Activated hedgehog gene pattern correlates with dismal clinical outcome and tumor microenvironment heterogeneity in hepatocellular carcinoma.

Background: Activation of the Hedgehog signaling pathway is linked to the initiation and development of human hepatocellular carcinoma (HCC). However, its impact on clinical outcomes and the HCC microenvironment remains unclear. Methods: We performed comprehensive analyses of Hedgehog pathway genes in a large cohort of HCC patients. Specifically, we utilized univariate Cox regression analysis to identify Hedgehog genes linked to overall survival, and the LASSO algorithm was used to construct a Hedgehog-related gene pattern. We subsequently examined the correlation between the Hedgehog pattern and the HCC microenvironment employing the CIBERSORT and ssGSEA algorithms. Furthermore, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and the anti-PD-L1 treatment dataset (IMvigor210) are used to evaluate the clinical response of the Hedgehog pattern in predicting immune checkpoint inhibitors. Results: We found that the Hedgehog activation score (HHAS), a prognostic score based on 11 Hedgehog genes, was significantly associated with HCC patient survival. Patients exhibiting high HHAS experienced markedly reduced survival rates compared to those with low HHAS, and HHAS emerged as an independent prognostic factor for HCC. Functional enrichment analysis unveiled the association of the HHAS phenotype with functions related to the immune system, and further investigation demonstrated that HCC patients exhibiting low HHAS displayed elevated levels of anti-tumor immune activation in CD8+ T cells, while high HHAS were linked to immune escape phenotypes and increased infiltration of immune suppressive cells. In addition, in the Immune Checkpoint Inhibitor (ICI) cohort of IMvigor210, patients with higher HHAS had worse ICI treatment outcomes and shortened survival time, indicating that the HHAS is a useful indicator for predicting patient response to immunotherapy. Conclusions: In summary, our study offers valuable insights for advancing research on Hedgehog and its impact on tumor immunity, which provides an opportunity to optimize prognosis and immune therapy for HCC.

Targeted modulation of intestinal epithelial regeneration and immune response in ulcerative colitis using dual-targeting bilirubin nanoparticles.

Rationale: The therapeutic benefits of bilirubin in the treatment of ulcerative colitis (UC) are considerable, whereas the underlying mechanism of bilirubin on UC remains unclear remains unexplored. In addition, the weak hydrophilicity and toxicity have limited its translational applications. Methods: We have developed a colon dual-targeting nanoparticle, for orally delivering bilirubin through hydrogel encapsulation of hyaluronic acid (HA)-modified poly (lactic-co-glycolic acid) (PLGA) nanoparticles (HA-PLGABilirubin). Confocal microscopy and in vivo imaging were used to evaluate the uptake and the targeted property of HA-PLGABilirubin in UC. Immunohistochemistry, immunofluorescence, and transcriptomic analyses were applied to examine the therapeutic effect and potential mechanism of HA-PLGABilirubin in UC. Results: Our results indicated that HA-PLGAbilirubin can significantly enhance the release of bilirubin at simulated intestinal pH and demonstrate higher cellular uptake in inflammatory macrophages. Moreover, in vivo biodistribution studies revealed high uptake and retention of HA-PLGAbilirubin in inflamed colon tissue of UC mouse model, resulting in effective recovery of intestinal morphology and barrier function. Importantly, HA-PLGAbilirubin exerted potent therapeutic efficacy against ulcerative colitis through modulating the intestinal epithelial/stem cells regeneration, and the improvement of angiogenesis and inflammation. Furthermore, genome-wide RNA-seq analysis revealed transcriptional reprogramming of immune response genes in colon tissue upon HA-PLGAbilirubin treatment in UC mouse model. Conclusion: Overall, our work provides an efficient colon targeted drug delivery system to potentiate the treatment of ulcerative colitis via modulating intestinal epithelium regeneration and immune response in ulcerative colitis.

Risks of digestive diseases in long COVID: evidence from a population-based cohort study.

