Depletion of proteasome subunit PSMD1 induces cancer cell death via protein ubiquitination and DNA damage, irrespective of p53 status.

Hepatocellular carcinoma (HCC) is characterized by high incidence and fatality rates worldwide. In our exploration of prognostic factors in HCC, the 26s proteasome subunit, non-ATPase 1 (PSMD1) protein emerged as a significant contributor, demonstrating its potential as a therapeutic target in this aggressive cancer. PSMD1 is a subunit of the 19S regulatory particle in the 26S proteasome complex; the 19S particle controls the deubiquitination of ubiquitinated proteins, which are then degraded by the proteolytic activity of the complex. Proteasome-targeting in cancer therapy has received significant attention because of its practical application as an established anticancer agent. We investigated whether PSMD1 plays a critical role in cancer owing to its prognostic significance. PSMD1 depletion induced cell cycle arrest in G2/M phase, DNA damage and apoptosis of cancer cells, irrespective of the p53 status. PSMD1 depletion-mediated cell death was accompanied by an increase in overall protein ubiquitination. These phenotypes occurred exclusively in cancer cells, with no effects observed in normal cells. These findings indicate that PSMD1 depletion-mediated ubiquitination of cellular proteins induces cell cycle arrest and eventual death in cancer cells, emphasizing PSMD1 as a potential therapeutic target in HCC.

IL-22 signaling promotes sorafenib resistance in hepatocellular carcinoma via STAT3/CD155 signaling axis.

Introduction: Sorafenib is currently the first-line treatment for patients with advanced hepatocellular carcinoma (HCC). Nevertheless, sorafenib resistance remains a huge challenge in the clinic. Therefore, it is urgent to elucidate the mechanisms underlying sorafenib resistance for developing novel treatment strategies for advanced HCC. In this study, we aimed to investigate the role and mechanisms of interleukin-22 (IL-22) in sorafenib resistance in HCC. Methods: The in vitro experiments using HCC cell lines and in vivo studies with a nude mouse model were used. Calcium staining, chromatin immunoprecipitation, lactate dehydrogenase release and luciferase reporter assays were employed to explore the expression and roles of IL-22, STAT3 and CD155 in sorafenib resistance. Results: Our clinical results demonstrated a significant correlation between elevated IL-22 expression and poor prognosis in HCC. Analysis of transcriptomic data from the phase-3 STORM-trial (BIOSTORM) suggested that STAT3 signaling activation and natural killer (NK) cell infiltration may associate sorafenib responses. STAT3 signaling could be activated by IL-22 administration in HCC cells, and then enhanced sorafenib resistance in HCC cells by promoting cell proliferation and reducing apoptosis in vitro and in vivo. Further, we found IL-22/STAT3 axis can transcriptionally upregulate CD155 expression in HCC cells, which could significantly reduce NK cell-mediated HCC cell lysis in a co-culture system. Conclusions: Collectively, IL-22 could contribute to sorafenib resistance in HCC by activating STAT3/CD155 signaling axis to decrease the sensitivities of tumor cells to sorafenib-mediated direct cytotoxicity and NK cell-mediated lysis. These findings deepen the understanding of how sorafenib resistance develops in HCC in terms of IL-22/STAT3 signaling pathway, and provide potential targets to overcome sorafenib resistance in patients with advanced HCC.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication.

BACKGROUND: Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered. AIM: To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy. METHODS: Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature. RESULTS: The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis. CONCLUSION: The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

MicroRNAs in hepatocellular carcinoma treatment: Charting the path forward.

MicroRNAs (miRNAs) are recognized for their involvement in the regulation of gene expression and exhibit significant potential in both the prognostic assessment and treatment of hepatocellular carcinoma (HCC). HCC, like other tumors, seldom occurs in isolation; instead, it evolves within a microenvironment featuring oncogenic and tumor-suppressive elements. When combined with suitable delivery vehicles, miRNA technology provides the capability to directly engage with these elements, thereby hindering tumor formation and progression. Ongoing research in this domain holds the promise of enabling a more efficacious and multi-modal treatment approach for HCC in the near future.

Scutellarin activates IDH1 to exert antitumor effects in hepatocellular carcinoma progression.

