Hepatocellular Carcinoma Research Articles

Innovative Deep Learning Models for Accurate Segmentation and Classification in Oncological Diagnosis Data

Accurate identification and classification of tumours are essential for effectively diagnosing and treating hepatocellular carcinoma and metastatic disease. However, the heterogeneous nature of tumours, characterized by irregular boundaries and variations in shape, size, and location, poses significant challenges for precise and automated segmentation and classification. With recent advances in artificial intelligence, deep learning has emerged as a powerful tool for medical image analysis. Although current clinical methods offer baseline performance in tumour classification, there is still considerable scope for improving diagnostic accuracy. This research proposes an innovative deep-learning framework to enhance the segmentation and classification of tumours. The approach begins by enhancing image contrast using histogram equalization and reducing noise via a median filter, regions are then accurately segmented from abdominal CT images using Mask R-CNN, a state-of-the-art model based on region-based convolutional neural networks. The segmented outputs are further processed using an Enhanced Swin Transformer to mitigate overfitting and boost classification performance. Experimental results demonstrate that the proposed model achieves superior accuracy and robustness across diverse CT image datasets, exhibiting strong performance even in noise.

Magnesium microspheres for enhanced transarterial chemoembolization therapy of hepatocellular carcinoma: From animal models to a pilot clinical study.

Transarterial chemoembolization (TACE) has been extensively used in clinic to treat unresectable hepatocellular carcinoma (HCC). Herein, magnesium microspheres (Mg MSs) were used as embolic devices to enhance lipiodol-mediated TACE. After being dispersed in lipiodol and injected into tumors, Mg MSs would continuously generate hydrogen and magnesium hydroxide, which could neutralize the acidic tumor microenvironment, restore exhausted CD8+ T cells, reverse immunosuppression, and trigger specific T cell-mediated antitumor responses, synergistically resulting in inhibited tumor growth. As demonstrated in a rabbit orthotopic liver cancer model, artery infusion of Mg MS-dispersed lipiodol offered greatly enhanced therapeutic outcome compared to lipiodol-based or polymeric-bead-based TACE. In a pilot clinical study, among 15 eligible patients with HCC, 11 patients achieved complete response and 3 patients achieved partial responses without unexpected treatment-related adverse events during the 1 to 3 months' follow-up. The objective response rate of Mg-enhanced TACE was ~93.3% in this small-scale trial, much higher than that of current TACE therapies.

Pitfalls in contrast enhanced ultrasound: lack of washout in malignant liver lesions. A scoping review.

Contrast-enhanced ultrasound (CEUS) is a reliable examination procedure to differentiate benign and malignant liver lesions, which is superior to contrast enhanced computed tomography (CECT) and equally to contrast enhanced magnetic resonance imaging (CEMRI) in large comparative studies. In this review, the data on the enhancement of malignant liver lesions in the late phase in CEUS are analyzed in detail. Hypoenhancement in the late phase on CEUS with SonoVue® is a typical feature of metastases and other malignant tumors. However, this is not guaranteed in every case. It is explicitly analyzed in the present studies which malignant lesions did not demonstrate washout in the late phase with SonoVue®. Lack of washout is known for some hepatocellular carcinomas. However, there are also a few rare exceptions described for metastases of neuroendocrine tumors. The possible causes are analyzed. While metastases and cholangiocellular carcinoma demonstrate an early marked washout, this can start very late in neuroendocrine metastases. Some predominantly well differentiated hepatocellular carcinomas in the cirrhotic liver may also show no or only very delayed and faintly washout in the late phase. Isoenhancement at the beginning of the late phase does not rule out metastases or HCC (in the cirrhotic liver). This contrast behavior is known for some HCC in the cirrhotic liver, but it is atypical, poorly reported and understood, especially in liver metastases. The present review analyzes the data on isoenhancement in the late phase of malignant liver lesions. The novel aspect is the focus on liver metastases.

Engineering exosomes for liver disease: a new insight in regenerative medicine and drug delivery.