BACKGROUND: In the post-pandemic era, a wide range of COVID-19 sequelae is of growing health concern. However, the risks of digestive diseases in long COVID have not been comprehensively understood. To investigate the long-term risk of digestive diseases among COVID patients. METHODS: In this large-scale retrospective cohort study with up to 2.6 years follow-up (median follow-up: 0.7 years), the COVID-19 group (n = 112,311), the contemporary comparison group (n = 359,671) and the historical comparison group (n = 370,979) predated the COVID-19 outbreak were built using UK Biobank database. Each digestive outcome was defined as the diagnosis 30 days or more after the onset of COVID-19 infection or the index date. Hazard ratios (HRs) and corresponding 95% confidence intervals (CI) were computed utilizing the Cox regression models after inverse probability weighting. RESULTS: Compared with the contemporary comparison group, patients with previous COVID-19 infection had higher risks of digestive diseases, including gastrointestinal (GI) dysfunction (HR 1.38 (95% CI 1.26 to 1.51)); peptic ulcer disease (HR 1.23 (1.00 to 1.52)); gastroesophageal reflux disease (GERD) (HR 1.41 (1.30 to 1.53)); gallbladder disease (HR 1.21 (1.06 to 1.38)); severe liver disease (HR 1.35 (1.03 to 1.76)); non-alcoholic liver disease (HR 1.27 (1.09 to 1.47)); and pancreatic disease (HR 1.36 (1.11 to 1.66)). The risks of GERD were increased stepwise with the severity of the acute phase of COVID-19 infection. Even after 1-year follow-up, GERD (HR 1.64 (1.30 to 2.07)) and GI dysfunction (HR 1.35 (1.04 to 1.75)) continued to pose risks to COVID-19 patients. Compared to those with one SARS-CoV-2 infection, reinfected patients were at a higher risk of pancreatic diseases (HR 2.57 (1.23 to 5.38)). The results were consistent when the historical cohort was used as the comparison group. CONCLUSIONS: Our study provides insights into the association between COVID-19 and the long-term risk of digestive system disorders. COVID-19 patients are at a higher risk of developing digestive diseases. The risks exhibited a stepwise escalation with the severity of COVID-19, were noted in cases of reinfection, and persisted even after 1-year follow-up. This highlights the need to understand the varying risks of digestive outcomes in COVID-19 patients over time, particularly those who experienced reinfection, and develop appropriate follow-up strategies.

Adverse clinical outcomes and immunosuppressive microenvironment of RHO-GTPase activation pattern in hepatocellular carcinoma.

BACKGROUND: Emerging evidence suggests that Rho GTPases play a crucial role in tumorigenesis and metastasis, but their involvement in the tumor microenvironment (TME) and prognosis of hepatocellular carcinoma (HCC) is not well understood. METHODS: We aim to develop a tumor prognosis prediction system called the Rho GTPases-related gene score (RGPRG score) using Rho GTPase signaling genes and further bioinformatic analyses. RESULTS: Our work found that HCC patients with a high RGPRG score had significantly worse survival and increased immunosuppressive cell fractions compared to those with a low RGPRG score. Single-cell cohort analysis revealed an immune-active TME in patients with a low RGPRG score, with strengthened communication from T/NK cells to other cells through MIF signaling networks. Targeting these alterations in TME, the patients with high RGPRG score have worse immunotherapeutic outcomes and decreased survival time in the immunotherapy cohort. Moreover, the RGPRG score was found to be correlated with survival in 27 other cancers. In vitro experiments confirmed that knockdown of the key Rho GTPase-signaling biomarker SFN significantly inhibited HCC cell proliferation, invasion, and migration. CONCLUSIONS: This study provides new insight into the TME features and clinical use of Rho GTPase gene pattern at the bulk-seq and single-cell level, which may contribute to guiding personalized treatment and improving clinical outcome in HCC.

Habitual fish oil use and risk of COVID-19-related outcomes: Evidence from a large scale cohort study and Mendelian randomization analysis.

BACKGROUND & AIMS: Previous findings for the effects of fish oil on COVID-19-related outcomes remain largely inconclusive and controversy persists. Large population-based studies in real-life settings are required to explore the impact of habitual fish oil use on Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, Coronavirus disease 2019 (COVID-19)-related hospitalization and death. To investigate the associations between habitual fish oil use and SARS-CoV-2infection, COVID-19-related outcome. METHODS: Cohort study based on the UK Biobank. 466,572 participants were enrolled. For Mendelian randomization (MR) study, single-nucleotide variants were selected for exposures of fish-oil-derived n-3 PUFAs, including docosapentaenoic acid (DPA). RESULTS: 146,969 (31.5%) participants reported their habitual fish oil use at baseline. Compared with non-fish-oil-users, the hazard ratios for habitual users were 0.97 (95% confidence interval [CI] 0.94 to 0.99) for SARS-CoV-2 infection, 0.92 (95% CI 0.85 to 0.98) for COVID-19-related hospitalization and 0.86 (95% CI 0.75 to 0.98) for COVID-19-related death. MR showed that a higher level of circulating DPA is casually associated with a lower risk of severe COVID-19 (IVW, odds ratio = 0.26, 95% CI 0.08-0.88, P = 0.030). CONCLUSIONS: In this large cohort, we found that habitual fish oil use was significantly associated with lower risks of SARS-CoV-2 infection, hospitalization and death from COVID-19. MR analyses further support a possible causal role of DPA, one of the components of fish oil and valid biomarkers of dietary intake, in reducing the risk of severe COVID-19.

