Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine

Persistence of hepatitis C virus in peripheral blood mononuclear cells of patients who achieved sustained virological response following treatment with direct-acting antivirals is associated with a distinct pre-existing immune exhaustion status

Hepatitis C virus (HCV) is a primary hepatotropic pathogen responsible for acute and chronic hepatitis C, however, it can also cause "occult" infection (OCI), defined as the presence of the virus' genetic material in hepatocytes and/or peripheral blood cells, but not in plasma/serum. Assessment of the sustained virologic response (SVR) after treatment with direct-acting antivirals (DAA) is based exclusively on HCV-RNA testing in plasma/serum, which may preclude the diagnosis of post-treatment OCI. Possible clinical consequences of OCI were described previously, but its occurrence after DAA-based antiviral treatment programs and determinants of the virus persistence are not fully elucidated. The aim of this study was to assess the incidence of post-treatment OCI after successful DAA-based treatment and to identify clinical and immunological factors associated with this phenomenon. In 97 patients treated with DAA, HCV-RNA was tested by RT-PCR in peripheral blood mononuclear cells (PBMC) at baseline (i.e., before the onset of treatment) and at the time of SVR assessment. Before treatment, HCV-RNA was detectable in all patients' PBMC. All subjects responded to therapy according to the clinical criteria, but 9 (9.3%) patients revealed the HCV-RNA in PBMC at SVR. In most of these cases, post-DAA OCI was related to switch of the dominant infecting genotype. Post-treatment OCI was characterized by significantly lower pre-treatment HCV viral load and lower expression of Tim-3 (T-cell immunoglobulin and mucin domain-containing protein 3) on CD8+ T-cells. Our results imply that post-treatment OCI may be related to lower pretreatment viral load as well as distinct pre-existing immune exhaustion status.

Modality-Aware Distillation Network for Microvascular Invasion Prediction of Hepatocellar Carcinoma From MRI Images

Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a crucial histopathologic prognostic factor associated with cancer recurrence after liver transplantation or hepatectomy. Recently, clinicoradiologic characteristics are combined with medical images to enhance the HCC prediction. However, compared to medical imaging data, the clinicoradiologic characteristics (e.g., APOe4 genotyping) is not easy to collect or even unavailable, as it requires more efforts of clinicians and more medical instruments for collecting diverse measurements. This work explores how to transfer the knowledge of a teacher network learned from non-image clinical data and image data to a student network with only image data such that the student network can leverage the transferred clinical information to boost HCC classification with only imaging data as input. Specifically, we present a modality-aware distillation network (MD-Net) to transform non-image clinicoradiologic from the teacher network to the student network. The teacher network integrates non-image clinicoradiologic characteristics with two 3D MRI modality images via two MRI-clinical-fusion modules and a symmetric attention (SA) module, while the student network extracts features from two modality MRI data via two MRI-only modules and then refine these two MRI features via a SA module. A classification-level distillation and a feature-level distillation are jointly utilized to transfer the clinical information between teacher and student networks. Furthermore, we design a novel self-supervised task to predict clinicoradiologic characteristics from the imaging data to further enhance the downstream HCC classification. The experimental results from our collected dataset and a multi-modal sarcasm detection dataset have demonstrated the effectiveness of our approach. Specifically, we achieved an AUC score of 71.86% and 75.51% respectively, surpassing the performance of the state-of-the-art classification methods.

Nomogram for prediction of hepatocellular carcinoma recurrence after liver resection

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy with high mortality. Liver resection (LR) is a curative treatment for early-stage HCC, but the prognosis of HCC patients after LR is unsatisfactory because of tumor recurrence. Prognostic prediction models with great performance are urgently needed. The present study aimed to establish a novel prognostic nomogram to predict tumor recurrence in HCC patients after LR.

METHODS

We retrospectively analyzed 726 HCC patients who underwent LR between October 2011 and December 2016. Patients were randomly divided into the training cohort (n = 508) and the testing cohort (n = 218). The protein expression of 14 biomarkers in tumor tissues was assessed by immunohistochemistry. The nomogram predicting recurrence-free survival (RFS) was established by a multivariate Cox regression analysis model and was evaluated by calibration curves, Kaplan-Meier survival curves, time-dependent areas under the receiver operating characteristic (ROC) curves (AUCs), and decision curve analyses in both the training and testing cohorts.

RESULTS

Alpha-fetoprotein [hazard ratio (HR) = 1.013, P = 0.002], portal vein tumor thrombosis (HR = 1.833, P < 0.001), ascites (HR = 2.024, P = 0.014), tumor diameter (HR = 1.075, P < 0.001), E-cadherin (HR = 0.859, P = 0.011), EMA (HR = 1.196, P = 0.022), and PCNA (HR = 1.174, P = 0.031) immunohistochemistry scores were found to be independent factors for RFS. The 1-year and 3-year AUCs of the nomogram for RFS were 0.813 and 0.739, respectively. The patients were divided into the high-risk group and the low-risk group by median value which was generated from the nomogram, and Kaplan-Meier analysis revealed that the high-risk group had a shorter RFS than the low-risk group in both the training (P < 0.001) and testing cohorts (P < 0.001).

CONCLUSIONS

Our newly developed nomogram integrated clinicopathological data and key gene expression data, and was verified to have high accuracy in predicting the RFS of HCC patients after LR. This model could be used for early identification of patients at high-risk of postoperative recurrence.

[Hepatocellular carcinoma: Histological and molecular classifications]

Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumour, with a poor prognosis, ranking third for cancer mortality worldwide. HCC is a morphologically and molecularly heterogeneous tumour. This update aims to address this heterogeneity by describing the different histological and molecular subtypes of HCC. Morphologically, eight subtypes have been described according to the WHO classification: steatohepatitic, macrotrabecular massive (MTM), clear cell, chromophobe, scirrhous, fibrolamellar, lymphocyte-rich and neutrophil-rich. Other HCCs are classified as non-specific (not otherwise specified or NOS). These subtypes may be associated with a different prognosis, particularly the MTM, which displays a poorer survival than the other subtypes. Genomically, most HCCs present mutations in the TERT promoter, while other mutations occured later in carcinogenesis, such as TP53 and CTNNB1. TP53 mutated HCCs are associated with a poor prognosis and the MTM subtype. From a transcriptomic standpoint, two classifications are particularly noteworthy, as they are associated with both prognosis (proliferative vs. non-proliferative classification) and clinical, morphological and genomic tumour characteristics (G1-G6 classification). In conclusion, the morphological heterogeneity of HCC, directly linked to molecular heterogeneity, is associated with prognosis. This strongly supports the specification of the different HCC subtypes in our reports.

Hepatitis B Virus Promotes Angiogenesis in Hepatocellular Carcinoma by Increasing m6A Modification of VEGFA mRNA via IGF2BP3

Angiogenesis plays a crucial role in the development of HBV-related hepatocellular carcinoma (HCC). VEGFA is a key angiogenic factor, and while its transcriptional regulation by HBV has been extensively studied, its posttranscriptional regulation by HBV remains poorly understood. Building on our previous findings that delineated an RBM15/YTHDF2/IGF2BP3 regulatory axis in m6A-mediated RNA metabolism in HCC, this study further explores the posttranscriptional regulation of VEGFA by HBV. By MeRIP-qPCR and integrating MeRIP-seq data, we discovered that HBV enhances m6A methylation of VEGFA mRNA. Comprehensive cellular and molecular biology experiments demonstrated that HBV induces the upregulation of IGF2BP3, which serves as a key "reader" that recognizes and stabilizes VEGFA mRNA in an m6A methylation-dependent manner. This stabilization leads to elevated VEGFA expression, promoting enhanced cellular functions such as HUVEC migration and tube formation. Furthermore, in an HBV-associated HCC xenograft model, IGF2BP3 knockdown resulted in decreased VEGFA expression and inhibited tumor growth. This study expands our understanding of HBV-driven angiogenesis and identifies the IGF2BP3-VEGFA axis as a potential therapeutic target for antiangiogenic strategies in HBV-related HCC.

Construction of a survival prediction model for patients with hepatocellular carcinoma (HCC) based on real clinical data: a single-center retrospective study

Background

Given the rising incidence of hepatocellular carcinoma (HCC) globally, especially in China, information about independent risk factors for survival and disease prognosis of the illness is scarce. In the field of HCC research, there is an urgent need for a scientific basis to enhance the accuracy of clinical diagnosis, optimize the course of therapy, and accurately predict the prognosis. Against this backdrop, the objective of this work was to develop a scientific, efficient, and methodical nomogram to forecast the survival prognosis of HCC.

Methods

A real-world study collected clinical data from January 1, 2011, to December 31, 2019, for individuals with HCC. Overall survival (OS) was determined using Kaplan-Meier analysis. Independent risk variables were identified using Cox proportional hazards regression. A nomogram predicting 1-, 3-, and 5-year OS was created. The reliability of the predictions of the model was assessed using receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA).

