Prediction Of Key Molecules Participated In Key HBV Mutations Selection And Network Construction In Peripheral Blood Lymphocytes Of Patients With Hepatocellular Carcinoma

Hepatocellular carcinoma （HCC） is the sixth most common cancer and the thirdleading cause of cancer related death. More than50%of HCC cases occur in China,and the occurrence of HCC is caused by the comprehensive effect of environmentalfactors, viral factors and genetic factors. The molecular mechanism ofhepatocarcinogenesis is complex and a lot of genes participate in the occurrence anddevelopment of HCC. Chronic infection of hepatitis B virus （HBV） is a major riskfactor of HCC. Chronic HBV infection leads to chronic inflammation, and upregulatesome cytokines and activate the expression of some enzymes in the transcriptionallevel, which increasing the instability of virus and host genome. HBV mutants whichparticipate in the inflammatory network regulation are selected by imbalancedimmune selection and possess synergistic protumorigenic effect. HCC specific HBVmutations such as C1653T, T1753V and A1762T/G1764A gradually accumulate fromchronic HBV infection to hepatocarcinogenesis, and may predict HCC occurrence.A1762T/G1764A, preS deletion （<100bp） and viral load have significant relationswith short survival time of HCC, and A1762T/G1764A and viral load are independentrisk factors of HBV related HCC. Therefore, HBV mutation is an important riskfactor of HCC.Recent years, gene microarray and bioinformatics tools are widely used inscreening differentially expressed genes and predicting diagnostic and prognosticmolecular markers of HCC. MicroRNAs （miRNAs） act as post-transcriptionalregulators of mRNA expression and participate in many cellular processes. Becausesingle miRNAtargets several mRNAs and single mRNAtargets several miRNAs, andmoreover, there is a many-to-many relationship between mRNA and miRNAs. Butcurrent studies just concentrated on single or some differentially expressed genes inone signaling pathway, and a few differentially expressed miRNAs and their targetmRNA from HCC and surrounding tissues, they neglected the network interactionbetween miRNA-mRNA. Taking HBV mutation as a point of cut-in, this studyfocused on the expression profile and network interaction between miRNAs and theirtarget genes/signaling pathways in peripheral blood lymphocytes （PBL） of patientswith hepatocellular carcinoma, and played an important role in elucidating theimmune selection mechanism of HBV mutations and predicting diagnostic and prognostic molecular markers of HCC.Objective: Taking HBV mutation as a point of cut-in, we screened differentiallyexpressed genes and differentially expressed miRNAs in PBL of HCC and non-HCCHBV infected patients to find the variation law of immune network and key immunesub-network markers and find key driver sub-network markers directed by differentHBV mutations in hepatocyte signaling network.Methods: Nested PCR was used to amplify EnhII/BCP/PC and preS regions ofHCC and non-HCC HBV infected patients and obtained HBV mutations, and selected26HCC cases and15non-HCC HBV cases to extract PBL for total RNA. AffymetrixGeneChip PrimeView Human Gene Expression Array and Affymetrix GeneChipmiRNA3.0Array were used to detect mRNA and miRNA expression profiles.Softwares such as SPSS16.0, R software, GSEA （Gene set enrichment analysis）,GO（Gene Ontology）, KEGG （Kyoto Encyclopedia of Genes and Genomes） database,Clone/Gene ID Converter, Cytoscape, STRING, netbox, Chilibot, Moleculeannotation system（MAS） were used to analyze, mine and display microarrayhybridization data.Results:1. Identification of differentially expressed genes and pathwayBased on2.0fold change of microarray expression data, this study identified168differentially expressed genes including114up-regulated genes and54down-regulated genes, and ITGB1, ITGA2B, ITGB1, THBS1, SOS1, TLN1, CD79Awere reported to have relations with hepatocarcinogenesis or immune.We performedGO and KEGG pathway enrichment analysis, found that differentially expressedgenes were significantly enriched in9pathways including Focal adhesion pathway,Primary immunodeficiency pathway, Arrhythmogenic right ventricularcardiomyopathy （ARVC） pathway, p53signaling pathway, MAPK signaling pathway,Gap junction pathway, Systemic lupus erythematosus pathway, Regulation of actincytoskeleton pathway, Graft-versus-host disease pathway. It has been reported thatFocal adhesion pathway, Primary immunodeficiency pathway, p53signaling