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OBJECTIVE@#To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes.@*METHODS@#The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score.@*RESULTS@#A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect.@*CONCLUSION@#Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.
Subject(s)
Humans , Cell Cycle , Multiple Myeloma/genetics , Prognosis , Risk FactorsABSTRACT
OBJECTIVE@#To explore the role of ferroptosis-related genes in multiple myeloma(MM) through TCGA database and FerrDb, and build a prognostic model of ferroptosis-related genes for MM patients.@*METHODS@#Using the TCGA database containing clinical information and gene expression profile data of 764 patients with MM and the FerrDb database including ferroptosis-related genes, the differentially expressed ferroptosis-related genes were screened by wilcox.test function. The prognostic model of ferroptosis-related genes was established by Lasso regression, and the Kaplan-Meier survival curve was drawn. Then COX regression analysis was used to screen independent prognostic factors. Finally, the differential genes between high-risk and low-risk patients were screened, and enrichment analysis was used to explore the mechanism of the relationship between ferroptosis and prognosis in MM.@*RESULTS@#36 differential genes related to ferroptosis were screened out from bone marrow samples of 764 MM patients and 4 normal people, including 12 up-regulated genes and 24 down-regulated genes. Six prognosis-related genes (GCLM, GLS2, SLC7A11, AIFM2, ACO1, G6PD) were screened out by Lasso regression and the prognostic model with ferroptosis-related genes of MM was established. Kaplan-Meier survival curve analysis showed that the survival rate between high risk group and low risk group was significantly different(P<0.01). Univariate COX regression analysis showed that age, sex, ISS stage and risk score were significantly correlated with overall survival of MM patients(P<0.05), while multivariate COX regression analysis showed that age, ISS stage and risk score were independent prognostic indicators for MM patients (P<0.05). GO and KEGG enrichment analysis showed that the ferroptosis-related genes was mainly related to neutrophil degranulation and migration, cytokine activity and regulation, cell component, antigen processing and presentation, complement and coagulation cascades, haematopoietic cell lineage and so on, which may affect the prognosis of patients.@*CONCLUSION@#Ferroptosis-related genes change significantly during the pathogenesis of MM. The prognostic model of ferroptosis-related genes can be used to predict the survival of MM patients, but the mechanism of the potential function of ferroptosis-related genes needs to be confirmed by further clinical studies.
Subject(s)
Humans , Multiple Myeloma , Ferroptosis , Prognosis , Hematopoietic System , Blood CoagulationABSTRACT
Duodenal-type follicular lymphoma (DFL) is a unique subtype of follicular lymphoma (FL), which often involves the second portion of duodenum (descending part of duodenum). Due to its specific pathological features, such as lack of follicular dendritic cells meshwork and disappearance of activation-induced cytidine deaminase expression, DFL presents an inert clinical course and is often confined to the intestinal tract. Inflammation-related biomarkers suggest that the microenvironment may play a likely role in the pathogenesis and favorable prognosis of DFL. Since patients generally have no obvious clinical symptoms and low progression rate, the treatment regimen for DFL is mainly observation and waiting (W&W) strategy. This study will review the latest research progress of epidemiology, diagnosis, treatment and prognosis of DFL in recent years.
Subject(s)
Humans , Lymphoma, Follicular/drug therapy , Duodenal Neoplasms/pathology , Prognosis , Tumor MicroenvironmentABSTRACT
OBJECTIVE@#To analyze and predict the effect of coronavirus infection on hematopoietic system and potential intervention drugs, and explore their significance for coronavirus disease 2019 (COVID-19).@*METHODS@#The gene expression omnibus (GEO) database was used to screen the whole genome expression data related with coronavirus infection. The R language package was used for differential expression analysis and KEGG/GO enrichment analysis. The core genes were screened by PPI network analysis using STRING online analysis website. Then the self-developed apparent precision therapy prediction platform (EpiMed) was used to analyze diseases, drugs and related target genes.@*RESULTS@#A database in accordance with the criteria was found, which was derived from SARS coronavirus. A total of 3606 differential genes were screened, including 2148 expression up-regulated genes and 1458 expression down-regulated genes. GO enrichment mainly related with viral infection, hematopoietic regulation, cell chemotaxis, platelet granule content secretion, immune activation, acute inflammation, etc. KEGG enrichment mainly related with hematopoietic function, coagulation cascade reaction, acute inflammation, immune reaction, etc. Ten core genes such as PTPRC, ICAM1, TIMP1, CXCR5, IL-1B, MYC, CR2, FSTL1, SOX1 and COL3A1 were screened by protein interaction network analysis. Ten drugs with potential intervention effects, including glucocorticoid, TNF-α inhibitor, salvia miltiorrhiza, sirolimus, licorice, red peony, famciclovir, cyclosporine A, houttuynia cordata, fluvastatin, etc. were screened by EpiMed plotform.@*CONCLUSION@#SARS coronavirus infection can affect the hematopoietic system by changing the expression of a series of genes. The potential intervention drugs screened on these grounds are of useful reference significance for the basic and clinical research of COVID-19.
