Genomics-Based Analysis Of Cuproptosis-Related Prognostic Model In Diffuse Large B-Cell Lymphoma

Chapter 1 Construction of a prognostic cuproptosis-related long noncoding RNAs risk model for diffuse large B-cell lymphomaObjective:Diffuse large B-cell lymphoma(DLBCL)remains the most common type of non-Hodgkin lymphoma(NHL)in adults,accounting for approximately 25%to 30%of newly diagnosed NHL patients annually.In the era of immunochemotherapy,although first-line R-CHOP significantly improve the survival status of DLBCL patients,about 40%of patients did not respond well to standard first-line chemotherapy due to the high heterogeneity of DLBCL.The international prognostic index provides clinically useful guidelines for prognosis assessment of DLBCL patients.However,the impact of tumor microenvironment on prognosis is not considered,so those no longer meet the needs of optimal prognosis management of DLBCL patients.Therefore,exploring the molecular mechanisms of DLBCL and searching for new biological markers to establish a more accurate prognostic model are of great significance in improving the prognosis of DLBCL patients.Cuproptosis is a copper-triggered programmed cell death that relies on mitochondria respiration.Cuproptosis is closely related to immune cell infiltration in various tumors and plays a crucial role in the occurrence,development,and metastasis of diverse tumors.Studies have shown that the serum copper content is an independent prognostic factor in lymphoma patients and closely related to tumor activity.Copper compounds induced apoptosis in lymphoma cells and inhibited lymphoma growth in mouse models.However,the mechanism of cuproptosis in DLBCL progression,its biological function,and its interaction with the tumor microenvironment have not been fully clarified yet.Long noncoding RNAs(lncRNAs)are a group of non-coding RNAs longer than 200 nucleotides,which play a role in the development and metastasis of tumors.Currently,more and more studies have shown that lncRNAs are correlated with the prognosis of DLBCL patients,but most of them exhibit unsatisfactory predictive performance.Cuproptosis-related lncRNAs may play important roles in the occurrence,metastasis,and drug resistance of many malignant tumors.However,the molecular mechanisms of cuproptosis-related lncRNAs in DLBCL remain largely elusive.Therefore,gaining a deeper understanding of the molecular mechanisms and clinical significance of cuproptosis-related lncRNAs in DLBCL will contribute to the development of more reliable prognostic and predictive biomarkers for DLBCL,which is critical for assessing prognosis accurately and optimizing treatment decisions.Objective:1.To screen cuproptosis-related prognosis lncRNAs and construct a prognostic model for DLBCL.2.To construct nomogram using cuproptosis-related lncRNAs prognostic model combined with clinical features.3.To explore the potential molecular biological functions and mechanisms associated with the cuproptosis-related lncRNAs prognosis model.Methods:1.RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas(TCGA).The gene expression profiles and clinical information of the GSE10846 dataset were downloaded from the Gene Expression Omnibus database.The messenger RNA and lncRNA expression matrices were obtained using a custom Perl script.2.We collected cuproptosis-related genes from the previous studies.Pearson correlation analysis was used to correlate the expression levels of lncRNAs and cuproptosis-related genes to identify cuproptosis-related lncRNAs.3.According to univariate Cox,least absolute shrinkage and selection operator(Lasso)and multivariate Cox regression analysis,we identified seven cuproptosis-related lncRNAs and established a risk prediction model.The risk score for each patient was calculated,and the median risk score was used as the cut-off point to divide DLBCL patients into high-risk and low-risk groups.Principal component analysis and Kaplan-Meier survival curves were used to evaluate the predictive ability of the model.Internal validation was performed on the GSE10846 dataset,and external validation was conducted on TCGA dataset.In addition,a nomogram model combining the cuproptosis-related signature with clinical features was developed.Receiver operating characteristic curve and calibration plot were displayed to validate the predictive accuracy of the nomogram model.4.Gene Ontology function analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used to predict the function of differentially expressed genes.The singlesample gene set enrichment analysis and the ESTIMATE algorithm were used to analyze immune status between high-and low-risk groups.5.Finally,potential effective drugs for DLBCL were identified through drug sensitivity analysis.Results:1.We identified a set of seven cuproptosis-related lncRNAs including LINC00294,RNF139-AS1,LINC00654,WWC2-AS2,LINC00661,LINC01165 and LINC01398.Based on this set of lncRNAs,we constructed a risk model for