Results

Data from 1,128 HCC cases showed 1-, 3-, and 5-year OS rates were 86.3%, 65.3%, and 43.1%, respectively. Univariate Cox regression identified 13 variables influencing HCC survival including age, HCC screening status, hepatitis C virus (HCV) status, nonalcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) status, liver cirrhosis, elevated alpha-fetoprotein (AFP), Child-Pugh grade, tumor size, tumor number, treatment method, tumor thrombus, and extrahepatic metastasis (P<0.05). Multivariate analysis confirmed HCC screening status, tumor size, ALD, Child-Pugh classification, and therapy method as independent prognostic factors (P<0.05). The nomogram achieved an area under the ROC curve (AUC) of 0.868. Calibration curves of the 1-, 3-, and 5-year survival times and the DCA curve confirmed its predictive accuracy.

Conclusions

Patients without HCC screening, tumor size >5 cm, ALD, Child-Pugh grade C, and conservative treatment had a poor survival prognosis. A nomogram based on these risk variables provides a reliable tool for predicting the survival chances of patients with HCC.

AI-based phenotyping of hepatic fiber morphology to inform molecular alterations in metabolic dysfunction-associated steatotic liver disease

BACKGROUND AND AIMS

Hepatic fiber morphology may significantly enhance our understanding of molecular alterations in metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to comprehensively characterize hepatic fiber morphological phenotypes in MASLD and their associated molecular alterations using multilayer omics analyses.

APPROACH AND RESULTS

To quantify the morphological phenotypes of hepatic fibers, the artificial intelligence-based FibroNest algorithm (PharmaNest) was applied to 94 MASLD-affected liver biopsies, among which 12 (13%) had concurrent HCC. FibroNest identified 327 fiber phenotypes that were summarized into 8 major principal components, named FibroPC1-8. Next, molecular alterations captured by morphological fiber phenotypes were evaluated by comparison with genome-wide transcriptomics of paired liver samples. Pathway analyses revealed that FibroPCs more sensitively captured MASLD-related molecular alterations, such as upregulation of interleukin-6 and susceptibility to resmetirom, compared with the histological fibrosis stage. Among them, FibroPC4, which reflects reticular fibers, was associated with a gene signature predictive of incident HCC from MASLD. Furthermore, we used a spatial single-cell transcriptome, CosMx, to reveal the cell-cell interactions driving MASLD pathogenesis, as captured by FibroPC4. CosMx revealed that the FibroPC4-rich microenvironment contains HCC-promoting HSCs located adjacent to periportal endothelial cells. Neighboring cell analyses suggested that the HCC-promoting phenotype of HSCs was acquired by insulin growth factor-binding protein 7 secreted from senescent periportal endothelial cells. Consistently, in vitro experiments showed that insulin growth factor-binding protein 7 transformed HSCs into an HCC-promoting phenotype.

CONCLUSIONS

Hepatic morphological fiber phenotyping can reveal the disease progression and underlying mechanisms of MASLD.

Mapping the knowledge domains of literature on hepatocellular carcinoma and liver failure: a bibliometric approach

Background

Hepatocellular carcinoma (HCC) accounts for 75-85% of primary liver cancers, with its incidence continually rising, posing a threat to socio-economic development. Currently, liver resection is the standard treatment for HCC. However, post-hepatectomy liver failure (PHLF) is a severe and formidable postoperative complication that increases patients' medical expenses and mortality risk. Additionally, liver failure can occur at any stage of HCC development, severely affecting patients' quality of life and prognosis.

Method

Using the Web of Science Core Collection, this bibliometric study analyzed English articles and reviews on HCC and liver failure from 2003 to 2023. Bibliometric tools like CiteSpace, VOSviewer, and R-studio were employed for data visualization and analysis, focusing on publication trends, citation metrics, explosive intensity, and collaborative networks. Use the Comparative Toxicogenomics and Genecards databases to screen for genes related to liver failure, and perform enrichment analyses using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PubMed on the identified differentially expressed genes.

Results

The study identified a significant increase in publications on HCC and liver failure, with key contributions from journals such as the World Journal of Gastroenterology and the Journal of Hepatology. The United States, China, and Japan were the leading countries in research output. Prominent authors and institutions, including Kudo Masatoshi and Sun Yat-sen University, were identified. Enrichment analysis showed drug metabolism, oxidative stress, lipid metabolism, and other pathways are closely related to this field. Research hotspots included risk prediction models and novel therapies.

Conclusion

This bibliometric analysis highlights the growing research interest and advancements in HCC and liver failure. Future research should focus on improving risk prediction, developing new therapies, and enhancing international collaboration to address these critical health issues.

Assessing the effect of modifiable risk factors on hepatocellular carcinoma: evidence from a bidirectional Mendelian randomization analysis

BACKGROUND

The pathogenesis of hepatocellular carcinoma (HCC) involves a variety of environmental risk factors, some of which have yet to be fully clarified. Using the Mendelian randomization (MR) approach, this study comprehensively investigates the causal effect of genetically predicted modifiable risk factors on HCC.

METHODS

Genetic variants related to the 50 risk factors that had been identified in previous research were derived from genome-wide association studies. Summary statistics for the discovery cohort and validation cohort of HCC were sourced from the FinnGen consortium and the UK Biobank, respectively. Bidirectional MR analysis and sensitivity analysis were performed to establish causative risk factors for HCC.

RESULTS

Through the inverse variance weighted method, the results of the discovery cohort indicated that waist circumference, nonalcoholic fatty liver disease (NAFLD), alanine aminotransferase (ALT) levels, and aspartate aminotransferase (AST) levels were significantly linked to HCC occurrence risk. Furthermore, body fat percentage, glycated hemoglobin (HbA1c), obesity class 1-3, waist-to-hip ratio, iron, ferritin, transferrin saturation, and urate had suggestive associations with HCC. The validation cohort further confirmed that NAFLD and ALT levels were strongly related to HCC. Reverse MR indicated that genetic susceptibility to HCC was connected to NAFLD and transferrin saturation. Sensitivity analyses showed that most of the findings were robust.

CONCLUSION

This MR study delivers evidence of the complex causal relationship between modifiable risk factors and HCC. These findings offer new insights into potential prevention and treatment strategies for HCC.

The role of transketolase in the immunotherapy and prognosis of hepatocellular carcinoma: a multi-omics approach

Objective

To explore the role of transketolase (TKT) in the immunotherapy and prognosis of hepatocellular carcinoma (HCC).

Materials and methods

TKT expression across various cancers and its associations with tumor immunity and prognosis were analyzed using nomogram models. A multi-omics approach was employed, including bulk RNA-seq analysis, methylation profiling, single-cell analysis, and spatial transcriptomics. Experimental methods included RT-qPCR, siRNA transfection, luciferase reporter assay, and chromatin immunoprecipitation.

Results

TKT was significantly upregulated in multiple cancers and correlated with immune cell infiltration, particularly in HCC. Elevated TKT expression was associated with poor overall survival (OS) in HCC and was an independent prognostic factor (p < 0.05). Drug sensitivity analysis suggested that higher TKT expression was associated with reduced sensitivity to several chemotherapeutic agents, including sorafenib (p < 0.01). Furthermore, hypermethylation of the TKT promoter and low TKT expression were linked to improved OS in HCC (log-rank test p = 0.005). Single-cell analysis revealed that TKT was predominantly expressed in the monocyte/macrophage cluster associated with HCC, and pseudo-time series analysis highlighted TKT's role in cell differentiation within this cluster. Spatial transcriptomics confirmed the close association between TKT and macrophage distribution in HCC. Moreover, STAT3 was found to directly regulate TKT expression by binding to its promoter region.

Conclusion

Our findings suggest that TKT may play a role in tumor immunity and prognosis in HCC. Although these results provide insights into the potential involvement of TKT in immune cell infiltration and survival outcomes, further studies are required to fully elucidate its role in immunotherapy.

Rising Incidence of Early-Onset Liver Cancer and Intrahepatic Bile Duct Cancer: Analysis of the National Childhood Cancer Registry Database

Background/Objectives: Early-onset cancer is an emerging global health concern, including in the United States. However, data on early-onset liver and intrahepatic bile duct cancer remain limited. This study aims to fill this gap by analyzing trends in early-onset liver and intrahepatic bile duct cancer in the United States over the past two decades. Methods: This study used National Childhood Cancer Registry data to examine temporal trends in early-onset liver and intrahepatic bile duct cancer in the United States. The analysis involved estimating age-adjusted incidence rates of early-onset liver and intrahepatic bile duct cancer, stratified by histological type, ethnicity, and sex. Results: In 2021, the age-adjusted incidence rate of early-onset liver and intrahepatic bile duct cancer was estimated at 0.53 per 100,000 population (95% Confidence Interval [CI]: 0.48-0.59). From 2001 to 2021, the age-adjusted incidence rate showed a significant annual percent change (APC) of 1.35% (95% CI: 0.87-1.83%). When stratified by sex, the age-adjusted incidence rate in females increased significantly (APC: 3.07%, 95% CI: 2.26-3.87%) while remaining stable in males. Among racial and ethnic groups, non-Hispanic American Indian and Alaska Native (AIAN) individuals had the highest age-adjusted incidence rate, recorded at 2.67 per 100,000 population (95% CI: 0.95-5.85). By histological type, hepatic carcinoma had the highest age-adjusted incidence rate, significantly increasing over time (APC: 1.47%, 95% CI: 0.96-1.99%). In contrast, the incidence rates for hepatoblastoma and unspecified hepatic tumors remained stable between 2001 and 2021. Conclusions: Our study identified an increasing incidence of early-onset liver and intrahepatic bile duct cancer in the United States, primarily driven by cases in females and hepatic carcinoma.