Exosomes, nanoscale extracellular vesicles derived from endosomes, have emerged as crucial mediators of intercellular communication, significantly influencing physiological balance and disease development. Their biogenesis occurs via two different pathways-ESCRT-dependent and ESCRT-independent mechanisms-that regulate the selective packing of lipids, proteins, and nucleic acids. This review offers a mechanistic understanding of exosome production, cargo sorting, and secretion, highlighting their dynamic regulation in response to cellular stress conditions. Exosomes in the liver promote metabolic control, immunological modulation, fibrosis development, and the pathogenesis of hepatocellular carcinoma via modulating interactions among hepatocytes, Kupffer cells, and hepatic stellate cells. Furthermore, exosomes function as potential diagnostic biomarkers, with their molecular content indicative of disease conditions such as viral hepatitis, non-alcoholic fatty liver disease (NAFLD), and hepatocellular cancer. Recent advancements in exosome engineering, including targeted surface alterations, hybrid vesicle technologies, and hydrogel-based delivery methods, have shown their therapeutic promise for precision medicine. However, challenges such as heterogeneity in exosome isolation, cargo variability, off-target effects, and immunogenicity pose translational barriers. The standardization of isolation procedures, enhancement of cargo-loading tactics, and establishment of regulatory frameworks are essential for their clinical use. Overcoming these restrictions will enable exosome-based precision diagnostics and therapies, establishing them as leaders in next-generation regenerative medicine and tailored drug delivery. This study distinctly highlights the use of modified exosomes in liver disorders, integrating biogenesis mechanisms with novel treatment approaches and delivery systems.

ROLE OF EARLY ARTERIAL PHASE IMAGING IN ACCURATELY DIFFERENTIATING HEPATOCELLULAR CARCINOMA FROM DYSPLASTIC NODULES IN CIRRHOTIC PATIENTS

Objective: To determine the diagnostic accuracy of early arterial phase contrast-enhanced CT imaging in distinguishing hepatocellular carcinoma (HCC) from dysplastic nodules (DN) in cirrhotic patients. Study Design: Cross-sectional observational study conducted at a tertiary care hospital’s radiology department in Lahore. Methods: A total of 73 cirrhotic patients with focal liver lesions detected on screening were recruited using convenience sampling. Multi-phase contrast-enhanced CT scans were performed, with special focus on the early arterial phase (~30–35 seconds post-contrast injection). Imaging features assessed included lesion size, enhancement pattern, presence of washout, and stromal invasion. Lesions were categorized as HCC or DN based on imaging criteria and clinical/pathologic correlation. Chi-square analysis was used to evaluate associations between imaging features and lesion type, and diagnostic performance (sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV]) of early arterial phase imaging was calculated against the reference standard diagnosis. Results: The mean age of patients was 29±6 years, with 72.6% male. All patients had chronic liver disease (commonly hepatitis-related or alcohol-related cirrhosis). Early arterial phase CT revealed that both HCC and DN lesions predominantly showed heterogeneous enhancement (>75% of lesions). However, hallmark features distinguishing HCC from DN were identified. Arterial-phase washout was observed in 61.6% of HCCs versus only 17.8% of DNs. Similarly, stromal invasion was evident in 82.2% of HCCs compared to 23.3% of DNs. These differences were statistically significant (p < 0.001). Early arterial phase imaging correctly identified HCC with a sensitivity of 91.6% and specificity of 72.7%, while for DNs the sensitivity was 87.5% and specificity 72.7%. The PPV for HCC was 88% and NPV 80%, indicating high accuracy in confirming HCC and a reasonable ability to rule it out. Conclusion: Early arterial phase CT imaging provides high diagnostic sensitivity for HCC in cirrhotic patients and significantly aids in differentiating HCC from dysplastic nodules. Characteristic arterial-phase findings such as contrast washout and stromal invasion are much more frequent in HCC than in DN, improving confidence in non-invasive diagnosis. Incorporating an early arterial phase in routine liver imaging protocols is recommended to enhance early detection and proper characterization of HCC in at-risk cirrhotic populations.

