Transcriptomics Study Of Aflatoxin B1 Effect On Human Hepatocyte Cell Line HL-7702 And Primary Hepatocellular Carcinoma With TP53 Mutantion

Research content:The study was divided into four parts:1.The effect of aflatoxin B1 on the biological behavior of human hepatocyte cell line HL-7702;2.The whole transcription sequencing study of the effect of aflatoxin B1 on human hepatocyte cell line HL-7702 and differential expression analysis;3.Whole transcriptome association analysis of aflatoxin B1 on human hepatocyte cell line HL-7702;4.Combined transcriptome analysis and validation of aflatoxin B1 on human hepatocyte cell line HL-7702 and primary hepatocellular carcinoma with TP53 mutationObjective:To study the effect of secondary metabolites of AFB1 in liver microsome on normal liver cell line HL-7702Materials and Methods:AFB1 and NADPH?2 mM final concentration?and liver microsomes?1.5 mg/mL final concentration?mixed with PBS,placed in a 3 7?,5%CO2 incubator for 30 minutes,and obtain a secondary metabolite mixture.The above mixture was added to normal human liver cell line HL-7702,incubated in an incubator for 30 minutes,then HL-7702 washed three times with PBS,and then cultured in DMEM complete medium containing 10%fetal bovine serum.The effect of different concentrations of AFB1 on the growth activity of cell line HL-7702 was detected by MTT assay from 24 hours to 96 hours.Flow cytometry was used to detect the effect of HL-7702 cell cycle and apoptosis 24 hours after AFB1 treatment.The changes of 8-hydroxydeoxyguanosine?8-OHdG?in HL-7702 cell line 24 hours after AFB1 treatment were detected by enzyme-linked immunosorbent assay.The Sanger method was used to detect TP53 R249S mutation in HL-7702 cell line 96 hours after AFB1 treat.Data statistics and calculations were performed using SPSS 22.0 software package,and mapping was performed using GraphPad Prism 6.0 software.The description of the measurement data conforming to the normal distribution is described by means of mean ± standard deviation.The t-test was used to compare the groups between the measured data of the normal distribution.P<0.05 was considered to be statistically significant.Results:1.MTT results showed that the secondary metabolites of AFB1 in liver microsome metabolism inhibited the growth activity of liver cell line HL-7702.The cell growth activity showed significant difference from 72 hours to 96 hours after AFB1 treat.The larger of AFB1 concentration,the lower of HL-7702 cell growth activity.2.Flow cytometry showed that the ratio of G1-G0 phase or G2-M phase of HL-7702 cells treated with 2?M and 0.2?M AFB1 was significantly different from that of 0.02?M group?P<0.05?.There was no significant difference between the 0.02 ?M treated group and the liver microsome control group and the blank control group3.The 8-OHdG content of HL-7702 cells treated with 2?M and 0.2?M AFB1 was significantly increased compared with the concentration of 0.02?M?P<0.001?.The 0.02 ?M AFB1 treated group has not significant differences compared with the liver microsome control group and the blank control group.4.HL-7702 cells treated with AFB1 at a concentration of 2 ?M after liver microsome metabolism to induce a mutation G to T in the third base of the TP53 R249S.Conclusion:The product of AFB1 in liver microsome metabolism inhibits the growth activity of liver cell line HL-7702 and leads to G2/M cell cycle arrest which is concentration-dependent;however,short-term intervention of AFB1 at 2 ?M and below does not cause early apoptosis of HL-7702 cells.HL-7702 cells treated with AFB1 in liver microsomes can induce TP53 R249S third base mutation from G to TObjective:To detect the changes in the whole transcriptome of AFB1 on liver cell line HL-7702 by whole transcriptome sequencing and to analyze the differential expression of the whole transcriptome.Materials and Methods:The experimental group used AFB1?0.2 ?M?and NADPH?2 mM final concentration?and liver microsomes?1.5 mg/mL final concentration?,and control group used liver microsomes and NADPH,incubated in a constant temperature incubator for 30 minutes.The HL-7702 cells were treated with mixture for 30 minutes and then washed three times with PBS,and then added to the complete medium for further 48 hours.Trypsin digestion,collection of cells,labeling,liquid nitrogen freezing,dry ice transport to the testing company for whole transcriptome