Survival Of Hepatocellular Carcinoma Patients Research Articles

Transjugular intrahepatic portosystemic shunt for esophagogastric variceal bleeding in patients with hepatocellular carcinoma and portal vein tumor thrombus

BACKGROUND Whether hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT) and acute esophagogastric variceal bleeding (EGVB) can improve the success rate of endoscopic hemostasis and overall survival (OS) from transjugular intrahepatic portosystemic shunt (TIPS) remains controversial. AIM To compare the clinical outcomes between TIPS and standard treatment for such HCC patients. METHODS This monocenter, retrospective cohort study included patients diagnosed as HCC with PVTT and upper gastrointestinal bleeding. Patients were grouped by the treatment (TIPS or standard conservative treatment). The success rate of endoscopic hemostasis, OS, rebleeding rates, and main causes of death were analyzed. RESULTS Between July 2015 and September 2021, a total of 77 patients (29 with TIPS and 48 with standard treatment) were included. The success rate of endoscopic hemostasis was 96.6% in the TIPS group and 95.8% in the standard treatment group. All the 29 patients in TIPS group successful underwent TIPS procedure and had a better OS compared with standard treatment within the first 160 days after treatment (68 days vs 43 days, P = 0.022), but shorter OS after 160 days (298 days vs 472 days, P = 0.022). Cheng’s Classification of PVTT, total bilirubin and Child-Pugh class were independently negative associated with OS (all P < 0.05). The main causes of death were liver failure or hepatic encephalopathy (75.9%) in the TIPS group and rebleeding (68.8%) in the standard treatment. CONCLUSION TIPS could reduce the risk of early death due to rebleeding and prolong short-term survival in HCC patients with PVTT and acute EGVB, which deserves further investigation.

Circulating tumor DNA (ctDNA) as a biomarker of response to therapy in advanced Hepatocellular carcinoma treated with Nivolumab.

Circulating tumor DNA (ctDNA) is a promising non-invasive marker for detection, diagnosis, treatment selection, and prognosis of hepatocellular carcinoma (HCC). This study aimed to examine the utility of ctDNA as a prognostic and predictive tool in HCC patients treated with nivolumab. We analyzed pre-treatment ctDNA from 44 HCC patients using comprehensive genomic testing on a commercially available platform. We utilized log rank test and univariate Cox models to correlate overall survival (OS) and progression-free survival (PFS) with ctDNA expressions. Of 44patients, 77.3% were men with median age of 67years. All but 3patients had at least one alteration identified, and TP53 was the most commonly altered gene (52.3%). Median OS was 17.5months (95% CI: 12.7, NA). Mutations involving PIK3CA, BRCA1, and CCND1 amplification were associated with shorter OS (P 0.0001, 0.0001 and 0.01, respectively). Median PFS time was 4.01months (95% CI: 3.06, 9.33). Mutations involving KIT and PIK3CA were associated with shorter PFS (P 0.0001 and 0.0004, respectively), while mutation involving CTNNB1 were associated with longer PFS (p= 0.04). ctDNA profiling may provide a benefit for prediction of survival and progression of HCC patients treated with nivolumab. Future studies are needed for confirmation.

The Trend of the Treatment of Advanced Hepatocellular Carcinoma: Combination of Immunotherapy and Targeted Therapy.

Hepatocellular carcinoma (HCC) is a common type of tumor worldwide. The development of systemic treatment of advanced HCC has remained stagnant for a considerable period. During the last years, a series of new treatment regimens based on the combination of immunotherapeutic drugs and targeted drugs have been gradually developed, increased the objective response rate (ORR), overall survival (OS), and progression free survival (PFS) of HCC patients. Among the different combination therapy groups, atezolizumab plus bevacizumab and sintilimab plus IBI-305 seem to have unique advantages, while head-to-head comparisons are still needed. A comprehensive understanding of the developments, the ongoing clinical trials and the mechanisms of combination of immunotherapy and targeted therapy might lead to the development of new combination strategies and solving current challenges such as the molecular biomarkers, the clinical administration order of drugs and the second-line treatments after combination therapy.

Small HBV surface antigendrives regorafenib resistance in HCC via KIAA1429-dependent m6A modification of CCR9.