Investigating Causality and Shared Genetic Architecture between Neurodegenerative Disorders and Inflammatory Bowel Disease.

Published observational studies have revealed the connection between neurodegenerative disorders and inflammatory bowel disease (IBD), whereas the causal association remains largely unclear. Our study aims to assess the causality and identify the shared genetic architecture between neurodegenerative disorders and IBD. Two-sample Mendelian randomization analyses were performed to assess the causality between IBD and neurodegenerative disorders (amyotrophic lateral sclerosis [ALS], Alzheimer's disease [AD], Parkinson's disease [PD], and multiple sclerosis [MS]). Shared genetic loci, functional interpretation, and transcriptomic profiles were further investigated in ALS and IBD. We identified that genetic predisposition to IBD was suggestively associated with lower odds of ALS (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.94 to 0.99). In contrast, IBD was not genetically associated with an increased risk of AD, PD, or MS (and vice versa). Two shared genetic loci (rs6571361 and rs7154847) were derived, and SCFD1, G2E3, and HEATR5A were further identified as novel risk genes with enriched functions related to membrane trafficking. G2E3 was differentially expressed and significantly correlated with SCFD1 in patients with ALS or IBD. Our study reveals the suggestively protective role of IBD on ALS, and does not support the causality of AD, PD, or MS on IBD (and vice versa). Our findings indicate possible shared genetic architecture and pathways between ALS and IBD. These results provide insights into the pathogenesis and therapeutics of IBD and neurodegenerative disorders.

Associations of habitual glucosamine use with SARS-CoV-2 infection and hospital admission and death with COVID-19: Evidence from a large population based cohort study.

The coronavirus disease 2019 (COVID-19) pandemic has led to a fundamental number of morbidity and mortality worldwide. Glucosamine was indicated to help prevent and control RNA virus infection preclinically, while its potential therapeutic effects on COVID-19-related outcomes are largely unknown. To assess the association of habitual glucosamine use with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, hospital admission, and mortality with COVID-19 in a large population based cohort. Participants from UK Biobank were reinvited between June and September 2021 to have SARS-CoV-2 antibody testing. The associations between glucosamine use and the risk of SARS-CoV-2 infection were estimated by logistic regression. Hazard ratios (HRs) and 95% confidence intervals (CIs) for COVID-19-related outcomes were calculated using COX proportional hazards model. Furthermore, we carried out propensity-score matching (PSM) and stratified analyses. At baseline, 42 673 (20.7%) of the 205 704 participants reported as habitual glucosamine users. During median follow-up of 1.67 years, there were 15 299 cases of SARS-CoV-2 infection, 4214 cases of COVID-19 hospital admission, and 1141 cases of COVID-19 mortality. The fully adjusted odds ratio of SARS-CoV-2 infection with glucosamine use was 0.96 (95% CI: 0.92-1.01). The fully adjusted HR were 0.80 (95% CI: 0.74-0.87) for hospital admission, and 0.81 (95% CI: 0.69-0.95) for mortality. The logistic regression and Cox proportional hazard analyses after PSM yielded consistent results. Our study demonstrated that habitual glucosamine use is associated with reduced risks of hospital admission and death with COVID-19, but not the incidence of SARS-CoV-2 infection.

Regulation of Fatty Acid Metabolism and Inhibition of Colorectal Cancer Progression by Erchen Decoction.