sequencing and sequencing data analysis.Results:The following transcriptomes were found to be significantly differentially expressed by whole transcriptome sequencing:1.1027 gene mRNA was significantly differentially expressed,of which 432 were up-regulated and down-regulated by 595.GO enrichment analysis showed that AFB1 caused significant differential expression of mRNA mainly involved in regulating cell cycle,apoptosis,proliferation,metabolism,adhesion,and cytochemical stimulation.Biological processes such as response,DNA damage repair,and angiogenesis.KEGG pathway analysis suggested that AFB1 may affect TNF signaling pathway,TGF-?,chromosomal recombination,P53 signaling pathway,NF-?B signaling pathway,cell cycle,adhesion and AMPK signaling pathway.2.29 lncRNA were significantly differentially expressed,of which 15 were up-regulated and 14 were down-regulated.3.9 miRNAs were significantly differentially expressed,of which 3 were up-regulated and 6 were down-regulated.4.72 circRNAs were significantly differentially expressed,of which 35 were up-regulated and 37 were down-regulatedConclusion:AFB1 affects the whole transcriptome expression of normal liver cell line HL-7702.The differential gene enrichment analysis shows that AFB1 affects the biological functions of HL-7702 cell cycle,apoptosis,proliferation,adhesion and DNA damage repair..It may be involved in the regulation of TNF signaling pathway,TGF-?,chromosomal recombination,P53 signaling pathway,NF-?B signaling pathway,cell cycle,adhesion and AMPK signaling pathways.Objective:To explore the correlation between the transcriptome changes of AFB1 affecting liver cell line HL-7702 and its regulation mechanism at the expression level.Materials and Methods:Analytical materials were derived from the full transcriptome sequencing data from the second part of the paper.Correlation analysis of significant differentially expressed whole transcriptome data using Novofinder,miRanda-3.3a,PITA,RNAhybrid,psRobot,GOSeq-topGO:Release 2.12,KOBAS:version 2.0,Cytoscape,etc.Construct the ceRNA network.Results:1.AFB1 affects the HL-7702 cell line with significant differential expression of 29 IncRNA and mRNA significantly differentially expressed between 757 genes in coexistence or co-expression relationship.Among them,lncRNAs were up-regulated,and there were 234 target genes with up-regulated mRNA;lncRNAs were down-regulated and 439 target genes were down-regulated with mRNA.Functional enrichment analysis revealed that these genes are involved in cell cycle regulation,differentiation,cell metabolism,DNA recombination,and damage repair,and are enriched in P53 signaling pathways and cancer-associated signaling pathways.2.Significantly differentially expressed lncRNA-miRNA association analysis suggests that there may be a mutual regulatory relationship between IncRNA and miRNA:CDKN2B-AS1 and hsa-miR-122-5p and hsa-miR-455-3p,CTD-3014M21.1 and hsa-miR-411-5p and hsa-miR-3591-3p,LINC00162 and hsa-miR-3591-3p and hsa-miR-494-3p,PP7080 and hsa-miR-122-5p and hsa-miR-3690,PSMA3-AS1 and hsa-miR-455-3p and hsa-miR-411-5p,RP11-658F2.8 and hsa-miR-31-5p,SBF2-AS1 and hsa-miR-411-5p,SCARNA9 and hsa-miR-379-5p.3.Nine significantly differentially expressed miRNAs?hsa-miR-455-3p,hsa-miR-411-5p,hsa-miR-31-5p,hsa-miR-381-3p,hsa-miR-379?-5p,hsa-miR-494-3p,hsa-miR-122-5p,hsa-miR-3690,hsa-miR-3591-3p)regulated 534 significantly differentially expressed target genes.Gene enrichment analysis suggests that these target genes are involved in the regulation of cellular molecular function,cellular metabolism,cell development processes and protein binding,and regulate cell cycle,PI3K-Akt signaling pathway,P53 signaling pathway,AMPK signaling pathway,NF-kB signaling pathway Wait.4.AFB1 probably affect HL-7702 cells between following circRNA and genes:hsa_circ₀078538-EZR,hsa_circ₀017348-ZNF124,novel_circ₀005089-ZNF124,novel_circ₀002289-CEP128,novel_circ₀000551-BIRC2)5.Total transcriptome differential expression data were analyzed by ceRNA network,and a total of six IncRNA-miRNA-gene networks were constructed with six miRN,As?up regulation:hsa-miR-455-3p,hsa-miR-411-5p,hsa-miR-31-5p;down-regulation:hsa-miR?