Paracancerous binuclear hepatocytes assessed by computer program is a novel biomarker for short term recurrence of hepatocellular carcinoma after surgery

Hepatocellular carcinoma (HCC) is notorious for its high likelihood of recurrence even after radical surgery, which calls for effective adjuvant therapy based on more precise patient selection. The decline of the abundance of binuclear hepatocytes (ABH) in paracancerous liver tissues has been reported to indicate pathological changes in liver cells, leading to short-term recurrence within 2 years. In this research, we analyzed 34 HCC patients and 22 patients underwent liver surgery for non-HCC diseases. An ImageJ script was used to assess binuclear hepatocytes in the HE-staining specimens of paracancerous liver tissues. ABH significantly decreased in HCC patients and indicated poorer outcomes. Immunohistochemistry (IHC) assays suggested ploidy-related regulation of arginase 1 (ARG1) expression. Our findings suggested computer-assisted assessment of ABH as a possible biomarker for short-term HCC recurrence.

Combined TACE with Targeted and Immunotherapy versus TACE Alone Improves DFS in HCC with MVI: A Multicenter Propensity Score Matching Study

Background

Hepatocellular carcinoma (HCC) with microvascular invasion (MVI) is associated with high recurrence and poor survival outcomes. Although adjuvant therapies such as transcatheter arterial chemoembolization (TACE), targeted therapy, and immunotherapy show potential in improving outcomes, the optimal postoperative treatment strategy remains undetermined. This study evaluates the efficacy of different adjuvant treatments on disease-free survival (DFS) and overall survival (OS) in HCC patients with MVI following curative resection.

Methods

A retrospective cohort of 409 HCC patients with MVI who underwent curative resection from three clinical centers between 2017 and 2024 was analyzed. Patients were stratified into three groups: TACE alone (n=132), TACE + targeted therapy (n=58), and TACE + targeted immunotherapy (n=68). Propensity score matching (PSM) was employed to balance confounding factors. Kaplan-Meier survival curves and Cox regression models were used to assess DFS and OS. A nomogram was constructed for individualized DFS prediction.

Results

After PSM, both the TACE + targeted therapy and TACE + targeted immunotherapy groups exhibited significantly prolonged DFS compared to TACE alone (median DFS: 16 vs 22 and 21 months, respectively; p=0.027). No significant differences were observed in OS across the groups. The nomogram for DFS demonstrated robust predictive performance, with a C-index of 0.709 and 0.645 in the training and validation cohorts, respectively, supporting its utility in clinical decision-making.

Conclusion

In HCC patients with MVI, adjuvant TACE combined with targeted therapy or targeted immunotherapy significantly enhances DFS, though no OS benefit was observed. The developed nomogram provides a reliable tool for risk stratification and personalized postoperative management in this high-risk patient population.

Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study

BACKGROUND

The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection.

METHODS

We retrospectively collected clinical data from patients with HCC and CHB treated at the Fourth Affiliated Hospital of Guangxi Medical University from January 2022 to December 2022, including demographics, comorbidities, and laboratory parameters. The datasets were randomly divided into a training set (361 cases) and a validation set (155 cases) in a 7:3 ratio. Variables were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and multifactor logistic regression. The prediction model of HCC risk in CHB patients was constructed based on five machine learning models, including logistic regression (LR), K-nearest neighbour (KNN), support vector machine (SVM), random forest (RF) and artificial neural network (ANN). Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the predictive performance of the model in terms of identification, calibration and clinical application. The SHapley Additive exPlanation (SHAP) method was used to rank the importance of the features and explain the final model.

RESULTS

Among the five ML models constructed, the RF model has the best performance, and the RF model predicts the risk of HCC in patients with CHB in the training set [AUC: 0.996, 95% confidence interval (CI) (0.991-0.999)] and internal validation set [AUC: 0.993, 95% CI (0.986-1.000)]. It has high AUC, specificity, sensitivity, F1 score and low Brier score. Calibration showed good agreement between observed and predicted risks. The model yielded higher positive net benefits in DCA than when all participants were considered to be at high or low risk, indicating good clinical utility. In addition, the SHAP plot of the RF showed that age, basophil/lymphocyte ratio (BLR), D-Dimer, aspartate aminotransferase/alanine aminotransferase (AST/ALT), γ-glutamyltransferase (GGT) and alpha-fetoprotein (AFP) can help identify patients with CHB who are at high or low risk of developing HCC.

CONCLUSION

ML models can be used as a tool to predict the risk of HCC in patients with CHB. The RF model has the best predictive performance and helps clinicians to identify high-risk patients and intervene early to reduce or delay the occurrence of HCC. However, the model needs to be further improved through large sample studies.

Des-γ-carboxy Prothrombin in hepatocellular carcinoma post-operative recurrence risk evaluation

BACKGROUND

While the value of Des-γ-carboxy prothrombin in hepatocellular carcinoma diagnosis has been widely acknowledged, whether or how Des-γ-carboxy prothrombin could be used in recurrence evaluation remains largely unexplored.

METHODS

We performed a multicenter retrospective analysis including an Exploration Cohort (1074 patients, 5133 Des-γ-carboxy prothrombin measurements) and a Validation Cohort (263 patients, 612 Des-γ-carboxy prothrombin measurements) to investigate whether Des-γ-carboxy prothrombin could evaluate patients' prognosis. We introduced the Des-γ-carboxy prothrombin dynamic rate as a normalized quantitative measurement of Des-γ-carboxy prothrombin dynamic change. Des-γ-carboxy prothrombin dynamic rates were further applied in a high-risk liver cirrhosis patient cohort (PreCar Cohort, 542 liver cirrhosis patients, 2023 Des-γ-carboxy prothrombin measurements).

RESULTS

Here, we show a post-operative decrease of Des-γ-carboxy prothrombin in the Exploration Cohort, making the Des-γ-carboxy prothrombin threshold in diagnosis unsuitable for prognosis, while Des-γ-carboxy prothrombin dynamic rates significantly associate with recurrence risk. Categorizing patients based on Des-γ-carboxy prothrombin dynamic rates and final concentrations shows that patients negative for both exhibit the best median recurrence-free survival and patients positive for both show the worst median recurrence-free survival. Patients with consistently positive status have a significantly lower median recurrence-free survival compared to those whose status reverted to negative. These findings are validated in the Validation Cohort. Furthermore, the Des-γ-carboxy prothrombin dynamic rates in the PreCar Cohort can identify an additional 28% of cirrhosis patients progressing to hepatocellular carcinoma.

CONCLUSIONS

These results expand on the clinical utilization of the hepatocellular carcinoma diagnosis biomarker, Des-γ-carboxy prothrombin, by proposing a quantification measurement of Des-γ-carboxy prothrombin dynamics to monitor hepatocellular carcinoma recurrence. This measurement is not limited in prognosis but can also improve the sensitivity of early hepatocellular carcinoma screening.

Red Meat, Poultry, and Fish Consumption and the Risk of Liver Cancer: A Prospective Cohort Study of 0.5 Million Chinese Adults

BACKGROUND

Epidemiological evidence on meat consumption and liver cancer risk is limited and inconclusive; moreover, no prospective study has been conducted to investigate this association in China. Hence, we performed this study to examine the association of red meat, poultry, and fish consumption with the risk of liver cancer in a Chinese population.

METHODS

A total of 510,048 Chinese adults of ages 30 to 79 years were included and were followed up through December 31, 2016. Red meat, poultry, and fish consumption was evaluated using an interviewer-administered laptop-based questionnaire. HRs and 95% confidence intervals (CI) for liver cancer incidence were calculated using Cox regression.

RESULTS

Over a mean follow-up of 9.94 years, 1,906 liver cancer cases were observed. Each 50 g/day increase in red meat (HR 0.72; 95% CI, 0.49-1.05), poultry (HR 0.93; 95% CI, 0.83-1.03), and fish (HR 0.95; 95% CI, 0.85-1.05) consumption was not associated with the risk of liver cancer in the whole study population; however, subgroup analysis revealed an inverse association with poultry consumption in rural residents but not in urban residents (Pinteraction = 0.046). The initial associations did not change materially in a series of sensitivity analyses.

