Research On Occupational Benzene Exposure Risk Matrix Assessment And Biological Effect Factors

Objective:Benzene is an important industrial petrochemical and organic volatile compounds.It is widely used in pesticide,paint,shoemaking and other industries,causing occupational exposure.The hazards of occupational benzene exposure are mainly chronic poisoning caused by long-term low-dose exposure and acute poisoning caused by short-term high-dose exposure.In the production environment,benzene is mainly in the form of steam,which can enter the human body through the respiratory tract,skin and gastrointestinal tract.Benzene is also the main component of gasoline.At the same time,automobile exhaust,industrial waste gas,and cigarette smoke can also produce benzene,causing air pollution.The Benzene Occupational Exposure Matrix can evaluate the benzene exposure level that lacks occupational monitoring data,analyze the differences in benzene exposure levels between different occupations and types of work,and analyze the trend of benzene exposure over time;based on the benzene occupational exposure history of individual organisms,use the benzene occupational exposure matrix to estimate the instantaneous exposure level and cumulative exposure of biological individuals.The benzene occupational exposure matrix can also provide data support for the formulation of health policies,risk assessment and occupational hazard monitoring.The aim of this study is to construct the job exposure matrix of benzene for different occupations and jobs in China,so as to establish an accessible occupational benzene exposure database for risk assessment and health supervision of occupational benzene exposure,and to provide a theoretical basis for future related research.Further use the expression profiles of lnc RNAs and m RNAs in the peripheral blood of workers with different occupational benzene exposure levels in public databases to identify and analyze the toxicity mechanism of benzene,and find the key genes that may be play an important role in the pathogenesis of acute and chronic lymphocytic leukaemia,non-Hodgkin's lymphoma,and multiple myeloma caused by benzene exposure through bioinformatics methods.In order to find potential targets for early monitoring and early warning of occupational benzene exposure,and to provide a theoretical basis for elucidating the molecular mechanism of occupational benzene exposure to leukemia.Immune cells in the tumor microenvironment are an important prognostic indicator in diffuse large B-cell lymphoma(DLBCL).However,information on the heterogeneity and risk stratification of these cells is limited.We sought to develop a novel immune model to evaluate the prognostic intra-tumoral immune landscape of patients with DLBCL.Methods:In this study,the occupational benzene exposure risk matrix was constructed for risk assessment and health supervision of occupational benzene exposure,and further bioinformatics methods were used to screen key genes that may play an important role in the pathogenesis of leukemia caused by benzene exposure,and then establish the best personalized risk prognosis prediction model for DLBCL patients,in order to clarify the occupational benzene exposure,pathogenesis of leukemia caused by benzene exposure and personalized risk prognosis prediction.In the first part,a total of 5807 environmental measurements of occupational exposure to benzene covering 66 occupations and 91 jobs were collected from 1949 to 2018,and then the 5-fold cross-validation method was used to construct and verify the linear mixed effect models constructed for different measurements(short-term exposure concentrations and time weighted average concentrations),in which the time trend of exposure was a fixed effect,while the job and factory were enrolled as fixed effects.The optimal models were determined by continuously optimizing the model parameters.And then the stability and reliability of the model were evaluated by correlation coefficients and Bland Altman diagram.Finally,the final model and the time and job specific benzene job exposure matrix were fitted and constructed with the whole dataset.In the second part,we collect the benzene occupational exposure data set(GSE5073718)in the Gene Expression Omnibus(GEO).The data set includes 4 patients with chronic benzene poisoning,3 benzene workers(benzene exposure group)and 3 Healthy controls who have not been exposed to benzene.Data analysis was performed by limma package in R software to identify the differentially expressed genes in benzene poisoning group and benzene exposed group.GSEA analysis were conducted to explore the significant enrichment pathways by using GSEA 4.1.0.The Oncomine database was used to analyze the expression level of differentially expressed genes in leukemia