Erchen decoction (ECD) is a traditional Chinese prescription widely used in the treatment of various diseases such as obesity, fatty liver, diabetes, and hypertension. In this study, we investigated the effect of ECD on fatty acid metabolism in a colorectal cancer (CRC) mouse model fed a high-fat (HF) diet. The HF-CRC mouse model was established by azoxymethane (AOM)/dextran sulphate sodium (DSS) combined with a high-fat diet. Mice were then gavaged with ECD. Change in the body weight was recorded every two weeks for 26 weeks. Changes in blood glucose (GLU), total cholesterol (TC), total triglycerides (TG), and C-reactive protein (CRP) were measured. Colorectal tissues were collected to observe changes in colorectal length and tumorigenesis. Hematoxylin-eosin (HE) staining and immunohistochemical staining were performed to observe changes in intestinal structure and inflammatory markers. Fatty acids and the expression of related genes in colorectal tissues were also studied. ECD gavage inhibited HF-induced weight gain. CRC induction and HF diet intake resulted in increased GLU, TC, TG, and CRP, where ECD gavage reduced these elevated indicators. ECD gavage also increased colorectal length and inhibited tumorigenesis. HE staining revealed that ECD gavage suppressed inflammatory infiltration of colorectal tissues. ECD gavage suppressed the fatty acid metabolism abnormalities caused by HF-CRC in colorectal tissues. Consistently, ECD gavage lowered ACSL4, ACSL1, CPT1A, and FASN levels in colorectal tissues. Conclusions. ECD inhibited HF-CRC progression through the regulation of fatty acid metabolism.

Identification of shared fatty acid metabolism related signatures in dilated cardiomyopathy and myocardial infarction.

Aim: It is to be elucidated the risk-predictive role of differentially expressed fatty acid metabolism related genes (DE-FRGs) in dilated cardiomyopathy (DCM) and myocardial infarction. Materials & methods: Four gene enrichment analyses defined DE-FRGs' biological functions and pathways. Three strategies were applied to identify risk biomarkers and construct a nomogram. The 4-DE-FRG correlation with immune cell infiltration, drugs, and ceRNA was explored. Results: DE-FRGs were enriched in lipid metabolism. A risk nomogram was established by ACSL1, ALDH2, CYP27A1 and PPARA, demonstrating a good ability for DCM and myocardial infarction prediction. PPARA was positively correlated with adaptive immunocytes. Thirty-five drugs are candidate therapeutic targets. Conclusion: A nomogram and new biological targets for early diagnosis and treatment of DCM and myocardial infarction were provided.

Dilated cardiomyopathy (DCM) and myocardial infarction (MI) are two common types of heart disease. This study investigated the fatty acid metabolism related genes to predict the risk of DCM or MI. Four of them (ACSL1, ALDH2, CYP27A1 and PPARA) were effective in predicting disease risk. Additionally, PPARA was found to be associated with immune cell infiltration, and 35 drugs emerged as potential therapeutic targets for these diseases. This study may provide insights into the early diagnosis and treatment of DCM and MI.

Lack of Causal Associations of Inflammatory Bowel Disease with Parkinson's Disease and Other Neurodegenerative Disorders.

BACKGROUND: Observational studies have indicated associations between inflammatory bowel disease (IBD) and neurodegenerative diseases, including Parkinson's disease (PD). OBJECTIVE: To evaluate the causal associations of IBD with PD and other selected neurodegenerative disorders using updated data. METHODS: Bidirectional two-sample Mendelian randomization studies using genome-wide association studies summary statistics of IBD and PD. RESULTS: We found a lack of evidence for the causal association of IBD on PD (odds ratio [OR], 1.014; 95% confidence interval [CI], 0.967-1.063; P = 0.573). Reverse analysis also indicated no evidence of a causal effect for PD on IBD (OR, 0.978; 95% CI, 0.910-1.052; P = 0.549). The causality between IBD and Alzheimer's disease, amyotrophic lateral sclerosis, and multiple sclerosis was unfounded (all P > 0.05). CONCLUSIONS: The updated analyses provide no clear evidence for causal associations of IBD with PD or the other three neurodegenerative diseases. Potential confounders might contribute to the previously observed associations, and further investigations are warranted. © 2023 International Parkinson and Movement Disorder Society.

Ginsenoside Rk1 attenuates radiation-induced intestinal injury through the PI3K/AKT/mTOR pathway.