Isochlorate dehydrogenase 1 (IDH1) is an important metabolic enzyme for the production of α-ketoglutarate (α-KG), which has antitumor effects and is considered to have potential antitumor effects. The activation of IDH1 as a pathway for the development of anticancer drugs has not been attempted. We demonstrated that IDH1 can limit glycolysis in hepatocellular carcinoma (HCC) cells to activate the tumor immune microenvironment. In addition, through proteomic microarray analysis, we identified a natural small molecule, scutellarin (Scu), which activates IDH1 and inhibits the growth of HCC cells. By selectively modifying Cys297, Scu promotes IDH1 active dimer formation and increases α-KG production, leading to ubiquitination and degradation of HIF1a. The loss of HIF1a further leads to the inhibition of glycolysis in HCC cells. The activation of IDH1 by Scu can significantly increase the level of α-KG in tumor tissue, downregulate the HIF1a signaling pathway, and activate the tumor immune microenvironment in vivo. This study demonstrated the inhibitory effect of IDH1-α-KG-HIF1a on the growth of HCC cells and evaluated the inhibitory effect of Scu, the first IDH1 small molecule agonist, which provides a reference for cancer immunotherapy involving activated IDH1.

The m6A methyltransferase METTL5 promotes neutrophil extracellular trap network release to regulate hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets. METHODS: The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it. RESULTS: We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both in vitro and in vivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC. CONCLUSION: The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis.

Integrated analyses for identification of a three-gene signature associated with Chaihu Shugan San formula for hepatocellular carcinoma treatment.

Chaihu Shugan San (CSS) is a well-known traditional herbal formula that has the potential to ameliorate hepatocellular carcinoma (HCC); however, its mechanism of action remains unknown. Here, we identified the key targets of CSS against HCC and developed a prognostic model to predict the survival of patients with HCC. The effect of CSS plus sorafenib on HCC cell proliferation was evaluated using the MTT assay. LASSO-Cox regression was used to establish a three-gene signature model targeting CSS. Correlations between immune cells, immune checkpoints and risk score were determined to evaluate the immune-related effects of CSS. The interactions between the components and targets were validated using molecular docking and Surface Plasmon Resonance (SPR) assays. CSS and sorafenib synergistically inhibited HCC cell proliferation. Ten core compounds and 224 targets were identified using a drug compound-target network. The prognostic model of the three CSS targets (AKT1, MAPK3 and CASP3) showed predictive ability. Risk scores positively correlated with cancer-promoting immune cells and high expression of immune checkpoint proteins. Molecular docking and SPR analyses confirmed the strong binding affinities of the active components and the target genes. Western blot analysis confirmed the synergistic effect of CSS and sorafenib in inhibiting the expression of these three targets. In conclusion, CSS may regulate the activity of immune-related factors in the tumour microenvironment, reverse immune escape, enhance immune responses through AKT1, MAPK3, and CASP3, and synergistically alleviate HCC. The co-administration of sorafenib with CSS has a strong clinical outlook against HCC.

Lifestyle factors, glycemic traits, and lipoprotein traits and risk of liver cancer: a Mendelian randomization analysis.

The current state of knowledge on the relationship between lifestyle factors, glycemic traits, lipoprotein traits with liver cancer risk is still uncertain despite some attempts made by observational studies. This study aims to investigate the causal genetic relationship between factors highly associated with liver cancer incidence by using Mendelian randomization (MR) analysis. Employing MR analysis, this study utilized previously published GWAS datasets to investigate whether lifestyle factors, glycemic traits, and lipoprotein traits would affect the risk of liver cancer. The study utilized three MR methods, including inverse variance-weighted model (IVW), MR Egger, and weighted median. Furthermore, MR-Egger analyses were performed to detect heterogeneity in the MR results. The study also conducted a leave-one-out analysis to assess the potential influence of individual SNPs on the MR analysis results. MR-PRESSO was used to identify and remove SNP outliers associated with liver cancer. MR analyses revealed that 2-h glucose (odds ratio, OR 2.33, 95% confidence interval, CI 1.28-4.21), type 2 diabetes mellitus (T2DM, OR 1.67, 95% CI 1.18-2.37), body mass index (BMI, OR 1.67, 95% CI 1.18-2.37), waist circumference (OR 1.78, 95% CI 1.18-2.37) were associated with increased risk of liver cancer. On the contrary, apolipoproteins B (APOB, OR 0.67, 95% CI 0.47-0.97), and low-density lipoprotein (LDL, OR 0.62, 95% CI 0.42-0.92) were negatively related to liver cancer risk. Additionally, after adjusting for BMI, apolipoproteins A-I (APOA-I, OR 0.56, 95% CI, 0.38-0.81), total cholesterol (TC, OR 0.72, 95% CI, 0.54-0.94), and total triglycerides (TG, OR 0.57, 95% CI, 0.40-0.78) exhibited a significant inverse correlation with the risk of liver cancer. This study supports a causal relationship between 2-h glucose, T2DM, BMI, and waist circumference with the increased risk of liver cancer. Conversely, the study reveals a cause-effect relationship between TC, TG, LDL, APOA-I, and APOB with a decreased risk of liver cancer.

