Prognosis Of Hepatocellular Carcinoma Research Articles

Effect of nucleos(t)ide analogue discontinuation on the prognosis of HBeAg-negative hepatitis B virus-related hepatocellular carcinoma after hepatectomy: A propensity score matching analysis.

Although nucleos(t)ide analogues (NAs) are thought to reduce the risk of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), the effect of NA discontinuation on the prognosis of HBV-related HCC after hepatectomy is rarely reported. We aimed to investigate the potential for hepatitis B virus e antigen (HBeAg)-negative HBV-related HCC patients to discontinue NAs based on preoperative hepatitis B virus surface antigen (HBsAg) status. This historical cohort study involved 1232 NA-treated HBeAg-negative patients who underwent curative hepatectomy for HBV-related HCC from 2014 to 2019. The recurrence-free survival (RFS) and overall survival (OS) of patients discontinuing NAs before surgery were compared with those continuing NAs. Propensity score matching (PSM) was used to balance baseline characteristics. Of all enrolled patients, 839 (68.1%) patients continued NAs, and 393 (31.9%) patients discontinued NAs. Continuation of NAs was identified as an independent risk factor for RFS (HR 2.047, 95% CI 1.348-3.109, p < 0.001 before PSM and HR 2.756, 95% CI 1.537-4.942, p < 0.001 after PSM) in HBsAg-negative patients. Similarly, subgroup survival analyses showed that NA discontinuation was associated with better RFS (p = 0.029 before PSM and p < 0.001 after PSM) and comparable OS (p = 0.935 before PSM and p = 0.115 after PSM) than NA continuation in HBsAg-negative patients. The interaction between HBsAg status and continuation or discontinuation of NAs was significant (p for interaction <0.001). These findings demonstrate the potential for HBeAg-negative HBV-related HCC patients who have achieved HBsAg seroclearance to discontinue NAs under strict monitoring.

Ferritin light chain as a potential biomarker for the prognosis of liver hepatocellular carcinoma

High expression of the ferritin light chain (FTL) in cancer promotes its onset and progression and is associated with tumour evolution. However, the significance of FTL in pan-cancer progression and prognosis in humans remains unclear. Therefore, we selected various bioinformatics databases to perform a pan-cancer analysis on a public dataset. Our results showed that FTL was differentially expressed in pan-cancer tissues compared to normal tissues. High FTL expression significantly correlated with the clinicopathological characteristics of patients with liver hepatocellular carcinoma (LIHC). The subsequent validation experiments confirmed these observations. Notably, our study found for the first time that FTLs are closely associated with LIHC and that FTLs have important clinical diagnostic and prognostic value for patients with LIHC. We confirmed that FTL expression was closely associated with altered DNA cycles and immune infiltration in LIHC. In conclusion, high levels of FTL expression are associated with poor prognosis in LIHC patients and are expected to be a potential prognostic and immune marker for LIHC.

Addition of Immune Checkpoint Inhibitor Showed Better Efficacy for Infiltrative Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy and Lenvatinib: A Multicenter Retrospective Study.

