Zhipeng Liu’s research while affiliated with First Affiliated Hospital of China Medical University and other places

Background and aims Alcohol-related liver disease (ALD) is a worldwide burden. Cuproptosis has been shown to play a key role in the development of several diseases. However, the role and mechanisms of cuproptosis in ALD remain unclear. Methods The RNA-sequencing data of ALD liver samples were downloaded from the Gene Expression Omnibus (GEO) database. Bioinformatical analyses were performed using the R data package. We then identified key genes through multiple machine learning methods. Immunoinfiltration analyses were used to identify different immune cells in ALD patients and controls. The expression levels of key genes were further verified. Results We identified three key cuproptosis-related genes (CRGs) (DPYD, SLC31A1, and DBT) through an in-depth analysis of two GEO datasets, including 28 ALD samples and eight control samples. The area under the curve (AUC) value of these three genes combined in determining ALD was 1.0. In the external datasets, the three key genes had AUC values as high as 1.0 and 0.917, respectively. Nomogram, decision curve, and calibration curve analyses also confirmed these genes’ ability to predict the diagnosis. These three key genes were found to be involved in multiple pathways associated with ALD progression. We confirmed the mRNA expression of these three key genes in mouse ALD liver samples. Regarding immune cell infiltration, the numbers of B cells, CD8 (+) T cells, NK cells, T-helper cells, and Th1 cells were significantly lower in ALD patient samples than in control liver samples. Single sample gene set enrichment analysis (ssGSEA) was then used to estimate the immune microenvironment of different CRG clusters and CRG-related gene clusters. In addition, we calculated CRG scores through principal component analysis (PCA) and selected Sankey plots to represent the correlation between CRG clusters, gene clusters, and CRG scores. Finally, the three key genes were confirmed in mouse ALD liver samples and liver cells treated with ethanol. Conclusions We first established a prognostic model for ALD based on 3 CRGs and robust prediction efficacy was confirmed. Our investigation contributes to a comprehensive understanding of the role of cuproptosis in ALD, presenting promising avenues for the exploration of therapeutic strategies.

Background and aims Cuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI). Methods The datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes. Results Seventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues. Conclusion Our findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI.

Background and Aims Acute hepatitis E (AHE) is still a public health issue worldwide. Here, we report the global burden of AHE in 204 countries and territories from 1990 to 2019 by age, sex and socio‐demographic index (SDI), and predict the future trends to 2030. Methods Data on AHE were collected from the Global Burden of Diseases, Injuries and Risk Factors Study 2019. The average annual percentage change (AAPC) and joinpoint analysis were used to determine the burden trend. Results In 2019, there were 19.47 million (95% UI, 16.04 to 23.37 million) incident cases of AHE globally, with a 19% increase since 1990. Age‐standardized rate (ASR) of disability‐adjusted life years (DALYs), prevalent and incident cases declined from 1990 to 2019. In 2019, the ASR of incidence, prevalence and DALYs due to HEV infection were highest in the same regions of South Asia for both sexes. Southern Sub‐Saharan Africa presented the highest increases in the ASR for incidence of HEV infection in both males (AAPC = .25) and females (AAPC = .24) from 1990 to 2019. Incident cases are higher in males than females before 55–59 years old. The SDI values were negatively correlated with the age‐standardized DALYs. Between 2019 and 2030, the ASR for incidence and prevalence of HEV for both sexes showed an increasing trend. Conclusions Although the overall ASR of AHE decreased, the burden of AHE remains an underappreciated problem for society. The findings may provide useful information for policymakers to develop appropriate strategies aimed at reducing the burden of AHE.

Background and aims Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Method The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes. Results Four datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples. Conclusion Our study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.

Purpose Cuproptosis is a novel mechanism of copper-dependent cell death mechanism that can regulate the progression, immune response, and prognosis of tumors. However, the potential roles of cuproptosis-related genes (CRGs) in the clinical outcomes, tumor microenvironment (TME), and immunotherapy of pancreatic cancer (PC) remain unclear. Methods We comprehensively evaluated the CRG patterns in PC samples from two GEO datasets and TCGA based on 19 CRGs. LASSO and multivariate Cox regression were used to construct the cuproptosis model, and a nomogram was constructed to predict the sensitivity of anticancer drugs. Results Methylation regulated the expression level of eight CRGs in PC. Three distinct cuproptosis-related patterns with different biological processes and prognoses were developed. The immune infiltration features of the three cuproptosis patterns were immune-excluded, immune-inflamed, and immune-desert phenotypes, respectively. Higher expression of CRGs indicated a poor prognosis of PC. Based on the cuproptosis phenotype associated signature genes, we constructed a cuproptosis score to study the cuproptosis modification pattern of the individual sample. Univariate and multivariate Cox regression analyses confirmed the cuproptosis risk score model is an independent prognosis biomarker. The high-risk group was characterized by poor prognosis, high expression of CRGs, high frequency of mutation and immune activation, and immunotherapy advantage. The sensitivity of anticancer drugs was significantly different between the high- and low-risk score groups. CRG pattern associated with the clinical-pathological features, TME, and prognosis of PC. Conclusions The newly developed cuproptosis model could guide the design of individualized treatment strategies and facilitate accurate prognosis prediction for PC.

