Objective:To construct a prognostic risk model based on lactate metabolism-related genes screened using bioinformatics methods in renal cell carcinoma patients，and investigate the clinical prognosis and immune characteristics of renal cell carcinoma.Methods:Gene expression data and clinical information of patients with renal cell carcinoma were downloaded from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma（TCGA-KIRC）dataset. Lactate metabolism-related gene sets were obtained from the Gene Set Enrichment Analysis（GSEA）database. The R package DEseq2 was employed to identify differentially expressed genes associated with lactate metabolism within the TCGA-KIRC dataset. GO and KEGG enrichment analyses were performed using the clusterProfiler package. Prognosis-related genes were screened via univariate Cox regression analysis and the intersection with lactate metabolism-related differentially expressed genes was obtained. A risk model was constructed using LASSO regression followed by multivariate Cox regression analysis to calculate risk scores. This risk model was subsequently validated using the GSE29609 dataset. Patients were stratified into high-risk and low-risk groups based on the median risk score. The expression profiles of key immune molecule genes and immune checkpoint genes were compared between the two groups. Survival analysis curves for immune checkpoint genes were generated using the survival and survminer R packages. Differences in tumor mutation burden（TMB）between the high-risk and low-risk groups were assessed，and corresponding TMB survival analysis curves were plotted. Finally，the tumor immune dysfunction and exclusion（TIDE）algorithm was used to evaluate disparities in immunotherapy response potential between the two risk groups.Results:An optimal prognostic risk model incorporating seven lactate metabolism- and prognosis-related genes（ LDHD，PER2，ACADM，FLI1，LIPA，TCIRG1，SLC25A4）was constructed and successfully validated in the GSE29609 dataset. Univariate Cox regression analysis revealed that a high-risk score was significantly associated with poor prognosis（ HR=2.915，95% CI：2.451-3.470， P<0.001）. Multivariate Cox regression analysis confirmed that this risk model could serve as an independent prognostic factor for patients with renal cell carcinoma（ HR=2.231，95% CI：1.829-2.722， P<0.001）. Patients in the high-risk group exhibited significantly worse outcomes compared to the low-risk group，regardless of whether they had early-stage or advanced-stage renal cell carcinoma（both P<0.001）. Analyses related to the immune microenvironment indicated an upregulated immunosuppressive phenotype in the high-risk group. Furthermore，the TMB was significantly higher in the high-risk group than in the low-risk group（ P=0.032），and patients within the high-risk group exhibiting higher TMB levels demonstrated even poorer survival（ P<0.001）. Finally，the TIDE score was significantly elevated in the high-risk group in comparison to the low-risk group（ P<0.001）. Conclusions:The risk model based on lactate metabolism-related genes constructed in this study can guide the prognosis of renal cell carcinoma. Patients in the high-risk group are more prone to immune escape and formation of an inhibitory immune microenvironment，leading to worse prognoses. This risk model may serve as a biomarker for predicting immunotherapy response.

Metabolic associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver disease worldwide， and its progression to liver fibrosis is a key influencing factor for prognosis and the risk of complications. In recent years， novel drugs， such as selective thyroid hormone receptor-β agonists， glucagon-like peptide-1 receptor agonists， and fibroblast growth factor 21 analogs， have shown preliminary efficacy in the treatment of MAFLD-related liver fibrosis； however， such drugs have limited overall effectiveness， and there is still a lack of ideal therapeutic strategy to address the disease across its different stages. Traditional Chinese medicine （TCM）， with its characteristics of multiple targets and systemic regulation， has shown unique advantages in this field. This article systematically reviews the basic and clinical research on the anti-fibrotic mechanisms of compound TCM prescriptions and their active components in recent years， focusing on the key processes including hepatic stellate cell activation， lipid metabolism disorders， oxidative stress， immune inflammation， and gut-liver axis dysfunction. Meanwhile， it is pointed out that there are still certain issues in current research， including ambiguities in the clarification of mechanisms， a lack of standardized evaluation systems， and the need to improve the quality of clinical evidence. Future research should emphasize the standardization and quality control of TCM herbal preparations and integrate emerging technologies， such as omics analysis， organoid models， and real-world data， to advance TCM intervention of MAFLD-related liver fibrosis toward well-defined mechanisms， clear therapeutic pathways， and robust scientific evidence. TCM is expected to play a vital role in the multi-dimensional targeted intervention and stage-specific management of MAFLD-related liver fibrosis， in order to provide new perspectives and comprehensive solutions for the precise treatment of chronic liver diseases.