The prognosis of infiltrative hepatocellular carcinoma (HCC) is dismal. Hepatic arterial infusion chemotherapy (HAIC) plus Lenvatinib (Len) and immune checkpoint inhibitor (ICI) have shown promising results for HCC. However, this three combination therapy on infiltrative HCC is unknown. In this study, we compared HAIC plus lenvatinib (Len) and programmed cell death protein-1 (PD-1) inhibitor with HAIC plus Len for infiltrative HCC. This multi-center cohort study included patients with infiltrative HCC who received HAIC combined with Len (HAIC+Len group, n = 173) or HAIC combined with Len and PD-1 inhibitor (HAIC+Len+ICI group, n = 128) as the first-line treatment from January 2019 to December 2021. To balance any intergroup differences, one-to-one propensity score matching (PSM) was applied. Overall survival (OS) and progression-free survival (PFS) were compared between the two groups. After PSM, the median OS was 14.1 ± 1.0 and 16.1 ± 1.4 months in the HAIC+Len and HAIC+Len+ICI groups, respectively. The median PFS was 4.6 ± 0.4 months in the HAIC+Len group and 7.5 ± 0.8 months in the HAIC+Len+ICI group. The HAIC+Len+ICI group showed significantly better OS (hazard ratio [HR], 0.66; 95% CI, 0.49-0.90; P = 0.008) and PFS (HR, 0.53; 95% confident index [CI], 0.40-0.70; P < 0.001) compared with the HAIC+Len group. Subgroup analysis revealed that for OS in HCC without metastasis, the addition of PD-1 inhibitor was not significant (HR, 0.68; 95% CI, 0.43-1.07; P = 0.091). No difference was observed in OS between low (2-3 cycles) and high (4-6 cycles) level of HAIC cycles (HR, 0.99; 95% CI, 0.67-1.44; P = 0.938). The HAIC+Len+ICI group had a longer PFS and OS compared with the HAIC+Len group, demonstrating an acceptable safety profile. This triple combination strategy may be an alternative treatment for infiltrative HCC management.

ADH4—a potential prognostic marker for hepatocellular carcinoma with possible immune-related implications

ObjectiveThis study aims to explore ADH4 expression in hepatocellular carcinoma (HCC), its prognostic impact, and its immune correlation to provide novel insights into HCC prognostication and treatment.MethodsHCC prognostic marker genes were rigorously selected using GEO database, Lasso regression, GEPIA, Kaplan-Meier and pROC analyses. The expression of interested markers (ADH4, DNASE1L3, RDH16, LCAT, HGFAC) in HCC and adjacent tissues was assessed by Immunohistochemistry (IHC). We observed that ADH4 exhibited low expression levels in liver cancer tissues and high expression levels in normal liver tissues. However, the remaining four genes did not manifest any statistically significant differences between hepatocellular carcinoma (HCC) tissue and adjacent non-cancerous tissue. Consequently, ADH4 became the primary focus of our research. ADH4 expression was validated by signed-rank tests and unpaired Wilcoxon rank sum tests across pan-cancer and HCC datasets. Clinical significance and associations with clinicopathological variables were determined using Kaplan-Meier, logistic regression and Cox analyses on TCGA data. The ADH4-related immune responses were explored by Spearman correlation analysis using TIMER2 data. CD68, CD4, and CD19 protein levels were confirmed by IHC in HCC and non-cancerous tissues.ResultsADH4 showed significant downregulation in various cancers, particularly in HCC. Moreover, low ADH4 expression was associated with clinicopathological variables and served as an independent prognostic marker for HCC patients. Additionally, ADH4 affects a variety of biochemical functions and may influence cancer development, prognosis, and treatment by binding to immune cells. Furthermore, at the immune level, the low expression pattern of ADH4 is TME-specific, indicating that ADH4 has the potential to be used as a target for cancer immunotherapy.ConclusionThis study highlights the diagnostic, prognostic and immunomodulatory roles of ADH4 in HCC. ADH4 could serve as a valuable biomarker for HCC diagnosis and prognosis, as well as a potential target for immunotherapeutic interventions.

