system, termed Magnetic beads@HER2-Exos@HER2-SERS detection nanoprobes (HER2-MEDN). This system enabled us to efficiently extract and analyze HER2-positive exosomes, refining our predictive model to achieve an accuracy greater than 0.94. Our study has demonstrated the potential of the HER2-MEDN system in accurately predicting early treatment response, offering novel insights and methodologies for assessing the efficacy of neoadjuvant therapy in HER2-positive breast cancer.

Surface-enhanced Raman scattering-based strategies for tumor markers detection: A review

The presence of malignant tumors poses a significant threat to people's life and well-being. As biochemical parameters indicate the occurrence and development of tumors, tumor markers play a pivotal role in early cancer detection, treatment, prognosis, efficient monitoring, and other aspects. Surface-enhanced Raman scattering (SERS) is considered a potent tool for the detection of tumor markers owing to its exceptional advantages encompassing high sensitivity, superior selectivity, rapid analysis speed, and photobleaching resistance nature. This review aims to provide a comprehensive understanding of SERS applications in the detection of tumor markers. Firstly, we introduce the SERS enhancement mechanism, classification of active substrates, and SERS detection techniques. Secondly, the latest research progress of in vitro SERS detection of different types of tumor markers in body fluids and the application of SERS imaging in biomedical imaging are highlighted in sections of the review. Finally, according to the current status of SERS detection of tumor markers, the challenges and problems of SERS in biomedical detection are discussed, and insights into future developments in SERS are offered.

Telomere Length and Telomerase Activity as Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromosome ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering insights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.