A substantial body of literature, including our own, points to a connection between hepatitis B virus (HBV) infection and the development of drug resistance in hepatocellular carcinoma (HCC), particularly against sorafenib. However, the influence of HBV on resistance to regorafenib, another therapeutic agent, has been less studied. In this study, we used the GEO database (GSE87630) and clinical samples to demonstrate that C-C motif chemokine receptor 9 (CCR9) was highly expressed in HBV-related HCC and predicted poor overall survival. Its overexpression correlated with HBsAg-positive HCC patients. Both univariate and multivariable Cox regression analysis elucidated CCR9 was an independent risk factor for poor overall survival in HCC patients. Our in vitro findings further revealed that HBV structural proteins, small HBV surface antigen (SHBs), triggered an upregulation of CCR9. Functional assays showed that SHBs enhanced HCC cell proliferation, migration, and invasion, increased ABCB1 and ABCC1 expression, and promoted regorafenib resistance via CCR9. Intriguingly, overexpression of HBV plasmid and an AAV-HBV mouse model both exhibited a significant elevation in global N6-methyladenosine (m6A) levels. Further investigations revealed that SHBs elevated these m6A levels, upregulated CCR9 and stabilized CCR9 mRNA through KIAA1429-mediated m6A modification, with sites 1373 and 1496 on CCR9 mRNA being critical for modification. In conclusion, SHBs promoted HCC progression and regorafenib resistance via KIAA1429-mediatedm6A modification of CCR9. Our findings suggested that CCR9 could be a potential prognostic biomarker and a valuable molecular therapeutic target of regorafenib resistance in HBV-related HCC.

Integrated analysis reveals an aspartate metabolism-related gene signature for predicting the overall survival in patients with hepatocellular carcinoma.

Deregulating cellular metabolism is one of the prominent hallmarks of malignancy, with a critical role in tumor survival and growth. However, the role of reprogramming aspartate metabolism in hepatocellular carcinoma (HCC) are largely unknown. The multi-omics data of HCC patients were downloaded from public databases. Univariate and multivariate stepwise Cox regression were used to establish an aspartate metabolism-related gene signature (AMGS) in HCC. The Kaplan-Meier and receiver operating characteristic curve analyses were performed to evaluate the predictive ability for overall survival (OS) in HCC patients. Gene set enrichment analysis and immune infiltration analysis were operated to determine the potential mechanisms underlying the AMGS. Single-cell RNA sequencing (scRNA-seq) data of liver cancer stem cells were visualized by t-SNE algorithm. In vivo and in vitro experiments were implemented to investigate the biological function of CAD in HCC. In addition, a nomogram based on the AMGS and clinicopathologic characteristics was constructed by univariate and multivariate Cox regression analyses. Patients in the high-AMGS subgroup exerted advanced tumor status and poor prognosis. Mechanistically, the high-AMGS subgroup patients had significantly enhanced proliferation and stemness-related pathways, increased infiltration of regulatory T cells and upregulated expression levels of suppressive immune checkpoints in the tumor immune microenvironment. Notably, scRNA-seq data revealed CAD, one of the aspartate metabolism-related gene, is significantly upregulated in liver cancer stem cells. Silencing CAD inhibited proliferative capacity and stemness properties of HCC cells in vitro and in vivo. Finally, a novel nomogram based on the AMGS showed an accurate prediction in HCC patients. The AMGS represents a promising prognostic value for HCC patients, providing a perspective for finding novel biomarkers and therapeutic targets for HCC.

Exploration of Key Genes Combining with Immune Infiltration Level andTumor Mutational Burden in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a lethal malignancy due to its heterogeneity and aggressive behavior. Recently, somatic mutations and tumor cell interactions with the surrounding tumor immune microenvironment (TIME) have been reported to participate in HCC carcinogenesis and predict HCC progression. In this study, we aimed to investigate the association between tumor mutational burden (TMB) and TIME in HCC. Additionally, we sought to identify differentially expressed genes (DEGs) associated with HCC prognosis and progression. The expression, clinical, and mutational data were downloaded from the cancer genome atlas (TCGA) database. The immune infiltration levels and TMB levels of the HCC samples were estimated and the samples were divided into immune cluster (ICR)-1 and 2 based on immune infiltration score and high and low TMB groups based on TMB score. Thereafter, differential gene expression analysis was conducted to identify the DEGs in the ICR1/2 and high/low TMB groups, and the intersecting DEGs were selected. Thereafter, Cox regression analysis was performed on 89 significant DEGs, among which 19 were associated with prognosis. These 19 DEGs were then used to construct a prognostic model based on their expression levels and regression coefficients. Thereafter, we analyzed the DEGs in mutant and wildtype TP53 HCC samples and identified high BCL10 and TRAF3 expression in the mutant TP53 samples. BCL10 and TRAF3 expression was detected by real-time quantitative reverse transcription PCR and immunohistochemistry, and their clinical correlation, biological function, and immune infiltration levels were analyzed by chi-square analyses, Gene Set Enrichment Analysis (GSEA), and "ssGSEA", respectively. The results of our study revealed that immune infiltration level was correlated with TMB and that they synergistically predicted poor prognosis of HCC patients. DEGs enriched in immune-related pathways could serve as indicators of immunotherapy response in HCC. Among these DEGs, BCL10 and TRAF3 were highly expressed in HCC tissues, especially in the mutant TP53 group, and they co-operatively exhibited immunological function, thereby affecting HCC progression and prognosis. In this study, we identified BCL10 and TRAF3 as potential prognostic indicators in HCC patients. Additionally, we found that BCL10 and TRAF3 influence TMB and TIME in HCC patients and can be used for the development of immune-based therapies for improving the long-term survival of HCC patients.