Aims Global healthcare costs are significantly increased by acute hepatitis C. In this study, our goal was to assess the prevalence, incidence, and years lived with disability (YLDs) of acute hepatitis C globally in terms of numbers, age-standardized rates (ASRs), and percent changes. Methods Data on acute hepatitis C were acquired from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Numbers, ASRs, and percent changes of prevalence, incidence, and YLDs’ rates per 100,000 population were systematically analysed using the GBD 2019 modelled data. Results In 2019, acute hepatitis C numbers were 636,315.62 (95% uncertainty interval (UI): 560,704.41–736,991.98), 5,514,735.38 (95% UI: 4,859,438.18–6,387,263.87) and 8914.5 (95% UI: 4256.87–17539.11) for the point prevalence, incidence, and YLDs, respectively. The ASRs were 8.53 (95% UI: 7.54–9.88), 73.93 (95% UI: 65.33–85.60), and 0.12 (95% UI: 0.06–0.24) per 100,000 population for the point prevalence, incidence, and YLDs, respectively. From 1990 to 2019, the percent changes in the age-standardized prevalence, incidence, and YLDs rates decreased. Moreover, Central Sub-Saharan Africa, Central Asia, and Western Sub-Saharan Africa had the highest age-standardized prevalence, incidence, and YLDs rates in 2019. Notably, China exhibited the largest decrease in percentage change in the ASR prevalence, incidence, and YLDs from 1990 to 2019. Additionally, Egypt, Mongolia, and Angola had the highest burden of acute hepatitis C from 1990 to 2019. Conclusions Globally, the burden of acute hepatitis C has decreased significantly in many countries over the last 30 years. However, it continues to increase in low-income countries. Therefore, more international cooperation and multifaceted and multisectoral actions are required for the better monitoring of acute hepatitis C.

Background Liver cancer is one of the most common cancers worldwide. We aimed to report the burden of liver cancer at the global, regional, and national levels in 204 countries from 1990 to 2019, stratified by etiology, sex, age, and sociodemographic index (SDI). Methods Data of mortality, incidence, and disability-adjusted life years (DALYs) of liver cancer and its etiology were available from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2019. The trends in the liver cancer burden were assessed by the annual percentage change. All estimates are presented as numbers and age-standardized rates (ASRs) per 100,000 population, with uncertainty intervals (UIs). Results Globally, 484,577 (95% UI 444,091–525,798) mortalities, 534,364 (486,550–588,639) incident cases, and 12,528,422 (11,400,671–13,687,675) disability-adjusted life years (DALYs) due to liver cancer occurred in 2019. The ASRs were 5.95 (5.44–6.44), 6.51 (5.95–7.16), and 151.08 (137.53–164.8) per 100,000 population for the mortalities, incidences, and DALYs, respectively. From 1990 to 2019, the numbers increased, whereas the ASRs decreased. Hepatitis B and Hepatitis C are the major causes of liver cancer mortality. The liver cancer mortality in 2019 increased with age, peaking at 65–69 and 70–74 age group in males and females, respectively, and the number was higher in males than in females. Generally, there were nonlinear associations between the ASR and SDIs values at the regional and national levels. China had the highest numbers of mortalities, incident cases, and DALYs, whereas Mongolia has the highest ASR in 2019. Conclusion Liver cancer remains a major public health issue worldwide, but etiological and geographical variations exist. It is necessary to increase awareness of the population regarding liver cancer, its etiologies and the importance of early detection, and diagnosis and treatment.

Background: Photodynamic therapy (PDT) has been reported to be a promising therapy for colon cancer because of its substantial safety features and its ability to induce a systematic reaction rather than local effects on the focal lesion in the intestine. Autophagy and apoptosis play important roles in the response to PDT. However, the role of autophagy after PDT treatment has not yet been clarified. Methods: In this study, we investigated the relationship between apoptosis and autophagy in porphyrin IX (PpIX)-mediated PDT (PpIX-PDT) in HCT116 colon cancer cells. PpIX-PDT decreased cell viability in a concentration- and light dose-dependent manner. Results: PpIX-PDT results in nuclear condensation, increased the expression of Caspase-3, Bax, and PARP, and decreased expression of Bcl-2. PpIX-PDT also induces the double membrane autophagosome, up-regulates LC3B, Atg7, Beclin-1, and Bcl-2 expression and down-regulates P62 expression. Inhibition of autophagy using chloroquine (CQ) or Atg7 knockdown with a shRNA enhances apoptotic cell death. Based on these findings, autophagy plays a self-protective role in HCT116 cells in response to PpIX-PDT treatment. Discussion: Both autophagy and apoptosis were induced by PpIX-PDT in HCT116 cells, and the inhibition of autophagy strengthened the proapoptotic effect of PpIX-PDT. Thus, the appropriate modulation of autophagy may be as a potential therapeutic target for colon cancer cells treated with PpIX-PDT.

Copper Cysteamine (Cu-Cy) is a new photosensitizer and a novel radiosensitizer that can be activated by light, X-ray and microwave to produce singlet oxygen for cancer treatment. However, the killing mechanism of Cu-Cy nanoparticles on cancer cells is not clear yet and Cu-Cy nanoparticles as novel radiosensitizers have never been tested on colorectal cancers. Here, for the first time, we investigate the treatment efficiency of Cu-Cy nanoparticles on SW620 colorectal cells and elucidate the underlying mechanisms of the effects. The results show that X-ray activated Cu-Cy nanoparticles may kill SW620 cancerscells is in a dose-dependent manner. The JC-1 staining shows the mitochondrial membrane potential is decreased after the treatment. The observations confirm that Cu-Cy nanoparticles may improve X-ray radiotherapy on cancer treatment and X-ray activated Cu-Cy nanoparticles can be efficiently destroy colorectal cancer cells by inducing apoptosis as well as autophagy. As a new type of radiosensitizers and photosensitizers, Cu-Cy nanoparticles have a good potential for colorectal cancer treatment and the discovery of autophagy induced by X-ray irradiated Cu-Cy nanoparticles sheds a good insight to the mechanism of Cu-Cy for cancer treatment as a new radiosensitizers.