Radiation-induced intestinal injury (RIII) frequently occurs during radiotherapy; however, methods for treating RIII are limited. Ginsenoside Rk1 (RK1) is a substance that is derived from ginseng, and it has several biological activities, such as antiapoptotic, antioxidant and anticancer activities. The present study was designed to investigate the potential protective effect of Rk1 on RIII and the potential mechanisms. The results showed that RK1 treatment significantly improved the survival rate of the irradiated rats and markedly ameliorated the structural injury of the intestinal mucosa observed by histology. Treatment with RK1 significantly alleviated radiation-induced intestinal epithelial cell oxidative stress apoptosis. Moreover, RNA-Seq identified 388 differentially expressed genes (DEGs) and showed that the PI3K-AKT pathway might be a key signaling pathway by which RK1 exerts its therapeutic effects on RIII. The western blotting results showed that the p-PI3K, p-AKT and p-mTOR expression levels, which were increased by radiation, were markedly inhibited by Rk1, and these effects were reversed by IGF-1. The present study demonstrates that Rk1 can alleviate RIII and that the mechanism underlying the antiapoptotic effects of RK1 may involve the suppression of the PI3K/Akt/mTOR pathway. This study provides a promising therapeutic agent for RIII.

A Nomogram model for the early warning of essential hypertension risks based on the principles of traditional Chinese medicine syndrome elements / 数字中医药（英文）

@#[Objective] To construct a Nomogram model for the prediction of essential hypertension (EH) risks with the use of traditional Chinese medicine (TCM) syndrome elements principles in conjunction with cutting-edge biochemical detection technologies. [Methods] A case-control study was conducted, involving 301 patients with essential hypertension in the hypertensive group and 314 without in the control group. Comprehensive data, including the information on the four TCM diagnoses, general data, and blood biochemical indicators of participants in both groups, were collected separately for analysis. The differentiation principles of syndrome elements were used to discern the location and nature of hypertension. One-way analysis was carried out to screen for potential risk factors of the disease. Least absolute shrinkage and selection operator (LASSO) regression was used to identify factors that contribute significantly to the model, and eliminate possible collinearity problems. At last, multivariate logistic regression analysis was used to both screen and quantify independent risk factors essential for the prediction model. The “rms” package in the R Studio was used to construct the Nomogram model, creating line segments of varying lengths based on the contribution of each risk factor to aid in the prediction of risks of hypertension. For internal model validation, the Bootstrap program package was utilized to perform 1000 repetitions of sampling and generate calibration curves. [Results] The results of the multivariate logistic regression analysis revealed that the risk factors of EH included age, heart rate (HR), waist-to-hip ratio (WHR), uric acid (UA) levels, family medical history, sleep patterns (early awakening and light sleep), water intake, and psychological traits (depression and anger). Additionally, TCM syndrome elements such as phlegm, Yin deficiency, and Yang hyperactivity contributed to the risk of EH onset as well. TCM syndrome elements liver, spleen, and kidney were also considered the risk factors of EH. Next, the Nomogram model was constructed using the aforementioned 14 risk predictors, with an area under the curve (AUC) of 0.868 and a 95% confidence interval (CI) ranging from 0.840 to 0.895. The diagnostic sensitivity and specificity were found to be 80.7% and 85.0%, respectively. Internal validation confirmed the model’s robust predictive performance, with aconsistency index (C-index) of 0.879, underscoring the model’s strong predictive ability. [Conclusion] By integrating TCM syndrome elements, the Nomogram model has realized the objective, qualitative, and quantitative selection of early warning factors for developing EH, resulting in the creation of a more comprehensive and precise prediction model for EH risks.

Development and validation of a novel ubiquitination-related gene prognostic signature based on tumor microenvironment for colon cancer.

Background: Colon cancer (CC) is one of the most common cancers with high morbidity globally. Ubiquitination is involved in the characterization of multiple biological processes, and some ubiquitinated enzymes are associated with the prognosis of CC. However, the prognostic model associated with ubiquitination-related genes (URGs) for CC is unavailable. Methods: Gene expression data, somatic mutations, transcriptome profiles, microsatellite instability status (MSI) status, and clinical information for CC were obtained from The Cancer Genome Atlas (TCGA) dataset. Seven URGs were used for establishing a prognostic prediction model, which was constructed and validated in GSE17538. Besides, genomic variance analysis (GSVA) was used to explore further the differences in biological pathway activation status between the high-risk and low-risk groups. Finally, the single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithm analysis were used to characterize the cellular infiltration in the microenvironment. Results: A seven-URG prognostic signature was established, based on which patients in the training and test groups could be divided into high-risk and low-risk groups. The results demonstrated that the model has a solid ability to predict the prognosis of CC patients. Conclusions: We established a prognostic prediction model for CC based on ubiquitination. Then we analyzed the genetic characteristics associated with ubiquitination and the tumor microenvironment (TME) cell infiltration in CC. These results are worthy of exploring new clinical treatment strategies for CC.

Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.

Objective: Energy metabolism plays a crucial role in the improvement of heart dysfunction as well as the development of heart failure (HF). The current study is designed to identify energy metabolism-related diagnostic biomarkers for predicting the risk of HF due to myocardial infarction. Methods: Transcriptome sequencing data of HF patients and non-heart failure (NF) people (GSE66360 and GSE59867) were obtained from gene expression omnibus (GEO) database. Energy metabolism-related differentially expressed genes (DEGs) were screened between HF and NF samples. The subtyping consistency analysis was performed to enable the samples to be grouped. The immune infiltration level among subtypes was assessed by single sample gene set enrichment analysis (ssGSEA). Random forest algorithm (RF) and support vector machine (SVM) were applied to identify diagnostic biomarkers, and the receiver operating characteristic curves (ROC) was plotted to validate the accuracy. Predictive nomogram was constructed and validated based on the result of the RF. Drug screening and gene-miRNA network were analyzed to predict the energy metabolism-related drugs and potential molecular mechanism. Results: A total of 22 energy metabolism-related DEGs were identified between HF and NF patients. The clustering analysis showed that HF patients could be classified into two subtypes based on the energy metabolism-related genes, and functional analyses demonstrated that the identified DEGs among two clusters were mainly involved in immune response regulating signaling pathway and lipid and atherosclerosis. ssGSEA analysis revealed that there were significant differences in the infiltration levels of immune cells between two subtypes of HF patients. Random-forest and support vector machine algorithm eventually identified ten diagnostic markers (MEF2D, RXRA, PPARA, FOXO1, PPARD, PPP3CB, MAPK14, CREB1, MEF2A, PRMT1) for risk prediction of HF patients, and the proposed nomogram resulted in good predictive performance (GSE66360, AUC = 0.91; GSE59867, AUC = 0.84) and the clinical usefulness in HF patients. More importantly, 10 drugs and 15 miRNA were predicted as drug target and hub miRNA that associated with energy metabolism-related genes, providing further information on clinical HF treatment. Conclusion: This study identified ten energy metabolism-related diagnostic markers using random forest algorithm, which may help optimize risk stratification and clinical treatment in HF patients.

Current therapy option for necrotizing enterocolitis: Practicalities and challenge.

Necrotizing enterocolitis (NEC) is one of the most prevalent neonatal gastrointestinal disorders. Despite ongoing breakthroughs in its treatment and prevention, the incidence and mortality associated with NEC remain high. New therapeutic approaches, such as breast milk composition administration, stem cell therapy, immunotherapy, and fecal microbiota transplantation (FMT) have recently evolved the prevention and the treatment of NEC. This study investigated the most recent advances in NEC therapeutic approaches and discussed their applicability to bring new insight to NEC treatment.

Development and validation of a novel mitophagy-related gene prognostic signature for glioblastoma multiforme.

BACKGROUND: Glioblastoma multiforme (GBM) is one of the most malignant tumors in brain with high morbidity and mortality. Mitophagy plays a significant role in carcinogenesis, metastasis, and invasion. In our study, we aim to construct a mitophagy-related risk model to predict prognosis in GBM. METHODS: RNA-seq data combined with clinical information were downloaded from TCGA. The 4-gene risk model and nomograph was then constructed and validated in external cohort. Evaluation of immune infiltration, functional enrichment and tumor microenvironment (TME) were then performed. RESULT: A mitophagy-related risk model was established and patients in TCGA and CGGA were classified into low-risk and high-risk groups. In both cohorts, patients in low-risk group had improved survival, while high-risk group had poor prognosis. Also, the risk model was identified as an independent factor for predicting overall survival via Cox regression. Furthermore, a prognostic nomogram including mitophagy signatures was established with excellent predictive performance. In addition, the risk model was closely associated with regulation of immune infiltration as well as TME. CONCLUSION: In conclusion, our study constructed a mitophagy-related risk model, which can be utilized for the clinical prognostic prediction in GBM.