Identifying epithelial-mesenchymal transition-related genes as prognostic biomarkers and therapeutic targets of hepatocellular carcinoma by integrated analysis of single-cell and bulk-RNA sequencing data.

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally. Patients with advanced HCC tend to have poor prognoses and shortened survival. Recently, data from bulk RNA sequencing have been employed to discover prognostic markers for various cancers. However, they fall short in precisely identifying core molecular and cellular activities within tumor cells. In our present study, we combined bulk-RNA sequencing (bulk RNA-seq) data with single-cell RNA sequencing (scRNA-seq) to develop a prognostic model for HCC. The goal of our research is to uncover new biomarkers and enhance the accuracy of HCC prognosis prediction. Integrating single-cell sequencing data with transcriptomics were used to identify epithelial-mesenchymal transition (EMT)-related genes (ERGs) implicated in HCC progression and their clinical significance was elucidated. Utilizing marker genes derived from core cells and ERGs, we constructed a prognostic model using univariate Cox analysis, exploring a multitude of algorithmic combinations, and further refining it through multivariate Cox analysis. Additionally, we conducted an in-depth investigation into the disparities in clinicopathological features, immune microenvironment composition, immune checkpoint expression, and chemotherapeutic drug sensitivity profiles between high- and low-risk patient cohorts. We developed a prognostic model predicated on the expression profiles of eight signature genes, namely HSP90AA1, CIRBP, CCR7, S100A9, ADAM17, ENG, PGF, and INPP4B, aiming at predicting overall survival (OS) outcomes. Notably, patients classified with high-risk scores exhibited a propensity towards diminished OS rates, heightened frequencies of stage III-IV disease, increased tumor mutational burden (TMB), augmented immune cell infiltration, and diminished responsiveness to immunotherapeutic interventions. This study presented a novel prognostic model for predicting the survival of HCC patients by integrating scRNA-seq and bulk RNA-seq data. The risk score emerges as a promising independent prognostic factor, showing a correlation with the immune microenvironment and clinicopathological features. It provided new clinical tools for predicting prognosis and aided future research into the pathogenesis of HCC.

Mito-LND and (E)-Akt inhibitor-IV: novel compounds inducing endoplasmic reticulum stress and ROS accumulation against hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality. Although multi-kinase inhibitors can prolong the overall survival of late-stage HCC patients, the emergence of drug resistance diminishes these benefits, ultimately resulting in treatment failure. Therefore, there is an urgent need for novel and effective drugs to impede the progression of liver cancer. This study employed a concentration gradient increment method to establish acquired sorafenib or regorafenib-resistant SNU-449 cells. Cell viability was assessed using the cell counting kit-8 assay. A library of 793 bioactive small molecules related to metabolism screened compounds targeting both parental and drug-resistant cells. The screened compounds will be added to both the HCC parental cells and the drug-resistant cells, followed by a comprehensive assessment. Intracellular adenosine triphosphate (ATP) levels were quantified using kits. Flow cytometry was applied to assess cell apoptosis and reactive oxygen species (ROS). Real-time quantitative PCR studied relative gene expression, and western blot analysis assessed protein expression changes in HCC parental and drug-resistant cells. A xenograft model in vivo evaluated Mito-LND and (E)-Akt inhibitor-IV effects on liver tumors, with hematoxylin and eosin staining for tissue structure and immunohistochemistry staining for endoplasmic reticulum stress protein expression. From the compound library, we screened out two novel compounds, Mito-LND and (E)-Akt inhibitor-IV, which could potently kill both parental cells and drug-resistant cells. Mito-LND could significantly suppress proliferation and induce apoptosis in HCC parental and drug-resistant cells by upregulating glycolytic intermediates and downregulating those of the tricarboxylic acid (TCA) cycle, thereby decreasing ATP production and increasing ROS. (E)-Akt inhibitor-IV achieved comparable results by reducing glycolytic intermediates, increasing TCA cycle intermediates, and decreasing ATP synthesis and ROS levels. Both compounds trigger apoptosis in HCC cells through the interplay of the AMPK/MAPK pathway and the endoplasmic reticulum stress response. In vivo assays also showed that these two compounds could significantly inhibit the growth of HCC cells and induce endoplasmic reticulum stress. Through high throughput screening, we identified that Mito-LND and (E)-Akt inhibitor-IV are two novel compounds against both parental and drug-resistant HCC cells, which could offer new strategies for HCC patients.