Subject(s)
Humans , COVID-19 , Computational Biology , Follistatin-Related Proteins , Hematopoietic System , Pharmaceutical Preparations , SARS-CoV-2ABSTRACT
Objective: Present study investigated the mechanism of heart failure associated with coronavirus infection and predicted potential effective therapeutic drugs against heart failure associated with coronavirus infection. Methods: Coronavirus and heart failure were searched in the Gene Expression Omnibus (GEO) and omics data were selected to meet experimental requirements. Differentially expressed genes were analyzed using the Limma package in R language to screen for differentially expressed genes. The two sets of differential genes were introduced into the R language cluster Profiler package for gene ontology (GO) and Kyoto gene and genome encyclopedia (KEGG) pathway enrichment analysis. Two sets of intersections were taken. A protein interaction network was constructed for all differentially expressed genes using STRING database and core genes were screened. Finally, the apparently accurate treatment prediction platform (EpiMed) independently developed by the team was used to predict the therapeutic drug. Results: The GSE59185 coronavirus data set was searched and screened in the GEO database, and divided into wt group, ΔE group, Δ3 group, Δ5 group according to different subtypes, and compared with control group. After the difference analysis, 191 up-regulated genes and 18 down-regulated genes were defined. The GEO126062 heart failure data set was retrieved and screened from the GEO database. A total of 495 differentially expressed genes were screened, of which 165 were up-regulated and 330 were down-regulated. Correlation analysis of differentially expressed genes between coronavirus and heart failure was performed. After cross processing, there were 20 GO entries, which were mainly enriched in virus response, virus defense response, type Ⅰ interferon response, γ interferon regulation, innate immune response regulation, negative regulation of virus life cycle, replication regulation of viral genome, etc. There were 5 KEGG pathways, mainly interacting with tumor necrosis factor (TNF) signaling pathway, interleukin (IL)-17 signaling pathway, cytokine and receptor interaction, Toll-like receptor signaling pathway, human giant cells viral infection related. All differentially expressed genes were introduced into the STRING online analysis website for protein interaction network analysis, and core genes such as signal transducer and activator of transcription 3, IL-10, IL17, TNF, interferon regulatory factor 9, 2'-5'-oligoadenylate synthetase 1, mitogen-activated protein kinase 3, radical s-adenosyl methionine domain containing 2, c-x-c motif chemokine ligand 10, caspase 3 and other genes were screened. The drugs predicted by EpiMed's apparent precision treatment prediction platform for disease-drug association analysis were mainly TNF-α inhibitors, resveratrol, ritonavir, paeony, retinoic acid, forsythia, and houttuynia cordata. Conclusions: The abnormal activation of multiple inflammatory pathways may be the cause of heart failure in patients after coronavirus infection. Resveratrol, ritonavir, retinoic acid, amaranth, forsythia, houttuynia may have therapeutic effects. Future basic and clinical research is warranted to validate present results and hypothesis.
Subject(s)
Humans , Betacoronavirus , COVID-19 , Computational Biology , Coronavirus Infections/complications , Gene Expression Profiling , Gene Ontology , Heart Failure/virology , Pandemics , Pneumonia, Viral/complications , SARS-CoV-2ABSTRACT
Objective To analyze and predict hematopoietic injury caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and potential therapeutic drugs, and to provide theoretical basis for clinical treatment of the hematopoietic injury. Methods The gene expression omnibus (GEO) database was used to screen the whole genome expression data related to SARS-CoV-2 infection. The R language package was used for differential expression analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis. The core genes were screened by protein-protein interaction (PPI) network analysis using STRING online analysis website. Then the self-developed apparent precision therapy prediction platform (EpiMed) was used to analyze diseases, drugs and related target genes. Results A total of 222 differential genes were screened, including 172 up-regulated and 50 down-regulated. GO enrichment analysis suggested that gene is mainly related to type I interferon response, cell cycle regulation, inflammatory cell migration, innate immune response, secretion of blood particles and vesicles, chemokines and their receptors. KEGG enrichment analysis suggested that gene is mainly related to viral infection, myocardial injury, complement and coagulation cascade, cell chemotaxis, platelet activation, acute inflammation, immune response, cellular signal transduction and so on. Ten core genes such as STAT1, IL-6, IRF7, TNF, MX1, ISG15, IFIH1, IRF9, DDX58 and GBP1were screened by PPI network analysis. EpiMed screened 10 drugs with potential intervention effects, including Rabdosia rubescens, sirolimus, glucocorticoid, Houttuynia cordata, Polygonum multiflorum, Red peony, tretinoin, Glycyrrhiza, cyclosporine A, fluvastatin and so on. Conclusions SARS-CoV-2 infection can damage the hematopoietic system by changing the expression of a series of genes. The potential intervention drugs screened from this have certain reference significance for the basic and clinical research of coronavirus disease 2019 (COVID-19).
