Homotypic cell membrane-camouflaged biomimetic PLGA nanoparticle loading triptolide for the treatment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-associated death worldwide. Beside early detection, early diagnosis, and early surgery, it is urgent to try new strategies for the treatment of HCC. Triptolide (TPL) has been employed to treat HCC. However, its clinical applications were restricted by the narrow therapeutic window, severe toxicity, and poor water-solubility. In this study, we developed cancer cell membrane-camouflaged biomimetic PLGA nanoparticles loading TPL (TPL@mPLGA) with the homologous targeting property for the treatment of HCC. The TPL@mPLGA was successfully prepared with particle size of 195.5 ± 7.5 nm and zeta potential at -21.5 ± 0.2 mV with good stability. The drug loading (DL) of TPL@mPLGA was 2.94%. After Huh-7 cell membrane coating, the natural Huh-7 cell membrane proteins were found to be retained on TPL@mPLGA, thus endowing the TPL@mPLGA with enhanced accumulation at tumor site, and better anti-tumor activity in vitro and in vivo when compared with TPL or TPL@PLGA. The TPL@mPLGA showed enhanced anti-tumor effects and reduced toxicity of TPL, which could be adopted for the treatment of HCC.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

Transcriptomic and genomic characteristics of intrahepatic metastases of primary liver cancer.

BACKGROUND: Patients with primary multifocal hepatocellular carcinoma (HCC) have a poor prognosis and often experience a high rate of treatment failure. Multifocal HCC is mainly caused by intrahepatic metastasis (IM), and though portal vein tumor thrombosis (PVTT) is considered a hallmark of IM, the molecular mechanism by which primary HCC cells invade the portal veins remains unclear. Therefore, it is necessary to recognize the early signs of metastasis of HCC to arrange better treatment for patients. RESULTS: To determine the differential molecular features between primary HCC with and without phenotype of metastasis, we used the CIBERSORTx software to deconvolute cell types from bulk RNA-Seq based on a single-cell transcriptomic dataset. According to the relative abundance of tumorigenic and metastatic hepatoma cells, VEGFA+ macrophages, effector memory T cells, and natural killer cells, HCC samples were divided into five groups: Pro-T, Mix, Pro-Meta, NKC, and MemT, and the transcriptomic and genomic features of the first three groups were analyzed. We found that the Pro-T group appeared to retain native hepatic metabolic activity, whereas the Pro-Meta group underwent dedifferentiation. Genes highly expressed in the group Pro-Meta often signify a worse outcome. CONCLUSIONS: The HCC cohort can be well-typed and prognosis predicted according to tumor microenvironment components. Primary hepatocellular carcinoma may have obtained corresponding molecular features before metastasis occurred.

Hepatitis B-related hepatocellular carcinoma: classification and prognostic model based on programmed cell death genes.

Instruction: Hepatitis B virus (HBV) infection is a major risk factor for hepatocellular carcinoma (HCC). Programmed cell death (PCD) is a critical process in suppressing tumor growth, and alterations in PCD-related genes may contribute to the progression of HBV-HCC. This study aims to develop a prognostic model that incorporates genomic and clinical information based on PCD-related genes, providing novel insights into the molecular heterogeneity of HBV-HCC through bioinformatics analysis and experimental validation. Methods: In this study, we analyzed 139 HBV-HCC samples from The Cancer Genome Atlas (TCGA) and validated them with 30 samples from the Gene Expression Omnibus (GEO) database. Various bioinformatics tools, including differential expression analysis, gene set variation analysis, and machine learning algorithms were used for comprehensive analysis of RNA sequencing data from HBV-HCC patients. Furthermore, among the PCD-related genes, we ultimately chose DLAT for further research on tissue chips and patient cohorts. Besides, immunohistochemistry, qRT-PCR and Western blot analysis were conducted. Results: The cluster analysis identified three distinct subgroups of HBV-HCC patients. Among them, Cluster 2 demonstrated significant activation in DNA replication-related pathways and tumor-related processes. Analysis of copy number variations (CNVs) of PCD-related genes also revealed distinct patterns in the three subgroups, which may be associated with differences in pathway activation and survival outcomes. DLAT in tumor tissues of HBV-HCC patients is upregulated. Discussion: Based on the PCD-related genes, we developed a prognostic model that incorporates genomic and clinical information and provided novel insights into the molecular heterogeneity of HBV-HCC. In our study, we emphasized the significance of PCD-related genes, particularly DLAT, which was examined in vitro to explore its potential clinical implications.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

