Construction of a Prognostic Model of Multiple Myeloma Based on Metabolism-Related Genes / 中国实验血液学杂志

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.

Omics Analysis of Ferroptosis and Establishment of Prognostic Model for multiple myeloma Patients / 中国实验血液学杂志

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.

Bioinformatics Analysis of the Influence of Coronavirus Infection on Hematopoietic System and Potential Intervention Drugs and Their Significance for COVID-19 / 中国实验血液学杂志

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.

Exploration of Mechanism of Guben Qingyuan Prescription Combined with Androgen Deprivation Therapy Against Castration-resistant Prostate Cancer from AR/AR-V7 Signaling Pathway / 中国实验方剂学杂志

Objective:To explore the efficacy and mechanism of Guben Qingyuan prescription combined with androgen deprivation therapy （ADT） in the treatment of castration-resistant prostate cancer （CRPC）. Method:A CRPC-bearing mouse model was established. When the tumor volume reached about 100 mm³， 50 CRPC-bearing BALB/c nude mice were randomly divided into the model group， ADT group， and ADT+low-， medium-， high-dose Guben Qingyuan prescription groups， with 10 mice in each group. After grouping， it was ensured that there was no statistically significant difference in tumor volume between groups. The mice in the model group was treated with the same amount of normal saline （10 mL·kg^-1） by gavage， twice a day， while those in the other groups were provided with bicalutamide （5 mg·kg^-1） for intragastric administration， once a day， and then with goserelin （0.36 mg·kg^-1） for intraperitoneal injection on the 10th day. On the basis of ADT， the ones in the ADT+Guben Qingyuan prescription groups further received Guben Qingyuan prescription at the low （2.5 g·kg^-1）， medium （25 g·kg^-1）， and high doses （50 g·kg^-1） by gavage， twice a day. After 25 days of continuous administration， the tumor tissue was harvested for recording the tumor growth and calculating the tumor inhibition rate. The mRNA and protein expression levels of androgen receptor （AR）， androgen receptor splice variant-7 （AR-V7）， and prostate-specific antigen （PSA） were detected by real-time polymerase chain reaction （Real-time PCR） and Western blot assay. Result:The tumor inhibition rates of the ADT+low-， medium-， and high-dose Guben Qingyuan prescription groups were 27.95%， 46.71%， and 44.46%， respectively， and the inhibition rates in the ADT+medium- and high-dose Guben Qingyuan prescription groups were significantly increased as compared with that in the ADT group （<italic>P</italic><0.05）. As revealed by comparison with the ADT group， Guben Qingyuan prescription at the medium and high doses significantly down-regulated the mRNA and protein expression levels of AR， AR-V7， and PSA （<italic>P</italic><0.05）. Conclusion:Guben Qingyuan prescription combined with ADT is efficient in controlling the tumor growth in CRPC-bearing mice， which is related to the regulation of AR/AR-V7 signaling pathway.

Exploration of omics mechanism and drug prediction of coronavirus-induced heart failure based on clinical bioinformatics / 中华心血管病杂志

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.

Correlation Analysis between Serum Complement C3，C4 Levels and LDL-C in Patients with Premature Coronary Artery Disease / 中山大学学报(医学科学版)

@#【Objective】The aim of this study was to investigate the associations between serum complement C3，C4 and low density lipoprotein cholesterol（LDL- C）levels and early- onset coronary heart disease.【Methods】We enrolled 255 cases of coronary angiography confirmed coronary artery disease from January 2018 to September 2018. All the patients were divided into early- onset coronary heart disease group（108 cases）and late- onset coronary heart disease group（147 cases）. Besides ，100 healthy subjects were enrolled and used as controls. Serum levels of C3 ，C4 and LDL-C were analyzed by automatic biochemical analyzer.【Results】Levels of serum C3，C4 and LDL-C in early-onset coronary heart disease group，late-onset coronary heart disease group and healthy control group were significantly different（P < 0.05）. In early-onset coronary heart disease group，C3 and C4 were positively correlated with LDL-C（P < 0.05）. However ，there was no significant correlation （P > 0.05） between C3 ，C4 and LDL- C in late- onset coronary heart disease group and healthy control group.【Conclusions】The levels of C3 and C4 were positively correlated with LDL-C only in the early-onset coronary heart disease patients.

Research progress of platelet apoptosis mechanism in antineoplastic drugs-induced thrombopenia / 解放军医学杂志

Platelets are the blood cells essential for human hemostasis, wound healing and human health. Drug-induced thrombopenia refers to a disease in which the drug causes platelet counts fall below the normal range (<100×109/L), resulting in a series of symptoms, including bleeding, nausea, vomiting, and abdominal pain, etc. The antineoplastic drugs-induced thrombopenia increases not only the potential bleeding risk of patients, but may also reduce the dose of anti-tumor drugs and prolong the treatment interval, or even lead to the ceasing of antitumor therapy in serious cases, which affects the clinical efficacy and survival of patients, leading to the increased medical costs. In recent years, a large number of studies have confirmed that antineoplastic drugs-induced thrombopenia is a disease caused through a non-immune-mediation, including platelet apoptosis. The research status has been reviewed in present paper of platelet apoptosis mechanism in antineoplastic drugs-induced thrombopenia to provide theoretical basis for clinical practice and scientific research.