Prognostic Significance of Iron Metabolism and Immune-Related Genes as Risk Markers in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with significant heterogeneity, which poses challenges in predicting prognosis and treatment outcomes. The impact of iron metabolism and immune-related genes (IMRGs) on HCC patient prognoses remains elusive. We utilized The Cancer Genome Atlas (TCGA) dataset to obtain mRNA expression data and clinical information from HCC patients. Through the application of LASSO regression and univariate/multivariate Cox regression analyses, we identified five IMRGs significantly associated with survival of HCC patients. We constructed a prognostic model comprising these five genes. The model demonstrated excellent predictive performance, not only within TCGA dataset but also when validated using the Gene Expression Omnibus (GEO) dataset. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses presented significant variations in functional categories, such as apical plasma membrane and collagen-containing extracellular matrix. Several pathways, including the PI3K-AKT signaling pathway and the calcium signaling pathway, exhibited significant variations among HCC patients with varying prognoses (P < 0.05). Immune infiltration analysis indicated significantly lower levels of various immune cells, immune functions, and immune checkpoints, such as B cells, CD8+ T cells, and TILs, in the high-risk group (P < 0.05). Immunophenoscore results suggested that the low-risk group may exhibit a more favorable response to immune therapy. Furthermore, the CellMiner database predicted anti-tumor drugs significantly associated with prognostic genes (P < 0.001). In conclusion, our findings highlight the predictive role of IMRGs in prognosis and immune treatment of HCC, indicating that ADAMTS13, CRHBP, VIPR1, FCN3, and CLEC1B may serve as potential prognostic biomarkers for HCC.

Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma.

Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.

Tyrosine hydroxylase inhibits HCC progression by downregulating TGFß/Smad signaling.

The alteration of metabolic processes has been found to have significant impacts on the development of hepatocellular carcinoma (HCC). Nevertheless, the effects of dysfunction of tyrosine metabolism on the development of HCC remains to be discovered. This research demonstrated that tyrosine hydroxylase (TH), which responsible for the initial and limiting step in the bio-generation of the neuro-transmitters dopamine and adrenaline, et al. was shown to be reduced in HCC. Increased expression of TH was found facilitates the survival of HCC patients. In addition, decreased TH indicated larger tumor size, much more numbers of tumor, higher level of AFP, and the presence of cirrhosis. TH effectively impairs the growth and metastasis of HCC cells, a process dependent on the phosphorylation of serine residues (S19/S40). TH directly binds to Smad2 and hinders the cascade activation of TGFß/Smad signaling with the treatment of TGFß1. In summary, our study uncovered the non-metabolic functions of TH in the development of HCC and proposes that TH might be a promising biomarker for diagnosis as well as an innovative target for metastatic HCC.

Integration and the risk of liver cancer-Is there a real risk?

Adeno-associated virus (AAV)-based gene therapies are in clinical development for haemophilia and other genetic diseases. Since the recombinant AAV genome primarily remains episomal, it provides the opportunity for long-term expression in tissues that are not proliferating and reduces the safety concerns compared with integrating viral vectors. However, AAV integration events are detected at a low frequency. Preclinical studies in mouse models have reported hepatocellular carcinoma (HCC) after systemic AAV administration in some settings, though this has not been reported in large animal models. The risk of HCC or other cancers after AAV gene therapy in clinical studies thus remains theoretical. Potential risk factors for HCC after gene therapy are beginning to be elucidated through animal studies, but their relevance to human studies remains unknown. Studies to investigate the factors that may influence the risk of oncogenesis as well as detailed investigation of cases of cancer in AAV gene therapy patients will be important to define the potential risk of AAV genotoxicity.

Monitoring for liver cancer post-gene therapy-How much and how often?

