Observational studies have reported conflicting associations between periodontitis (PD) and hepatocellular carcinoma (HCC). To overcome these limitations, we performed a two-sample Mendelian randomization (MR) analysis to investigate the potential association between PD and HCC.

We used summary data from genome-wide association studies (GWASs) of European ancestry, integrating data from chronic/acute periodontitis (CP/AP) samples (n1 = 34,615; n2 = 277,036; n3 = 410,811) and HCC samples (n1 = 456,348; n2 = 475,638). The inverse variance-weighted (IVW) approach represents our primary analysis method, supplemented by MR-Egger regression, weighted median, weighted-mode, and simple-mode methods. Pleiotropy and heterogeneity tests were also performed.

IVW analysis suggested that PD had no effect on HCC (Group 1: odds ratio [OR] = 0.912, 95% confidence interval [CI] = 0.690-1.204, P = .514; Group 2: OR = 1.038, 95% CI = 0.895-1.203, P = .623; Group 3: OR = 0.966, 95% CI = 0.851-1.096, P = .591; Group 4: OR = 1.103, 95% CI = 0.576-2.113, P = .768; Group 5: OR = 1.257, 95% CI = 0.511-1.037, P = .540; Group 6: OR = 0.728, 95% CI = 0.511-1.037, P = .079). Four complementary analyses further support this conclusion. Both the IVW and MR-Egger results indicate that the instrumental variables in each group did not exhibit significant pleiotropy. MR-Egger regression analysis showed no evidence of pleiotropic effects.

Our MR analysis suggests that PD does not significantly impact the risk of developing HCC. These results provide a new perspective on the relationship between these 2 conditions.

This MR study suggests no significant genetic causal relationship between PD and HCC, providing a new perspective. It indicates that clinicians may not need to over-intervene in periodontal disease to prevent liver cancer, thereby avoiding unnecessary psychological burden on patients.

Microvascular invasion (MVI) is a critical factor in hepatocellular carcinoma (HCC) prognosis, particularly in hepatitis B virus (HBV)-related cases. This editorial examines a recent study by Xu et al who developed models to predict MVI and high-risk (M2) status in HBV-related HCC using contrast-enhanced computed tomography (CECT) radiomics and clinicoradiological factors. The study analyzed 270 patients, creating models that achieved an area under the curve values of 0.841 and 0.768 for MVI prediction, and 0.865 and 0.798 for M2 status prediction in training and validation datasets, respectively. These results are comparable to previous radiomics-based approaches, which reinforces the potential of this method in MVI prediction. The strengths of the study include its focus on HBV-related HCC and the use of widely accessible CECT imaging. However, limitations, such as retrospective design and manual segmentation, highlight areas for improvement. The editorial discusses the implications of the study including the need for standardized radiomics approaches and the potential impact on personalized treatment strategies. It also suggests future research directions, such as exploring mechanistic links between radiomics features and MVI, as well as integrating additional biomarkers or imaging modalities. Overall, this study contributes significantly to HCC management, paving the way for more accurate, personalized treatment approaches in the era of precision oncology.

Liver cancer is a significant global health concern due to its poor prognosis, often resulting from late-stage diagnosis and limited treatment options. While non-invasive methods such as ultrasound, blood tests (like AFP and PIVKA-II), CT scans, and MRIs are commonly employed in liver cancer diagnosis, they can occasionally be limited in sensitivity or associated with high costs. This has heightened the demand for innovative, non-invasive biomarkers that enable early and accurate diagnosis, leading to increased interest in the potential of exosomes. Exosomes are small vesicles released by cells and have the potential to serve as biomarkers for liver cancer. They contain a variety of biomolecules, including nucleic acids, proteins, and lipids, which can offer important information about cell health and disease progression. Developing fast, accurate, sensitive, and reliable techniques for detecting exosomes is essential. Biosensors, analytical tools for biological samples, have emerged as powerful instruments for analyzing exosomes. This review focuses on recent advancements in biosensor technology for exosome detection and explores future perspectives. The goal is to promote the development of innovative biosensor-based methods for detecting exosomes to enable earlier diagnosis and better clinical management of liver cancer.