Identification and Validation of a Novel Tertiary Lymphoid Structures-Related Prognostic Gene Signature in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors originating from the digestive system. Tertiary lymphoid structures (TLS), non-lymphoid tissues outside of the lymphoid organs, are closely connected to chronic inflammation and tumorigenesis. However, the detailed relationship between TLS and HCC prognosis remained unclear. In this study, we aimed to construct a TLS-related gene signature for predicting the prognosis of HCC patients. The Cancer Genome Atlas (TCGA) clinical data from 369 HCC tissues and 50 normal liver tissues were utilized to examine the differential expression of TLS-related genes. Based on least absolute shrinkage and selection operator (LASSO) Cox regression analysis, the prognostic model was constructed using the TCGA cohort and validated in the GSE14520 cohort and International Cancer Genome Consortium (ICGC) cohort. The Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were employed to validate the predictive ability of the prognostic model. Furthermore, Cox regression analysis was applied to identify whether the TLS score could be employed as an independent prognosis factor. A nomogram was developed to predict the survival probability of HCC patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for TLS-related genes. Genetic mutation analysis, the CIBERSORT algorithm, and single-sample gene set enrichment analysis (ssGSEA) were used to assess the tumor mutation landscape and immune infiltration. Finally, the role of the TLS score in HCC therapy was investigated. Six genes were included in the construction of our prognostic model (CETP, DNASE1L3, PLAC8, SKAP1, C7, and VNN2), and we validated its accuracy. Survival analysis showed that patients in the high-TLS score group had a significantly better overall survival than those in the low-TLS score group. Univariate, multivariate Cox regression analysis and the establishment of a nomogram indicated that the TLS score could independently function as a potential prognostic marker. A significant association between TLS score and immunity was revealed by an analysis of gene alterations and immune cell infiltration. In addition, two subtypes of the TLS score could accurately predict the effectiveness of sorafenib, transcatheter arterial chemoembolization (TACE), and immunotherapy in HCC patients. In this research, we conducted and validated a prognostic model associated with TLS that may be helpful for predicting clinical outcomes and treatment responsiveness for HCC patients.

Circulatory Agrin Serves as a Prognostic Indicator for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), the predominant form of liver cancer, is associated with high mortality rates both in the United States and globally. Despite current advances in immunotherapy regimens, there is a scarcity of biomarkers to guide therapy selection. Alpha-fetoprotein (AFP) and glypican-3 have been proposed as biomarkers for HCC, but they do not provide any prognostic benefit for modeling disease progression. Agrin, a secreted proteoglycan, is frequently overexpressed in HCC and plays prominent role(s) in the liver tumor microenvironment (TME) to promote hepatocarcinogenesis. Here we employed a pilot single-center retrospective investigation to assess the prognostic value of agrin in HCC. Our evidence suggests that elevated serum agrin levels are associated with poor prognosis and performance among HCC patients. Multivariate Cox regression models indicate that secreted agrin serves as a better prognostic indicator compared to AFP that is significantly correlated with other secreted biomarkers (e.g., IL6). Cumulatively, this work demonstrates a promising clinical value of agrin in the detection and prognosis of HCC.

Advances in hepatocellular carcinoma drug resistance models.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Surgery has been the major treatment method for HCC owing to HCC's poor sensitivity to radiotherapy and chemotherapy. However, its effectiveness is limited by postoperative tumour recurrence and metastasis. Systemic therapy is applied to eliminate postoperative residual tumour cells and improve the survival of patients with advanced HCC. Recently, the emergence of various novel targeted and immunotherapeutic drugs has significantly improved the prognosis of advanced HCC. However, targeted and immunological therapies may not always produce complete and long-lasting anti-tumour responses because of tumour heterogeneity and drug resistance. Traditional and patient-derived cell lines or animal models are used to investigate the drug resistance mechanisms of HCC and identify drugs that could reverse the resistance. This study comprehensively reviewed the established methods and applications of in-vivo and in-vitro HCC drug resistance models to further understand the resistance mechanisms in HCC treatment and provide a model basis for possible individualised therapy.

Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment

BackgroundHepatocellular carcinoma (HCC) is the most common type of primary liver cancer and second leading cause of cancer-related deaths worldwide. The heightened mortality associated with HCC is largely attributed to its propensity for metastasis, which cannot be achieved without remodeling or loss of the basement membrane (BM). Despite advancements in targeted therapies and immunotherapies, resistance and limited efficacy in late-stage HCC underscore the urgent need for better therapeutic options and early diagnostic biomarkers. Our study aimed to address these gaps by investigating and evaluating potential biomarkers to improve survival outcomes and treatment efficacy in patients with HCC.MethodIn this study, we collected the transcriptome sequencing, clinical, and mutation data of 424 patients with HCC from The Cancer Genome Atlas (TCGA) and 240 from the International Cancer Genome Consortium (ICGC) databases. We then constructed and validated a prognostic model based on metastasis and basement membrane-related genes (MBRGs) using univariate and multivariate Cox regression analyses. Five immune-related algorithms (CIBERSORT, QUANTISEQ, MCP counter, ssGSEA, and TIMER) were then utilized to examine the immune landscape and activity across high- and low-risk groups. We also analyzed Tumor Mutation Burden (TMB) values, Tumor Immune Dysfunction and Exclusion (TIDE) scores, mutation frequency, and immune checkpoint gene expression to evaluate immune treatment sensitivity. We analyzed integrin subunit alpha 3 (ITGA3) expression in HCC by performing single-cell RNA sequencing (scRNA-seq) analysis using the TISCH 2.0 database. Lastly, wound healing and transwell assays were conducted to elucidate the role of ITGA3 in tumor metastasis.ResultsPatients with HCC were categorized into high- and low-risk groups based on the median values, with higher risk scores indicating worse overall survival. Five immune-related algorithms revealed that the abundance of immune cells, particularly T cells, was greater in the high-risk group than in the low-risk group. The high-risk group also exhibited a higher TMB value, mutation frequency, and immune checkpoint gene expression and a lower tumor TIDE score, suggesting the potential for better immunotherapy outcomes. Additionally, scRNA-seq analysis revealed higher ITGA3 expression in tumor cells compared with normal hepatocytes. Wound healing scratch and transwell cell migration assays revealed that overexpression of the MBRG ITGA3 enhanced migration of HCC HepG2 cells.ConclusionThis study established a direct molecular correlation between metastasis and BM, encompassing clinical features, tumor microenvironment, and immune response, thereby offering valuable insights for predicting clinical outcomes and immunotherapy responses in HCC.

Immune landscape of hepatocellular carcinoma: The central role of TP53-inducible glycolysis and apoptosis regulator.

This study aims to address the substantive issue of lacking reliable prognostic biomarkers in hepatocellular carcinoma (HCC) by investigating the relationship between TP53-inducible glycolysis and apoptosis regulator (TIGAR) and HCC prognosis using The Cancer Genome Atlas database. (1) Integrated statistical analyses, including logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test, were conducted to explore the association between TIGAR expression and clinical-pathological features of HCC. (2) The Kaplan-Meier method combined with univariate and multivariate Cox regression models underscored TIGAR as a prognostic factor in HCC. (3) Gene set enrichment analysis (GSEA) revealed key pathways associated with TIGAR, while single-sample gene set enrichment analysis (ssGSEA) determined its relevance to cancer immune infiltration. (1) Elevated TIGAR expression was significantly correlated with decreased survival outcomes in HCC patients. (2) GSEA highlighted the significant link between TIGAR and humoral immunity. (3) ssGSEA revealed a positive correlation between TIGAR expression and infiltration of Th1 and Th2 cells and a negative correlation with Th17 cell infiltration. TIGAR, as a potential prognostic biomarker for HCC, holds significant value in immune infiltration. Understanding the role of TIGAR could contribute to improved prognostic predictions and personalized treatment strategies for HCC patients.

Integrating bulk-RNA and single-cell analysis reveals heterogeneous expression of cuproptosis-related sorafenib-resistant genes in hepatocellular carcinoma