Hepatocellular carcinoma (HCC) has long been recognized as a complication in people with chronic liver disease, particularly those with cirrhosis. Two gene therapies for haemophilia A and B recently approved in Europe and the US utilize adeno-associated virus (AAV) vectors designed to target hepatocytes. A number of other AAV gene therapies are undergoing clinical investigation for both liver and extrahepatic diseases, many of which likely transduce hepatocytes as well. Although AAV vectors predominantly persist in episomal forms, concerns about insertional mutagenesis have arisen due to findings in pre-clinical models and in a small subset of human HCC cases featuring wild-type AAV integrations in proximity to potential oncogenes. Despite the absence of any causative link between AAV vector therapy and HCC in approved extrahepatic gene therapies or haemophilia gene therapy trials, the package inserts for the recently approved haemophilia gene therapies advise HCC screening in subsets of individuals with additional risk factors. In this review, we discuss HCC risk factors, compare various screening modalities, discuss optimal screening intervals, and consider when to initiate and possibly discontinue screening. At this early point in the evolution of gene therapy, we lack sufficient data to make evidence-based recommendations on HCC screening. While AAV vectors may eventually be shown to be unassociated with risk of HCC, we presently favour a cautious approach that entails regular surveillance until such time as it is hopefully proven to be unnecessary.

[Bupleuri Radix-Paeoniae Radix Alba medicated plasma exerts effects on HepG2 hepatoma cells by regulating miR-1297/PTEN signaling axis].

The present study aimed to investigate the effect and mechanism of Bupleuri Radix-Paeoniae Radix Alba medicated plasma on HepG2 hepatoma cells by regulating the microRNA-1297(miR-1297)/phosphatase and tensin homologue deleted on chromosome 10(PTEN) signaling axis. Real-time quantitative PCR(RT-qPCR) was carried out to determine the mRNA levels of miR-1297 and PTEN in different hepatoma cell lines. The dual luciferase reporter assay was employed to verify the targeted interaction between miR-1297 and PTEN. The cell counting kit-8(CCK-8) was used to detect cell proliferation, and the optimal concentration and intervention time of the medicated plasma were determined. The cell invasion and migration were examined by Transwell assay and wound healing assay. Cell cycle distribution was detected by PI staining, and the apoptosis of cells was detected by Annexin V-FITC/PI double staining. The mRNA levels of miR-1297, PTEN, protein kinase B(Akt), and phosphatidylinositol 3-kinase(PI3K) were determined by RT-qPCR. Western blot was employed to determine the protein levels of PTEN, Akt, p-Akt, caspase-3, caspase-9, B-cell lymphoma-2(Bcl-2), and Bcl-2-associated X protein(Bax). The results showed that HepG2 cells were the best cell line for subsequent experiments. The dual luciferase reporter assay confirmed that miR-1297 could bind to the 3'-untranslated region(3'UTR) in the mRNA of PTEN. The medicated plasma inhibited the proliferation of HepG2 cells, and the optimal intervention concentration and time were 20% and 72 h. Compared with the blank plasma, the Bupleuri Radix-Paeoniae Radix Alba medicated plasma, miR-1297 inhibitor, miR-1297 inhibitor + medicated plasma all inhibited the proliferation, invasion, and migration of HepG2 cells, increased the proportion of cells in the G_0/G_1 phase, decreased the proportion of cells in the S phase, and increased the apoptosis rate. The medicated plasma down-regulated the mRNA levels of miR-1297, PI3K, and Akt and up-regulated the mRNA level of PTEN. In addition, it up-regulated the protein levels of PTEN, Bax, caspase-3, and caspsae-9 and down-regulated the protein levels of p-Akt, p-PI3K, and Bcl-2. In conclusion, Bupleuri Radix-Paeoniae Radix Alba medicated plasma can inhibit the expression of miR-1297 in HepG2 hepatoma cells, promote the expression of PTEN, and negatively regulate PI3K/Akt signaling pathway, thereby inhibiting the proliferation and inducing the apoptosis of HepG2 cells.

Research progress on oncoprotein hepatitis B X­interacting protein (Review).

Hepatitis B X­interacting protein (HBXIP) is a membrane protein located on the lysosomal surface and encoded by the Lamtor gene. It is expressed by a wide range of tumor types, including breast cancer, esophageal squamous cell carcinoma and hepatocellular carcinoma, and its expression is associated with certain clinicopathological characteristics. In the past decade, research on the oncogenic mechanisms of HBXIP has increased and the function of HBXIP in normal cells has been gradually elucidated. In the present review, the following was discussed: The normal physiological role of the HBXIP carcinogenic mechanism; the clinical significance of high levels of HBXIP expression in different tumors; HBXIP regulation of transcription, post­transcription and post­translation processes in tumors; the role of HBXIP in improving the antioxidant capacity of tumor cells; the inhibition of ferroptosis of tumor cells and regulating the metabolic reprogramming of tumor cells; and the role of HBXIP in promoting the malignant progression of tumors. In conclusion, the present review summarized the existing knowledge of HBXIP, established its carcinogenic mechanism and discussed future related research on HBXIP.

