Regulation Of Alveolar Macrophages Homeostasis By Lkb1 And The Related Research On Tumor Epigenetics

Topic one:Regulation of alveolar macrophages homeostasis by Lkb1 in the cells.The metabolomics analysis was performed based on the gas chromatography-mass spectrometry or multi-reaction monitoring technology.The Seahorse XF technology was used to analyze the cellular metabolism.Gene level of the cells was tested by real-time fluorescence quantitative polymerase chain reaction(RT-qPCR)technology.The protein level was tested by western blot.Reactive oxygen levels were obtained from the detection kit.The examination associated with the immunophenotype was performed by flow cytometry analysis.If the design of the experiment was paired,the paired test was used,while the comparison of two independent groups of samples was examined by t test.Results:There was lipid storage in AM in Cd11cCreLkb1f/f mice compared with Lkb1f/f mice.The results of metabolomics analysis showed that in AM of CdllcCreLkb1f/f mice the examined levels of nicotinamide adenine dinucleotide(NAD)and so on were down regulated compared with the AM of Lkb1f/f mice,while the levels of linoleic acid,oleic acid,and ?-D-fructose 6-phosphate were up regulated with statistical difference(P<0.05).The results of Seahorse XF experiment showed that in AM of Cd11cCreLkb1f/f mice there was enhanced glycolysis process and breathing capacity,and increased ATP production.The examination of reactive oxygen species(ROS)demonstrated that Lkb1 deficient AM produced more ROS,and the ROS inhibitor could rescue the absence of AM ratio in Cd11cCreLkb1f/f to some degree.Both the gene and protein levels of peroxisome proliferator-activated receptor-?(PPAR-?)were decreased in AM of Cd11cCreLkb1f/f mice,its agonist could rescue the lipid storage in AM partially.Conclusion:Lkb1 plays an critical role in the intracellular regulation of glucose or lipid metabolism in AM.ROS inhibitor or PPAR-? agonist could rescue the proportion of Lkb1 deficient AM or its lipid accumulation to a certain extent.Part 1 The establishment of Cd11cCreLkblf/f conditional knockout mouse and the identification of its immunophenotypeObjective:To clarify the critical role of Lkbl in the alveolar macrophage(AM)when it exerted its immune function.Methods:After amplifying the mouse DNA we performed the agarose gel electrophoresis to identify its genotype.Alveolar lavage fluid was obtained from the Lkb1f/f and Cd11cCreLkb1f/f mice and the lung tissue was taken to prepare the single cell suspension in order to do the Flow cytometry analysis.The Click-iTTM Plus EdU kit was used to examine the cells' proliferation.By intranasal drops,Staphylococcus aureus was used to build the pneumonia model.The deletion of macrophages in the lung was performed according to the protocol of macrophage deletion kit from Nano Sciences company.The comparison of two independent continuous variables was performed by t test.Results:We had established Cd11cCreLkb1f/f conditional knockout mouse by crossbred,the examined results showed that both the absolute number and percent of AM in CdllcCreLkb1f/f mice were obviously decreased,and the cell's apoptosis was increased compared by Lkb1f/f mice(P<0.05),but the macrophage precursors,monocytes and fetal macrophages were not changed.The results of pneumonia model demonstrated that there was more severe lung inflammation,more infected bacteria,increased percent of neutrophils and decreased percent of eosinophils in CdllcCreLkb1f/f mice or the AM deletion group compared with Lkb1f/f mice or the controlled group of deletion experiment,with statistical difference(P<0.05).Conclusion:Lkb1 deficient in AM could result in the absence of its number or ratio,this absence of AM came from its own increased apoptotic or necrotic cells,and could make the lung of the mouse vulnerable to pathogen infection and imbalance the percent of neutrophils/eosinophils.Part 2 Metabolism related test and the rescue experiments of AM in CdllcCreLkb1f/f miceObjective:To explore the influence of Lkb0 on the metabolism of AM,rescue the absence of Lkb0 deficient AM or its function.Methods:We used the flow cytometry or magnetic bead sorting technology to purify AM.Oil red O was used to stain the lipidPart 3 The critical signaling pathways and genes in Lkb1 deficient alveolar macrophageObjective:To explore the affection of Lkb1 deficiency on the transcript levels of important genes in AM and the changes of related pathways.Methods:We used the flow cytometry sorting technology to select AM cells and performed the RNA-seq analysis,the examined platform was BGISEQ-500.Cytohubba plug-in was used to screen the key genes.The heatmap was obtained from R software.Results:The different genes(Cd11cCreLkb1f/f vs Lkb1f/f)were mainly enriched in pathways such as inflammatory response,glycerolipid metabolic process,lipid storage,almost all genes accumulated in those pathways were up regulated in AM of CdllcCreLkb1f/f mice.The results of scores for Hub genes showed that genes as C-X-C motif chemokine receptor 2(CXCR2),Toll like receptor 2(TLR2),mitogen-activated protein kinase 3(MAPK3),CD40,chemokine(C-C motif)receptor 7(CCR7)and so on were relatively important and their expressions were up regulated in AM of CdllcCreLkb1f/f mice.The results of gene set enrichment analysis(GSEA)showed the same inflammatory response or metabolism related pathways as Cytoscape.Conclusion:The related genes in inflammatory response and glycerolipid metabolic process were up regulated in Lkb1 deficient AM,some key genes such as TLR2,CD40,CCR7 might play an important role in this process.Topic two:The epigenetics associated research on gastric cancer and melanomaPart 1 The DNA methylation subsets of patients with gastric cancer and the construction of prognosis predicting modelObjective:To establish prognosis assessment model for the prediction of patients with high-risk gastric cancer based on the DNA methylation subtypes of gastric cancer and provide the evidence for clinical diagnosis or treatment.Methods:We used the Cox risk regression analysis to determine the independent prognosis related methylation sites and performed the division of patients' subsets,the risk assessment model was built by coxph function.The pathway enrichment of genes was performed by Cytoscape software.Correlation analysis was performed by Spearman or Pearson analysis.The parametric or non-parametric test was