Abstract Objectives Cuproptosis represents the copper-dependent novel cell death pattern. However, the effects of cuproptosis-related sorafenib-resistant genes on prognosis, treatment response, and sorafenib resistance in hepatocellular carcinoma (HCC) patients are still unclear. The present work aims to develop a cuproptosis-related signature for predicting HCC prognosis. Methods Cuproptosis-related sorafenib-resistant differentially expressed genes (CRSRDEGs) were identified by correlation analysis between cuproptosis genes and sorafenib-resistant genes using electronic databases TCGA and GEO. Besides, the cuproptosis-related sorafenib-resistant risk score model (CRSRRSM) was established through LASSO and univariate Cox regression analyses. Later, this model was adopted for analyzing HCC patient prognosis. Certain potential drugs and treatment sensitivity were also analyzed in HCC patients receiving sorafenib or transarterial chemoembolization (TACE) treatment. Results The CRSRRSM achieved excellent efficiency in predicting the prognosis and sorafenib or TACE treatment response of HCC patients. As revealed by somatic mutational analyses, CRSRRSM was associated with tumor mutational burden (TMB), especially for TP53, CSMD3, and OBSCN mutations. According to functional enrichment analysis, CRSRRSM was closely correlated with tumor-related pathways, cuproptosis-related tricarboxylic acid (TCA) cycle, and drug resistance. Notably, potential drugs such as sepantronium bromide, AZD8055, and RO-3306, the promising alternatives for treating HCC patients with sorafenib resistance, were also proposed based on CRSRRSM. Furthermore, single-cell transcriptomic analysis revealed that high-risk malignant cells demonstrated an increased capacity of proliferation and immune evasion. Conclusions A model, designated CRSRRSM, was constructed that can effectively predict the prognosis, sorafenib treatment response, and potential drugs for sorafenib resistance in HCC patients. This model provides potential implications for clinical management of HCC patients with sorafenib resistance.

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.

Optimizing the resveratrol fragments for novel in silico hepatocellular carcinoma de novo drug design

Hepatocellular carcinoma (HCC) incidence varies widely around the world and is impacted by factors such as the prevalence of chronic hepatitis B and C infections, alcohol intake, and access to healthcare. The proteins (BRAF_human, VGFR3_human, EGFR_human and UFO_human) play a vital role in hepatocellular carcinoma prognosis, which involves cell proliferation, cell growth, transmission of extracellular signals to the cell nucleus and consequently regulating many other cellular processes. Fostamatinib has been studied for its possible use in the treatment of hepatocellular cancer because it is a more convenient therapy choice for patients and has minor side effects on the human body. However, resveratrol phytochemical has been investigated for its potential use in the prevention and treatment of a wide range of disorders, including cancer, cardiovascular disease, diabetes, and neurological problems due to its frequently antioxidant, anti-inflammatory, and immune-modulating characteristics, which can aid in the prevention of chronic illnesses. This study developed de novo-based fragment-optimized resveratrol (FOR), enhancing therapeutic potential and lowering toxicity. The docking study was performed with four target proteins, and the findings reveal that the vascular endothelial growth factor receptor 3 protein possessed the highest binding energy values of −7.6 kcal/mol with FOR. Additionally, it completely fulfills the criteria of drug-likeliness rules. Thus, FOR proves to be an efficient drug candidate for future in-vivo studies against hepatocellular carcinoma.

EMP3 inhibits the formation of heterotypic cell-in-cell structures in hepatocellular carcinoma

Heterotypic cell-in-cell (heCIC) structures represent a unique intercellular interaction where tumor cells internalize immune cells to enhance the killing efficiency of immune cells. However, the mechanism of heCIC structure formation remains to be fully elucidated. In this study, we explored the role of epithelial membrane protein 3 (EMP3), a PMP-22/EMP/MP20 protein family member highly expressed in the patients with hepatocellular carcinoma and poor prognosis, in the formation of the heCIC structure formed by natural killer cells and hepatocellular carcinoma cells. The analysis of monoclonal hepatocellular carcinoma cell lines revealed that EMP3 presented low expression in the cells with high capability to form heCIC structure and high expression in those with low capability. Knocking down the expression of EMP3 by gene editing promoted the formation of heCIC structures, while overexpression of EMP3 significantly inhibited this process. Additionally, the expression of factors involved in the heCIC structure formation suggested that EMP3 inhibited the formation of heCIC structures by modulating the adhesion ability and cytoskeleton of tumor cells. The findings lay a foundation for enhancing the heCIC-mediated tumor immunotherapy by targeting EMP3.