DLBCL.2.This risk prognosis model can stratify DLBCL into high-and low-risk groups,with the high-risk group being associated with shorter survival time than the low-risk group.Nomogram-based risk scale demonstrates an accurate and objective prediction ability.The risk score was an independent prognostic factor for DLBCL patients,without clinical features interfering.3.By analyzing the immune landscapes between two groups,we found that regulatory T cells,neutrophil,mast cells,eosinophils,γδ T cells and type 2 helper T cells were significantly increased in the high-risk DLBCL group.4.Functional enrichment analysis revealed that the differentially expressed genes were mainly concentrated in phospholipid metabolic process,cellular carbohydrate metabolic process,regulation of carbohydrate biosynthetic process,primary bile acid biosynthesis pathway,reactive oxygen species response,mitogen-activated protein kinase signaling pathway,hypoxia-inducible factor 1 signaling pathway and Ras signaling pathway.5.Finally,drug sensitivity analysis revealed that the half-maximal inhibitory concentration of AKT inhibitor Ⅷ,bortezomib,crizotinib,phenformin,vinorelbine and pyrimethamine were statistically different between the high-risk and low-risk groups of DLBCL patients.Patients in the low-risk group were more sensitive to AKT inhibitor VIII,bortezomib,crizotinib and phenformin than those in the high-risk group.And patients in the high-risk group were more sensitive to vinorelbine and pyrimethamine than those in the low-risk group.Conclusion:1.The present study established a risk prognosis model consisting of seven cuproptosisrelated lncRNAs(LINC00654,LINC00294,LINC00661,LINC01165,LINC01398,RNF139AS1,WWC2-AS2),which may help to more accurately assess the prognosis of DLBCL patients.2.We demonstrated that the prognosis signature of seven cuproptosis-related lncRNAs was closely related to immune cell infiltration of DLBCL microenvironment and participated in the formation of the tumor immunosuppressive microenvironment.3.The differentially expressed genes between the high-and low-risk DLBCL groups were mainly involved in signal transduction,cell metabolism,inflammatory infiltration and immune imbalance signal pathways.4.DLBCL patients in the high-risk group are resistant to most chemotherapy drugs,but they show greater sensitivity to vinorelbine and pyrimethamine.Therefore,vinorelbine and pyrimethamine may have great potential as novel therapeutic agents for DLBCL patients.Chapter 2 Identification of cuproptosis-related subtypes and establishment of the prognostic model in diffuse large B-cell lymphomaBackground:Diffuse large B cell lymphoma(DLBCL)is a highly heterogeneous and aggressive lymphoma with various molecular abnormalities and clinical presentations,resulting in significantly different patient outcomes.Many molecular subtypes of DLBCL are associated with significant differences in prognosis.Although many classification methods based on molecular mutation types have been established,their predictive performance is still limited.Therefore,it is of great significance to explore more comprehensive and effective biomarkers for improving the prognosis of DLBCL patients.Copper is an essential cofactor for all living things.Under normal conditions,serum copper levels maintain a dynamic equilibrium.Cuproptosis is a copper-dependent form of mitochondrial cell death,which is closely associated with the progression and prognosis of various tumors.The serum copper content in lymphoma patients is closely associated with their prognosis.Excessive copper ions can cause cell death in DLBCL.However,the effects and prognostic value of cuproptosis related genes in different subtypes of DLBCL remain unclear.Therefore,further exploration of the mechanism of cuproptosis-related genes in different molecular subtypes of DLBCL would contribute to the early diagnosis and precise treatment of DLBCL patients.Objective:1.To identify cuproptosis-related subtypes in DLBCL and explore the differences in clinical characteristics and immune microenvironment among those subtypes.2.To screen differentially expressed genes between cuproptosis-related subtypes and construct a prognostic model for DLBCL.3.To explore the potential molecular mechanisms and molecular biological functions associated with differentially expressed genes between cuproptosis-related subtypes in the prognosis model for DLBCL.Methods:1.RNA-Seq data and clinical information for DLBCL were collected from the gene expression omnibus database:GSE11318 datase,GSE10846 data set.Ten cuproptosis-related genes were obtained by reviewing the literature.Hallmark genes sets were obtained from MSigDB.2.Based on the expression profiles of ten cuproptosis-related genes indentified from GSE11318 dataset,two distinct subtypes were obtained by consistency clustering analysis.The R package was used to analyze the difference of prognosis,clinical features and immune microenvironment between