Hepatocellular carcinoma (HCC) seriously threatens the human health. Previous investigations revealed that γ-glutamyltranspeptidase (GGT) was tightly associated with the chronic injury, hepatic fibrosis, and the development of HCC, therefore might act as a potential indicator for monitoring the HCC-related processes. Herein, with the contribution of a structurally optimized probe ETYZE-GGT, the bimodal imaging in both far red fluorescence (FL) and photoacoustic (PA) modes has been achieved in multiple HCC-related models. To our knowledge, this work covered the most comprehensive models including the fibrosis and developed HCC processes as well as the premonitory induction stages (autoimmune hepatitis, drug-induced liver injury, non-alcoholic fatty liver disease). ETYZE-GGT exhibited steady and practical monitoring performances on reporting the HCC stages via visualizing the GGT dynamics. The two modes exhibited working consistency and complementarity with high spatial resolution, precise apparatus and desirable biocompatibility. In cooperation with the existing techniques including testing serum indexes and conducting pathological staining, ETYZE-GGT basically realized the universal application for the accurate pre-clinical diagnosis of as many HCC stages as possible. By deeply exploring the mechanically correlation between GGT and the HCC process, especially during the premonitory induction stages, we may further raise the efficacy for the early diagnosis and treatment of HCC.

Hepatocellular carcinoma (HCC), renowned for its bleak prognosis and high recurrence rates, necessitates innovative strategies for prognosis assessment and therapeutic intervention. In this pursuit, we systematically investigated the influence of anesthesia-related genes (ANARGs) on HCC outcomes. Leveraging data from The Cancer Genome Atlas (TCGA), our study scrutinized RNA sequencing data and clinical profiles from 374 HCC patients alongside 50 non-tumor liver samples to unravel ANARG expression patterns and their clinical relevance. Employing consensus clustering, we segregated HCC samples into two distinct subtypes based on ANARG profiles, unveiling significant survival disparities between them. Further differential expression analysis pinpointed pivotal genes and pathways distinguishing these subtypes, notably implicating lipid metabolism and the MTOR signaling pathway in HCC pathogenesis. A prognostic model, comprising five key ANARGs (DAGLA, CYP26B, HAVCR, G6PD and AKR1B), exhibited robust predictive capability for patient outcomes, validated across independent patient cohorts. Furthermore, immune infiltration analysis uncovered a nuanced interplay between ANARG expression and the tumor immune microenvironment, spotlighting variations in immune cell infiltration and function across the identified HCC subtypes. This comprehensive analysis underscores not only the prognostic significance of ANARGs in HCC but also their potential to modulate the tumor microenvironment, providing novel insights for tailoring anesthetic management and therapeutic strategies in HCC care. Our findings advocate for a more integrative approach to HCC management, amalgamating molecular profiling with traditional clinical parameters to refine patient stratification and personalize treatment strategies.

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Hepatocellular carcinomas (HCC) have a high morbidity and mortality rate, and is difficult to cure and prone to recurrence when it has already developed. Therefore, early detection and efficient treatment of HCC is necessary.

In this study, we synthesized a novel NDI polymer with uniform size, long-term stability, and high near-infrared two-zone (NIR-II) absorption efficiency, which can greatly enhance the effect of photothermal therapy (PTT) after intravenous injection into Huh-7-tumor bearing mice.

The in vitro and in vivo studies showed that NDI polymer exhibited excellent NIR-guided PTT treatment, and the antitumor effect was approximately 88.5%, with obvious antimetastatic effects.

This study developed an NDI polymer-mediated integrated diagnostic and therapeutic modality for NIR-II fluorescence imaging and photothermal therapy.

The prevention and early diagnosis of liver cancer remains a global medical challenge. During the malignant transformation of hepatocytes, a variety of oncogenic cellular signalling molecules, such as novel high mobility group-Box 3, angiopoietin-2, Golgi protein 73, glypican-3, Wnt3a (a signalling molecule in the Wnt/β-catenin pathway), and secretory clusterin, can be expressed and secreted into the blood. These signalling molecules are derived from different signalling pathways and may not only participate in the malignant transformation of hepatocytes but also become early diagnostic indicators of hepatocarcinogenesis or specific targeted molecules for hepatocellular carcinoma therapy. This article reviews recent progress in the study of several signalling molecules as sensitive biomarkers for monitoring hepatocarcinogenesis.