The Association of Metformin, Other Antidiabetic Medications, and Statins with the Prognosis of Hepatocellular Carcinoma in Patients with Type 2 Diabetes: A Retrospective Cohort Study.

This study aimed to explore whether the prediagnostic use of metformin and statins is associated with the prognosis of patients with hepatocellular carcinoma (HCC) and type 2 diabetes. We identified 1383 eligible individuals who had both type 2 diabetes and HCC diagnosed between 1998 and 2017 from several Finnish registers. Cox models were fitted for cause-specific and all-cause mortality in relation to the use of antidiabetic medications and statins prior to the HCC diagnosis. Prediagnostic metformin use was associated with decreased overall mortality (hazard ratio 0.84, 95% confidence interval 0.74-0.94) compared with nonuse in patients with type 2 diabetes. Similarly, slightly decreased HCC mortality and other-cause mortality were observed among metformin users. The results were inconclusive regarding metformin use and both overall and HCC mortality among patients with localized HCC. No discernible contrast between statin users and nonusers was found in overall mortality nor HCC mortality in either the whole cohort or patients with localized cancer.

Autophagy-related biomarkers in hepatocellular carcinoma and their relationship with immune infiltration

BackgroundAutophagy regulation plays vital roles in many cancers. We aimed to investigate the expression, prognostic value, and immune infiltration of autophagy-related genes in hepatocellular carcinoma (HCC) by bioinformatics analysis.MethodHuman autophagy-related differentially expressed genes (DEGs) between adjacent and HCC tissues were identified. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also evaluated immune infiltration and the response to tumor-sensitive drugs. Finally, we verified the expression of these proteins in clinical samples by immunohistochemistry (IHC), RNA isolation and real-time reverse transcription polymerase chain reaction (RT‒PCR).ResultsA total of 57 autophagy-related DEGs were identified. The HUB genes (BIRC5, CDKN2A, SPP1, and IGF1) were related to the diagnosis and prognosis of HCC. The HUB genes were significantly enriched in immune-related pathways. Furthermore, correlation analysis revealed that HUB gene expression was associated with immune infiltration. We identified 35 tumor-sensitive drugs targeting the HUB genes. Finally, by IHC, we discovered that the protein of CDKN2A, BIRC5, and SPP1 were upregulated in HCC tissues, while IGF1 was downregulated in HCC tissues compared with the levels in paracarcinoma tissues; by RT‒PCR, we discovered that the mRNA of CDKN2A, BIRC5, and SPP1 were upregulated in HCC tissues, while the mRNA of IGF1 was downregulated in HCC tissues compared with the levels in paracarcinoma tissues.ConclusionWe screened and validated four autophagy-related genes associated with immune infiltration and prognosis in patients with HCC.

Transcriptomic analysis of Paraoxonase 1 expression in hepatocellular carcinoma and its potential impact on tumor immunity.

Hepatocellular carcinoma (HCC) is characterized by a complex pathogenesis that confers aggressive malignancy, leading to a lack of dependable biomarkers for predicting invasion and metastasis, which results in poor prognoses in patients with HCC. Glycogen storage disease (GSD) is an uncommon metabolic disorder marked by hepatomegaly and liver fibrosis. Notably, hepatic adenomas in GSD patients present a heightened risk of malignancy compared to those in individuals without the disorder. In this investigation, PON1 emerged as a potential pivotal gene for HCC through bioinformatics analysis. Transcriptomic profiling data of liver cancer were collected and integrated from TCGA and GEO databases. Bioinformatics analysis was conducted to identify mutated mRNAs associated with GSD, and the PON1 gene was selected as a key gene. Patients were grouped based on the expression levels of PON1, and differences in clinical characteristics, biological pathways, immune infiltration, and expression of immune checkpoints were compared. The expression levels of the PON1 gene showed significant differences between the high-expression group and the low-expression group in HCC patients. Further analysis indicated that the PON1 gene at different expression levels might influence the clinical manifestations, biological processes, immune infiltration, and expression of immune checkpoints in HCC. Additionally, immunohistochemistry (IHC) results revealed high expression of PON1 in normal tissues and low expression in HCC tissues. These findings provide important clues and future research directions for the early diagnosis, prognosis, immunotherapy, and potential molecular interactions of HCC. Our investigation underscores the noteworthy prognostic significance of PON1 in HCC, suggesting its potential pivotal role in modulating tumor progression and immune cell infiltration. These findings establish PON1 as a novel tumor biomarker with significant implications for the prognosis, targeted therapy, and immunotherapy of patients with HCC.