CONCLUSIONS

Red meat and fish consumption is not associated with the risk of liver cancer in this Chinese population. The inverse association with poultry consumption in Chinese rural residents should be interpreted with caution.

IMPACT

This is the first prospective study examining the association between meat consumption and the risk of liver cancer in the Chinese population.

Loss of AXIN1 regulates response to lenvatinib through a WNT/KDM5B/p15 signalling axis in hepatocellular carcinoma

BACKGROUND AND PURPOSE

As a highly heterogeneous cancer, hepatocellular carcinoma (HCC) shows different response rates to the multi-kinase inhibitor lenvatinib. Thus, it is important to explore genetic biomarkers for precision lenvatinib therapy in HCC.

EXPERIMENTAL APPROACH

The effect and mechanism of AXIN1 mutation on HCC were revealed by cell proliferation assay, long-term clone formation assay, sphere formation assay and small molecule inhibitor library screening. A new therapeutic strategy targeting HCC with AXIN1 mutation was evaluated in humanized models (patient-derived xenograft [PDX] and patient-derived organoid [PDO]).

KEY RESULTS

Based on The Cancer Genome Atlas (TCGA) data, we screened 6 most frequently lost tumour suppressor genes in HCC (TP53, ARID1A, AXIN1, CDKN2A, ARID2 and PTEN) and identified AXIN1 as the most crucial gene for lenvatinib sensitivity. Further study showed that AXIN1-knockout HCC cells had a more malignant phenotype and lower sensitivity to lenvatinib in vitro and in vivo. Mechanistically, the WNT pathway and its target gene c-Myc were activated when AXIN1 was missing, and the expression of tumour suppressor p15 was inhibited by transcription co-repressors c-Myc and Miz-1, resulting in the exacerbation of the resistant phenotype. Screening of a library of epigenetic-related enzyme inhibitors showed that a KDM5B inhibitor up-regulated p15 expression, leading to increased sensitivity to lenvatinib in vitro and in vivo.

CONCLUSION AND IMPLICATIONS

AXIN1-deficient patients have a lower response to lenvatinib, which may be associated with suppression of p15 mediated by WNT pathway activation. KDM5B inhibitors can restore p15 levels, resulting in efficient killing of resistant cells in HCC.

Phase 3 Validation of PAaM for Hepatocellular Carcinoma Risk Stratification in Cirrhosis

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) risk stratification is an urgent unmet need for cost-effective HCC screening and early detection in patients with cirrhosis to improve poor HCC prognosis.

METHODS

Molecular (prognostic liver secretome signature with α-fetoprotein) and clinical (aMAP [age, male sex, albumin-bilirubin, and platelets] score) variable-based scores were integrated into PAaM (prognostic liver secretome signature with α-fetoprotein plus age, male sex, albumin-bilirubin, and platelets), which was subsequently validated in 2 phase 3 biomarker validation studies: the statewide Texas HCC Consortium and nationwide HCC Early Detection Strategy prospective cohorts, following the prospective specimen collection, retrospective blinded evaluation design. The associations between baseline PAaM and incident HCC were assessed using Fine-Gray regression, with overall death and liver transplantation as competing events.

RESULTS

Of 2156 patients with cirrhosis in the Texas HCC Consortium, PAaM identified 404 (19%) high-risk, 903 (42%) intermediate-risk, and 849 (39%) low-risk patients with annual HCC incidence rates of 5.3%, 2.7%, and 0.6%, respectively. Compared with low-risk patients, high- and intermediate-risk groups had sub-distribution hazard ratios for incident HCC of 7.51 (95% CI, 4.42-12.8) and 4.20 (95% CI, 2.52-7.01), respectively. Of 1328 patients with cirrhosis in the HCC early detection strategy, PAaM identified 201 high-risk (15%), 540 intermediate-risk (41%), and 587 low-risk (44%) patients, with annual HCC incidence rates of 6.2%, 1.8%, and 0.8%, respectively. High- and intermediate-risk groups were associated with sub-distribution hazard ratios for incident HCC of 6.54 (95% CI, 3.85-11.1) and 1.77 (95% CI, 1.02-3.08), respectively. Subgroup analysis showed robust risk stratification across HCC etiologies, including metabolic dysfunction-associated steatotic liver disease and cured hepatitis C infection.

CONCLUSIONS

PAaM enables accurate HCC risk stratification in patients with cirrhosis from contemporary etiologies.

Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

Nanomaterials for liver cancer targeting: research progress and future prospects

The incidence and mortality rates of liver cancer in China remain elevated. Although early-stage liver cancer is amenable to surgical resection, a significant proportion of patients are diagnosed at advanced stages. Currently, in addition to surgical resection for hepatocellular carcinoma, the primary treatment modalities predominantly include chemotherapy. The widespread use of chemotherapy, which non-selectively targets both malignant and healthy cells, often results in substantial immunosuppression. Simultaneously, the accumulation of chemotherapeutic agents can readily induce drug resistance upon reaching the physiological threshold, thereby diminishing the efficacy of these treatments. Besides chemotherapy, there exist targeted therapy, immunotherapy and other therapeutic approaches. Nevertheless, the development of drug resistance remains an inevitable challenge. To address these challenges, we turn to nanomedicine, an emerging and widely utilized discipline that significantly influences medical imaging, antimicrobial strategies, drug delivery systems, and other related areas. Stable and safe nanomaterials serve as effective carriers for delivering anticancer drugs. They enhance the precision of drug targeting, improve bioavailability, and minimize damage to healthy cells. This review focuses on common nanomaterial carriers used in hepatocellular carcinoma (HCC) treatment over the past five years. The following is a summary of the three drugs: Sorafenib, Gefitinib, and lenvatinib. Each drug employs distinct nanomaterial delivery systems, which result in varying levels of bioavailability, drug release rates, and therapeutic efficacy.

Association between early job loss and prognosis among hepatocellular carcinoma survivors

BACKGROUND

Early job loss after curative treatment for hepatocellular carcinoma (HCC) is associated with significant socioeconomic and health challenges, potentially worsening patient outcomes.

AIMS

To examine the impact of early job loss on all-cause mortality among HCC survivors following curative treatment.

METHODS

We conducted a retrospective cohort study using Korean National Health Insurance Service data on 4578 HCC survivors (aged 35-54) with economic activity treated between 2009 and 2015. Primary and secondary outcomes were all-cause mortality and HCC recurrence, respectively. Early job loss was defined as a shift from insurer to dependent status. Adjusted hazard ratio (HR) and 95% confidence interval (CI) were estimated using multivariable Cox regression models, and subgroup analyses were performed. Causal mediation analysis assessed early HCC recurrence as a mediator between early job loss and all-cause mortality.

RESULTS

Among 4578 patients (median follow-up, 8.3 years), 1189 (26%) died including 989 (25%) in the job-maintained group and 200 (35%) in the early job loss group (P < .001). Early job loss was significantly associated with increased risk of all-cause mortality (adjusted HR 1.52 [95% CI 1.30-1.78]), but not with HCC recurrence (adjusted HR 1.07 [95% CI 0.91-1.25]). Subgroup analyses showed prominent association among middle-income level, non-liver cirrhosis, non-alcoholism, or surgical resection group. Early HCC recurrence plays a significant mediating role on the relationship between early job loss and all-cause mortality (mediated proportion 19%, 95% CI 5-31%).

CONCLUSIONS

Early job loss may increase risk of all-cause mortality among HCC survivors undergoing curative treatment.

Novel histone modifications and liver cancer: emerging frontiers in epigenetic regulation

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and its onset and progression are closely associated with epigenetic modifications, particularly post-translational modifications of histones (HPTMs). In recent years, advances in mass spectrometry (MS) have revealed a series of novel HPTMs, including succinylation (Ksuc), citrullination (Kcit), butyrylation (Kbhb), lactylation (Kla), crotonylation (Kcr), and 2-hydroxyisobutyrylation (Khib). These modifications not only expand the histone code but also play significant roles in key carcinogenic processes such as tumor proliferation, metastasis, and metabolic reprogramming in HCC. This review provides the first comprehensive analysis of the impact of novel HPTMs on gene expression, cellular metabolism, immune evasion, and the tumor microenvironment. It specifically focuses on their roles in promoting tumor stem cell characteristics, epithelial-mesenchymal transition (EMT), and therapeutic resistance. Additionally, the review highlights the dynamic regulation of these modifications by specific enzymes, including "writers," "readers," and "erasers."