-122-5p,hsa-miR-3690,hsa-miR-3591-3p).Conclusion:Association analysis of AFB1 affects the HL-7702 transcriptome difference suggests that there is a regulation relationship between lncRNA,miRNA,circRNA and mRNA.Six lncRNA-miRNA-gene regulatory networks were constructed with significantly differentially expressed miRNAs?hsa-miR-455-3p,hsa-miR-411-5p,hsa-miR-31-5p;hsa-miR-122-5p,hsa-miR-3690,hsa-miR-3591-3p?.Objective:To analyze the differential expression data of the whole transcriptome in the second part of the present study and the difference between the TCGA database TP53 R249S mutation and the non-mutated HCC expression profile,and to explore the molecular markers that AFB1 and TP53 R249S mutant HCC have a synergistic effect and study their role in TP53 R249S mutations in HCC,explore the mechanisms to AFB1 associated HCC.Materials and methods:HCC expression profiles?mRNA,lncRNA and miRNA?,clinical pathological parameters and prognostic data were obtained from the TCGA database,and differential expression profiles was analyzed by group divided with TP 5 3 R249S mutation or not.Then the full transcription of differential expression was subjected to joint analysis with the second part of the paper.Finally candidate differential expression profile information obtained by intersection analysis.The HCC samples of TP53 R249S mutation sequencing have been verified in our samples,and their relationship with clinical pathological parameters and prognosis is analyzed.GO and KEGG were used for molecular biological function and related pathway mechanism prediction.Differential expression analysis of TCGA primary liver cancer expression profile data was performed using the EdgeR software package.Candidate expression profiles of cancer tissue and paracancerous tissue were analyzed by paired-sample t-test.Secondly,statistical analysis of the relative expression of genes in TP53 R249S mutant and non-mutant tumor and paracancerous tissue samples was performed using an independent sample t test.Chi-square test was used to compare the distribution of clinical factors between the mutant and non-mutant groups,and the high expression and low expression groups of the candidate expression profiles.The clinical factors and clinical prognosis were analyzed using Kaplan-Meier survival curve and one-way Cox risk model.The statistical difference between the curves of each group was compared by Log Rank test.Hazard Ratio?HR?and 95%Confidence Interval?CI?were used to assess the relationship between TP53 R249S mutation status and gene expression levels and clinical outcome.Statistical analysis was performed using SPSS 22.0,P<0.05 was considered to be statistically significant.Statistical plots were plotted using GraphPad Prism 6.0 software.Results:1.The whole transcriptome sequencing data of HL-7702 cell line after AFB1 treated and the expression profile of HCC TP53 R249S mutation in TCGA database were combined to obtained 6 differential genes,including up-regulated genes:CTXN1,CDCP1,CALB2;down-regulated genes:CRYAB,EN03,GPRC5A.2.In independent sample validation,the expression levels of CDCP1,CALB2,CRYAB,EN03 and GPRC5A in cancer tissues were lower than those in adjacent tissues?P<0.05?,and CALB2,CRYAB and GPRC5A in TP53 R249S mutant cancer tissues.The mRNA expression level was higher than that of TP53 non-mutated cancer tissues?P<0.05?.3.CDCP1 and CTXN1 may be significantly associated with HBV DNA replication?both P=0.035?and associated with liver fibrosis?both P=0.058?.CTXN1 and GPRC5A may be significantly associated with the degree of differentiation of HCC?both P=0.047?.4.The TP53 R249S mutation was associated with the TNM stage of the TCGA database HCC?P=0.039?,and the later the stage,the greater the likelihood of mutation.Patients with non-mutated TP53 R249S had a longer overall survival?t=1791 days?than patients with mutations?t=334 days?.For patients with important relapsed survival,HCC patients with non-mutated IP53 R249S had a lower risk of recurrence?HR=0.37,95%CI=0.19-0.73,P=0.003?5.Bioinformatics functional enrichment analysis suggests that CALB2,CRYAB and GPRC5A may be involved in the regulation of TP53 gene.Conclusion:The whole transcriptome sequencing data and the expression profile of HCC TP53 R249S mutation in the TCGA database were conducted to joint analysis to obtained six genes with significantly differential expression of mRNA,including CTXN1,CDCP1,CALB2,CRYAB,EN03,and GPRC5A.Among them,CALB2,CRYAB and GPRC5A may be involved in the regulation of TP53 gene and related to TP53 R249S mutation.The TP53 R249S mutation is associated with poor prognosis in patients with HCC.