Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse ...Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology.By leveraging these genes,our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy.Methods Sample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases.In the initial stage,we identified 67 differentially expressed genes associated with immune response in CD8+T cells.Subsequently,we narrowed our focus to three key genes,namely CXCL13,GBP2,and GZMB,which were used to construct a prognostic model.The accuracy of the model was assessed using the validation set data and receiver operating characteristic(ROC)curves.Furthermore,we employed various methods,including Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,immune infiltration,and correlation analyses with CD274(PD-L1)to explore the model's predictive efficacy in immunotherapeutic responses.Additionally,we investigated the potential underlying biological pathways that contribute to divergent treatment responses.Results We successfully developed a model capable of predicting the prognosis of patients with TNBC.The areas under the curve(AUC)values for the 1-,3-,and 5-year survival predictions were 0.618,0.652,and 0.826,respectively.Employing this risk model,we stratified the samples into high-and low-risk groups.Through KEGG enrichment analysis,we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism,whereas the low-risk group demonstrated significant enrichment in cytokine pathways.Furthermore,immune landscape analysis revealed noteworthy variations between(PD-L1)expression and risk scores,indicating that our model effectively predicted the response of patients to immune-based treatments.Conclusion Our study demonstrates the potential of CXCL13,GBP2,and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC.These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.展开更多
Objective:CD8+T cells are the key effector cells in the anti-tumor immune response.The mechanism underlying the infiltration of CD8+T cells in esophageal squamous cell carcinoma(ESCC)has not been clearly elucidated.Me...Objective:CD8+T cells are the key effector cells in the anti-tumor immune response.The mechanism underlying the infiltration of CD8+T cells in esophageal squamous cell carcinoma(ESCC)has not been clearly elucidated.Methods:Fresh ESCC tissues were collected and grouped according to the infiltration density of CD8+T cells.After the transcriptome sequencing on these samples and the combined analyses with The Cancer Genome Atlas(TCGA)ESCC data,a secreted protein DEFB1 was selected to explore its potential role in the infiltration of CD8+T cells.Bioinformatics analyses,histological verification and in vitro experiments were then performed.Results:DEFB1 was highly expressed in ESCC,and the high expression of DEFB1 was an independent risk factor for overall survival.Since the up-regulation or down-regulation of DEFB1 did not affect the proliferation,migration and apoptosis of ESCC cells,we speculated that the oncogenic effect of DEFB1 was achieved by regulating microenvironmental characteristics.Bioinformatics analyses suggested that DEFB1 might play a major role in the inflammatory response and anti-tumor immune response,and correlate to the infiltration of immature dendritic cell(imDC)in ESCC.Histological analyses further confirmed that there were less CD8+T cells infiltrated,less CD83+mature DC(mDC)infiltrated and more CD1a+imDC infiltrated in those ESCC samples with high expression of DEFB1.After the treatment with recombinant DEFB1 protein,the maturation of DC was hindered significantly,followed by the impairment of the killing effects of T cells in both 2D and 3D culture in vitro.Conclusions:Tumor-derived DEFB1 can inhibit the maturation of DC and weaken the function of CD8+T cells,accounting for the immune tolerance in ESCC.The role of DEFB1 in ESCC deserves further exploration.展开更多
Background:Cytotoxic T lymphocytes(CD8+T)cells function critically in mediating anti-tumor immune response in cancer patients.Characterizing the specific functions of CD8+T cells in lung adenocarcinoma(LUAD)could help ...Background:Cytotoxic T lymphocytes(CD8+T)cells function critically in mediating anti-tumor immune response in cancer patients.Characterizing the specific functions of CD8+T cells in lung adenocarcinoma(LUAD)could help better understand local anti-tumor immune responses and estimate the effect of immunotherapy.Methods:Gens related to CD8+T cells were identified by cluster analysis based on the single-cell sequencing data of three LUAD tissues and their paired normal tissues.Weighted gene co-expression network analysis(WGCNA),consensus clustering,differential expression analysis,least absolute shrinkage and selection operator(LASSO)and Cox regression analysis were conducted to classify molecular subtypes for LUAD and to develop a risk model using prognostic genes related to CD8+T cells.Expression of the genes in the prognostic model,their effects on tumor cell invasion,and interactions with CD8+T cells were verified by cell experiments.Results:This study defined two LUAD clusters(CD8+0 and CD8+1)based on CD8+T cells,with cluster CD8+0 being significantly associated with the prognosis of LUAD.Three heterogeneous subtypes(clusters 1,2,and 3)differing in prognosis,genome mutation events,and immune status were categorized using 42 prognostic genes.A prognostic model created based on 11 significant genes(including CD200R1,CLEC17A,ZC3H12D,GNG7,SNX30,CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2,and KRT81)was able to independently estimate the death risk for patients in different LUAD cohorts.Moreover,the model also showed general applicability in external validation cohorts.Low-risk patients could benefit more from taking immunotherapy and were significantly related to the resistance to anticancer drugs.The results from cell experiments demonstrated that the expression of CD200R1,CLEC17A,ZC3H12D,GNG7,and SNX30 was significantly downregulated,while that of CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2 and KRT81 was upregulated in LUAD cells.Inhibition of CD200R1 greatly increased the invasiveness of the LUAD cells,but inhibiting CDCP1 expression weakened the invasion ability of LUAD cells.Conclusion:This study defined two prognostic CD8+T cell clusters and classified three heterogeneous molecular subtypes for LUAD.A prognostic model predictive of the potential effects of immunotherapy on LUAD patients was developed.展开更多
基金supported by Joint Funds for the Innovation of Science and Technology,Fujian Province[Grant number:2020Y9039]Fujian Provincial Health Technology Project[Grant number:2022GGA032].