Single Nucleotide Polymorphisms in TGF-β1 and Their Association with HCC Development in HCV Patients

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, with chronic hepatitis C virus (HCV) infection serving as a principal risk factor. Genetic polymorphisms in cytokine genes such as transforming growth factor beta 1 (TGF-β1) may modulate susceptibility to HCC by influencing the hepatic microenvironment and carcinogenic progression. Objective: To investigate the association between the TGF-β1 -509 C/T promoter polymorphism and the risk of HCC among chronic HCV patients in a Pakistani population. Methods: This comparative study enrolled 80 adult patients from Sheikh Zayed Hospital, Lahore, including 40 with chronic HCV infection without HCC and 40 with HCC secondary to chronic HCV. Genomic DNA was extracted from whole blood samples and genotyped for TGF-β1 -509 C/T using PCR-RFLP. Demographic, clinical, and laboratory data were collected, and genotype distributions were compared between groups. Statistical analyses included chi-square testing, odds ratio calculation, and logistic regression to assess associations and control for confounders. Results: The TT genotype and T allele of TGF-β1 -509 were more frequent in HCC patients compared to those with HCV alone. The TT genotype was associated with an increased, but not statistically significant, risk of HCC (OR 2.51; 95% CI 0.79–8.03; p=0.120). Clinical parameters such as tumor size and serum AFP were higher in TT and CT carriers, suggesting a trend toward more aggressive disease. Conclusion: While the TGF-β1 -509 TT genotype and T allele showed higher prevalence and risk estimates in HCC patients with chronic HCV, statistical significance was not reached. These findings suggest a possible genetic contribution to HCC susceptibility in this population, meriting further investigation in larger cohorts.

Stratification of Hepatocellular Carcinoma Using N6-Methyladenosine

Background: The N6-methyladenosine (m6A) modification of eukaryotic mRNA is the most prevalent of such epigenetic modifications and has recently been identified as a potential player in the pathogenesis and progression of hepatocellular carcinoma (HCC). With the increasing emergence of immunotherapy in the treatment of HCC, we have evaluated the potential of m6A-related genes in predicting overall survival and the therapeutic efficacy of immunotherapy in HCC patients. Methods: We employed transcriptomic data from TCGA-LIHC and GSE76427, comprising a total of 485 HCC patients, as the training set. Based on 23 recognized m6A regulators, we performed clustering analysis on HCC patients. The intersecting differentially expressed genes (DEGs) among subtypes were used in least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression analyses to construct the risk model. For the quantification of a risk model of HCC patients, a risk score was developed and correlated with clinical and immunological parameters. Furthermore, a single-cell transcriptomic atlas was used to analyze the relationship between model genes and immune cell subpopulations. Mechanistic studies included in vitro assays to validate the association between the m6A-related gene ANLN and the progression of HCC. Results: Internal (TCGA and GEO) and external validation (ICGC) suggested that an 8-gene risk score provides an accurate and stable prognostic assessment for HCC. Furthermore, the high-risk score, characterized by elevated TP53 mutation frequency, tumor mutation burden (TMB), and tumor stem cell characteristics indicated a poor prognosis. The prognostic signature was associated with immune cell infiltration in HCC. Those patients with a high-risk score had lower immune tolerance with a better prediction of the efficacy of immunotherapy. The risk model helps to assess and predict the response and prognosis of HCC patients to immune checkpoint inhibitors (ICIs). Additionally, single-cell RNA sequencing data revealed that the high-risk group had a higher proportion of T cells and fewer immunosuppressive T cells, potentially correlating with a better response to immunotherapy. Finally, in vitro experiments showed that ANLN, an m6A-related gene, promoted the proliferation and migration of HCC cells. Conclusions: In this study, we identified and validated an m6A gene signature consisting of eight genes that can be used to predict prognosis and immunotherapy efficacy in HCC patients.

Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent malignancy influenced by the interplay between the immune system and tumor progression, but the detailed biological mechanism still elusive. To address this, we integrate single-cell RNA sequencing (scRNAseq) data with bulk sequencing data to investigate the prognostic significance of tumor-associated macrophages (TAMs) signatures in HCC. Utilizing bioinformatics approaches, including differential gene expression analysis, Cox regression, and logistic regression modeling, we constructed a robust prognostic model that effectively stratifies HCC patients into distinct risk groups with significant differences in survival outcomes. Applying our model to multiple HCC cohorts, robust predictive and prognostic performances were observed. Moreover, examination of the tumor microenvironment (TME) revealed distinct patterns of immune cell infiltration between high-risk and low-risk patient groups, which may contribute to the poorer outcomes observed in high-risk patients. Finally, drug sensitivity and AutoDock simulations suggest that the signature genes we identified could be potential targets for HCC therapy. In summary, this study provides novel insights into the HCC tumor microenvironment and its interaction with TAMs, offering a prognostic model with potential for improving patient stratification and guiding the development of novel therapeutic approaches. Future research ought to concentrate on confirming our findings in larger, prospective studies and examining the functional implications of TAMs in HCC progression.