AKR1B10 expression characteristics in hepatocellular carcinoma and its correlation with clinicopathological features and immune microenvironment.

Hepatocellular carcinoma (HCC) represents a major global health threat with diverse and complex pathogenesis. Aldo-keto reductase family 1 member B10 (AKR1B10), a tumor-associated enzyme, exhibits abnormal expression in various cancers. However, a comprehensive understanding of AKR1B10's role in HCC is lacking. This study aims to explore the expression characteristics of AKR1B10 in HCC and its correlation with clinicopathological features, survival prognosis, and tumor immune microenvironment, further investigating its role and potential regulatory mechanisms in HCC. This study conducted comprehensive analyses using various bioinformatics tools and databases. Initially, differentially expressed genes related to HCC were identified from the GEO database, and the expression of AKR1B10 in HCC and other cancers was compared using TIMER and GEPIA databases, with validation of its specificity in HCC tissue samples using the HPA database. Furthermore, the relationship of AKR1B10 expression with clinicopathological features (age, gender, tumor size, staging, etc.) of HCC patients was analyzed using the TCGA database's LIHC dataset. The impact of AKR1B10 expression levels on patient prognosis was evaluated using Kaplan-Meier survival analysis and the Cox proportional hazards model. Additionally, the correlation of AKR1B10 expression with tumor biology-related signaling pathways and tumor immune microenvironment was studied using databases like GSEA, Targetscan, and others, identifying microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that regulate AKR1B10 expression to explore potential regulatory mechanisms. Elevated AKR1B10 expression was significantly associated with gender, primary tumor size, and fibrosis stage in HCC tissues. High AKR1B10 expression indicated poor prognosis and served as an independent predictor for patient outcomes. Detailed mechanism analysis revealed a positive correlation between high AKR1B10 expression, immune cell infiltration, and pro-inflammatory cytokines, suggesting a potential DANCR-miR-216a-5p-AKR1B10 axis regulating the tumor microenvironment and impacting HCC development and prognosis. The heightened expression of AKR1B10 in HCC is not only related to significant clinical-pathological traits but may also influence HCC progression and prognosis by activating key signaling pathways and altering the tumor immune microenvironment. These findings provide new insights into the role of AKR1B10 in HCC pathogenesis and highlight its potential as a biomarker and therapeutic target.

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis.

Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML) algorithms to assist clinicians in the decision-making process for treatment. Retrospective analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database, and cases from 2010 to 2015 were assigned to the developing sets, while cases from 2016 to 2017 were assigned to the testing set. Missing values were addressed using the multiple imputation technique. Four algorithms were utilized to construct the models, comprising traditional logistic regression (LR) and automated machine learning (AutoML) analysis such as gradient boost machine (GBM), deep neural net (DL), and generalized linear model (GLM). We evaluated the models' performance using LR-based metrics, including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), as well as AutoML-based metrics, such as feature importance, SHapley Additive exPlanation (SHAP) Plots, and Local Interpretable Model Agnostic Explanation (LIME). A total of 6207 patients were included in this study, with 2683, 1780, and 1744 patients allocated to the training, validation, and test sets, respectively. Among the different models evaluated, the GBM model demonstrated the highest performance in the training, validation, and test cohorts, with respective AUC values of 0.805, 0.780, and 0.795. Furthermore, the GBM model outperformed other AutoML models in terms of accuracy, achieving 0.747, 0.700, and 0.706 in the training, validation, and test cohorts, respectively. Additionally, the study revealed that tumor size and tumor location were the most significant predictors influencing the AutoML model's ability to accurately predict LIM. The AutoML model utilizing the GBM algorithm for GIST patients can effectively predict the risk of LIM and provide clinicians with a reference for developing individualized treatment plans.