Computed tomography-based radiomics predicts the fibroblast-related gene EZH2 expression level and survival of hepatocellular carcinoma

BACKGROUND Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer. The primary treatment strategies for HCC currently include liver transplantation and surgical resection. However, these methods often yield unsatisfactory outcomes, leading to a poor prognosis for many patients. This underscores the urgent need to identify and evaluate novel therapeutic targets that can improve the prognosis and survival rate of HCC patients. AIM To construct a radiomics model that can accurately predict the EZH2 expression in HCC. METHODS Gene expression, clinical parameters, HCC-related radiomics, and fibroblast-related genes were acquired from public databases. A gene model was developed, and its clinical efficacy was assessed statistically. Drug sensitivity analysis was conducted with identified hub genes. Radiomics features were extracted and machine learning algorithms were employed to generate a radiomics model related to the hub genes. A nomogram was used to illustrate the prognostic significance of the computed Radscore and the hub genes in the context of HCC patient outcomes. RESULTS EZH2 and NRAS were independent predictors for prognosis of HCC and were utilized to construct a predictive gene model. This model demonstrated robust performance in diagnosing HCC and predicted an unfavorable prognosis. A negative correlation was observed between EZH2 expression and drug sensitivity. Elevated EZH2 expression was linked to poorer prognosis, and its diagnostic value in HCC surpassed that of the risk model. A radiomics model, developed using a logistic algorithm, also showed superior efficiency in predicting EZH2 expression. The Radscore was higher in the group with high EZH2 expression. A nomogram was constructed to visually demonstrate the significant roles of the radiomics model and EZH2 expression in predicting the overall survival of HCC patients. CONCLUSION EZH2 plays significant roles in diagnosing HCC and therapeutic efficacy. A radiomics model, developed using a logistic algorithm, efficiently predicted EZH2 expression and exhibited strong correlation with HCC prognosis.

Deep Learning-Based Prediction of Post-treatment Survival in Hepatocellular Carcinoma Patients Using Pre-treatment CT Images and Clinical Data.

The objective of this study was to develop and evaluate a model for predicting post-treatment survival in hepatocellular carcinoma (HCC) patients using their CT images and clinical information, including various treatment information. We collected pre-treatment contrast-enhanced CT images and clinical information including patient-related factors, initial treatment options, and survival status from 692 patients. The patient cohort was divided into a training cohort (n = 507), a testing cohort (n = 146), and an external CT cohort (n = 39), which included patients who underwent CT scans at other institutions. After model training using fivefold cross-validation, model validation was performed on both the testing cohort and the external CT cohort. Our cascaded model employed a 3D convolutional neural network (CNN) to extract features from CT images and derive final survival probabilities. These probabilities were obtained by concatenating previously predicted probabilities for each interval with the patient-related factors and treatment options. We utilized two consecutive fully connected layers for this process, resulting in a number of final outputs corresponding to the number of time intervals, with values representing conditional survival probabilities for each interval. Performance was assessed using the concordance index (C-index), the mean cumulative/dynamic area under the receiver operating characteristics curve (mC/D AUC), and the mean Brier score (mBS), calculated every 3months. Through an ablation study, we found that using DenseNet-121 as the backbone network and setting the prediction interval to 6months optimized the model's performance. The integration of multimodal data resulted in superior predictive capabilities compared to models using only CT images or clinical information (C index 0.824 [95% CI 0.822-0.826], mC/D AUC 0.893 [95% CI 0.891-0.895], and mBS 0.121 [95% CI 0.120-0.123] for internal test cohort; C index 0.750 [95% CI 0.747-0.753], mC/D AUC 0.819 [95% CI 0.816-0.823], and mBS 0.159 [95% CI 0.158-0.161] for external CT cohort, respectively). Our CNN-based discrete-time survival prediction model with CT images and clinical information demonstrated promising results in predicting post-treatment survival of patients with HCC.