DCAF13 Regulates Cell Proliferation and Immune Escape of Hepatocellular Carcinoma Through Activating the NF-κB Pathway.

Hepatocellular carcinoma (HCC), the third leading cause of global cancer deaths, has a high unmet clinical need due to limited therapeutic efficacy. Immune escape mechanisms in the tumor microenvironment further complicate treatment. Advances in bioinformatics and machine learning offer potential for identifying novel biomarkers and therapeutic targets. This study aimed to identify immune-related prognostic biomarkers for HCC using integrative bioinformatics and machine learning, and validate their functional roles in tumor progression and immune escape. mRNA data from TCGA and GEO databases were analyzed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and three machine learning models (Random Forest, Boruta, XGBoost) were applied to screen key genes. Candidate genes were validated using qRT-PCR, Western blot, and functional assays (CCK8, colony formation, LDH, flow cytometry) in HCC tissues and cell lines. Immune correlations were assessed via CIBERSORT, and TNF-α/NF-κB pathway involvement was investigated. Total 26 genes were screened as HCC biomarkers through machine learning analysis. DCAF13 emerging as an independent prognostic factor. It was overexpressed in HCC tissues and cells, correlating with poor survival. Sh-DCAF13 suppressed proliferation, reduced PD-L1 expression, enhanced CD8 + T cell cytotoxicity, and decreased T cell apoptosis, inhibiting immune escape. TNF-α overexpression reversed these effects by restoring NF-κB activation. DCAF13 is a promising therapeutic target for HCC. Its role in modulating immune escape via the NF-κB pathway highlights potential strategies for personalized immunotherapy. Integrating machine learning with experimental validation provides a robust framework for biomarker discovery in oncology.

Interactions between tumor microenvironment and resistance to transarterial and systemic treatments for HCC

Hepatocellular carcinoma (HCC) is a malignant tumor originating from hepatocytes, often developing against a backdrop of chronic inflammation and liver fibrosis. The primary risk factor for HCC is cirrhosis, and early detection is crucial for improving outcomes. Despite advances in treatment, the prognosis remains poor, with a 5-year survival rate of approximately 15%-38%. Growing evidence highlights the critical role of the tumor microenvironment (TME) in modulating tumor initiation, growth, progression, and, in some cases, suppression. The TME is a complex ecosystem composed of immune cells, cancer-associated fibroblasts, extracellular matrix components, and other factors such as growth factors and cytokines. By shaping tumor cell behavior, the TME facilitates immune evasion and contributes to resistance to treatment. Tumor-associated immune cells, including regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages, contribute to immune suppression and progression. On the other hand, immune activation via immune checkpoint inhibition has shown promise in improving outcomes, especially when combined with other treatments such as transarterial chemoembolization (TACE), selective internal radiation therapy (SIRT), and systemic therapies. Studies have demonstrated the potential of targeting the TME to enhance treatment efficacy, with immune modulation emerging as a key therapeutic strategy. This review explores the complex interactions within the TME in HCC, highlighting its role in therapy resistance and immune evasion. It also discusses current therapeutic approaches to target the TME to improve clinical outcomes in HCC patients.

Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is the sixth most common malignancy globally and remains one of the leading causes of cancer-related mortality. Its incidence continues to rise worldwide, and it is currently the fastest-growing cancer by incidence in the United States. HCC most often arises in the context of chronic liver disease, particularly cirrhosis. While chronic viral hepatitis (hepatitis B and C) has traditionally been the primary etiologic factor, recent advances in antiviral therapies and prevention strategies have shifted the epidemiological landscape. Metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-related liver disease are increasingly prominent risk factors, especially in Western populations. This shift underscores the need for targeted risk factor modification, improved early detection, and enhanced surveillance protocols. The management of HCC necessitates a multidisciplinary approach, incorporating locoregional therapies, surgical resection, liver transplantation, and systemic therapies for advanced-stage disease. Recent advances in systemic treatments, including immune checkpoint inhibitors and combination therapies, have transformed the therapeutic landscape. Despite these developments, significant challenges persist in optimizing treatment, identifying predictive biomarkers, and personalizing therapy. Ongoing research is focused on refining molecular classifications and advancing precision medicine strategies to improve outcomes. This review provides a comprehensive overview of the etiology, surveillance strategies, diagnostic approaches, molecular features, and current treatment modalities for HCC.

Diagnostic and Prognostic Value of Combined Detection of Serum Protein Induced by Vitamin K Absence or Antagonist-II, Alpha-Fetoprotein, and Spliced Hepatitis B Virus in Hepatitis B Virus-Induced Hepatocellular Carcinoma.

Objective: To demonstrate the diagnostic and prognostic value of combined detection of serum abnormal prothrombin II (PIVKA II), α-fetoprotein (AFP), and spliced variants of hepatitis B virus genomes (spHBV) in HBV-induced hepatocellular carcinoma (HCC). Materials and Methods: From March 2018 to May 2019, samples were collected from 125 patients with HBV-related hepatocellular carcinoma (HBV-HCC), 125 patients with pure HBV (HBV group), and 125 patients with HBV-induced cirrhosis (HBV cirrhosis group), all of whom were receiving treatment at the hospital. Serum levels of PIVKA-II, AFP, and spHBV were measured using an immunochemiluminescence detection system, a fully automated immunoassay analyzer, and a real-time quantitative polymerase chain reaction instrument, respectively. Kaplan-Meier method was applied to analyze relationship among serum PIVKA-II, AFP, spHBV, and prognosis of patients with HBV-HCC; cyclooxygenase (COX)risk regression analyzed factors affecting prognosis of patients with HBV-HCC; receiver operating characteristic (ROC)curve evaluated diagnostic and prognostic predictive efficacy of serum PIVKA-II, AFP, and spHBV alone or combined for HBV-HCC. Results: The serum concentrations of PIVKA-II, AFP, and spHBV in the HBV-HCC group were significantly higher than those in the HBV cirrhosis group and the HBV group (all p < 0.05). The HBV cirrhosis group also showed significantly higher levels compared with the HBV group (p < 0.05). Serum PIVKA-II, AFP, spHBV, tumor number, tumor-node-metastasis (TNM) stage, and extrahepatic metastasis differed markedly between dead patients and surviving patients (p < 0.05). PIVKA-II, AFP, and spHBV in patients with HBV-HCC were related to tumor number, TNM staging, and extrahepatic metastasis (p < 0.05).The 36-month survival rate of patients with high-expression PIVKA-II was inferior to patients with low expression (χ2 = 6.561, p = 0.010); the 36-month survival rate of patients with high-expression AFP was inferior to patients with low expression (χ2 = 4.789, p = 0.029); and the 36-month survival rate of patients with high-expression spHBV was inferior to patients with low expression (χ2 = 5.761, p = 0.016). Multivariate logistic regression analysis showed that high expression of PIVKA-II, AFP, spHBV in serum, multiple tumors, TNM staging of stage III-IV, and extrahepatic metastasis were all risk factors for death in patients with HBV-HCC (p < 0.05). The area under the curve (AUC) of the combination of serum PIVKA-II, AFP, and spHBV in the diagnosis for HBV-HCC was markedly higher than PIVKA-II, AFP, and spHBV alone diagnosis (p < 0.05). The AUC predicted by the combination of serum PIVKA-II, AFP, and spHBV in predicting the prognosis of patients with HBV-HCC was markedly higher than that predicted by the three factors alone (p < 0.05). Conclusions: Serum PIVKA-II, AFP, and spHBV joint detection has significant clinical value for diagnosis and prognosis of HBV-HCC.

Geographical Distance from Transplant Center and Impact on Waitlist Outcomes and Healthcare Utilization Pre-Listing.