Objective To investigate the effects of glutathione peroxidase 7(GPX7)on the proliferation and senescence of hepatocellular carcinoma(HCC)cells and its potential value as a therapeutic target.Methods Clinical and transcriptomic data from HCC patients in The Cancer Genome Atlas(TCGA)database were analyzed to evaluate the relationship between GPX7 expression and prognosis.Western blotting,qRT-PCR,CCK-8 assay,EdU staining,and SA-β-Gal staining were employed to compare the expression and function of GPX7 in HCC cell lines and normal liver cells.A stable GPX7-knockdown Hep3B cell line was established,and transcriptomic changes were analyzed using RNA-seq.The PI3K inhibitor LY294002 and its activator 740 Y-P were utilized to determine the role of GPX7 in regulating cell senescence via the PI3K-AKT pathway.An orthotopic xenograft model was constructed using 18 male nude mice(6 weeks old,18～22 g)to observe tumor growth.Tumor and adjacent tissue samples from 56 HCC patients(obtained from the Eighth Medical Center of Chinese PLA General Hospital between January 2012 and December 2022)were analyzed to assess the relationship between GPX7 expression and clinicopathological features.Results TCGA data analysis revealed that GPX7 was significantly highly expressed in HCC tumor tissues(P<0.01),and the patients with high GPX7 expression had obviously shorter overall survival(OS)(P=0.018).Western blotting and qRT-PCR showed that the expression level of GPX7 was notably higher in the HCC cell lines than the normal liver cells(P<0.01).After GPX7 knockdown,the CCK-8 absorbance values of HCC cells were significantly reduced(P<0.01),the proportion of EdU-positive cells was obviously decreased(P<0.01),and the proportion of SA-β-Gal positive cells was notably increased(P<0.01).RNA-seq analysis revealed that differentially expressed genes were significantly enriched in the PI3K-AKT signaling pathway(P<0.05).The PI3K inhibitor LY294002 significantly enhanced the GPX7 knockdown-induced cell senescence(P<0.01),while the activator 740 Y-P partially reversed this effect(P<0.05).In the xenograft model,GPX7 knockdown significantly inhibited tumor growth in nude mice(P<0.01),and the PI3K activator 740 Y-P partially reversed this effect(P<0.01).Clinical sample analysis displayed that high GPX7 expression was negatively correlated with tumor differentiation(P<0.05),and its high expression was associated with shortened OS(HR=2.61,95%CI:1.26～5.39,P=0.005).Conclusion GPX7 regulates cell proliferation and senescence through the PI3K-AKT pathway,and may serve as a potential therapeutic target for HCC treatment.

Objective To investigate the effects of insulin-like growth factor binding protein 7(IGFBP7)on the sensitivity of glioma cells to temozolomide(TMZ)and the related mechanism.Methods IGFBP7 mRNA expression levels in TMZ-sensitive(U87 TMZ-S,U251 TMZ-S)and TMZ-resistant(U87 TMZ-R,U251 TMZ-R)glioma cells were analyzed using RNA sequencing data from the gene expression omnibus(GEO)dataset GSE151680.TMZ-resistant U87 and U251 cell lines were established via stepwise dose escalation.IGFBP7 expressions in TMZ-R cells were detected by quantitative real-time PCR(qPCR)and Western blotting.IGFBP7 was stably knock-downed in TMZ-R cells while IGFBP7 was stably overexpressed in TMZ-S cells using lentiviral infection.Cell viability,migration,invasion and TMZ sensitivity were assessed using CCK-8 assay,apoptosis assay,wound healing assay,Transwell invasion assay and colony formation assay respectively.Cellular senescence was detected by β-galactosidase(SA-β-Gal)staining.The expression levels of senescence molecular markers cyclin-dependent kinase inhibitor 1(p21)and tumor protein p53(p53),as well as DNA damage marker γ-H2A histone family member X(γ-H2AX)were determined by Western blotting.The differences in mRNA expressions of IGFBP7 between glioma tissues and normal tissues as well as the correlations with the overall survival of glioma patients were analyzed using the cancer genome atlas(TCGA),Chinese Glioma Genome Atlas(CGGA),genotype-tissue expression(GTEx)database.Results Compared to normal glioma cells,IGFBP7 expressions were significantly elevated in TMZ-R glioma cells.Overexpression of IGFBP7 in TMZ-S glioma cells enhanced cell viability but suppressed apoptosis following TMZ treatment.The expressions of senescence-associated marker(p21,p53)and DNA damage marker(γ-H2AX)were upregulated in these cells.Notably,IGFBP7 expressions were significantly higher in glioma tissues than in normal tissues,and high IGFBP7 expressions were associated with poor prognosis in glioma patients.Conclusion Knockdown of IGFBP7 promotes TMZ-induced cell senescence and DNA damage,thereby enhancing the sensitivity of gliomas cells to TMZ.