Expression and clinical significance of NLRC5 in hepatocellular carcinoma

ABSTRACT NLRC5, the largest member of the nucleotide-binding and oligomerization domain (NOD)-like receptor (NLR) family, has been reported to participate in the regulation of immune function and is associated with chronic inflammatory diseases. However, the biological function of NLRC5 in hepatocellular carcinoma (HCC) has not been fully demonstrated. The aim of this study is to evaluate NLRC5 expression in the tumor tissues of HCC patients undergoing surgical treatment, assess its prognostic value, and explore its relationship with critical immune-related molecules within the tumor microenvironment. A total of 100 patients with hepatitis B virus-associated HCC receiving surgical treatment were enrolled in the study. Immunohistochemical results were obtained by scoring the intensity of cellular staining and the percentage of positive cells in the tissue sections. The association between NLRC5 expression levels and the main clinicopathological factors was analyzed by Chi-square test method. The prognostic values were analyzed by COX regression model and the Kaplan-Meier survival curve. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive performance of NLRC5 in postoperative patients with HCC. IHC showed that high expression of NLRC5 was observed in 67% of HCC tissue samples. Chi-square test showed that NLRC5 was a risk factor associated with tumor number, satellite nodule, and envelope invasion. Kaplan-Meier survival curves and COX survival analysis showed that high expression of NLRC5 was significantly associated with decreased overall survival (OS) in HCC patients (HR = 1.79, 95% CI 1.03–3.12, p = .041). However, univariate logistic regression analysis revealed that NLRC5 showed positive relationship with GZMB and CD8α suggesting its role in immune escape of HCC. ROC curve analysis showed that the combination of tumor number, envelope invasion, and NLRC5 expression (area under the curve = 0.824, sensitivity = 77.30%, specificity = 82.4%) can more accurately evaluate the prognosis of HCC patients compared to the combination of only tumor number and envelope invasion (area under the curve = 0.690, sensitivity = 43.9%, specificity = 94.1%).NLRC5 plays a crucial role in progression of HCC and can be considered as a potential prognostic and predictive biomarker. Targeting NLRC5 may provide an attractive therapeutic approach for HCC.

Expression of signal recognition particle 14 in hepatocellular carcinoma and its relationship with disease progression and patient survival.

To investigate the expression of signal recognition particle 14 (SRP14) in hepatocellular carcinoma (HCC) and its clinical significance. The data of SRP14 expression in HCC were obtained from bioinformatics study, and from investigation with quantitative reverse transcription polymerase chain reaction (qRT-PCR), immunohistochemical staining and Western blotting in clinical samples. The Kaplan-Meier analysis was used to determine the associations between SRP14 mRNA expression and the overall survival, progression-free survival, and disease-specific survival of HCC patients. The effect of SRP14 on the proliferation and migration of HCC cells were determined by EdU staining, MTS, Transwell and wound-healing assays. The potential mechanism for SRP14 regulating HCC was explored through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis as well as qRT-PCR. According to the data from GSE14520, TNMplot database and clinical samples, compared with paired tumor-adjacent tissues, non-paired tumor-adjacent tissues and normal tissues, the mRNA expression of SPR14 in HCC tissues was upregulated (all P<0.05). In clinical samples, compared with paired tumor-adjacent tissues, the protein expression of SPR14 in HCC tissues was increased (P<0.05). The increased mRNA expression of SRP14 was associated with good overall survival, progression-free survival, and disease-specific survival in HCC patients. SRP14 inhibited the proliferation and migration of HCC cells in vitro. According to the KEGG and GO enrichment analysis, in non-specific HCC, the genes co-expressed with SRP14 may predominantly regulate protein synthesis, processing, and transport, while in nonalcoholic fatty liver disease related HCC, the genes co-expressed with SRP14 could control multiple signaling pathways such as MAPK, cAMP, PI3K-Akt, and Wnt. Mechanistically, SRP14 up-regulated the mRNA expression of tumor suppressor gene GPRC5A inHCC cells (P<0.05). SRP14 may regulate HCC progression and influence patient prognosis.

Novel genetic variants in the NLRP3 inflammasome-related PANX1 and APP genes predict survival of patients with hepatitis B virus-related hepatocellular carcinoma.