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Objective To investigate the survival status and pathogens in adult patients with severe community-acquired pneumonia (SCAP) for the past ten years in our hospital. Methods A total of 159 adult patients with SCAP were enrolled for this study from January 2007 to December 2016 in our hospital. Patients were divided into early stage group (from January 2007 to December 2011, n=71) and late stage group (from January 2012 to December 2016, n=88). The clinical data, pathogen distribution and prognosis were compared between two groups. Results (1) The proportion of patients with blood urea nitrogen (BUN) > 7.1 mmol/L was significantly higher in late stage group than that of early stage group (P<0.05). There were no significant differences in baseline data, vital signs, imaging findings and other laboratory examinations between the two groups (P>0.05). (2) For distribution of pathogens, 42 and 49 cases were detected pathogens in early stage group and late stage group. The detection rate of Legionella pneumophila was significantly higher in late stage group than that in early stage group (26.5% vs. 7.1%, P<0.05). (3) For complications, the incidence of septic shock was significantly higher in late stage group than that in the early stage group (22.7%vs. 9.9%, P<0.05). The fatality rate within 30 d after admission was significantly higher in late stage group than that of early stage group (43.2%vs. 25.4%, P<0.05). Results of multi-factor Cox proportional hazard regression analysis showed that septic shock and respiratory acidosis were independent risk factors of mortality in early stage group (P<0.05) while septic shock, chronic obstructive pulmonary disease (COPD) and multi-lobar infiltrates were independent risk factors of mortality in late stage group ( P<0.05). Conclusion In the past ten years, basic clinical characteristics of adult patients with SCAP in our hospital have changed little, but detection rate of legionella has showed increasing trend, and the short-term mortality rate has increased. Whether or not patients are combined with septic shock is a key factor affecting the prognosis.
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Objective To investigate the survival status and pathogens in adult patients with severe community-acquired pneumonia (SCAP) for the past ten years in our hospital. Methods A total of 159 adult patients with SCAP were enrolled for this study from January 2007 to December 2016 in our hospital. Patients were divided into early stage group (from January 2007 to December 2011, n=71) and late stage group (from January 2012 to December 2016, n=88). The clinical data, pathogen distribution and prognosis were compared between two groups. Results (1) The proportion of patients with blood urea nitrogen (BUN) > 7.1 mmol/L was significantly higher in late stage group than that of early stage group (P<0.05). There were no significant differences in baseline data, vital signs, imaging findings and other laboratory examinations between the two groups (P>0.05). (2) For distribution of pathogens, 42 and 49 cases were detected pathogens in early stage group and late stage group. The detection rate of Legionella pneumophila was significantly higher in late stage group than that in early stage group (26.5% vs. 7.1%, P<0.05). (3) For complications, the incidence of septic shock was significantly higher in late stage group than that in the early stage group (22.7%vs. 9.9%, P<0.05). The fatality rate within 30 d after admission was significantly higher in late stage group than that of early stage group (43.2%vs. 25.4%, P<0.05). Results of multi-factor Cox proportional hazard regression analysis showed that septic shock and respiratory acidosis were independent risk factors of mortality in early stage group (P<0.05) while septic shock, chronic obstructive pulmonary disease (COPD) and multi-lobar infiltrates were independent risk factors of mortality in late stage group ( P<0.05). Conclusion In the past ten years, basic clinical characteristics of adult patients with SCAP in our hospital have changed little, but detection rate of legionella has showed increasing trend, and the short-term mortality rate has increased. Whether or not patients are combined with septic shock is a key factor affecting the prognosis.
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Objective To investigate the effect of life events and coping styles on attitude toward seeking professional psychological help in college students.Methods Nine hundred college students were survey by attitude toward seeking professional psychological help questionnaire (ATSPPHQ),adolescent self-rating life events check list and coping style questionnaire.Results The total score,the scores of expecting and acceptance factor of ATSPPHQ of female were significantly higher than those of male (P < 0.05);there was no statistic difference in scores of need and trust factor of ATSPPHQ between male and female(P <0.05).There was statistic difference in total score and score of each factor of ATSPPHQ among difference grade (P < 0.05).The total score and each factor score of ATSPPHQ of science & engineering profession students were significantly higher than those of literature and history profession students(P < 0.05).There was no statistic difference in total score and score of each factor of ATSPPHQ among another variables(P > 0.05).Problem solving and help-seeking of coping styles were positive correlation with attitude toward seeking professional psychological help (P < 0.05);all factors of life events and self-blame,fantasy,avoidance,rationalization factor of coping style were negative correlation with attitude toward seeking professional psychological help(P < 0.05).The punishment,problem solving,self-blame and help-seeking were the influence factors of attitude toward seeking professional psychological help.Poblem solving and help-seeking had positive predictive effect (P < 0.05);punishment,self-blame had negative predictive effect (P < 0.05).The immature coping style and mixed coping style had intermediary effect between life events and the attitude toward seeking professional psychological help.Conclusions The attitude toward seeking professional psychological help of college students is different in gender,grade and profession.Life events and coping style have a certain impact on the attitude toward seeking professional psychological help.Coping style play an intermediary role between the life events and the attitude toward seeking professional psychological help.