Construction of a pyroptosis-related classifier for risk prediction of acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) is a common cardiovascular disease that has a high mortality. Pyroptosis is a programmed cell death mediated by inflammasome. It remains to be clarified on the expression pattern and risk predictive role of pyroptosis-related genes in AMI. METHODS: The gene expression data were extracted from the Gene Expression Omnibus (GEO), and pyroptosis-related genes were obtained from published articles. Pyroptosis-related differential expressed genes were selected between normal and AMI samples and then we explored their immune infiltration level using CIBERSORT. Univariate Cox and LASSO regression were applied to establish a classifier based on pyroptosis-related genes. ROC analysis was utilized to evaluate the classifier. RESULTS: In this study, we obtained 20 pyroptosis-related genes which showed differential expression in AMI and normal samples. Among the differential expressed genes, GZMB was significantly positively associated with activated NK cells (R = 0.71, p < 0.01), while NLRP3 exhibited a negative correlation with resting NK cells (R = -0.66, p < 0.01). 9 genes (NLRP9, GSDMD, CASP8, AIM2, GPX4, NOD1, NOD2, SCAF11, GSDME) were eventually identified as a predictive risk classifier for AMI patients. With the classifier, patients at high and low risk could be discriminated. Further external validation showed the high accuracy of the classifier (AUC = 0.75). CONCLUSIONS: Pyroptosis-related genes are closely related to immune infiltration in AMI, and a 9-gene classifier has good performance in predicting the risk of AMI with high accuracy, which could provide a new way for targeted treatment in AMI.

Rho GTPase signaling in rheumatic diseases.

Rho guanosine triphosphatase (GTPases), as molecular switches, have been identified to be dysregulated and involved in the pathogenesis of various rheumatic diseases, mainly including rheumatoid arthritis, osteoarthritis, systemic sclerosis, and systemic lupus erythematosus. Downstream pathways involving multiple types of cells, such as fibroblasts, chondrocytes, synoviocytes, and immunocytes are mediated by activated Rho GTPases to promote pathogenesis. Targeted therapy via inhibitors of Rho GTPases has been implicated in the treatment of rheumatic diseases, demonstrating promising effects. In this review, the effects of Rho GTPases in the pathogenesis of rheumatic diseases are summarized, and the Rho GTPase-mediated pathways are elucidated. Therapeutic strategies using Rho GTPase inhibitors in rheumatic diseases are also discussed to provide insights for further exploration of targeted therapy in preclinical studies and clinical practice. Future directions on studies of Rho GTPases in rheumatic diseases based on current understandings are provided.

Investigating regulatory patterns of NLRP3 Inflammasome features and association with immune microenvironment in Crohn's disease.

Introduction: Crohn's disease is characterized of dysregulated inflammatory and immune reactions. The role of the NOD-like receptor family, pyrin domain-containing 3 (NLRP3) inflammasome in Crohn's disease remains largely unknown. Methods: The microarray-based transcriptomic data and corresponding clinical information of GSE100833 and GSE16879 were obtained from the Gene Expression Omnibus (GEO) database. Identification of in the NLRP3 inflammasome-related genes and construction of LASSO regression model. Immune landscape analysis was evaluated with ssGSEA. Classification of Crohn's-disease samples based on NLRP3 inflammasome-related genes with ConsensusClusterPlus. Functional enrichment analysis, gene set variation analysis (GSVA) and drug-gene interaction network. Results: The expressions of NLRP3 inflammasome-related genes were increased in diseased tissues, and higher expressions of NLRP3 inflammasome-related genes were correlated with generally enhanced immune cell infiltration, immune-related pathways and human leukocyte antigen (HLA)-gene expressions. The gene-based signature showed well performance in the diagnosis of Crohn's disease. Moreover, consensus clustering identified two Crohn's disease clusters based on NLRP3 inflammasome-related genes, and cluster 2 was with higher expressions of the genes. Cluster 2 demonstrated upregulated activities of immune environment in Crohn's disease. Furthermore, four key hub genes were identified and potential drugs were explored for the treatment of Crohn's disease. Conclusions: Our findings indicate that NLRP3 inflammasome and its related genes could regulate immune cells and responses, as well as involve in the pathogenesis of Crohn's disease from transcriptomic aspects. These findings provide in silico insights into the diagnosis and treatment of Crohn's disease and might assist in the clinical decision-making process.