The nod-like receptor protein 3 (NLRP3) is one of the most characterized inflammasomes involved in the pathogenesis of several cancers, including hepatocellular carcinoma (HCC). However, the effects of genetic variants in the NLRP3 inflammasome-related genes on survival of hepatitis B virus (HBV)-related HCC patients are unclear. We performed multivariable Cox proportional hazards regression analysis to evaluate associations between 299 single-nucleotide polymorphisms (SNPs) in 16 NLRP3 inflammasome-related genes and overall survival (OS) of 866 patients with HBV-related HCC. We further performed expression quantitative trait loci (eQTL) analysis using the data from the GTEx project and 1000 Genomes projects, and performed differential expression analysis using the TCGA dataset to explore possible molecular mechanisms underlying the observed associations. We found that two functional SNPs (PANX1 rs3020013 A > G and APP rs9976425 C > T) were significantly associated with HBV-related HCC OS with the adjusted hazard ratio (HR) of 0.83 [95% confidence interval (CI) = 0.73-0.95, P = 0.008], and 1.26 (95% CI = 1.02-1.55, P = 0.033), respectively. Moreover, the eQTL analysis revealed that the rs3020013 G allele was correlated with decreased mRNA expression levels of PANX1 in both normal liver tissues (P = 0.044) and whole blood (P < 0.001) in the GTEx dataset, and PANX1 mRNA expression levels were significantly higher in HCC samples and associated with a poorer survival of HCC patients. However, we did not observe such correlations for APP rs9976425. These results indicated that SNPs in the NLRP3 inflammasome-related genes may serve as potential biomarkers for HBV-related HCC survival, once replicated by additional larger studies.

Efficacy and safety of HAIC combined with tyrosine kinase inhibitors versus HAIC monotherapy for advanced hepatocellular carcinoma: a multicenter propensity score matching analysis.

This study aimed to assess the clinical efficacy and safety of the combined approach involving hepatic arterial infusion chemotherapy (HAIC) and tyrosine kinase inhibitors (TKIs) for the treatment of advanced hepatocellular carcinoma (HCC). In this multicenter retrospective study conducted from January 2020 to December 2023, we reviewed advanced HCC patients who were treated either with HAIC alone or with a combination of HAIC and TKIs. To address initial disparities between the two groups, we employed propensity score matching (PSM). Tumor response evaluation was performed following RECIST 1.1 criteria. We compared survival outcomes, including overall survival (OS), progression-free survival (PFS), and objective response rate (ORR), between the two treatment groups. Safety assessments were conducted for all patients. Following the eligibility review, 138 patients underwent combined treatment with HAIC and TKIs (HT group), while 198 patients received HAIC monotherapy (HA group) and met the inclusion criteria for enrollment in this study. After PSM, 107 patients were assigned to each group. The HT group exhibited a longer median OS (18.0 versus 8.8 months; hazard ratio [HR], 0.52, p < 0.001) compared to the HA group. Median PFS was also longer in the HT group, although without statistical significance (6.0 versus 4.7 months; HR, 0.85, p = 0.265). The HT group demonstrated a higher ORR (41.1% versus 25.2%; p = 0.020). No significant differences were observed between the two groups in the incidence of all adverse events (AEs) or grade 3/4 AEs (any grade: 81.2% for HT versus 78.8% for HA, p = 0.68; grade 3/4: 18.1% for HT versus 13.6% for HA, p = 0.29). Importantly, all AEs were manageable and acceptable. Notably, no grade 5 AEs occurred in either group. Combination therapy involving HAIC and TKIs effectively prolonged survival in advanced HCC patients. It represented a preferable alternative to HAIC monotherapy, with manageable safety.

SNHG1: Redefining the Landscape of Hepatocellular Carcinoma through Long Noncoding RNAs.

Hepatocellular carcinoma (HCC) represents a global health concern, ranking as the sixth most common malignancy worldwide and the third leading cause of cancer-related mortality. Despite advances in research, the diagnosis and prognosis of such malignancy remain challenging. Alpha-fetoprotein, the current serum biomarker used in the management of HCC, has limited sensitivity and specificity, making early detection and effective management more difficult. Thus, new management approaches in diagnosis and prognosis are needed to improve the outcome and survival of HCC patients. SNHG1 is a long noncoding RNA mainly expressed in the cell and cytoplasm of cells and is consistently upregulated in tissues and cell lines of HCC, where it acts as an important regulator of various processes: modulation of p53 activity, sponging of microRNAs with consequent upregulation of their target mRNAs, regulation of fatty acid, iron and glucose metabolism, and interaction with immune cells. The deregulation of these processes results in abnormal cell division, angiogenesis, and apoptosis, thus promoting various aspects of tumorigenesis, including proliferation, invasion, and migration of cells. Clinically, a higher expression of SNHG1 predicts poorer clinical outcomes by significantly correlating with bigger, less differentiated, and more aggressive tumors, more advanced disease stages, and lower overall survival in HCC patients. This article comprehensively summarizes the current understanding of the multifaceted roles of SNHG1 in the pathogenesis of HCC, while also highlighting its clinicopathological correlations, therefore concluding that it has potential as a biomarker in HCC diagnosis and prognosis.