pathway,MAPK signaling pathway were related with tumorigenesis.2. Literature-based annotation of differentially expressed genesWe searched English keyword （“Cancer”） and differentially expressed genes inChilibot, and found83of168differentially expressed genes were co-existed at least once with keyword “cancer”, among which were68up-regulated genes and15down-regulated genes;67of168differentially expressed genes were co-existed atleast once with keyword “hepatocellular carcinoma”;48of168differentiallyexpressed genes were co-existed at least once with keyword “immune”, among whichwere32up-regulated genes and16down-regulated genes. There were63genesco-existed concurrently with “hepatocellular carcinoma” and “immune”, amongwhich were49up-regulated genes and14down-regulated genes. Furthermore,excluding genes co-existing with abstract, there were30genes co-existedconcurrently with “hepatocellular carcinoma” and “immune”, among which were24up-regulated genes and6down-regulated genes, these genes were potential geneswhich were related to the selection of HBV mutations during HCC occurrence anddevelopment.3. Interaction network map of HCC differentially expressed genesBased HCC vs.non-HCC≥1.7fold change（P<0.05）, We obtained62altered genesand49linker genes to analyze interaction of proteins encoded by differentiallyexpressed genes, and the map showed that the interactive degree of PIK3R1, SHC1,PTK2, GRB2, ITGB1, ITGA2B, ITGB3, COL1A1, PTPN1, COL1A2, FN1, PIK3CA,AKT1, CSK, ITGA6, RASA1, ITGB2, DOK1, TLN1, THBS1, CD79A, SOS1was≥10，and they were regarded as the key molecules of this interaction network map.4. Functional annotation analysis of differentially expressed genes（1） The biological process of differentially expressed genes were concentrated onregulation of response to stimulus, regulation of immune system process, locomotion,response to wounding and immune response, and these process were closely related toresponse of immune system.（2） The molecular functions of differentially expressed genes were concentratedon protein dimerization activity, enzyme binding, receptor binding, proteinheterodimerization activity, identical protein binding and kinase activity.（3） The human phenotypes related with differentially expressed genes wereconcentrated on abnormality of blood and blood-forming tissues, neoplasm,abnormality of leukocytes, abnormality of lymphocytes, hematological neoplasm,abnormality of immune system physiology, abnormality of B cells and recurrentinfections.（4） The co-expression genes of differentially expressed genes were concentrated on Genes up-regulated in CD34+cells isolated from bone marrow of CML （chronicmyelogenous leukemia） patients compared to those from normal donors, HumanStemCell Amundson08₉90genes, Human EmbryonicStemCellThomas08₁088genes, Genes with promoters bound by FOXP3in unstimulatedhybridoma cells, Human Breast Liu08₁878genes, and Human LiverTzur09₁908genes.5. Differentially expressed miRNAs and functional annotations of target genesBased HCC vs.non-HCC≥2.0fold change, there were103differentiallyexpressed miRNAs, among which were49up-regulated genes and54down-regulatedgenes. And target genes were mainly concentrated on DNA-dependent regulation oftranscription, signal transduction, multicellular organismal development,DNA-dependent transcription, transmembrane transport; and the functionalannotations were concentrated on pathways in cancer, MAPK signal pathway,Regulation of actin cytoskeleton, Endocytosis and Focal adhesion. The interactivedegree of miR-548a-3p, miR-181c-5p, miR-181d, miR-145-5p, miR-26b-5p,miR-195-5p, miR-182-5p, miR-421, miR-382-5p was≥15，and they were regarded asthe key miRNA.6. Network of mRNA and miRNAThe intersection of predicted target genes of differentially expressed miRNA anddifferentially expressed genes （≥2.0fold change） is a interactive network of57differentially expressed genes and14differentially expressed miRNA. Theintersection of hub genes and predicted target genes of differentially expressedmiRNA is a interactive network of39differentially expressed genes and14differentially expressed miRNA.Conclusion: Differentially expressed genes such as THBS1，TNL1, CD79A,SOS1, ITGB1，ITGA2B，ITGB3and differentially expressed miRNA such asmiR-548a-3p，miR-181c-5p，miR-181d，miR-145-5p，miR-26b-5p，miR-195-5p，miR-182-5p，miR-421，miR-382-5p may have relations with hepatocarcinogenesis orimmune, and may participate in the immune selection of HCC specific HBVmutations, but it needs further validation.