Pre-enrichment-free detection of hepatocellular carcinoma-specific ctDNA via PDMS and MEMS-based microfluidic sensor.

The growing interest in microfluidic biosensors has led to improvements in the analytical performance of various sensing mechanisms. Although various sensors can be integrated with microfluidics, electrochemical ones have been most commonly employed due to their ease of miniaturization, integration ability, and low cost, making them an established point-of-care diagnostic method. This concept can be easily adapted to the detection of biomarkers specific to certain cancer types. Pathological profiling of hepatocellular carcinoma (HCC) is heterogeneous and rather complex, and biopsy samples contain limited information regarding the tumor and do not reflect its heterogeneity. Circulating tumor DNAs (ctDNAs), which can contain information regarding cancer characteristics, have been studied tremendously since liquid biopsy emerged as a new diagnostic method. Recent improvements in the accuracy and sensitivity of ctDNA determination also paved the way for genotyping of somatic genomic alterations. In this study, three-electrode (Au-Pt-Ag) glass chips were fabricated and combined with polydimethylsiloxane (PDMS) microchannels to establish an electrochemical microfluidic sensor for detecting c.747G > T hotspot mutations in the TP53 gene of ctDNAs from HCC. The preparation and analysis times of the constructed sensor were as short as 2 h in total, and a relatively high flow rate of 30 µl/min was used during immobilization and hybridization steps. To the best of our knowledge, this is the first time a PDMS-based microfluidic electrochemical sensor has been developed to target HCC ctDNAs. The system exhibited a limit of detection (LOD) of 24.1 fM within the tested range of 2-200 fM. The sensor demonstrated high specificity in tests conducted with fully noncomplementary and one-base mismatched target sequences. The developed platform is promising for detecting HCC-specific ctDNA at very low concentrations without requiring pre-enrichment steps.

Integrative analysis unveils ECM signatures and pathways driving hepatocellular carcinoma progression: A multi-omics approach and prognostic model development.

Liver hepatocellular carcinoma (LIHC) is a highly lethal form of cancer that is among the deadliest cancer types globally. In terms of cancer-related mortality rates, liver cancer ranks among the top three, underscoring the severity of this disease. Insufficient analysis has been conducted to fully understand the potential value of the extracellular matrix (ECM) in immune infiltration and the prognostic stratification of LIHC, despite its recognised importance in the development of this disease. The scRNA-seq data of GSE149614 was used to conduct single-cell analysis on 10 LIHC samples. CellChat scores were calculated for seven cell populations in the descending cohort to investigate cellular communication, while PROGENy scores were calculated to determine tumour-associated pathway scores in different cell populations. The pathway analysis using GO and KEGG revealed the enrichment of ECM-associated genes in the pathway, highlighting the potential role of the ECM in LIHC development. By utilizing the TCGA-LIHC cohort, an ECM-based prognostic model for LIHC was developed using Lasso regression. Immune infiltration scores were calculated using two methods, and the performance of the ECM-related risk score was evaluated using an independent cohort from the CheckMate study. To determine the precise expression of ECM-associated risk genes in LIHC, we evaluated hepatocellular carcinoma cell lines using a range of assays, including Western blotting, invasion assays and Transwell assays. Using single-cell transcriptome analysis, we annotated the spatially-specific distribution of major immune cell types in single-cell samples of LIHC. The main cell types identified and annotated included hepatocytes, T cells, myeloid cells, epithelial cells, fibroblasts, endothelial cells and B cells. The utilisation of cellchat and PROGENy analyses enabled the investigation and unveiling of signalling interactions, protein functionalities and the prominent influential pathways facilitated by the primary immune cell types within the LIHC. Numerous tumour pathways, including PI2K, EGFR and TGFb, demonstrated a close correlation with the involvement of ECM in LIHC. Moreover, an evaluation was conducted to assess the primary ECM-related functional changes and biological pathway enrichment in LIHC. Differential genes associated with ECM were identified and utilised to create prognostic models. The prognostic stratification value of these models for LIHC patients was confirmed through validation in multiple databases. Furthermore, through immune infiltration analysis, it was discovered that ECM might be linked to the irregular expression and regulation of numerous immune cells. Additionally, histone acetylation was mapped against gene mutation frequencies and differential expression profiles. The prognostic stratification efficacy of the ECM prediction model constructed in the context of PD-1 inhibitor therapy was also examined, and it exhibited strong stratification performance. Cellular experiments, including Western blotting, invasion and Transwell assays, revealed that ECM-associated risk genes have a promoting effect on the development of LIHC. The creation of biomarkers for LIHC using ECM-related genes unveiled substantial correlations with immune microenvironmental infiltration and functional mutations in various tumour pathways. This enlightens us to the possibility that the influence of ECM on tumours may extend beyond simply promoting the fibrotic process and the stromal composition of tumours.