Does autoimmune disease impair the survival of hepatocellular carcinoma patients undergoing liver resection? A multi-institutional observational study

BackgroundPatients with autoimmune diseases (AD) generally carry an increased risk of developing cancer. However, the effect of AD in hepatocellular carcinoma (HCC) patients receiving surgical treatment is uncertain. The present study aimed to investigate the potential influence of AD on the survival of HCC patients undergoing hepatectomies.MethodsOperated HCC patients were identified from the Chang Gung Research Database, and the survival outcomes of HCC patients with or without AD were analyzed ad compared. Cox regression model was performed to identify significant risk factors associated with disease recurrence and mortality.ResultsFrom 2002 to 2018, a total of 5532 patients underwent hepatectomy for their HCC. Among them, 229 patients were identified to have AD and 5303 were not. After excluding cases who died within 30 days of surgery, the estimated median overall survival (OS) was 43.8 months in the AD (+) group and 47.4 months in the AD (–) group (P = 0.367). The median liver-specific survival and disease-free survival (DFS) were also comparable between the two groups. After Cox regression multivariate analysis, the presence of AD did not lead to a higher risk of all-cause mortality, liver-specific mortality, or disease recurrence.ConclusionOur study demonstrated that autoimmune disease does not impair the OS and DFS of HCC patients undergoing liver resections. AD itself is not a risk factor for tumor recurrence after surgery. Patients eligible for liver resections, as a result, should be considered for surgery irrespective of the presence of AD. Further studies are mandatory to validate our findings.

Tumor response assessment in hepatocellular carcinoma treated with immunotherapy: imaging biomarkers for clinical decision-making.

To compare the performance of 1D and 3D tumor response assessment for predicting median overall survival (mOS) in patients who underwent immunotherapy for hepatocellular carcinoma (HCC). Patients with HCC who underwent immunotherapy between 2017 and 2023 and received multi-phasic contrast-enhanced MRIs pre- and post-treatment were included in this retrospective study. Tumor response was measured using 1D, RECIST 1.1, and mRECIST, and 3D, volumetric, and percentage quantitative EASL (vqEASL and %qEASL). Patients were grouped into disease control vs progression and responders vs non-responders. Kaplan-Meier curves analyzed with log-rank tests assessed the predictive value for mOS. Cox regression modeling evaluated the association of clinical baseline parameters with mOS. This study included 37 patients (mean age, 69.1 years [SD, 8.0]; 33 men). The mOS was 16.9 months. 3D vqEASL and %qEASL successfully stratified patients into disease control and progression (vqEASL: HR 0.21, CI: 0.55-0.08, p < 0.001; %qEASL: HR 0.18, CI: 0.83-0.04, p = 0.013), as well as responder and nonresponder (vqEASL: HR 0.25, CI: 0.08-0.74, p = 0.007; %qEASL: HR 0.17, CI: 0.04-0.72, p = 0.007) for predicting mOS. The 1D criteria, mRECIST stratified into disease control and progression only (HR 0.24, CI: 0.65-0.09, p = 0.002), and RECIST 1.1 showed no predictive value in either stratification. Multivariate Cox regression identified alpha-fetoprotein > 500 ng/mL as a predictor for poor mOS (p = 0.04). The 3D quantitative enhancement-based response assessment tool qEASL can predict overall survival in patients undergoing immunotherapy for HCC and could identify non-responders. Using 3D quantitative enhancement-based tumor response criteria (qEASL), radiologists' predictions of tumor response in patients undergoing immunotherapy for HCC can be further improved. MRI-based tumor response criteria predict immunotherapy survival benefits in HCC patients. 3D tumor response assessment methods surpass current evaluation criteria in predicting overall survival during HCC immunotherapy. Enhancement-based 3D tumor response criteria are robust prognosticators of survival for HCC patients on immunotherapy.