Decompensated cirrhosis has a median survival of two years without liver transplantation (LT). This study investigates if distance from LT center affects waitlist mortality and receipt of LT. The study population was generated from the transplant database in London, Ontario, Canada. Adult patients on the waitlist for LT between January 1, 2012 and December 31, 2021, were included. Data was linked to the Institute for Clinical Evaluative Sciences (ICES) to examine clinically relevant outcomes, using ≤150km vs >150km to stratify descriptive analysis. Multivariate time-to-event analyses were conducted to evaluate the hazards of increasing distance from LT center on waitlist mortality and receipt of LT. Of the 552 patients meeting study criteria, 394 (71.4%) received LT in an overall predominantly male cohort (n=390, 70%), with a median age of 59 years (IQR 52-64) and median distance from the LT center of 110 km (IQR 59-191). There were no significant differences between patients living ≤150 km (n=362) vs >150 km (n=190) from the LT center. In terms of liver disease etiology-alcohol-related liver disease remained the most common (32.9% vs 33.2%; p=0.95) across both categories, with no difference in median MELD-Na scores between those that did and did not receive transplant(17 [IQR 9-25] vs 18 [IQR 10-27]; p=0.12). On multivariable analysis, distance to the LT center did not impact receipt of LT, waitlist mortality, or post-listing ED visits and hospitalizations. MELD-Na at listing was a significant predictor of increased waitlist mortality (HR 1.12; CI 1.09-1.16; p<0.01), while hepatocellular carcinoma (HCC) diagnosis was associated with reduced waitlist mortality (HR 0.13; CI 0.04-0.45; p <0.01). Patients further from the LT center had a higher median number of hospitalizations (2 vs 1; p=0.02) and emergency room (ED) visits (3 vs 2; p <0.01) in the year before LT listing, and significantly ED utilization within 90 days post-listing (0 [IQR 0-2] vs 0 [IQR 0-1]; p<0.05), albeit this was not consistent on multivariable analysis. Geographical distance does not significantly impact LT waitlist mortality or receipt of LT. However, differences in healthcare utilization suggest disparities may still manifest with a negative impact on patients in the pre-LT setting.

Immunophysiological comparison for induced hepatocellular carcinoma treated by alcoholic extract and nano-extract of opuntia ficus indica

Objective: This study aimed to assess the preventive effects of alcoholic and nano extracts of cactus pear fruit (Opuntia ficus-indica) pulp and peel against thioacetamide (TAA)-induced hepatic toxicity, oxidative stress, and inflammation in male albino rats. Methods: The rats used in this investigation were randomly distributed into six groups with 6 animals per group, taking into account weights as follows: Group 1: given only (NaCl % 0.9) for 14 weeks. The group2: is injected with thioacetamide (TAA) at a dosage of 200 mg/kg dissolved in distilled water and given for 14 weeks to induce Hepatic cancer. The group3: is given the alcoholic extract of prickly pear (pulp) at a dose of 100 mg/kg, after which TAA is given until the end of the experiment. The group4: given the alcoholic extract of prickly pear (peels) at a dose of 100g/kg, after which TAA is given until the end of the experiment. The group5: given extract in the nano form (pulp) (54 mg/kg), after which TAA is given until the end of the experiment. The group6: given extract in the nano form (peels) (50 mg/kg), after which TAA is given until the end of the. Results: TAA exposure markedly raised liver enzymes (ALP, AST, ALT) and total bilirubin, reduced antioxidant markers (GSH, SOD, COX), and increased malondialdehyde (MDA) and pro-inflammatory cytokines (TNF-α, IL-6, IL-1β, MCP-1) in comparison with control group. Treatment with alcoholic and nano extracts markedly increased liver function parameters, reinstated antioxidant status, and decreased oxidative damage and inflammatory cytokine levels. Conclusion: These findings suggest that prickly pear fruit extracts demonstrate significant hepatoprotective, antioxidant, and anti-inflammatory properties, potentially hindering the advancement of TAA-induced hepatocellular carcinoma.

An automated machine-learning model for prognostic risk stratification of intermediate-stage hepatocellular carcinoma after transarterial chemoembolization.