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients.

Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups related to ARLncRNAs. Results: The screening process identified 27 ARLncRNAs, with 13 being associated with HCC prognosis. Consequently, a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC. Patients in the high-risk group showed very poor prognoses in most clinical categories. The Riskscore was closely related to immune cell scores, such as macrophages, and the DEGs between different groups were implicated in metabolism, cell cycle, and mitotic processes. Notably, high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel, suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC. We further identified C2 as the Paclitaxel subtype, where patients exhibited higher Riskscores, reduced survival rates, and more severe clinical progression. Conclusion: The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC. The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression. With the identification of ARLncRNAs-related isoforms, these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.

Investigation of the feasibility of NRAV as a biomarker for hepatocellular carcinoma.

The long non-coding RNA, Negative Regulator of Antiviral Response (NRAV) has been identified as a participant in both respiratory virus replication and immune checkpoints, however, its involvement in pan-cancer immune regulation and prognosis, particularly those of hepatocellular carcinoma (HCC), remains unclear. To address this knowledge gap, we analyzed expression profiles obtained from The Cancer Genome Atlas (TCGA) database, comparing normal and malignant tumor tissues. We found that NRAV expression is significantly upregulated in tumor tissues compared to adjacent nontumor tissues. Kaplan-Meier (K-M) analysis revealed the prognostic power of NRAV, wherein overexpression was significantly linked to reduced overall survival in a diverse range of tumor patients. Furthermore, noteworthy associations were observed between NRAV, immune checkpoints, immune cell infiltration, genes related to autophagy, epithelial-mesenchymal transition (EMT), pyroptosis, tumor mutational burden (TMB), and microsatellite instability (MSI) across different cancer types, including HCC. Moreover, NRAV upregulation expression was associated with multiple pathological stages by clinical observations. Furthermore, our investigation revealed a substantial elevation in the expression of NRAV in both HCC tumor tissues and cells compared to normal tissues and cells. The inhibition of NRAV resulted in the inhibition of cell proliferation, migration, and invasion in HCC cells, while also influencing the expression of CD274 (PD-L1) and CD44, along with various biomarkers associated with EMT, autophagy, and pyroptosis. The aforementioned results propose NRAV as a promising prognostic biomarker for HCC.

Degradation of FAK-targeting by proteolytic targeting chimera technology to inhibit the metastasis of hepatocellular carcinoma.

Liver cancer is a prevalent malignant cancer, ranking third in terms of mortality rate. Metastasis and recurrence primarily contribute to the high mortality rate of liver cancer. Hepatocellular carcinoma (HCC) has low expression of focal adhesion kinase (FAK), which increases the risk of metastasis and recurrence. Nevertheless, the efficacy of FAK phosphorylation inhibitors is currently limited. Thus, investigating the mechanisms by which FAK affects HCC metastasis to develop targeted therapies for FAK may present a novel strategy to inhibit HCC metastasis. This study examined the correlation between FAK expression and the prognosis of HCC. Additionally, we explored the impact of FAK degradation on HCC metastasis through wound healing experiments, transwell invasion experiments, and a xenograft tumor model. The expression of proteins related to epithelial-mesenchymal transition (EMT) was measured to elucidate the underlying mechanisms. The results showed that FAK PROTAC can degrade FAK, inhibit the migration and invasion of HCC cells in vitro, and notably decrease the lung metastasis of HCC in vivo. Increased expression of E-cadherin and decreased expression of vimentin indicated that EMT was inhibited. Consequently, degradation of FAK through FAK PROTAC effectively suppressed liver cancer metastasis, holding significant clinical implications for treating liver cancer and developing innovative anti-neoplastic drugs.