Research progresses of imaging studies on preoperative prediction of microvascular invasion of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer, accounting for approximately 90% of liver cancer cases. It currently ranks as the fifth most prevalent cancer worldwide and represents the third leading cause of cancer-related mortality. As a malignant disease with surgical resection and ablative therapy being the sole curative options available, it is disheartening that most HCC patients who undergo liver resection experience relapse within five years. Microvascular invasion (MVI), defined as the presence of micrometastatic HCC emboli within liver vessels, serves as an important histopathological feature and indicative factor for both disease-free survival and overall survival in HCC patients. Therefore, achieving accurate preoperative noninvasive prediction of MVI holds vital significance in selecting appropriate clinical treatments and improving patient prognosis. Currently, there are no universally recognized criteria for preoperative diagnosis of MVI in clinical practice. Consequently, extensive research efforts have been directed towards preoperative imaging prediction of MVI to address this problem and the relative research progresses were reviewed in this article to summarize its current limitations and future research prospects.

Serum S-adenosylhomocysteine, rather than homocysteine, is associated with hepatocellular carcinoma survival: a prospective cohort study

BackgroundEmerging evidence suggested that S-adenosylhomocysteine (SAH) may be a better serum biomarker for cardiovascular disease than homocysteine (Hcy). However, the role of SAH in hepatocellular carcinoma (HCC) prognosis remains unclear. ObjectivesWe aimed to prospectively explore the relationships between serum SAH and related metabolites [Hcy, S-adenosylmethionine (SAM)] with HCC survival, and to evaluate the effect modifications by gene polymorphisms in one-carbon metabolism key enzymes. MethodsWe included 1080 newly diagnosed patients with HCC from the Guangdong Liver Cancer Cohort. Serum SAH, Hcy, and SAM were measured utilizing high-performance liquid chromatography–tandem mass spectrometry. Gene polymorphisms in one-carbon metabolism key enzymes were identified using kompetitive allele-specific polymerase chain reaction. Primary outcomes were liver cancer-specific survival (LCSS) and overall survival (OS). Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using multivariate Cox proportional hazards models. ResultsAfter a median follow-up of 3.6 y, 601 deaths occurred, with 552 (92%) attributed to HCC. Multivariable analysis revealed that patients in the highest quartile of serum SAH concentrations were significantly associated with worse survival compared with those in the lowest quartile, with HRs of 1.58 (95% CI: 1.19, 2.10; P-trend = 0.002) for LCSS and 1.54 (95% CI: 1.18, 2.02; P-trend = 0.001) for OS. There were no significant interactions between serum SAH concentrations and genetic variants of one-carbon metabolism key enzymes. No significant associations were found between serum Hcy, SAM concentrations, and SAM/SAH ratio with LCSS or OS. ConclusionsHigher serum SAH concentrations, rather than Hcy, were independently associated with worse survival in patients with HCC, regardless of the genetic variants of one-carbon metabolism key enzymes. These findings suggest that SAH may be a novel metabolism-related prognostic biomarker for HCC.

Establishing an oxidative stress mitochondria-related prognostic model in hepatocellular carcinoma based on multi-omics characteristics and machine learning computational framework

Hepatocellular carcinoma (HCC) has high incidence and mortality rates worldwide. Damaged mitochondria are characterized by the overproduction of reactive oxygen species (ROS), which can promote cancer development. The prognostic value of the interplay between mitochondrial function and oxidative stress in HCC requires further investigation. Gene expression data of HCC samples were collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). We screened prognostic oxidative stress mitochondria-related (OSMT) genes at the bulk transcriptome level. Based on multiple machine learning algorithms, we constructed a consensus oxidative stress mitochondria-related signature (OSMTS), which contained 26 genes. In addition, we identified six of these genes as having a suitable prognostic value for OSMTS to reduce the difficulty of clinical application. Univariate and multivariate analyses verified the OSMTS as an independent prognostic factor for overall survival (OS) in HCC patients. The OSMTS-related nomogram demonstrated to be a powerful tool for the clinical diagnosis of HCC. We observed differences in biological function and immune cell infiltration in the tumor microenvironment between the high- and low-risk groups. The highest expression of the OSMTS was detected in hepatocytes at the single-cell transcriptome level. Hepatocytes in the high- and low-risk groups differed significantly in terms of biological function and intercellular communication. Moreover, at the spatial transcriptome level, high expression of OSMTS was mainly in regions enriched in hepatocytes and B cells. Potential drugs targeting specific risk subgroups were identified. Our study revealed that the OSMTS can serve as a promising tool for prognosis prediction and precise intervention in HCC patients.