cuproptosis-related subtypes.Subsequently,the differentially expressed genes between subtypes were screened by limma analysis,followed by enrichment analyses for gene ontology and hallmark pathway enrichment analysis.3.The predictive model was trained using GES11318 dataset then verified using GSE10846 dataset.According to univariate Cox and Lasso Cox regression analysis,five genes differentially expressed between cuproptosis-related subtypes were screened to establish a risk model for predicting DLBCL prognosis.The risk score for each patient was calculated,and the median risk score was used as the cut-off point to divide DLBCL patients into high-risk and low-risk groups.Kaplan-Meier survival curve,receiver operating characteristic curve analysis,correlation analysis between clinical features and risk score,and independent prognostic analysis were used to evaluate the predictive activity of the prognostic model.4.The hallmark pathway activity of each DLBCL patients in GSE11318 dataset was estimated via single-sample gene set enrichment analysis.The Wilcoxon Rank-sum test was used to test the differentially active pathways between the high-and low-risk groups.We utilized two cutting-edge algorithms,ESTIMATE and CIBERSORT,to comprehensively assess immune cell infiltration between the high-risk and low-risk groups5.Tumor immune dysfunction and exclusion method was used to evaluate the potential immunotherapy efficacy between the high-and low-risk groups.Results:1.The expression profiles of ten cuproptosis-related genes identified from GSE11318 dataset was used for cluster analysis.Only at K=2,the two potential molecular subtypes of DLBCL were identified.Patient overall survival was correlated with DLBCL molecular subtypes,with the subtypes 2 of DLBCL presenting the worst prognosis.Two subtypes were not significantly correlated with gender but showed a significant relationship with stage and age.The immune score,stromal score and tumor purity were not statistically different between the different DLBCL subtypes.The immunoinflammatory chemokines CXCL9,CXCL10 and PRF1,and immunoclearance chemokines CCL2,ENTPD1,LGALS1 and TGFBR2 were significantly different between the different DLBCL subtypes.The differentially expressed genes between the different DLBCL subtypes were enriched in immunological response,glycolysis and inflammatory response pathways.2.We identified a set of five differentially expressed genes between cuproptosis-related subtypes including CDKN2A,KCNK12,SACS-AS1,LMO2 and HMCN1,according to which we construct a risk model for DLBCL.3.The model could effectively distinguish between high and low risk groups.The highrisk group was associated with shorter survival time than the low-risk group,and risk score was an independent prognostic factor for DLBCL patients.4.The differentially active pathways between the high-and low-risk groups were mainly enriched in hypoxia,reactive oxygen species pathway,oxidative phosphorylation pathways.There was no statistical difference in immune score between high-and low-risk groups.The ESTIMATE score of the high-risk group was significantly lower than that of the low-risk group,and the ESTIMATE score decreased with the increase of the risk score.Na?ve B cells and resting NK cells showed high abundance in high-risk DLBCL group but low abundance in lowrisk DLBCL group;In contrast,M0 macrophages and resting mast cells showed low abundance in high-risk DLBCL group and high abundance in low-risk DLBCL group.5.According to tumor immune dysfunction and exclusion score,the DLBCL patients were divided into two groups:those who responded to immunotherapy and those who did not respond.Risk scores were significantly higher in patients who responded to immunotherapy than those who did not respond and higher risk scores had little relationship to the number of the patients.Regardless of whether patients responded to immunotherapy or not,there was a significant difference in overall survival between the high-and low-risk groups.Patients in the high-risk group had lower overall survival than those in the low-risk group.Conclusion:1.We characterized the heterogeneity of DLBCL by identifying two cuproptosis-related subtypes.2.The present study established a risk prognosis model consisting of five differentially expressed genes between cuproptosis-related subtypes(CDKN2A,KCNK12,SACS-AS1,LMO2 and HMCN1),which may help to assess the prognosis of DLBCL patients with increased accuracy.3.The differentially active pathways between the high-and low-risk groups were mainly enriched in hypoxia,reactive oxygen species pathway,oxidative phosphorylation pathways.This five-genes signature-based risk model was significantly correlated with immune cell infiltration in DLBCL patients.4.This five-genes signature-based risk model is applicable to all patients regardless of whether they respond to immunotherapy.Immunotherapy is an encouraging approach to improve survival in high-risk DLBCL patients.