used to compare the samples in two or more independent groups.Results:We selected 610 independent prognosis related methylation sites(P<0.05)and divided the patients with gastric cancer into 7 methylation subsets,and built the predicted model of the prognosis risk based on the significantly changed methylation sites(P<0.05)in the sixth cluster which presented higher methylation level of sites and survival rate of patients than other subsets.This model could efficiently identify patients with gastric cancer in the high risk category from the low risk category with the area under the receiver operating characteristic curve more than 0.90,its efficiency was validated in another methylation files of patients with gastric cancer.The corresponding genes of independent prognosis associated methylation sites were enriched in the cancer pathway or gastric cancer signaling pathway.Among these genes,the expression level of transforming growth factor ?2(TGF?2)was changed among different survival states,T categories,grades,and tumor stages of the patients with gastric cancer,and it was up-regulated in patients with cancer compared with the normal,involved in the signaling pathways of this disease.Conclusion:We realized the identification of the subsets of patients with gastric cancer based on large number of DNA methylation files and established the evaluation model of prognosis risk that could efficiently find the patients with high risk.Some key corresponding genes to the independent prognosis related methylation sites such as TGF?2 was observed,these gene could provide new evidence and ideas for diagnosis and personalized risk assessment of patients with the gastric cancer.Part 2 Identification of melanoma subsets based on the DNA methylation files and the construction of the prognosis evaluation modelObjective:To build the risk assessment model for prediction of melanoma through the establishment of the DNA methylation subsets,and explore the key corresponding genes to the independent prognosis associated methylation sites.Methods:We identified the independent prognosis related methylation sites by Cox risk regression method and further did the subdivision based on 475 methylation files of patients with melanoma.The risk assessment model was built by R software and pathway enrichment of the site genes was performed by CIueGo.The parametric or non-parametric test was used according to if the data fulfilled the normal distribution and the homogeneity of variance.Results:We identified 256 melanoma independent prognosis related methylation sites(P<0.0001)and divided the patients into 7 methylation subgroups,among these subsets the methylation levels and survival time in the second subgroup were dramatically lower than other clusters(P<0.05).Thus we established the predicted model of the prognosis risk for patients with melanoma by using the significantly changed methylation sites in the second subset,this model could efficiently divide patients into high and low risk groups and had high examining efficiency with the area under the receiver operating characteristic curve of 0.833.After analyzing we found the number of dead patients increased and the methylated levels of patients decreased as the risk scores increased,the survival rate of patients with high risk scores was much lower than the patients with low risk scores.The results of correlation analysis revealed that there was negative correlation between the risk scores of patients with melanoma and their survival time(rs=-0.325,P<0.0001).The corresponding genes to the independent prognosis associated methylation sites were mainly enriched in the cancer or immunology related pathways.We identified 35 hub genes from these site genes,and among them there were significant differences in the expression levels of DOK2,GPBAR1,GBP4.PSMB9 among different methylation subgroups,survival states of the patients,tumor stages and clinical T categories and they had positive correlation(P<0.05).Conclusion:We realized the division of methylation subsets for the patients with melanoma based on the large number of the samples and constructed the prognosis risk assessment model with high examining effectiveness,meanwhile we found some critical site genes that were significantly correlated with the prognosis states of the patients,there were obviously positively correlation among these genes,indicating that they might promote the formation of melanoma together by the synergy,it was of great significance for explaining the molecular biological mechanism of the melanoma disease and provided a new target for clinical diagnosis or treatment.Part 3 The expression of m6a regulatory genes in patients with melanoma and its significanceObjective:To explore the critical role of regulatory genes of RNA epigenetic modification N6-methyladenosine(m6a)in the disease formation process of melanoma.Methods:We analyzed the expression of the regulatory genes of m6a based on Oncomine datasets,and validated them in the gene expression omnibus dataset(GEO).The hub genes were obtained by Cytohubba.The gene mutation was analyzed by using online tool-cBioportal.Results:We found that the expression of YTHDF1 and HNRNPA2B1 was up-regulated in patients with melanoma,and the efficiency of the combining regression analysis of these two genes was increased by about 10%compared with the single gene.The results of the gene enrichment for the critical genes in melanoma transcripts showed that the genes such as CDK2,CDK1,RRM2,CCNB1,CHEK1 were included in the p53 signaling pathway.There was positive correlation between these five genes and YTHDF1 or HNRNPA2B1,indicating that the two m6a regulatory genes might regulate the expression of the five hub genes above by affecting their m6a modification,further promote their inhibition of p53 signaling pathway.We also observed that the main mutation of YTHDF1 and HNRNPA2B1 was amplification,and there was significant difference between patients with and without mutation of m6a regulatory genes in different tumor stages' and treatment responses' groups.Conclusion:We diagnosed and identified the patients with melanoma by using the combining regressive method of m6a regulatory genes for the first time.Meanwhile,we found there was significant change in the expression levels of YTHDF1 and HNRNPA2B1 in patients with melanoma and they might have influence on the disease progress of the patients by p53 signaling pathway.