MASH as an emerging cause of hepatocellular carcinoma: current knowledge and future perspectives

Hepatocellular carcinoma is one of the deadliest and fastest-growing cancers. Among HCC etiologies, metabolic dysfunction-associated fatty liver disease (MAFLD) has served as a major HCC driver due to its great potential for increasing cirrhosis. The obesogenic environment fosters a positive energy balance and results in a continuous rise of obesity and metabolic syndrome. However, it is difficult to understand how metabolic complications lead to the poor prognosis of liver diseases and which molecular mechanisms are underpinning MAFLD-driven HCC development. Thus, suitable preclinical models that recapitulate human etiologies are essentially required. Numerous preclinical models have been created but not many mimicked anthropometric measures and the course of disease progression shown in the patients. Here we review the literature on adipose tissues, liver-related HCC etiologies and recently discovered genetic mutation signatures found in MAFLD-driven HCC patients. We also critically review current rodent models suggested for MAFLD-driven HCC study.

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.

Unlocking the potential of Traditional Chinese Medicine (TCM): Shipi Xiaoji formula (SPXJF) as a novel ferroptosis inducer in hepatocellular carcinoma

ETHNOPHARMACOLOGICAL RELEVANCE

Hepatocellular Carcinoma (HCC) is a major health concern with limited treatment options. Traditional Chinese Medicine (TCM) offers potential therapeutic approaches for HCC, and SPXJF, a TCM formula, has shown promise in clinical observations for prolonging the survival of liver cancer patients.

AIM OF THE STUDY

To investigate the anti-tumor effects of SPXJF on HCC cells and explore its potential mechanism, focusing on ferroptosis induction.

MATERIALS AND METHODS

LC/Q-TOF-MS was used for compound identification. Cell viability assays, EdU proliferation assay, colony formation assay, wound healing assay, Transwell assay, and Western-blotting were conducted to evaluate the effects of SPXJF on HCC cell proliferation, migration, and invasion. Bioinformatics analysis and RT-PCR were employed to identify potential ferroptosis-related genes and validate the results. Ferroptosis induction was investigated using ferroptosis inhibitors, ROS and lipid peroxidation detection, and TEM. In vivo experiments using a subcutaneous xenograft tumor model confirmed the anti-tumor effects of SPXJF and its ability to induce ferroptosis in HCC.

RESULTS

SPXJF effectively inhibited the proliferation, migration, and invasion of HCC cells in vitro. The mechanism of action was found to be related to the induction of ferroptosis, as evidenced by increased intracellular Fe2+ and ROS levels, decreased GSH levels, altered mitochondrial morphology, and upregulation of ferroptosis-inducing proteins ACSL4 and LPCAT3, along with downregulation of ferroptosis-inhibiting proteins xCT and GPX4. Bioinformatics analysis and RT-PCR further identified GSTZ1, CDC25A, AURKA, NOX4, and CAPG as potential ferroptosis-related genes regulated by SPXJF. In vivo experiments confirmed the anti-tumor effects of SPXJF and its ability to induce ferroptosis in HCC.

CONCLUSIONS

SPXJF exerts anti-tumor effects on HCC cells by inducing ferroptosis, and its mechanism of action involves the regulation of ferroptosis-related genes and proteins. This study provides a theoretical basis for the clinical treatment of HCC and the development of new anti-cancer drugs, offering a valuable contribution to the field of ethnopharmacology.

Clinical Applications of Artificial Intelligence (AI) in Human Cancer: Is It Time to Update the Diagnostic and Predictive Models in Managing Hepatocellular Carcinoma (HCC)?

In recent years, novel findings have progressively and promisingly supported the potential role of Artificial intelligence (AI) in transforming the management of various neoplasms, including hepatocellular carcinoma (HCC). HCC represents the most common primary liver cancer. Alarmingly, the HCC incidence is dramatically increasing worldwide due to the simultaneous "pandemic" spreading of metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD currently constitutes the leading cause of chronic hepatic damage (steatosis and steatohepatitis), fibrosis, and liver cirrhosis, configuring a scenario where an HCC onset has been reported even in the early disease stage. On the other hand, HCC represents a serious plague, significantly burdening the outcomes of chronic hepatitis B (HBV) and hepatitis C (HCV) virus-infected patients. Despite the recent progress in the management of this cancer, the overall prognosis for advanced-stage HCC patients continues to be poor, suggesting the absolute need to develop personalized healthcare strategies further. In this "cold war", machine learning techniques and neural networks are emerging as weapons, able to identify the patterns and biomarkers that would have normally escaped human observation. Using advanced algorithms, AI can analyze large volumes of clinical data and medical images (including routinely obtained ultrasound data) with an elevated accuracy, facilitating early diagnosis, improving the performance of predictive models, and supporting the multidisciplinary (oncologist, gastroenterologist, surgeon, radiologist) team in opting for the best "tailored" individual treatment. Additionally, AI can significantly contribute to enhancing the effectiveness of metabolomics-radiomics-based models, promoting the identification of specific HCC-pathogenetic molecules as new targets for realizing novel therapeutic regimens. In the era of precision medicine, integrating AI into routine clinical practice appears as a promising frontier, opening new avenues for liver cancer research and treatment.

Association of intratumoral microbiome diversity with hepatocellular carcinoma prognosis

The evidence that intratumoral microbiomes, as a rising hallmark of cancer, have a profound impact on cancer phenotypes is increasingly compelling. However, the impact of the composition and diversity of the intratumoral microbiome on the prognosis of patients undergoing surgical resection for hepatocellular carcinoma (HCC) remains incompletely understood. In this study, we revealed a high abundance of bacteria in the neoplastic tissues. The presence of bacterial lipopolysaccharide and lipoteichoic acid was detected alongside tumor-associated immune cells. By utilizing 16S rRNA gene sequencing, we identified a specific intratumoral microbiome signature that was highly predictive of the prognosis for HCC patients who underwent surgical resection. Specifically, the presence of Intestinimonas, Brachybacterium, and Rothia were identified as independent risk factors for the overall survival of HCC patients who underwent surgical resection.IMPORTANCEAlthough some studies have shown an abundance of bacteria in hepatocellular carcinoma (HCC), there is still limited understanding of the composition and diversity of the intratumoral microbiome that is favorable or adverse to the prognosis of HCC patients. Our results indicated that a greater abundance of bacteria could be observed in the neoplastic tissues than in nonneoplastic tissues. Bacterial cell wall components largely coincided with tumor-associated immune cells. The bacteria in the long overall survival (LOS) group were associated with metabolism and cytokine‒cytokine receptor interaction pathways, while bacteria in the short overall survival (SOS) group were associated with proinflammatory and cell proliferation pathways. Notably, specific taxa could independently predict HCC prognosis. Based on these findings, intratumoral microbiomes facilitate the use of precision medicine in clinical practice.

Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments

Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune microenvironment remain unclear. Three machine learning methods, namely k nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), are utilized to identify eight key HCC cell senescence markers (HCC-CSMs). Consensus clustering revealed molecular subtypes. The single-cell analysis explored the tumor microenvironment, immune checkpoints, and immunotherapy responses. In vitro, RNA interference mediated BIRC5 knockdown, and co-culture experiments assessed its impact. Cellular senescence-related genes predicted HCC survival information better than differential expression genes (DEGs). Eight key HCC-CSMs were identified, which revealed two distinct clusters with different clinical characteristics and mutation patterns. By single-cell RNA-seq data, we investigated the immunological microenvironment and observed that increasing immune cells allow hepatocytes to regain population dominance. This phenomenon may be associated with the HCC-CSMs identified in our study. By combining bulk RNA sequencing and single-cell RNA sequencing data, we identified the key gene BIRC5 and the natural killer (NK) cells that express BIRC5 at the highest levels. BIRC5 knockdown increased NK cell proliferation but reduced function, potentially aiding tumor survival. These findings provide insights into senescence-driven HCC progression and potential therapeutic targets.

Prevention of liver cancer in the era of next-generation antivirals and obesity epidemic

Preventive interventions are expected to substantially improve the prognosis of patients with primary liver cancer, predominantly HCC and cholangiocarcinoma. HCC prevention is challenging in the face of the evolving etiological landscape, particularly the sharp increase in obesity-associated metabolic disorders, including metabolic dysfunction-associated steatotic liver disease. Next-generation anti-HCV and HBV drugs have substantially reduced, but not eliminated, the risk of HCC and have given way to new challenges in identifying at-risk patients. The recent development of new therapeutic agents and modalities has opened unprecedented opportunities to refine primary, secondary, and tertiary HCC prevention strategies. For primary prevention (before exposure to risk factors), public health policies, such as universal HBV vaccination, have had a substantial prognostic impact. Secondary prevention (after or during active exposure to risk factors) includes regular HCC screening and chemoprevention. Emerging biomarkers and imaging modalities for HCC risk stratification and detection may enable individual risk-based personalized and cost-effective HCC screening. Clinical studies have suggested the potential utility of lipid-lowering, antidiabetic/obesity, and anti-inflammatory agents for secondary prevention, and some of them are being evaluated in prospective clinical trials. Computational and experimental studies have identified potential chemopreventive strategies directed at diverse molecular, cellular, and systemic targets for etiology-specific and/or agnostic interventions. Tertiary prevention (in conjunction with curative-intent therapies for HCC) is an area of active research with the development of new immune-based neoadjuvant/adjuvant therapies. Cholangiocarcinoma prevention may advance with recent efforts to elucidate risk factors. These advances will collectively lead to substantial improvements in liver cancer mortality rates.