patients.Protein-protein interaction(PPI)analysis was performed to investigate the interaction network between the identified genes through the Search Tool for the Retrieval of Interacting Genes database(STRING 10.5).The ESTIMATE and CIBERSORT algorithms were used to estimate the numbers of 22infiltrating immune cells based on the gene expression profiles of 229 patients with DLBCL who were recruited from a public database.The least absolute shrinkage and selection operator(LASSO)penalized regression analyses and nomogram model were used to construct and evaluate the prognostic immunoscore(PIS)model for overall survival prediction.An immune gene prognostic score(IGPS)was generated by Gene Set Enrichment Analysis(GSEA)and Cox regression analysis validated in an independent NCBI GEO dataset(GSE10846).Results:Through continuous optimization of the model structure,the optimal parameters of the two models were determined,and the final parameters were output based on the whole dataset.Between-job group variance and between-factory variance for benzene short-term exposure levels and time-weighted average concentrations accounted for94.76%and 67.92%of the database's large standard deviation,respectively.The short-term exposure level of benzene showed a linear downward trend before 1982,and then a slow upward trend.The benzene exposure concentration of most occupations and jobs exceeded the national occupational exposure limit(10mg/m~3).As for the time-weighted average concentration of benzene,the exposure levels showed a significant downward trend before 2007,and then tended to be stable in every year.Until the year of 2016,the exposure level of various occupations and jobs fluctuated again.However,on the whole,the time-weighted average concentrations of benzene for most occupations and jobs were still below the national occupational exposure limit(6 mg/m~3).Total of 222 genes were up-regulated in the benzene poisoning group,and 21 genes were up-regulated in the benzene-exposed group.The following genes in the benzene poisoning group and the benzene exposure group showed the same trend:KCNJ15,CXCR1,PI3,LINC02597,CYP4F3,ALPL,KRT237.The genes up-regulated in the benzene exposure group also showed an up-regulation trend in leukemia patients,among which KCNJ15,CXCR1,CYP4F3,and KRT23 were the most obvious.Differentially expressed genes are significantly enriched in the biological processes of immune response,defense response,and inflammatory response.A comparative analysis of the key proteins of protein interaction revealed that CXCR1,CCR2,STAT3 and PIK3CD are the key genes for the risk of benzene exposure.Kaplan-Meier curve analysis and log-rank test found that a higher proportion of activated natural killer cells was associated with a poor outcome.While resting NK cells were more representative of patients with better TME results(P=0.001).Activated and resting NK cells are independent risk factors for the prognosis of DLBCL.The adjusted HR was significantly 1.72(95%CI[1.20-2.48],P=0.001)and 0.53(95%CI[0.37-0.76],P=0.005).Poor prognosis is related to increased TME infiltration of activated NK cells in DLBCL samples and decreased TME number of resting NK cells A total of five immune cells were selected in the LASSO model and DLBCL patients with high PIS showed a poor prognosis(HR is 2.16;95%CI[1.33-3.50],P=0.002).Differences in immunoscores and their related outcomes were attributed to eight specific immune genes involved in the cytokine-cytokine receptor interaction and chemokine signaling pathways.The IGPS based on a HR weighted formula of eight genes is an independent prognostic factor(HR is 2.14,95%CI[1.40-3.28]),with high specificity and sensitivity in the validation dataset.Conclusions:The job exposure matrix constructed in this study can be used as the exposure concentration database for benzene exposure evaluation in occupational epidemiological studies,and can be used for risk assessment and management of occupational benzene exposure.There were significant differences in gene expression levels under different benzene exposure levels,among which KCNJ15,CXCR1,PI3,LINC02597,CYP4F3,ALPL,and KRT237 were significantly up-regulated in the benzene exposure group and the benzene poisoning group.The up-regulation of KCNJ15,CXCR1,CYP4F3,and KRT237 genes is associated with the risk of leukemia.The pathogenesis of occupational benzene poisoning-induced leukemia may be related to changes in the body's immune response and inflammatory response.The different abundance of tumor-infiltrating immune cells will affect the clinical outcome and molecular characteristics of DLBCL patients.Compared with the PIS model based on NK cells,Tregs and macrophages,the prognostic model based on immune-related gene characteristics has better predictive effect.