Currently, there is still a lack of noninvasive, automated, and accurate machine-learning(ML) model for prognostic risk stratification of intermediate-stage hepatocellular carcinoma(HCC) after transarterial chemoembolization(TACE) . We aimed to develop an ML model for prognostic risk stratification of intermediate-stage HCC after TACE to assist physicians in decision-making. Between April 2008 and October 2022, consecutive patients with intermediate-stage HCC undergoing initial conventional TACE(cTACE) were retrospectively enrolled from seven tertiary hospitals.A system utilizing natural language processing technology was used to extract clinical information from electronic medical records to develop the ML models.The primary outcomes were 2-year HCC-related death and cancer-related survival(CRS,defined as the interval from initial TACE to either HCC-related death or last follow-up).The ML models' performance and their comparison with various biomarkers were assessed. A total of 4,426 eligible patients were included(3906 male,520 female; median age, 54years±11[standard deviation];2,667 in the training cohort,667 in the internal test cohort,and 1,092 patients in the external test cohort).Six ML models were developed, with the XGBoost model demonstrating the best predictive performance. It achieved an AUC of 0.842 (95% CI, 0.827-0.857) in the training cohort, 0.815 (95% CI, 0.783-0.847) in the internal test cohort, and 0.798 (95% CI,0.771-0.824) in the external test cohort. Among high-risk patients stratified by the XGBoost model, those who received TACE combined with microwave ablation had significantly higher cumulative CRS rates than those treated with TACE alone. We developed a noninvasive, automated, and accurate ML model, the XGBoost model, with robust performance in prognostic risk stratification for intermediate-stage HCC following TACE.

Identification of Novel Molecular Panel as Potential Biomarkers of PAN-Gastrointestinal Cancer Screening: Bioinformatics and Experimental Analysis

PAN-gastrointestinal cancers (PAN-GI cancers), including the oral, esophageal, gastric, hepatocellular, pancreatic=, and colorectal cancers, are the leading cause of cancer-related mortality. Despite recent advances in identifying the molecular mechanisms driving these malignancies, the high incidence and recurrence of the PAN-gastrointestinal cancers and the low survival rates of patients indicate the need to introduce biomarkers for early diagnosis to improve diagnostic and therapeutic approaches. In the present study, using integrated transcriptomics, RNA-Seq and microarray data, from the TCGA and GEO databases, respectively, were combined to discover and validate a global biomarker panel for PAN-gastrointestinal cancers. In order to validate the bioinformatics data, the expression levels of genes in the molecular panel were evaluated using real-time quantitative polymerase chain reaction (qPCR) in tumor tissues of 21 patients with early diagnosis of gastric cancer and colorectal cancer (Stage I and II). By examining the transcriptomic profiles of six types of PAN-gastrointestinal cancers, a network of closely related hub genes (n = 167) with biomarker potential (p value &lt; 0.05) was identified. Also, using ROC curve analysis and the Youden index, a molecular panel consisting of AURKA, CEP55, DTL, and TTK was presented (95% confidence interval and p value &lt; 0.05), which showed exceptional sensitivity and specificity in differentiating malignant tissue from normal tissue (AUC &gt; 80%). The diagnostic efficacy of these markers was confirmed by further validation using qPCR in colorectal and gastric tumor samples (p value &lt; 0.05). In conclusion, a novel molecular signature panel including the AURKA, CEP55, DTL, and TTK genes could improve early cancer detection and diagnostic accuracy, and it may contribute to the treatment outcomes of PAN-gastrointestinal cancer patients.

ASO Author Reflections: Rethinking Recurrence Patterns After Resection of Large Hepatocellular Carcinoma: Time to Overcome the Current Staging Paradigm?

ASO Author Reflections: Rethinking Recurrence Patterns After Resection of Large Hepatocellular Carcinoma: Time to Overcome the Current Staging Paradigm?

STOX1 Isoform A Promotes Proliferation and Progression of Hepatocellular Carcinoma by Dual Mechanisms of Transcriptionally Upregulation of Cyclin B1 and Activation of ROS-Dependent PTEN/AKT1 Signaling.