AURKC Promotes Clear Cell Renal Cell Carcinoma Proliferation Through Upregulation of ERp57

In recent years, aurora kinase C (AURKC) has emerged as a potential therapeutic target for cancer, having been found to induce proliferation in a variety of cancers. However, at present, its precise mechanism remains unclear. In this study, the specific role of AURKC in renal clear cell carcinoma and its mechanism was investigated. The protein expression levels of AURKC were evaluated in clear cell carcinoma and adjacent normal tissues, followed by prognostic analysis. Subsequently, cell models with knocked-down and overexpressed AURKC were constructed for in vitro cell experiments, and tumor-bearing mouse models were constructed to confirm the specific role of AURKC in vivo. AURKC was found to be highly expressed in ccRCC, which was associated with poor prognosis. In the in vitro experiments, the expression levels of CyclinD1 and proliferating cell nuclear antigen (PCNA) proteins were downregulated after AURKC knockdown, and the cell proliferation ability was found to decrease significantly. After AURKC overexpression, the levels of ERp57 protein expression increased significantly, also significantly enhancing the cell proliferation ability. In addition, AURKC was found to interact with ERp57 and exhibited a colocalization relationship. In the in vivo experiments, AURKC downregulation significantly inhibited the expression of ERp57 protein and blocked the growth of tumor tissue in tumor-bearing mice. These results suggest that the abnormal expression of AURKC in ccRCC enhances the expression of ERp57 protein, thereby promoting the proliferation of clear cell renal cell carcinoma. Thus, AURKC shows potential as a target for the treatment of ccRCC.

Tumor microenvironment targeted nano-drug delivery systems for multidrug resistant tumor therapy

In recent years, nano-drug delivery systems (Nano-DDS) that target the tumor microenvironment (TME) to overcome multidrug resistance (MDR) have become a research hotspot in the field of cancer therapy. By precisely targeting the TME and regulating its unique pathological features, such as hypoxia, weakly acidic pH, and abnormally expressed proteins, etc., these Nano-DDS enable effective delivery of therapeutic agents and reversal of MDR. This scientific research community is increasing its investment in the development of diversified systems and exploring their anti-drug resistance potential. Therefore, it is particularly important to conduct a comprehensive review of the research progress of TME-targeted Nano-DDS in recent years. After a brief introduction of TME and tumor MDR, the design principle and structure of liposomes, polymer micelles and inorganic nanocarriers are focused on, and their characteristics as TME-targeted nanocarriers are described. It also demonstrates how these systems break through the cancer MDR treatment through various targeting mechanisms, discusses their synthetic innovation, research results and resistance overcoming mechanisms. The review was concluded with deliberations on the key challenges and future outlooks of targeting TME Nano-DDS in cancer therapy.

Hepatocellular carcinoma risk scores for non-viral liver disease: A systematic review and meta-analysis

Background & Aims

Hepatocellular carcinoma (HCC) risk prediction models may provide a more personalised approach to surveillance for HCC among patients with cirrhosis. This systematic review aims to summarise the performance of HCC prediction models in patients with non-viral chronic liver disease.

Method

The study was prospectively registered with PROSPERO (ID: CRD42022370078) and reported in accordance with PRISMA guidelines. MEDLINE and Embase databases were searched using a validated search filter for prediction model studies. Two reviewers independently assessed studies for inclusion and risk of bias. Measures of model performance (discrimination and calibration) to assess the risk of HCC at specified time points were identified. A random effects meta-analysis was performed on a subset of studies that reported performance of the same model.

Results

A total of 7,854 studies were identified. After review, 14 studies with a total of 94,014 participants were included; 45% of patients had viral hepatitis, 27% ALD (alcohol-related liver disease) and 19% MASLD (metabolic dysfunction-associated steatotic liver disease). Follow-up ranged from 15.1-138 months. Only one model was developed using a competing risk approach. Age (7 models) and sex (6 models) were the most frequently included predictors. Model discrimination (AUROC or c-statistic) ranged from 0.61-0.947. Only the 'aMAP' score (age, male sex, albumin, bilirubin, and platelets) had sufficient external validation for quantitative analysis, with a pooled c-statistic of 0.81 (95% CI 0.80-0.83). Calibration was reported in only 9 of 14 studies. All studies were rated at high risk of bias.

Conclusion

Studies describing risk prediction of HCC in non-viral chronic liver disease are poorly reported, have a high risk of bias and do not account for competing risk events. Patients with ALD and MASLD are underrepresented in development and validation cohorts. These factors remain barriers to the clinical utility and uptake of HCC risk models for those with the most common liver diseases.

Impact and implications

The recent EASL policy statement emphasises the potential of risk-based surveillance to reduce both hepatocellular carcinoma (HCC)-related deaths and surveillance costs. This study addresses the gap in understanding the performance of current HCC risk models in patients with non-viral liver diseases, reflecting the epidemiological landscape of liver disease in Western countries. In our review of these models we identified several key concerns regarding reporting standards and risk of bias and confirmed that patients with alcohol-related liver disease and metabolic dysfunction-associated steatotic liver disease are underrepresented in model development and validation cohorts. Additionally, most models fail to account for the significant risk of competing events, leading to potential overestimation of true HCC risk. This study highlights these critical issues that may hinder the implementation of risk models in clinical practice and offers key recommendations for future model development studies.

Gut-liver translocation of pathogen Klebsiella pneumoniae promotes hepatocellular carcinoma in mice

Hepatocellular carcinoma (HCC) is accompanied by an altered gut microbiota but whether the latter contributes to carcinogenesis is unclear. Here we show that faecal microbiota transplantation (FMT) using stool samples from patients with HCC spontaneously initiate liver inflammation, fibrosis and dysplasia in wild-type mice, and accelerate disease progression in a mouse model of HCC. We find that HCC-FMT results in gut barrier injury and translocation of live bacteria to the liver. Metagenomic analyses and bacterial culture of liver tissues reveal enrichment of the gut pathogen Klebsiella pneumoniae in patients with HCC and mice transplanted with the HCC microbiota. Moreover, K. pneumoniae monocolonization recapitulates the effect of HCC-FMT in promoting liver inflammation and hepatocarcinogenesis. Mechanistically, K. pneumoniae surface protein PBP1B interacts with and activates TLR4 on HCC cells, leading to increased cell proliferation and activation of oncogenic signalling. Targeting gut colonization using K. oxytoca or TLR4 inhibition represses K. pneumoniae-induced HCC progression. These findings indicate a role for an altered gut microbiota in hepatocarcinogenesis.

CircSCMH1 Accelerates Sorafenib Resistance in Hepatocellular Carcinoma by Regulating HN1 Expression via miR-485-5p

Sorafenib (SOR) is the first-line chemotherapeutic therapy for hepatocellular carcinoma (HCC) treatment, but SOR resistance is a key factor affecting the therapeutic effect. Emerging studies have suggested that circular RNAs (circRNAs) play an important role in the development of drug resistance in HCC cells. This paper aimed to elucidate the potential role and molecular mechanism of circRNA Scm polycomb group protein homolog 1 (circSCMH1) in SOR-resistant HCC cells. CircSCMH1, microRNA-485-5p (miR-485-5p), and hematological and neurological expressed 1 (HN1) contents were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Cell Counting Kit-8 (CCK8) assay was adopted to detect the SOR sensitivity of cells. Cell proliferation, migration, invasion, and apoptosis were assessed using colony formation, 5-Ethynyl-2'-deoxyuridine (EdU), transwell, and flow cytometry assays. Glucose metabolism was analyzed using commercial kits. HN1, B cell lymphoma-2 (Bcl-2), and Bcl-2-associated X (Bax) protein levels were assessed using western blot. Binding between miR-485-5p and circSCMH1 or HN1 was verified using a dual-luciferase reporter. Xenograft tumor model was used to explore the function of circSCMH1 in vivo. CircSCMH1 expression and HN1 abundances were increased, but the miR-485-5p level was reduced in SOR-resistant HCC tissues and cells. Deficiency of circSCMH1 enhanced SOR sensitivity by suppressing cell proliferation, migration, invasion, and glucose metabolism and inducing cell apoptosis in SOR-resistant HCC cell lines (Huh7/SOR and Hep3B/SOR). Mechanistically, circSCMH1 sponged miR-485-5p to positively regulate HN1 expression. Importantly, circSCMH1 depletion inhibited tumor growth and increased SOR sensitivity in vivo. CircSCMH1 promoted SOR resistance in HCC cells at least partly through upregulating HN1 expression by sponging miR-485-5p. These findings elucidated a new regulatory pathway of chemo-resistance in SOR-resistant HCC cells and provided a possible circRNA-targeted therapy for HCC.