Objective:To construct a prognostic risk model based on lactate metabolism-related genes screened using bioinformatics methods in renal cell carcinoma patients，and investigate the clinical prognosis and immune characteristics of renal cell carcinoma.Methods:Gene expression data and clinical information of patients with renal cell carcinoma were downloaded from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma（TCGA-KIRC）dataset. Lactate metabolism-related gene sets were obtained from the Gene Set Enrichment Analysis（GSEA）database. The R package DEseq2 was employed to identify differentially expressed genes associated with lactate metabolism within the TCGA-KIRC dataset. GO and KEGG enrichment analyses were performed using the clusterProfiler package. Prognosis-related genes were screened via univariate Cox regression analysis and the intersection with lactate metabolism-related differentially expressed genes was obtained. A risk model was constructed using LASSO regression followed by multivariate Cox regression analysis to calculate risk scores. This risk model was subsequently validated using the GSE29609 dataset. Patients were stratified into high-risk and low-risk groups based on the median risk score. The expression profiles of key immune molecule genes and immune checkpoint genes were compared between the two groups. Survival analysis curves for immune checkpoint genes were generated using the survival and survminer R packages. Differences in tumor mutation burden（TMB）between the high-risk and low-risk groups were assessed，and corresponding TMB survival analysis curves were plotted. Finally，the tumor immune dysfunction and exclusion（TIDE）algorithm was used to evaluate disparities in immunotherapy response potential between the two risk groups.Results:An optimal prognostic risk model incorporating seven lactate metabolism- and prognosis-related genes（ LDHD，PER2，ACADM，FLI1，LIPA，TCIRG1，SLC25A4）was constructed and successfully validated in the GSE29609 dataset. Univariate Cox regression analysis revealed that a high-risk score was significantly associated with poor prognosis（ HR=2.915，95% CI：2.451-3.470， P<0.001）. Multivariate Cox regression analysis confirmed that this risk model could serve as an independent prognostic factor for patients with renal cell carcinoma（ HR=2.231，95% CI：1.829-2.722， P<0.001）. Patients in the high-risk group exhibited significantly worse outcomes compared to the low-risk group，regardless of whether they had early-stage or advanced-stage renal cell carcinoma（both P<0.001）. Analyses related to the immune microenvironment indicated an upregulated immunosuppressive phenotype in the high-risk group. Furthermore，the TMB was significantly higher in the high-risk group than in the low-risk group（ P=0.032），and patients within the high-risk group exhibiting higher TMB levels demonstrated even poorer survival（ P<0.001）. Finally，the TIDE score was significantly elevated in the high-risk group in comparison to the low-risk group（ P<0.001）. Conclusions:The risk model based on lactate metabolism-related genes constructed in this study can guide the prognosis of renal cell carcinoma. Patients in the high-risk group are more prone to immune escape and formation of an inhibitory immune microenvironment，leading to worse prognoses. This risk model may serve as a biomarker for predicting immunotherapy response.

