A Model of Basement Membrane-Associated Gene Signature Predicts Liver Hepatocellular Carcinoma Response to Immune Checkpoint Inhibitors.

Liver hepatocellular carcinoma (LIHC) is a highly lethal malignant tumor originating from the digestive system, which is a serious threat to human health. In recent years, immunotherapy has shown significant therapeutic effects in the treatment of LIHC, but only for a minority of patients. The basement membrane (BM) plays an important role in the occurrence and development of tumors, including LIHC. Therefore, this study is aimed at establishing a risk score model based on basement membrane-related genes (BMRGs) to predict patient prognosis and response to immunotherapy. First, we defined three patterns of BMRG modification (C1, C2, and C3) by consensus clustering of BMRG sets and LIHC transcriptome data obtained from public databases. Survival analysis showed that patients in the C2 group had a better prognosis, and Gene Set Variation Analysis (GSVA) revealed that the statistically significant pathways were mainly enriched in the C2 group. Moreover, we performed Weighted Correlation Network Analysis (WGCNA) on the above three subgroups and obtained 179 intersecting genes. We further applied function enrichment analyses, and the results demonstrated that they were mainly enriched in metabolism-related pathways. Furthermore, we conducted the LASSO regression analysis and obtained 4 BMRGs (MPV17, GNB1, DHX34, and MAFG) that were significantly related to the prognosis of LIHC patients. We further constructed a prognostic risk score model based on the above genes, which was verified to have good predictive performance for LIHC prognosis. In addition, we analyzed the correlation between the risk score and the tumor immune microenvironment (TIM), and the results showed that the high-risk scoring group tended to be in an immunosuppressed status. Finally, we investigated the relationship between the risk score and LIHC immune function. The results demonstrated that the risk score was closely related to the expression levels of multiple immune checkpoints. Patients in the low-risk group had significantly higher IPS scores, and patients in the high-risk group had lower immune escape and TIDE score. In conclusion, we established a novel risk model based on BMRGs, which may serve as a biomarker for prognosis and immunotherapy in LIHC.

Prediction of Prognosis in Patients with Hepatocellular Carcinoma Based on Molecular Subtypes of Immune Genes.

For those patients with hepatocellular carcinoma (HCC), it is really a heavy burden. Herein, the immune genes of HCC were analyzed in groups to determine prognostic biomarkers related to immune genes in HCC. The mRNA data, clinical data in TCGA-LIHC dataset, and immune gene in the ImmPort database were collected for the combining usage with K-means concordance clustering to cluster HCC patients according to the immune gene matrix. Based on ssGSEA analysis result, HCC patients were sorted into high- and low-immune subtypes, and survival curve presented that patients in high-immune subtypes had a better prognosis. Subsequently, differential expression analysis was performed to obtain immune-related differentially expressed genes (IRGs). Cox and lasso analyses were performed for obtaining five optimal immune genes related to prognosis, and a risk assessment model was then established. Patient samples in the training and validation sets were, respectively, divided into high- and low-risk groups. K-M survival curves presented a better prognosis of patients in the low-risk group than in the high-risk group. The ROC curve indicated that this model was finely used for the prediction of prognosis. In addition, immune infiltration assessment revealed that NR0B1 and FGF9 had potential to impact the tumor immune microenvironment. Finally, using qRT-PCR and transwell assays, it was demonstrated that the macrophage chemotaxis was enhanced when NR0B1 and FGF9 were highly expressed in HCC cells. In general, a 5-gene prognostic risk assessment model was constructed based on immune genes and bioinformatics analysis methods, which provides some reference for the prognosis of HCC as well as immunotherapy.

Immune Analysis and Small Molecule Drug Prediction of Hepatocellular Carcinoma Based on Single Sample Gene Set Enrichment Analysis.

