Prognostic comparative genes predict targets for sorafenib combination therapies in hepatocellular carcinoma

Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma

The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify HCC-related biomarkers. Based on an analysis of scRNA-seq data, several marker genes expressed on tumor cells have been identified. Three machine-learning algorithms were used to identify shared diagnostic genes. Furthermore, logistic regression analysis was conducted to re-evaluate and identify essential biomarkers, which were then employed to develop a diagnostic prediction model. Additionally, AutoDockTools were used for molecular docking to investigate the association between the most sensitive drug and the core proteins. 44 genes were obtained by intersecting the WGCNA results, marker genes from scRNA-seq data, and up-regulated DEGs. Three machine-learning algorithms refined CDKN3, PPIA, PRC1, GMNN, and CENPW as hub biomarkers. GMNN and PRC1 were further selected by logistic regression analysis to build a nomogram. The molecular docking results showed that the drug NPK76-II-72-1 had a good binding ability with the GMNN and PRC1 proteins. The results highlighted CDKN3, PPIA, PRC1, GMNN, and CENPW as potential detection biomarkers for HCC patients. Our research offers novel insights into the diagnosis and treatment of HCC.

Recent updates of centromere proteins in hepatocellular carcinoma: a review

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide, with approximately 800,000 deaths worldwide each year. Owing to the atypical early symptoms and characteristics of HCC, over 80% of HCC patients cannot receive curative treatment. The treatment of HCC is facing a bottleneck, and new treatment methods are urgently needed. Since the pathogenesis of HCC is not yet clear, identifying the molecular mechanisms and therapeutic targets related to it is crucial. Centromeres are considered special deoxyribonucleic acid (DNA) sequences with highly repetitive sequences that are physically connected to the spindle during cell division, ensuring equal division of genetic material between daughter cells. The numerous proteins that aggregate on this sequence during cell division are called centromere proteins (CENPs). Currently, numerous studies have shown that CENPs are abnormally expressed in tumor cells and are associated with patient prognosis. The abnormal expression of CENPs is a key cause of chromosomal instability. Furthermore, chromosomal instability is a common characteristic of the majority of tumors. Chromosomal instability can lead to uncontrolled and sustained division and proliferation of malignant tumors. Therapeutic plans targeting CENPs play important roles in the treatment of HCC. For example, small ribonucleic acid (RNA) can silence CENP expression and prevent the occurrence and development of liver cancer. In recent years, studies of HCC-targeting CENPs have gradually increased but are still relatively novel, requiring further systematic elaboration. In this review, we provide a detailed introduction to the characteristics of CENPs and discuss their roles in HCC. In addition, we discuss their application prospects in future clinical practice.

Characterization of six clinical drugs and dietary intervention in the nonobese CDAA-HFD mouse model of MASH and progressive fibrosis

The choline-deficient l-amino acid defined-high-fat diet (CDAA-HFD) mouse model is widely used in preclinical metabolic dysfunction-associated steatohepatitis (MASH) research. To validate the CDAA-HFD mouse, we evaluated disease progression and responsiveness to dietary and pharmacological interventions with semaglutide, lanifibranor, elafibranor, obeticholic acid (OCA), firsocostat, and resmetirom. Disease phenotyping was performed in C57BL/6J mice fed CDAA-HFD for 3-20 wk and ranked using the MASLD Human Proximity Score (MHPS). Semaglutide, lanifibranor, elafibranor, OCA, firsocostat, or resmetirom were profiled as treatment intervention for 8 wk, starting after 6 wk of CDAA-HFD feeding. Semaglutide and lanifibranor were further evaluated as early (preventive) therapy for 9 wk, starting 3 wk after CDAA-HFD diet feeding. In addition, benefits of dietary intervention (chow reversal) for 8 wk were characterized following 6 wk of CDAA-HFD feeding. CDAA-HFD mice demonstrated a nonobese phenotype with fast onset and progression of MASH and fibrosis, high similarity to human MASH-fibrosis, and tumor development after 20 wk of diet-induction. Semaglutide and lanifibranor partially reversed fibrosis when administered as prevention but not as treatment intervention. Elafibranor was the only interventional drug therapy to improve fibrosis. In comparison, chow-reversal resulted in complete regression of steatosis with improved liver inflammation and fibrosis in CDAA-HFD mice. CDAA-HFD mice recapitulate histological hallmarks of advanced MASH with progressive severe fibrosis, however, in the absence of a clinical translational obese dysmetabolic phenotype. CDAA-HFD mice are suitable for profiling drug candidates directly targeting hepatic lipid metabolism, inflammation, and fibrosis. The timing of pharmacological intervention is critical for determining antifibrotic drug efficacy in the model.NEW & NOTEWORTHY The CDAA-HFD mouse model is widely used in preclinical MASH research, but validation of the model is lacking. This study presents the longitudinal characterization of disease progression. Furthermore, late-stage clinical compounds and dietary intervention (chow reversal) display distinct hepatoprotective effects in the model. Collectively, the study provides critical information guiding the use of the CDAA-HFD mouse model in preclinical drug discovery for MASH and fibrosis.

CDT1 is a Potential Therapeutic Target for the Progression of NAFLD to HCC and the Exacerbation of Cancer

Aims

This study aimed to identify potential therapeutic targets in the progression from non-alcoholic fatty liver disease (NAFLD) to hepatocellular carcinoma (HCC), with a focus on genes that could influence disease development and progression.