Short-term Outcomes of Laparoscopic Versus Open Liver Resection in the Elderly: A Propensity Score-matched Analysis.

BACKGROUND/AIM: With the aging of the population, there is a rising proportion of elderly patients undergoing liver resection. However, the safety and efficacy of laparoscopic liver resection (LLR) in the elderly have not yet been established. In this study, we compared the short-term results of LLR and open liver resection (OLR) in elderly patients using propensity score matched (PSM) analysis. PATIENTS AND METHODS: The study comprised 237 elderly patients aged 65 years and older who had undergone liver resection between 2015 to 2021, excluding biliary and vascular reconstruction and simultaneous surgeries other than liver resection. We conducted PSM analysis for baseline characteristics (age, sex, BMI, ASA-PS, disease, procedure, tumor size, and number of tumors) to eliminate potential selection bias. We then compared short-term postoperative outcomes between LLR and OLR groups in patients selected by PSM analysis. RESULTS: Applying PSM analysis, 90 cases each were selected for the LLR and OLR groups. The LLR group had a significantly lower complication rate (Clavien-Dindo: CD ≥II) (19% vs. 33%, p=0.03), especially bile leakage (CD ≥II) (0% vs. 6.7%, p=0.03) compared with those in the OLR group. In addition, a shorter operation time (244 min vs. 351 min, p<0.01), less blood loss (150 ml vs. 335 ml, p<0.01), and shorter hospital stay (8 days vs. 12 days, p<0.01) were observed in the LLR group. No operative or in-hospital deaths were observed in both groups. CONCLUSION: LLR can be safely performed in elderly patients and offers better short-term outcomes.

ARHGAP4 as a Prognostic Biomarker for Colon Liver Metastases After Surgical Resection.

BACKGROUND/AIM: To select and stratify patients for optimal treatment plans is challenging. Identification of cancer-related biomarkers that serve as predictors for prognosis and treatment response is essential to better predict treatment outcome and find future targets for therapy. Previous data has suggested ARHGAP4 as a relevant biomarker in colorectal cancer (CRC). The purpose of this study was to assess how ARHGAP4 expression affected patients undergoing surgery for colon liver metastasis (CLM) in terms of overall survival (OS). PATIENTS AND METHODS: A total of 251 patients undergoing resection of CLM from 2006 to 2017 were included. Corresponding resected tumor specimens were examined for ARHGAP4 expression levels by immunohistochemistry (IHC). The correlation between ARHGAP4 expression and postoperative survival was analyzed. RESULTS: High expression levels of ARHGAP4 were seen in 60% of patients. High expression levels of ARHGAP4 were correlated with adverse prognosis after hepatectomy due to CLM. Survival data generated using Cox proportional hazard model showed a statistically significant difference between high and low ARHGAP4 expression groups by univariate (HR=1.5, 95% CI=1.1-2.2) and multivariate (HR=1.5, 95% CI=1.0-2.1) analysis. In multivariate Cox regression, high ARHGAP4 expression, preoperative CEA levels and presence of vascular invasion by pathological examinations were independent predictive factors of overall survival. CONCLUSION: ARHGAP4 is a novel prognostic biomarker after resection of CLM.

Blocking the angiopoietin-2-dependent integrin ß-1 signaling axis abrogates small cell lung cancer invasion and metastasis.