Though patients with hepatocellular carcinoma (HCC) benefit from the treatment of immune checkpoint inhibitor (ICB), it is still of vital significance to develop more effective drugs and predict patients' response to ICB therapy. Herein, we utilized single sample gene set enrichment analysis (ssGSEA) to score the downloaded tumor samples from TCGA-LIHC based on 29 immune gene sets, thus reflecting the immunologic competence of samples. Then samples were classified into high, moderate, and low immunity groups. Additionally, we utilized survival analysis and ESTIMATE score to verify the reliability of the immunity grouping. We then performed differential expression analysis on the samples in these two groups and obtained 716 differentially expressed genes (DEGs). Next, the DEGs mentioned above were subjected to GO and KEGG analyses. The outcomes demonstrated that these DEGs were mostly correlated with the immune-related biological functions. To further verify biological processes in which DEGs might be involved, we constructed a protein-protein interaction network. Afterward, we used MCODE plugin to conduct subnetwork analysis. Thereafter, KEGG enrichment analysis was performed on two genes with the highest score in the subnetwork. The results exhibited that these genes were gathered in pathways such as Th1 and Th2 cell differentiation and NF-κB. Finally, we utilized Connectivity Map to find possible drugs for the treatment of HCC and obtained complex methyl-angolensate. The above results may contribute to distinguishing HCC patients who are eligible for immunotherapy and providing the foundations for the development of therapeutic drugs for HCC.

[Effects of Xinjierkang on two kidney one clip-induced hypertension and target organ injury in rats].

OBJECTIVE: To investigate the effects of Xinjierkang on two kidney one clip -induced hypertension and target organ injury in rats. METHODS: Two kidney one clip-induced hypertension rats model was established. Rats were divided into control group, model group, Xinjierkang group, and fosinopril group. At the end of 8th w, the hemodynamics indexes were recorded. The cardiac hypertrophy index was expressed as heart weight/body weight (HW/BW), the histological changes of heart, aorta and kidney were investigated by HE and/or Van Gieson stain. RESULTS: Compared with control group, the heart systolic and diastolic function were impaired, the heart weight index, cardiomyocytes cross section area (CSA), cardiac collagen deposition, vascular remodeling index and glomerulus area were increased markedly in model group rats. Administration of Xinjierkang and fosinopril markedly ameliorated hemodynamic indexes, inhibited the elevation of HW/BW ratio, CSA of cardiomyocytes, vascular remodeling index and glomerulus hypertrophy, decreased collagen deposition in heart. CONCLUSION: Xinjierkang has protective effects against two kidney one clip-induced hemodynamic impairment, cardiovascular remodeling and glomerulus hypertrophy in rats.

[Effects of a compound Chinese medicine Xinji' erkang on isoproterenol-induced ventricular remodeling in mice].

OBJECTIVE: To investigate the effects of Xinji' erkang (XJEK), a compound Chinese herbal medicine, on isoproterenol-induced ventricular remodeling in mice. METHODS: Isoproterenol was given subcutaneously (1 mg/kg, twice per day for 7 d) to induce ventricular remodeling in mice. Mice were divided into normal control group, model group, XJEK low-, medium- and high- dose groups, XJEK water layer group, XJEK n-butanol layer group and metoprolol group. All drugs were given by intragastric administration. At the end of the 7th day, the hearts of the rats were weighted, and myocardial hypertrophy index was expressed as heart weight/body weight (HW/BW). The histological changes were observed by hemotoxylin-eosin and Van Gieson staining. Colorimetric method was used to determine the content of hydroxyproline in heart, and the activity of superoxide dismutase (SOD) and the content of malondialdehyde (MDA) in serum. RESULTS: Compared with the isoproterenol injection only, XJEK potently inhibited cardiomyocyte hypertrophy and the increase of hydroxyproline content in heart (P<0.01), improved cardiac pathology change, inhibited the decrease of SOD activity and the increase of MDA content in serum (P<0.01). XJEK water layer also inhibited the increase of cardiomyocyte hypertrophy (P<0.01) while XJEK n-butanol layer inhibited cardiomyocyte hypertrophy and fibrosis (P<0.01). CONCLUSION: XJEK possesses protective effects against isoproterenol-induced ventricular remodeling in mice, which may be related to its actions in reducing the oxidative stress and improving the antioxidant activity of the body. XJEK water layer and XJEK n-butanol layer attenuated ventricular remodeling without significant oxidative stress state changing, which indicates that a non-antioxidative stress mechanism may exist.