Targeting N4-acetylcytidine suppresses hepatocellular carcinoma progression by repressing eEF2-mediated HMGB2 mRNA translation.

N4-acetylcytidine (ac4C) represents a novel messenger RNA (mRNA) modification, and its associated acetyltransferase N-acetyltransferase 10 (NAT10) plays a crucial role in the initiation and progression of tumors by regulating mRNA functionality. However, its role in hepatocellular carcinoma (HCC) development and prognosis is largely unknown. This study aimed to elucidate the role of NAT10-mediated ac4C in HCC progression and provide a promising therapeutic approach. The ac4C levels were evaluated by dot blot and ultra-performance liquid chromatography-tandem mass spectrometry with harvested HCC tissues. The expression of NAT10 was investigated using quantitative real-time polymerase chain reaction, western blotting, and immunohistochemical staining across 91 cohorts of HCC patients. To explore the underlying mechanisms of NAT10-ac4C in HCC, we employed a comprehensive approach integrating acetylated RNA immunoprecipitation and sequencing, RNA sequencing and ribosome profiling analyses, along with RNA immunoprecipitation, RNA pull-down, mass spectrometry, and site-specific mutation analyses. The drug affinity responsive targets stability, cellular thermal shift assay, and surface plasmon resonance assays were performed to assess the specific binding of NAT10 and Panobinostat. Furthermore, the efficacy of targeting NAT10-ac4C for HCC treatment was elucidated through in vitro experiments using HCC cells and in vivo HCC mouse models. Our investigation revealed a significant increase in both the ac4C RNA level and NAT10 expression in HCC. Notably, elevated NAT10 expression was associated with poor outcomes in HCC patients. Functionally, silencing NAT10 suppressed HCC proliferation and metastasis in vitro and in vivo. Mechanistically, NAT10 stimulates the ac4C modification within the coding sequence (CDS) of high mobility group protein B2 (HMGB2), which subsequently enhances HMGB2 translation by facilitating eukaryotic elongation factor 2 (eEF2) binding to the ac4C sites on HMGB2 mRNA's CDS. Additionally, high-throughput compound library screening revealed Panobinostat as a potent inhibitor of NAT10-mediated ac4C modification. This inhibition significantly attenuated HCC growth and metastasis in both in vitro experiments using HCC cells and in vivo HCC mouse models. Our study identified a novel oncogenic epi-transcriptome axis involving NAT10-ac4C/eEF2-HMGB2, which plays a pivotal role in regulating HCC growth and metastasis. The drug Panobinostat validates the therapeutic potential of targeting this axis for HCC treatment.

Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical features.