Small cell lung cancer (SCLC) is the most aggressive lung cancer entity with an extremely limited therapeutic outcome. Most patients are diagnosed at an extensive stage. However, the molecular mechanisms driving SCLC invasion and metastasis remain largely elusive. We used an autochthonous SCLC mouse model and matched samples from patients with primary and metastatic SCLC to investigate the molecular characteristics of tumor metastasis. We demonstrate that tumor cell invasion and liver metastasis in SCLC are triggered by an Angiopoietin-2 (ANG-2)/Integrin ß-1-dependent pathway in tumor cells, mediated by focal adhesion kinase/Src kinase signaling. Strikingly, CRISPR-Cas9 KO of Integrin ß-1 or blocking Integrin ß-1 signaling by an anti-ANG-2 treatment abrogates liver metastasis formation in vivo. Interestingly, analysis of a unique collection of matched samples from patients with primary and metastatic SCLC confirmed a strong increase of Integrin ß-1 in liver metastasis in comparison with the primary tumor. We further show that ANG-2 blockade combined with PD-1-targeted by anti-PD-1 treatment displays synergistic treatment effects in SCLC. Together, our data demonstrate a fundamental role of ANG-2/Integrin ß-1 signaling in SCLC cells for tumor cell invasion and liver metastasis and provide a potentially new effective treatment strategy for patients with SCLC.

Signaling pathways in liver cancer: pathogenesis and targeted therapy.

Liver cancer remains one of the most prevalent malignancies worldwide with high incidence and mortality rates. Due to its subtle onset, liver cancer is commonly diagnosed at a late stage when surgical interventions are no longer feasible. This situation highlights the critical role of systemic treatments, including targeted therapies, in bettering patient outcomes. Despite numerous studies on the mechanisms underlying liver cancer, tyrosine kinase inhibitors (TKIs) are the only widely used clinical inhibitors, represented by sorafenib, whose clinical application is greatly limited by the phenomenon of drug resistance. Here we show an in-depth discussion of the signaling pathways frequently implicated in liver cancer pathogenesis and the inhibitors targeting these pathways under investigation or already in use in the management of advanced liver cancer. We elucidate the oncogenic roles of these pathways in liver cancer especially hepatocellular carcinoma (HCC), as well as the current state of research on inhibitors respectively. Given that TKIs represent the sole class of targeted therapeutics for liver cancer employed in clinical practice, we have particularly focused on TKIs and the mechanisms of the commonly encountered phenomena of its resistance during HCC treatment. This necessitates the imperative development of innovative targeted strategies and the urgency of overcoming the existing limitations. This review endeavors to shed light on the utilization of targeted therapy in advanced liver cancer, with a vision to improve the unsatisfactory prognostic outlook for those patients.

Integrating network pharmacology, bioinformatics, and experimental validation to unveil the molecular targets and mechanisms of galangin for treating hepatocellular carcinoma.

BACKGROUND: Galangin, a flavonoid compound, is derived from Alpinia officinarum Hance. Previous studies have shown that galangin can inhibit the proliferation of hepatocellular carcinoma (HCC), but its mechanism is still unclear. This study aims to investigate the potential targets and molecular mechanisms of galangin on HCC through network pharmacology, bioinformatics, molecular docking, and experimental in vitro validation. METHODS: In this study, network pharmacology was used to investigate the targets and mechanisms of galangin in the treatment of HCC. AutoDockTools software was used to simulate and calculate the binding of galangin to its core targets. GO and KEGG enrichment analyses were conducted in the DAVID database to explore the main biological functions and signaling pathways impacted by galangin intervention. In addition, bioinformatics was applied to examine the correlation between the differential expressions of the anti-HCC core targets of galangin and the survival of patients with HCC. Finally, the findings obtained from network pharmacology and bioinformatics were verified in cell experiments. RESULTS: A total of 67 overlapping target genes of galangin and HCC were identified. Through the analysis of the protein-protein interaction (PPI) network, 10 hub genes with the highest degree of freedom were identified, including SRC, ESR1, MMP9, CDK4, CCNB1, MMP2, CDK2, CDK1, CHK1, and PLK1. These genes were found to be closely related to the degradation of the extracellular matrix, signal transduction, and the cell cycle. GO and KEGG enrichment analyses revealed that galangin exerts an anti-HCC role by affecting various signaling pathways, including the cell cycle, pathways in cancer, and the PI3K-Akt signaling pathway. The results of molecular docking indicated a significant interaction between galangin and CCNB1, CDK4, CDK1, and PLK1. Bioinformatics analysis revealed that CCNB1, CDK4, CDK1, and PLK1 were upregulated in the liver of patients with HCC at both the mRNA and protein levels. Flow cytometry analysis showed that galangin induced G0/G1 phase arrest and cell apoptosis in HepG2 and Huh7 cells. Additionally, galangin suppressed the expression of key proteins and mRNAs involved in the cell cycle pathway. CONCLUSIONS: These results suggest that galangin inhibits the growth of HCC cells by arresting the cell cycle at the G0/G1 phase.