The impact of psychological factors on the incidence of hepatocellular carcinoma (HCC) in humans remains unclear. Mendelian randomization (MR) study is a novel approach aimed at unbiased detection of causal effects. Therefore, we conducted a two-sample MR to determine if there is a causal relationship between psychological distress (PD), participation in leisure/social activities of religious groups (LARG), and HCC.

The genetic summary data of exposures and outcome were retrieved from genome-wide association studies (GWAS). We used PD and LARG as exposures and HCC as outcome. Five MR methods were used to investigate the causal relationship between PD, LARG, and HCC. The result of inverse variance weighted (IVW) method was deemed as principal result. Besides, we performed a comprehensive sensitivity analysis to verify the robustness of the results.

The IVW results showed that PD [odds ratio (OR) 1.006, 95% confidence interval (CI) 1.000-1.011, P = 0.033] and LARG (OR 0.994, 95% CI 0.988-1.000, P = 0.035) were causally associated with the incidence of HCC. Sensitivity analysis did not identify any bias in the results.

PD turned out to be a mild risk factor for HCC. In contrast, LARG is a protective factor for HCC. Therefore, it is highly recommended that people with PD are seeking positive leisure activities such as participation in formal religious social activities, which may help them reduce the risk of HCC.

Hepatocellular carcinoma (HCC) is among the world's third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant.

The current hepatocellular carcinoma (HCC) diagnostic approaches lack adequate sensitivity and specificity. So, this study was performed to develop an innovative model of surface-enhanced Raman spectroscopy (SERS) that can detect HCC patients by identifying the circulating tumor-derived exosomes.

Sixty participants, including normal controls, hepatitis C virus (HCV)-infected patients, and HCV-associated HCC patients, had their whole blood samples and exosomes separated from these samples analyzed using Raman spectroscopy (RS). A revolutionary model of SERS, based on an innovative glass and nano-gold, was designed to directly identify exosomes. Its measurements were simulated by Comsol Multiphysics (5.6).

The RS examination of the whole blood samples revealed no Raman peaks. Yet, the isolated exosomes from these samples generated Raman peaks at 400 and 1000 cm^-1 wavenumbers in the HCV group. A Raman shift was detected in HCC patients at 812, 852, and 878 cm^-1 wavenumbers with intensity ratios of 120, 130, and 60, respectively. The RS had a sensitivity and specificity of 95 % and 100 %, respectively, for detecting HCC. However, the newly-designed SERS was able to identify the HCC-derived exosomes, at 812 and 878 cm^-1 wavenumbers, with boosted intensity ratios of 9*10⁶ and 4*10⁶, respectively, in the whole blood samples.

The newly-developed SERS model has the potential to detect HCC patients through recognizing the tumor-derived exosomes non-invasively, with high accuracy, and without the need for laborious exosomal separation. Nonetheless, bringing this technology into the clinic demands the establishment of spectral databases and their validation using the current gold standards.

The global outbreak of COVID-19 possesses serious challenges and adverse impacts for patients with progression of chronic liver disease and has become a major threat to public health. COVID-19 patients have a high risk of lung injury and multiorgan dysfunction that remains a major challenge to hepatology. COVID-19 patients and those with liver injury exhibit clinical manifestations, including elevation in ALT, AST, GGT, bilirubin, TNF-α, and IL-6 and reduction in the levels of CD4 and CD8. Liver injury in COVID-19 patients is induced through multiple factors, including a direct attack of SARS-CoV-2 on liver hepatocytes, hypoxia reperfusion dysfunction, cytokine release syndrome, drug-induced hepatotoxicity caused by lopinavir and ritonavir, immune-mediated inflammation, renin-angiotensin system, and coagulopathy. Cellular and molecular mechanisms underlying liver dysfunction are not fully understood in severe COVID-19 attacks. High mortality and the development of chronic liver diseases such as cirrhosis, alcoholic liver disease, autoimmune hepatitis, nonalcoholic fatty liver disease, and hepatocellular carcinoma are also associated with patients with liver damage. COVID-19 patients with preexisting or developing liver disease should be managed. They often need hospitalization and medication, especially in conjunction with liver transplants. In the present review, we highlight the attack of SARS-CoV-2 on liver hepatocytes by exploring the cellular and molecular events underlying the pathophysiological mechanisms in COVID-19 patients with liver injury. We also discuss the development of chronic liver diseases during the progression of SARS-CoV-2 replication. Lastly, we explore management principles in COVID-19 patients with liver injury and liver transplantation.