This study aimed to investigate the use of radiomics features and clinical information by four machine learning algorithms for predicting the prognosis of patients with hepatocellular carcinoma (HCC) who have been treated with transarterial chemoembolization (TACE). A total of 105 patients with HCC treated with TACE from 2002 to 2012 were enrolled retrospectively and randomly divided into two cohorts for training (n = 74) and validation (n = 31) according to a ratio of 7:3. The Spearman rank, random forest, and univariate Cox regression were used to select the optimal radiomics features. Univariate Cox regression was used to select clinical features. Four machine learning algorithms were used to develop the models: random survival forest, eXtreme gradient boosting (XGBoost), gradient boosting, and the Cox proportional hazard regression model. The area under the curve (AUC) and C-index were devoted to assessing the performance of the models in predicting HCC prognosis. A total of 1,834 radiomics features were extracted from the computed tomography images of each patient. The clinical risk factors for HCC prognosis were age at diagnosis, TNM stage, and metastasis, which were analyzed using univariate Cox regression. In various models, the efficacy of the combined models generally surpassed that of the radiomics and clinical models. Among four machine learning algorithms, XGBoost exhibited the best performance in combined models, achieving an AUC of 0.979 in the training set and 0.750 in the testing set, demonstrating its strong prognostic prediction capability. The superior performance of the XGBoost-based combined model underscores its potential as a powerful tool for enhancing the precision of prognostic assessments for patients with HCC.

The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in the past decades, the overall survival (OS) of liver cancer is still disappointing. Machine learning models have several advantages over traditional cox models in prognostic prediction. This study aimed at designing an optimal panel and constructing an optimal machine learning model in predicting prognosis for HCC. A total of 941 HCC patients with completed survival data and preoperative clinical chemistry and immunology indicators from two medical centers were included. The OCC panel was designed by univariate and multivariate cox regression analysis. Subsequently, cox model and machine-learning models were established and assessed for predicting OS and PFS in discovery cohort and internal validation cohort. The best OCC model was validated in the external validation cohort and analyzed in different subgroups. In discovery, internal and external validation cohort, C-indexes of our optimal OCC model were 0.871 (95% CI, 0.863-0.878), 0.692 (95% CI, 0.667-0.717) and 0.648 (95% CI, 0.630-0.667), respectively; the 2-year AUCs of OCC model were 0.939 (95% CI, 0.920-0.959), 0.738 (95% CI, 0.667-0.809) and 0.725 (95% CI, 0.643-0.808), respectively. For subgroup analysis of HCC patients with HBV, aged less than 65, cirrhosis or resection as first therapy, C-indexes of our optimal OCC model were 0.772 (95% CI, 0.752-0.792), 0.769 (95% CI, 0.750-0.789), 0.855 (95% CI, 0.846-0.864) and 0.760 (95% CI, 0.741-0.778), respectively. In general, the optimal OCC model based on RSF algorithm shows prognostic guidance value in HCC patients undergoing individualized treatment.

UBA2 SUMOylates NQO1 and promotes the proliferation of hepatocellular carcinoma by modulating the MAPK pathway.

In our previous study, we found that small ubiquitin-related modifier (SUMO)-activating enzyme ubiquitin-associated-2 domain (UBA2) was upregulated in hepatocellular carcinoma (HCC) patients who were insensitive to chemoembolization. In this study, we aimed to investigate the role of UBA2 in HCC progression. Three cohorts were used to evaluate the efficacy of UBA2 as a prognostic factor for HCC. Our results indicated that UBA2 was associated with aggressive clinical behaviors and was a strong indicator of poor prognosis in HCC. Invitro experiments demonstrated that UBA2 accelerated cell growth, invasion, and migration. These results were further supported by invivo experiments. RNA-sequencing analysis indicated NQO1 as a target of UBA2, with its levels altering following UBA2 manipulation. The results were verified by western blotting (WB) and quantitative PCR. The SUMOplot Analysis Program predicted lysine residue K240 as a modification target of UBA2, which was confirmed by immunoprecipitation (IP) assays. Subsequent mutation of NQO1 at K240 in HCC cell lines and functional assays revealed the significance of this modification. In addition, the oncogenic effect of UBA2 could be reversed by the SUMO inhibitor ML792 invivo and invitro. In conclusion, our study elucidated the regulatory mechanism of UBA2 in HCC and suggested that the SUMO inhibitor ML792 may be an effective combinatory treatment for patients with aberrant UBA2 expression.