Hepatocellular carcinoma-the role of the underlying liver disease in clinical practice.

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related mortality. This particular type of cancer has the distinctive characteristic of mostly happening in individuals with an underlying liver disease. This makes the management of patients more challenging, since physicians must take into consideration two different conditions, the chronic liver disease and the tumor. The underlying liver disease has several implications in clinical practice, because different kinds of chronic liver disease can lead to varying degrees of risk of developing HCC, obstacles in surveillance, and differences in the efficacy of the treatment against HCC. A shift in the prevalence of liver diseases has been evident over the last few years, with viral hepatitis gradually losing the leading position as cause of HCC and metabolic dysfunction-associated steatotic liver disease gaining importance. Therefore, in an era of personalized medicine, it is imperative that physicians are aware of the underlying liver disease of individuals with HCC and its impact in the management of their tumors.

Present and future of new systemic therapies for early and intermediate stages of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a high mortality neoplasm which usually appears on a cirrhotic liver. The therapeutic arsenal and subsequent prognostic outlook are intrinsically linked to the HCC stage at diagnosis. Notwithstanding the current deployment of treatments with curative intent (liver resection/local ablation and liver transplantation) in early and intermediate stages, a high rate of HCC recurrence persists, underscoring a pivotal clinical challenge. Emergent systemic therapies (ST), particularly immunotherapy, have demonstrate promising outcomes in terms of increase overall survival, but they are currently bound to the advanced stage of HCC. This review provides a comprehensive analysis of the literature, encompassing studies up to March 10, 2024, evaluating the impact of novel ST in the early and intermediate HCC stages, specially focusing on the findings of neoadjuvant and adjuvant regimens, aimed at increasing significantly overall survival and recurrence-free survival after a treatment with curative intent. We also investigate the potential role of ST in enhancing the downstaging rate for the intermediate-stage HCC initially deemed ineligible for treatment with curative intent. Finally, we critically discuss about the current relevance of the results of these studies and the encouraging future implications of ST in the treatment schedules of early and intermediate HCC stages.

Cell division cyclin 25C knockdown inhibits hepatocellular carcinoma development by inducing endoplasmic reticulum stress.

BACKGROUND: Cell division cyclin 25C (CDC25C) is a protein that plays a critical role in the cell cycle, specifically in the transition from the G2 phase to the M phase. Recent research has shown that CDC25C could be a potential therapeutic target for cancers, particularly for hepatocellular carcinoma (HCC). However, the specific regulatory mechanisms underlying the role of CDC25C in HCC tumorigenesis and development remain incompletely understood. AIM: To explore the impact of CDC25C on cell proliferation and apoptosis, as well as its regulatory mechanisms in HCC development. METHODS: Hepa1-6 and B16 cells were transduced with a lentiviral vector containing shRNA interference sequences (LV-CDC25C shRNA) to knock down CDC25C. Subsequently, a xenograft mouse model was established by subcutaneously injecting transduced Hepa1-6 cells into C57BL/6 mice to assess the effects of CDC25C knockdown on HCC development in vivo. Cell proliferation and migration were evaluated using a Cell Counting Kit-8 cell proliferation assays and wound healing assays, respectively. The expression of endoplasmic reticulum (ER) stress-related molecules (glucose-regulated protein 78, X-box binding protein-1, and C/EBP homologous protein) was measured in both cells and subcutaneous xenografts using quantitative real-time PCR (qRT-PCR) and western blotting. Additionally, apoptosis was investigated using flow cytometry, qRT-PCR, and western blotting. RESULTS: CDC25C was stably suppressed in Hepa1-6 and B16 cells through LV-CDC25C shRNA transduction. A xenograft model with CDC25C knockdown was successfully established and that downregulation of CDC25C expression significantly inhibited HCC growth in mice. CDC25C knockdown not only inhibited cell proliferation and migration but also significantly increased the ER stress response, ultimately promoting ER stress-induced apoptosis in HCC cells. CONCLUSION: The regulatory mechanism of CDC25C in HCC development may involve the activation of ER stress and the ER stress-induced apoptosis signaling pathway.

