Chapter 1A Prognostic Model of Fatty Acid Metabolism Related Genes in Acute Myeloid LeukemiaBackgroundAcute myeloid leukemia(AML)is a malignant proliferative disease of myeloid Archaeocyte in the hematopoietic system.In recent years,with the development of hematopoietic stem cell transplantation,targeted therapy,and chimeric antigen receptor modified T cells,the complete remission rate and 5-year survival rate of AML patients have improved.However,some patients still experience recurrence and drug resistance,and the overall prognosis is poor.Therefore,exploring new therapeutic targets for AML is of great significance in improving patient prognosis.Fatty acid metabolism,as an important component of lipid metabolism,can participate in important physiological processes such as cell membrane generation and synthesis of various signaling molecules.Fatty acid peroxidation can promote the survival of AML cells and reduce their drug sensitivity.Therefore,research on the role and mechanism of fatty acid metabolism in AML can help identify new therapeutic targets and improve the prognosis of AML patients.ObjectiveEstablish a risk model related to fatty acid metabolism genes to predict the prognosis of acute myeloid leukemia,and search for new biological markers and potential therapeutic targets related to AML prognosis.Methods1.Take the transcriptome and clinical information of AML patients in TCGA and GEO databases as the training set and verification set.Construct a prognostic model for fatty acid metabolism related genes using univariate COX regression and LASSO algorithm.2.AML patients are divided into high-risk and low-risk groups according to the median prognosis score.Analyze the accuracy and independence of the prediction model with Kaplan-Meier survival curve,subject work characteristic curve,and other analysis methods.3.Utilize GO and KEGG enrichment analysis to compare the signaling pathways of differential gene enrichment between high-risk and low-risk groups,and explore the biological processes and molecular functions related to fatty acid metabolism.4.Compare the difference of immune cell infiltration between groups through two algorithms of ESTIMATE and CIBERSORT,and analyze the correlation between fatty acid metabolism and tumor immune microenvironment.5.By analyzing the expression levels of drug sensitivity related genes,compare the drug sensitivity differences between high-risk and low-risk groups,and predict targeted drugs with potential therapeutic effects.Results1.A prognostic model based on 11 fatty acid metabolism related genes(CBR1,MAO A,ENO3,OSTC,UROD,PCTP,MAPKAPK2,PLA2G4A,EPHX2,ACSL6,and IDI1)can accurately evaluate the prognosis of AML patients.2.Differential genes between high-risk and low-risk groups in immune related pathways,like signaling and NF-κB signaling pathways are significantly enriched,and the high-risk group has a higher degree of infiltration of immune cells such as M2 macrophages and monocytes.3.AML patients in low-risk group were more sensitive to cytarabine,vorinostat,miditoline and other chemotherapy drugs.4.The core gene CD 163 is negatively related to the prognosis of AML patients,and participates in the immune regulation of tumor microenvironment..ConclusionThis study screened 11 fatty acid metabolism genes that are associated with prognosis in AML patients,established a risk score that is negatively correlated with the prognosis of AML patients,and constructed a fatty acid metabolism related prognosis model based on the clinical characteristics of patients,which can accurately evaluate the prognosis of AML patients.At the same time,further analysis found that fatty acid metabolism genes participate in a variety of immune related signaling pathways,participate in the formation of tumor immune microenvironment,and affect the drug sensitivity of AML cells.In summary,the fatty acid metabolism gene model provides potential prognostic biomarkers and treatment targets for AML patients,which is conducive to personalized and precise treatment.Chapter 2A prognostic model for lactate metabolism related lncRNA in acute myeloid leukemiaBackgroundAcute myeloid leukemia(AML)is a hematological tumor which is highly invasive malignant and mainly characterized by the failure of differentiation and maturation of bone marrow blast cell,abnormal proliferation and apoptosis.At present,the incidence rate of AML is increasing year by year,which has seriously threatened human health.Although new treatment methods such as hematopoietic stem cell transplantation,chimeric antigen receptor T cell immunotherapy and chimeric antigen receptor NK cell immunotherapy have gradually been put into clinical application recently,the 5-year survival rate of adult AML patients is still low.Tumor cells often undergo a large amount of aerobic glycolysis during the proliferation process,and lactic acid,as one of the products of glycolysis,is closely related to the occurrence and development of tumors.Although some long chain non-coding RNA do not encode proteins,they can affect the development of AML cells by affecting the expression of genes related to lactate metabolism.Therefore,understanding the impact and mechanism of lactate metabolism related lncRNA on the prognosis of AML patients will help to discover new biomarkers and potential therapeutic targets in AML.ObjectiveEstablish a risk model for lncRNA related to lactate metabolism to predict the prognosis of AML patients,and clarify its impact and related mechanisms on the prognosis of AML patients.Methods1.Obtain the transcriptome data of AML patients and normal people from TCGA database and GTEx database,download the gene set related to lactate metabolism in MSigDB database,screen out the differentially expressed genes related to lactate metabolism in AML patients,and analyze the co-expressed lncRNA by Pearson test.2.Take the transcriptome and corresponding clinical information of AML patients in TCGA database and Beat AML database as the training set and validation set.Establish a prognostic model for lactate metabolism related lncRNA using univariate COX regression and LASSO regression.3.AML patients were divided into high-risk and low-risk groups by the median prognosis score,and the accuracy of the prediction model were evaluated using Kaplan-Meier survival curve,subject work characteristic curve,and other methods.4.Utilize the Metascape database for GO and KEGG enrichment analysis,and visualize using R language to explore the biological processes and molecular signaling pathways that lactate metabolism related lncRNAs may participate in AML.5.Analyze the differences in immune function between two groups using ESTIMATE and CIBERSORT algorithms,analyze the differences in immune matrix and immune cell infiltration,and clarify the correlation between risk score and immune response.Results1.Nine significantly differentially expressed lactate metabolism related genes(HBB,SLC16A3,PYGL,MPL,LDHAL6A,SLC16A8,COX6A2,SLC4A1,SPP1)were found in AML patients and normal control groups,and 12 co-expressed lncRNAs related to the prognosis of AML patients were screened.2.Based on 12 co-expressed lncRNAs,an AML related risk prediction model can be constructed and the prognosis of AML patients can be accurately evaluated,and this risk score is not affected by clinical characteristics such as patient age and gender.3.The differential genes between groups are mainly enriched in pathways such as cell formation,extracellular matrix construction,and cell adhesion,and are associated with NPM1 mutations and PML-RARa Fusion gene related.4.Lactate metabolism related genes may affect the physiological processes of AML cells by mediating immune cell responses and immune matrix infiltration.ConclusionIn this study,12 prognosis related lncRNAs related to lactate metabolism were screened out,and a relevant prognosis model was constructed accordingly.It was found that lactate metabolism related genes regulate the occurrence and development of AML cells by influencing extracellular matrix formation,cell adhesion and other pathways,and can mediate immune cell response and immune matrix infiltration in AML,thereby affecting the tumor microenvironment.In summary,this lncRNA prognostic model related to lactate metabolism can provide new biomarkers and potential therapeutic targets for AML patients. |