Dysregulation of transcription factors is one of the most common factors for the pathogenesis of hepatocellular carcinoma (HCC). To the best of our knowledge, no study has yet investigated the clinical significance and functional role of STOX1 in HCC. Real-time PCR, Western blotting and immunohistochemistry were performed to examine the expression of STOX1-A in HCC specimens. Animal experiment invivo and functional cell assays invitro were used to investigate the tumorigenic and proliferative ability of HCC cells. Luciferase and ROS assays were depolyed to investigate the molecular mechanisms underlying the biologic role of STOX1-A in HCC. In this study, we report that STOX1 isoform A (STOX1-A) is significantly upregulated in HCC tissues, and elevated STOX1-A levels are associated with poorer overall survival and progression-free survival in HCC patients. Functional assays demonstrated that STOX1-A upregulation promotes, whereas its silencing suppresses, HCC cell proliferation and growth both invitro and invivo. Mechanistic investigations revealed a dual mechanism by which STOX1-A drives HCC progression. First, STOX1-A transcriptionally upregulates cyclin B1, promoting cell proliferation. Second, it activates the AKT1 signaling pathway through reactive oxygen species (ROS)-mediated deactivation of PTEN. Furthermore, a positive correlation between STOX1-A expression and the levels of cyclin B1 and phosphorylated AKT1 (p-AKT1 Ser473) was observed in clinical HCC samples. Our findings identify a novel dual mechanism by which STOX1-A promotes HCC proliferation and growth, offering potential avenues for the development of anti-tumor therapeutic strategies targeting STOX1-A in HCC.

Screening of Candidate Inflammatory Markers of Epithelial Cells in Hepatocellular Carcinoma Based on Integration Analysis of TCGA/ICGC Databases and Single-cell Sequencing.

Hepatocellular Carcinoma (HCC) is closely linked to inflammatory reactions, with chronic liver diseases acting as major risk factors. In the inflammatory microenvironment, repeated damage and repair of liver cells lead to genetic mutations, abnormal proliferation, and tumorigenesis. This study aimed to investigate the expression profile of specific cell clusters under inflammatory stimulation in HCC and identify potential therapeutic drugs. Comprehensive analysis of HCC transcriptome data and single-cell sequencing data from TCGA, ICGC, and GEO databases was conducted to explore the specific molecular mechanisms of epithelial cells. Virtual screening of natural compounds in the ZINC database and in vitro cell experiments were performed to identify drugs that regulate the expression of inflammatory factors in epithelial cells. Analysis of the single-cell dataset revealed cell clusters closely associated with HCC, notably Epithelial cells, Hepatocytes, MSC, and iPS cells, with Epithelial cells playing a pivotal role in HCC development. Further investigation of TCGA data unveiled 83 differentially expressed genes (DEGs) related to inflammatory responses in HCC. Intersection analysis of DEGs in epithelial cells and HCC DEGs identified 12 common DEGs, including ADRM1, ATP2B1, FZD5, GPC3, KIF1B, KLF6, LY6E, MET, NAMPT, SERPINE1, SPHK1, and SRI. Prognostic analysis revealed that CCL7, GPR132, ITGB8, PTAFR, SELL, and VIP were influential in the survival prognosis of HCC. A prognostic model based on the expression levels of these genes demonstrated an increased risk of HCC associated with higher differential expression of inflammatory response genes. Additionally, molecular dynamics simulations indicated that compounds NADH and Deferoxamine formed stable docking models with the inflammatory protein VIP, suggesting their potential as candidates for targeted therapy. Inflammatory factors CCL7, GPR132, ITGB8, PTAFR, SELL, and VIP influence the inflammatory cascade response in HCC epithelial cells, and their expression correlates with the survival prognosis of HCC patients. Interfering with VIP expression effectively suppresses proliferation, migration, and invasion of HCC cells, as well as inhibiting the occurrence of inflammatory cascade reactions, thus slowing down the progression of hepatocellular carcinoma. Furthermore, compounds NADH and Deferoxamine have the potential to target and bind to the inflammatory protein VIP, highlighting their relevance in potential HCC treatment.

PD-1/PD-L1 blockade therapy in hepatocellular carcinoma: Current status and potential biomarkers.

PD-1/PD-L1 blockade therapy in hepatocellular carcinoma: Current status and potential biomarkers.