Interleukin-25 as a Potential Biomarker in Lung Metastasis of Hepatocellular Carcinoma with HBV History in Chinese Patients: A Single Center, Case-control Study.

Background: Interleukin-25 (IL-25) has been proved to play a role in the pathogenesis and metastasis of Hepatocellular carcinoma (HCC), but the relationship between the level of IL-25 and the metastasis and prognosis of HCC is still not clear. This study aimed to investigate the expression of IL-25 and other potential biochemical indicators among healthy people, HBV-associated HCC patients without lung metastasis and HBV-associated HCC patients with lung metastasis. Methods: From September 2019 to November 2021, 33 HCC patients without lung metastasis, 37 HCC patients with lung metastasis and 29 healthy controls were included in the study. IL-25 and other commonly used biochemical markers were measured to establish predictors of overall survival (OS) and progression-free survival (PFS) after treatment. Results: The serum level of IL-25 was increased in HCC patients than healthy controls (p < 0.001) and HCC patients with lung metastasis had higher IL-25 level than HCC patients without metastasis (p = 0.035). Lung metastasis also indicated higher death rate (p < 0.001) by chi-square test, higher GGT level (p = 0.024) and higher AFP level (p = 0.049) by non-parametric test. Kaplan-Meier analysis demonstrated that IL-25 was negatively associated with PFS (p = 0.024). Multivariate Cox-regression analysis indicated IL-25 (p = 0.030) and GGT (p = 0.020) to be independent predictors of poorer PFS, while IL-25 showed no significant association with OS. Conclusion: The level of IL-25 was significantly associated with disease progression and lung metastasis of HBV-associated HCC. The high expression of IL-25 predicted high recurrence rate and death probability of HCC patients after treatment. Therefore, IL-25 may be an effective predictor of prognosis in HCC.

Gender disparity between first and senior authors on liver cancer research in the top journals of Gastroenterology and Hepatology.

BACKGROUND: Gender disparity is pervasive in academic medicine. This study aimed to assess the disparity between men and women with regard to first and senior author positions in primary studies on liver cancer over the last two decades. METHODS: We conducted a review of articles published in high-impact factor journals of the field of Gastroenterology and Hepatology in 2005, 2010, 2015 and 2020. First and senior authors of all ages were considered as the study population. The authors' genders were determined using the online artificial intelligence tool genderize.io (https://genderize.io/). The disparity between men and women authors was assessed using the linear-by-linear association test. RESULTS: 665 original articles from 10 journals were reviewed. The point prevalence of first women authors was 25.0% compared with 75.0% for men. The point prevalence of senior women authors was 16.3% compared with 83.7% for men. From 2000 to 2020, the proportion of first women authors increased 14.4% to 26.8% compared with 85.6%-73.2% for men (P = 0.009), and the proportion of senior women authors increased from 7.4% to 19.5%, compared with 92.6%-80.5% for men (P = 0.035). The factor independently associated with a reduced representation of women among first authors was the region of author. The factor independently associated with a reduced representation of women among senior authors was the impact factor of journals. CONCLUSION: The findings indicated a remarkable increase in the proportion of women, both first and senior authors, over the past two decades in the field of liver cancers. However, the representation of women authors in this area is far less than that of men.