Background

Hepatocellular carcinoma, significantly driven by non-alcoholic fatty liver disease, represents a major global health challenge due to late-stage diagnosis and limited treatment options. This study utilized bioinformatics to analyze data from GEO and TCGA, aiming to uncover molecular biomarkers that bridge NAFLD to HCC. Through identifying critical genes and pathways, our research seeks to advance early detection and develop targeted therapies, potentially improving prognosis and personalizing treatment for NAFLD-HCC patients.

Objectives

Identify key genes that differ between NAFLD and HCC; Analyze these genes to understand their roles in disease progression; Validate the functions of these genes in NAFLD to HCC transition.

Methods

Initially, we identified a set of genes differentially expressed in both NAFLD and HCC using second-generation sequencing data from the GEO and TCGA databases. We then employed a Cox proportional hazards model and a Lasso regression model, applying machine learning techniques to the large sample data from TCGA. This approach was used to screen for key disease-related genes, and an external dataset was utilized for model validation. Additionally, pseudo-temporal sequencing analysis of single-cell sequencing data was performed to further examine the variations in these genes in NAFLD and HCC.

Results

The machine learning analysis identified IGSF3, CENPW, CDT1, and CDC6 as key genes. Furthermore, constructing a machine learning model for CDT1 revealed it to be the most critical gene, with model validation yielding an ROC value greater than 0.80. The single-cell sequencing data analysis confirmed significant variations in the four predicted key genes between the NAFLD and HCC groups.

Conclusion

Our study underscores the pivotal role of CDT1 in the progression from NAFLD to HCC. This finding opens new avenues for early diagnosis and targeted therapy of HCC, highlighting CDT1 as a potential therapeutic target.

Comprehensive Analysis of TICRR in Hepatocellular Carcinoma Based on Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA ( www.tcga-data.nci.nih.gov/tcga/ ) datasets and GEO ( www.ncbi.nlm.nih.gov/geo ) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy.

Recent progress in biomaterials-driven ferroptosis for cancer therapy

Ferroptosis, first suggested in 2012, is a type of non-apoptotic programmed cell death caused by the buildup of lipid peroxidation and marked by an overabundance of oxidized poly unsaturated fatty acids. During the last decade, researchers have uncovered the formation of ferroptosis and created multiple drugs aimed at it, but due to poor selectivity and pharmacokinetics, clinical application has been hindered. In recent years, biomedical discoveries and developments in nanotechnology have spurred the investigation of ferroptosis nanomaterials, providing new opportunities for the ferroptosis driven tumours treatment. Additionally, hydrogels have been widely studied in ferroptosis because of their unique 3D structure and excellent controllability. By using these biomaterials, it is possible to achieve controlled release and targeted delivery of drugs, thus increasing the potency of the drugs and minimizing adverse effects. Therefore, summarizing the biomedical nanomaterials, including hydrogels, used in ferroptosis for cancer therapy is a must. This article provides an overview of ferroptosis, detailing its properties and underlying mechanisms. It also categorizes and reviews the use of various nanomaterials in ferroptosis, along with relevant explanations and illustrations. In addition, we discuss the opportunities and challenges facing the application of nanomaterials in ferroptosis. Finally, the development prospects of this field are prospected. This review is intended to provide a foundation for the development and application of biomedical nanomaterials in ferroptosis.

Semaglutide reduces tumor burden in the GAN diet-induced obese and biopsy-confirmed mouse model of NASH-HCC with advanced fibrosis

Non-alcoholic steatohepatitis (NASH) is emerging as a major cause of hepatocellular carcinoma (HCC), however, it is not resolved if compounds in late-stage clinical development for NASH may have additional therapeutic benefits in NASH-driven HCC (NASH-HCC). Here, we profiled monotherapy with semaglutide (glucagon-like-receptor-1 receptor agonist) and lanifibranor (pan-peroxisome proliferator-activated receptor agonist) in a diet-induced obese (DIO) mouse model of NASH-HCC. Disease progression was characterized in male C57BL/6 J mice fed the GAN (Gubra Amylin NASH) diet high in fat, fructose and cholesterol for 12-72 weeks (n = 15 per group). Other GAN DIO-NASH-HCC mice fed the GAN diet for 54 weeks and with biopsy-confirmed NASH (NAFLD Activity Score ≥ 5) and advanced fibrosis (stage F3) received vehicle (n = 16), semaglutide (30 nmol/kg, s.c., n = 15), or lanifibranor (30 mg/kg, p.o., n = 15) once daily for 14 weeks. GAN DIO-NASH-HCC mice demonstrated progressive NASH, fibrosis and HCC burden. Tumors presented with histological and molecular signatures of poor prognostic HCC. Consistent with clinical trial outcomes in NASH patients, both lanifibranor and semaglutide improved NASH while only lanifibranor reduced fibrosis in GAN DIO-NASH-HCC mice. Notably, only semaglutide reduced tumor burden in GAN DIO-NASH-HCC mice. In conclusion, the GAN DIO-NASH-HCC mouse is a clinical translational model of NASH-HCC. Semaglutide improves both NASH and tumor burden in GAN DIO-NASH-HCC mice, highlighting the suitability of this preclinical model for profiling novel drug therapies targeting NASH-HCC.