Roles of X-box binding protein 1 in liver pathogenesis

The prevalence of drug-induced liver injury (DILI) and viral liver infections presents significant challenges in modern healthcare and contributes to considerable morbidity and mortality worldwide. Concurrently, metabolic dysfunctionassociated steatotic liver disease (MASLD) has emerged as a major public health concern, reflecting the increasing rates of obesity and leading to more severe complications such as fibrosis and hepatocellular carcinoma. X-box binding protein 1 (XBP1) is a distinct transcription factor with a basic-region leucine zipper structure, whose activity is regulated by alternative splicing in response to disruptions in endoplasmic reticulum (ER) homeostasis and the unfolded protein response (UPR) activation. XBP1 interacts with a key signaling component of the highly conserved UPR and is critical in determining cell fate when responding to ER stress in liver diseases. This review aims to elucidate the emerging roles and molecular mechanisms of XBP1 in liver pathogenesis, focusing on its involvement in DILI, viral liver infections, MASLD, fibrosis/cirrhosis, and liver cancer. Understanding the multifaceted functions of XBP1 in these liver diseases offers insights into potential therapeutic strategies to restore ER homeostasis and mitigate liver damage.

Evaluating microvascular invasion in hepatitis B virus-related hepatocellular carcinoma based on contrast-enhanced computed tomography radiomics and clinicoradiological factors

BACKGROUND

Microvascular invasion (MVI) is a significant indicator of the aggressive behavior of hepatocellular carcinoma (HCC). Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI. However, no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group (M2).

AIM

To develop and validate models based on contrast-enhanced computed tomography (CECT) radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC (HBV-HCC). The ultimate goal of the study was to guide surgical decision-making.

METHODS

A total of 270 patients who underwent surgical resection were retrospectively analyzed. The cohort was divided into a training dataset (189 patients) and a validation dataset (81) with a 7:3 ratio. Radiomics features were selected using intra-class correlation coefficient analysis, Pearson or Spearman's correlation analysis, and the least absolute shrinkage and selection operator algorithm, leading to the construction of radscores from CECT images. Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2, which were subsequently incorporated into predictive models. The models' performance was evaluated using calibration, discrimination, and clinical utility analysis.

RESULTS

Independent risk factors for MVI included non-smooth tumor margins, absence of a peritumoral hypointensity ring, and a high radscore based on delayed-phase CECT images. The MVI prediction model incorporating these factors achieved an area under the curve (AUC) of 0.841 in the training dataset and 0.768 in the validation dataset. The M2 prediction model, which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase, α-fetoprotein level, enhancing capsule, and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset. Calibration and decision curve analyses confirmed the models' good fit and clinical utility.

CONCLUSION

Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoperatively predict MVI and identify M2 among patients with HBV-HCC. Further studies are needed to evaluate the practical application of these models in clinical settings.

The assessment of impaired liver function and prognosis in hepatocellular carcinoma

INTRODUCTION

The impairment of liver function strongly limits the therapeutic options for hepatocellular carcinoma (HCC), and the assessment of liver function is key to finding the appropriate therapy for patients suffering from this disease. Furthermore, preexisting liver dysfunction has a negative impact on the prognosis of patients in addition to the malignant potential of HCC. Hence, defining the optimal treatment of patients with HCC requires a comprehensive examination with liver function being a crucial part of it.

AREAS COVERED

This review will provide an overview of the currently existing methods for evaluating the liver function in patients with HCC. Assessment of liver function includes scoring systems but also functional and technical methods. In addition, the role of these tests in different treatment facilities such as liver resection, transplantation, interventional and systemic therapy is summarized.

EXPERT OPINION

A comprehensive pretherapeutic assessment of the liver function includes laboratory-based scoring systems, as well as imaging- and non-imaging-based functional tests. Combining diverse parameters can help to improve the safety and efficacy of HCC therapy particularly in patients with compromised liver function. Future research should focus on optimizing pretherapeutic assessment recommendations for each therapy.

Association of diabetes mellitus with long-term prognosis after ablation therapy for patients with hepatocellular carcinoma: A single-center cohort study

BACKGROUND

This study investigated the clinical efficacy and prognostic factors of ablative treatment in hepatocellular carcinoma (HCC) patients with and without diabetes mellitus (DM).

METHODS

Retrospective data were collected from HCC patients who underwent ablation between January 2016 and December 2019. The baseline clinicopathological characteristics and long-term outcomes, such as overall survival (OS) and recurrence-free survival (RFS), were compared between those with and without DM. Predictive factors associated with survival and recurrence were identified through univariable and multivariable Cox regression analyses.

RESULTS

Of the 3528 patients enrolled in the study, 588 (16.7%) had concurrent DM. The 1-, 3-, and 5-year RFS rates in patients with DM (73.8%, 33.7%, and 5.8%, respectively) were significantly (P < 0.001) lower than those in the non-DM patients (70.4%, 37.6%, and 18.6%, respectively). Likewise, significant differences (P < 0.001) in the 1-, 3-, and 5-year OS rates were observed between the DM (99.9%, 78.1%, and 29.1%, respectively) and non-DM (99.9%, 85.9%, and 54.3%, respectively) patients. Multivariable Cox regression analysis identified DM as an independent risk factor for OS [hazard ratio (HR), 1.982; P < 0.001] and RFS (HR, 1.175; P = 0.002).

CONCLUSION

Patients with DM exhibited a poorer oncological prognosis than those without DM following ablation for HCC. DM was identified as an independent factor influencing the prognosis of HCC patients after curative ablation. Thus, active therapies targeting DM might enhance oncological outcomes and facilitate individualized treatment decisions.

Intra- and inter-patient diversity in hepatocellular carcinoma based on phosphorylation profiles-A pilot study in a single institution

BACKGROUND

Recent studies have addressed the efficacy of targeted drugs against hepatocellular carcinoma. However, most tumors escape a single kinase inhibition; co-inhibition of additional signaling pathways re-sensitizes resistant cancer cells to targeted drugs, thus reinforcing the importance of combination therapy for drug-resistant tumors. This study aimed to clarify the phosphorylation profiles of representative cancer-related tyrosine kinases in hepatocellular carcinoma to focus on potential therapeutic targets and to investigate the possibility of expanding combination therapy options using targeted drugs.

MATERIALS AND METHODS

Patients' whole blood, hepatocellular carcinoma tissue, and adjacent hepatic tissues were obtained during surgeries from 10 patients. All patients showed negative results for hepatitis B and hepatitis C RNA and none had a history of heavy drinking. The activation of receptor tyrosine kinases (RTKs) was analyzed by using a human RTK phosphorylation antibody array.

RESULTS

Among 62 different phospho-RTKs, 26 were activated in tumor tissues, of which ACK1, Dtk, Fyn, and Lyn were positive in 9 out of 10 cases. The median concordance rates of activated tumor and serum RTKs in each patient was 50 %. There was an inter- and intra-patient diversity of phosphorylation profiles in the serum, tumor of resected specimens, and non-tumor tissue of resected specimens in the same patients.

CONCLUSION

There was an intra- and inter- patient diversity in the activation of important and representative cancer-related RTKs. Expanding on this approach will allow us to learn how to predict the best combination of targets for each patient and to prioritize those combinations for clinical testing.

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.

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma

Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti-PD-1/PD-L1 outcomes centered on the cGAS-STING pathway in HCC. We identified classical pathways highly correlated with cGAS-STING pathway and constructed transformer survival model preserving raw structure of pathways. We also developed explainable XGBoost model for predicting anti-PD-1/PD-L1 outcomes using SHAP algorithm. We trained and validated transformer survival model on pan-cancer cohort and tested it on three independent HCC cohorts. Using 0.5 as threshold across cohorts, we divided each HCC cohort into two groups and calculated P values with log-rank test. TCGA-LIHC: C-index = 0.750, P = 1.52e-11; ICGC-LIRI-JP: C-index = 0.741, P = .00138; GSE144269: C-index = 0.647, P = .0233. We trained and validated [area under the receiver operating characteristic curve (AUC) = 0.777] XGBoost model on immunotherapy datasets and tested it on GSE78220 (AUC = 0.789); we also tested XGBoost model on HCC anti-PD-L1 cohort (AUC = 0.719). Our deep learning model and XGBoost model demonstrate potential in predicting survival risks and anti-PD-1/PD-L1 outcomes in HCC. We deployed these two prediction models to the GitHub repository and provided detailed instructions for their usage: deep learning survival model, https://github.com/mlwalker123/CSP_survival_model; XGBoost immunotherapy model, https://github.com/mlwalker123/CSP_immunotherapy_model.

Combined Bone Mineral Density (BMD) and Monocyte-to-Lymphocyte Ratio (MLR) Predicts Recurrence and Prognosis in Hepatocellular Carcinoma Patients Following Liver Resection

Background

Bone mineral density (BMD) and monocyte-to-lymphocyte ratio (MLR) were recently identified as novel risk factors for patients with several malignancies. The objective of this study was to validate the role of preoperative BMD/MLR as a potential prognostic biomarker in patients with hepatocellular carcinoma (HCC) undergoing liver resection.