BACKGROUND: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. METHODS: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately. RESULTS: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. CONCLUSIONS In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
Male ; Humans ; Female ; Coronary Artery Disease/genetics* ; Biological Specimen Banks ; East Asian People ; Risk Assessment/methods* ; Genetic Predisposition to Disease/genetics* ; Risk Factors ; Genome-Wide Association Study

Lamin B1 (LMNB1) is highly expressed in liver cancer tissues, and its influence and mechanism on the proliferation of hepatocellular carcinoma cells were explored by knocking down the expression of the protein. In liver cancer cells, siRNAs were used to knock down LMNB1. Knockdown effects were detected by Western blotting. Changes in telomerase activity were detected by telomeric repeat amplification protocol assay (TRAP) experiments. Telomere length changes were detected by quantitative real-time polymerase chain reaction (qPCR). CCK8, cloning formation, transwell and wound healing were performed to detect changes in its growth, invasion and migration capabilities. The lentiviral system was used to construct HepG2 cells that steadily knocked down LMNB1. Then the changes of telomere length and telomerase activity were detected, and the cell aging status was detected by SA-β-gal senescence staining. The effects of tumorigenesis were detected by nude mouse subcutaneous tumorigenesis experiments, subsequent histification staining of tumors, SA-β-gal senescence staining, fluorescence in situ hybridization (FISH) for telomere analysis and other experiments. Finally, the method of biogenesis analysis was used to find the expression of LMNB1 in clinical liver cancer tissues, and its relationship with clinical stages and patient survival. Knockdown of LMNB1 in HepG2 and Hep3B cells significantly reduced telomerase activity, cell proliferation, migration and invasion abilities. Experiments in cells and tumor formation in nude mice had demonstrated that stable knockdown of LMNB1 reduced telomerase activity, shortened telomere length, senesced cells, reduced cell tumorigenicity and KI-67 expression. Bioinformatics analysis showed that LMNB1 was highly expressed in liver cancer tissues and correlated with tumor stage and patient survival. In conclusion, LMNB1 is overexpressed in liver cancer cells, and it is expected to become an indicator for evaluating the clinical prognosis of liver cancer patients and a target for precise treatment.
Animals ; Mice ; Telomerase/metabolism* ; Carcinoma, Hepatocellular/genetics* ; Liver Neoplasms/genetics* ; Telomere Shortening ; In Situ Hybridization, Fluorescence ; Mice, Nude ; Telomere/pathology* ; Carcinogenesis

Objective:To investigate the expression of forkhead box protein O3(FOXO3) in pancreatic cancer and its effect on the motility and proliferation of pancreatic cancer cells.Methods:The FOXO3 expression in pancreatic cancer and adjacent tissues was retrieved from LinkedOmics database. Western blotting and real-time quantitative polymerase chain reaction were used to detect FOXO3 expression in pancreatic cancer cells and human pancreatic stellate cells. PANC-1 and MIAPaCa-2 pancreatic cancer cells with low FOXO3 expression were selected to transfect FOXO3 overexpression plasmid and negative control plasmid, respectively. The motility and proliferation ability of pancreatic cancer cells were detected by colony formation assay, cell scratch assay, Transwell assay and flow cytometry.Results:In the LinkedOmics database, the relative expression of FOXO3 protein in the cancer tissues of 64 patients with pancreatic cancer was significantly lower than that in the adjacent tissues ( t=8.36, P<0.001). The number of clones in PANC-1 cell line was (30.0±6.6) after overexpressed FOXO3, which was lower than that in negative control cells (92.7±6.7), and the difference was statistically significant ( t=11.54, P<0.001). After overexpressed FOXO3 in PANC-1 and MIAPaCa-2 cell lines, the scratch repair rate was significantly decreased compared with the control group. In Transwell experiment, the number of cells in FOXO3 overexpressed group in PANC-1 cell lines was (21.0±6.6), which was lower than that of negative control groups (55.7±8.5), and the difference was statistically significant ( t=5.59, P=0.005). The results of MIAPaCa-2 cell line were consistent with that of PANC-1 cell line. After overexpressing of FOXO3 in PANC-1 and MIAPaCa-2 cell lines, the proportion of cells in the G0/G1 phase decreased, while the proportion in the S phase increased. Conclusion:The expression of FOXO3 was decreased in pancreatic cancer. Overexpression of FOXO3 could significantly inhibit the proliferation, migration and invasion of pancreatic cancer cells and induce cell cycle arrest, which is a potential target for the treatment of pancreatic cancer.

BACKGROUND: Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults. METHODS: We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality. RESULTS: Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease. CONCLUSION Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.
Aged ; Arthritis, Rheumatoid ; Asians ; China/epidemiology* ; Humans ; Hypertension ; Middle Aged ; Multimorbidity