Methods

This investigation enrolled 442 adult patients diagnosed with HCC who underwent liver resection. The patients were classified into high- and low-BMD/MLR groups based on the median, and forward stepwise logistic regression was employed to identify independent predictors for early HCC recurrence. To mitigate the impact of confounding factors, a propensity score matching (PSM) analysis was conducted between patients in the high- and low-BMD/MLR groups. The Kaplan-Meier method was employed to assess and compare the disease-free survival (DFS) and overall survival (OS) between the two cohorts.

Results

The study categorized patients into high-BMD/MLR and low-BMD/MLR groups. Forward stepwise logistic regression analysis revealed that low BMD/MLR (P < 0.001), tumor size > 50 mm (P < 0.001), and AFP > 200 ug/L (P = 0.001) were significantly associated with the early recurrence of HCC. Moreover, the results suggested that DFS and OS were significantly shorter in the low-BMD/MLR group compared to the high-BMD/MLR group, both before and after PSM (P < 0.05).

Conclusion

Preoperative BMD/MLR held promise as a prognostic biomarker for early recurrence and prognosis in patients with HCC who underwent liver resection. Furthermore, the integration of tumor size, AFP level, and BMD/MLR demonstrated a robust predictive capacity for early recurrence within this patient population.

The impact of tumor burden score on prognosis in patients after radical resection of hepatocellular carcinoma: a single-center retrospective study

Purpose

This study examines the relationship between tumor burden score (TBS) and survival and recurrence following radical resection of hepatocellular carcinoma through a cohort study conducted in the Guangxi population of China.

Methods

This cohort study eventually recruited 576 HCC patients undergoing radical resection of HCC in the People's Hospital of Guangxi Zhuang Autonomous Region during 2013-2022. After determining the best threshold TBS, all cases were grouped to evaluate the relationship between TBS versus overall survival (OS) and cumulative recurrence. Using X-Tile software, the best threshold TBS to judge patient prognostic outcome following radical resection of HCC was 10.77.

Results

Kaplan-Meier curve analysis revealed that patients with high TBS showed considerably decreased OS relative to the control group, accompanied by an increased recurrence rate. According to multivariate Cox proportional regression, the patients with high TBS were associated with poorer OS (HR = 2.56, 95% CI 1.64-3.99, P < 0.001) and recurrence-free survival (RFS) (HR = 1.55, 95% CI 1.02-2.35, P < 0.001).

Conclusion

In patients undergoing radical resection for HCC, higher TBS was significantly related to shorter OS and RFS.

Utility of pelvic CT in patients undergoing surveillance for hepatocellular carcinoma: A retrospective multi-institutional study

OBJECTIVE

To determine the frequency, characteristics and clinical significance of incidental pelvic findings reported on abdominopelvic CT performed for hepatocellular carcinoma (HCC) surveillance in at-risk patients.

MATERIAL AND METHODS

This two-center retrospective study received institutional review board approval with a waiver of informed consent. The radiologic reports of the CT exams performed 1/1/2010-2/28/2023 for HCC surveillance were reviewed. Exams were obtained with intravenous contrast material and included hepatic arterial and portal venous phases of the abdomen; images of the pelvis were acquired during the portal venous phase. Reported imaging findings and imaging-related recommendations either by the radiologists or the corresponding caregiver, if present, were retrospectively tabulated. The patient's medical records were reviewed to determine if there were any recommendations that were considered clinically important and culminated in any further interventions or treatments.

RESULTS

259 adults (1st center: mean age, 60 ± 11 years, 49% male and 2nd center: 56.26 ± 6.2 years, 48% male) at risk for HCC underwent 327 abdominopelvic CT exams for HCC surveillance at two centers. A total of 622 pelvic findings (mean, 2.2/ exam) were reported, including 131 bladder, 120 alimentary tract, 133 vascular, 51 gynecologic, 37 prostate, 33 lymph node, 27 inguinal, 44 peritoneal, and 46 skeletal. 52 of 622 reported findings (8.3%) were associated with actionable recommendations. 24 of the 52 actionable recommendations/clinical suggestions were implemented as follows: five complimentary imaging, ten additional laboratory tests, and nine non-imaging recommendations. Of note, only eight applied recommendations culminated in a clinical outcome, which included four urinary tract infection treatments.

CONCLUSION

Pelvic CT findings were associated with a clinical benefit to the patient in 1.3% of exams. These results suggest that pelvic imaging should be omitted from CT-based HCC surveillance.

CLINICAL RELEVANCE

Without compromising valuable information, patients undergoing HCC surveillance-CT may not require additional pelvic coverage.

An overview of risk assessment and monitoring of malignant transformation in cirrhotic nodules

Cirrhotic liver nodules can progress to hepatocellular carcinoma (HCC) through a multi-step carcinogenesis model, with dysplastic nodules being particularly high risk. Currently, monitoring the progression of non-HCC cirrhotic nodules is primarily through dynamic observation, but there is a lack of sensitive, efficient, and convenient methods. Dynamic monitoring and risk evaluation of malignant transformation are essential for timely treatment and improved patient survival rates. Routine liver biopsies are impractical for monitoring, and imaging techniques like ultrasound, computed tomography, and magnetic resonance imaging are not suitable for all patients or for accurately assessing subcentimeter nodules. Identifying serum biomarkers with high sensitivity, specificity, and stability, and developing a multi-index evaluation model, may provide a more convenient and efficient approach to monitoring pathological changes in cirrhotic nodules.

Multiomics Analysis Identifies Prognostic Signatures for Sepsis-Associated Hepatocellular Carcinoma in Emergency Medicine

Objectives

Sepsis, caused by the body's response to infection, poses a life-threatening condition and represents a significant global health challenge. Characterized by dysregulated immune response to infection, sepsis may lead to organ dysfunction and failure, ultimately resulting in high mortality rates. The liver plays a crucial role in sepsis, yet the role of differentially expressed genes in septic patients remains unclear in hepatocellular carcinoma (HCC). In this study, we aim to investigate the significance of differentially expressed genes related to sepsis in the occurrence and prognosis of tumors in HCC.

Methods

We conducted analyses by obtaining gene transcriptome data and clinical data of HCC cases from The Cancer Genome Atlas (TCGA). Furthermore, we obtained transcriptomic sequencing results of septic patients from the Gene Expression Omnibus (GEO) database, identified intersecting differentially expressed genes between the two, and performed survival analysis on the samples using LASSO and Cox regression analysis. Combining analyses of tumor mutation burden (TMB) and immune function, we further elucidated the mechanisms of sepsis-related genes in the prognosis and treatment of HCC.

Results

We established a prognostic model consisting of four sepsis-related genes: KRT20, PAEP, CCR3, and ANLN. Both the training and validation sets showed excellent outcomes in the prognosis of tumor patients, with significantly longer survival times observed in the low-risk group based on this model compared to the high-risk group. Furthermore, analyses, such as differential analysis of tumor mutation burden, immune function analysis, GO/KEGG pathway enrichment analysis, and drug sensitivity analysis, also demonstrated the potential mechanisms of action of sepsis-related genes.

Conclusions

Models constructed based on sepsis-related genes have shown excellent predictive ability in prognosis and differential analysis of drug sensitivity among tumor patients. These predictive models can enhance patient prognosis and inform the creation of early treatment protocols for sepsis, consequently aiding in the prevention of sepsis-induced HCC development through the modulation of the overall immune status. This may play a crucial role in patient management and immunotherapy, providing valuable reference for subsequent research.

Altered Metabolites in Hepatocellular Carcinoma (HCC) Paving the Road for Metabolomics Signature and Biomarkers for Early Diagnosis of HCC

Globally, hepatocellular carcinoma (HCC) is one of the most commonly encountered cancers. Because the current early diagnostic tests for HCC are not very sensitive, most cases of the disease are discovered late when it is in its terminal stage. Cellular metabolism changes during carcinogenesis to enable cancer cells to adapt to the hypoxic milieu, boost anabolic synthesis, promote survival, and evade apoptotic death signals. Omic techniques represent a breakthrough in the field of diagnostic technology. For example, Metabolomics analysis could be used to identify these metabolite alterations. Understanding the metabolic alterations linked to HCC is crucial for improving high-risk patients' surveillance and understanding the illness's biology. This review highlights the metabolic alterations linked to energy production in cancer cells, as well as the significantly altered metabolites and pathways associated with hepatocarcinogenesis, including acylcarnitines (ACs), amino acids, proteins, lipids, carbohydrates, glucose, and lactate, which reflect the anabolic and catabolic changes occurring in these cells. Additionally, it discusses the clinical implications of recent metabolomics that may serve as potential biomarkers for early diagnosis and monitoring of the progression of HCC.