文摘Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology.By leveraging these genes,our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy.Methods Sample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases.In the initial stage,we identified 67 differentially expressed genes associated with immune response in CD8+T cells.Subsequently,we narrowed our focus to three key genes,namely CXCL13,GBP2,and GZMB,which were used to construct a prognostic model.The accuracy of the model was assessed using the validation set data and receiver operating characteristic(ROC)curves.Furthermore,we employed various methods,including Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,immune infiltration,and correlation analyses with CD274(PD-L1)to explore the model's predictive efficacy in immunotherapeutic responses.Additionally,we investigated the potential underlying biological pathways that contribute to divergent treatment responses.Results We successfully developed a model capable of predicting the prognosis of patients with TNBC.The areas under the curve(AUC)values for the 1-,3-,and 5-year survival predictions were 0.618,0.652,and 0.826,respectively.Employing this risk model,we stratified the samples into high-and low-risk groups.Through KEGG enrichment analysis,we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism,whereas the low-risk group demonstrated significant enrichment in cytokine pathways.Furthermore,immune landscape analysis revealed noteworthy variations between(PD-L1)expression and risk scores,indicating that our model effectively predicted the response of patients to immune-based treatments.Conclusion Our study demonstrates the potential of CXCL13,GBP2,and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC.These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.
基金supported by the National Natural Science Foundation of China(No.81972681,82103677)Tianjin Education Commission Research Plan Project(No.2021KJ201)+1 种基金Shenzhen High-level Hospital Construction Fund(No.G2022139)Tianjin Key Medical Discipline(Specialty)Construction Project(No.TJYXZDXK-009A).
文摘Objective:CD8+T cells are the key effector cells in the anti-tumor immune response.The mechanism underlying the infiltration of CD8+T cells in esophageal squamous cell carcinoma(ESCC)has not been clearly elucidated.Methods:Fresh ESCC tissues were collected and grouped according to the infiltration density of CD8+T cells.After the transcriptome sequencing on these samples and the combined analyses with The Cancer Genome Atlas(TCGA)ESCC data,a secreted protein DEFB1 was selected to explore its potential role in the infiltration of CD8+T cells.Bioinformatics analyses,histological verification and in vitro experiments were then performed.Results:DEFB1 was highly expressed in ESCC,and the high expression of DEFB1 was an independent risk factor for overall survival.Since the up-regulation or down-regulation of DEFB1 did not affect the proliferation,migration and apoptosis of ESCC cells,we speculated that the oncogenic effect of DEFB1 was achieved by regulating microenvironmental characteristics.Bioinformatics analyses suggested that DEFB1 might play a major role in the inflammatory response and anti-tumor immune response,and correlate to the infiltration of immature dendritic cell(imDC)in ESCC.Histological analyses further confirmed that there were less CD8+T cells infiltrated,less CD83+mature DC(mDC)infiltrated and more CD1a+imDC infiltrated in those ESCC samples with high expression of DEFB1.After the treatment with recombinant DEFB1 protein,the maturation of DC was hindered significantly,followed by the impairment of the killing effects of T cells in both 2D and 3D culture in vitro.Conclusions:Tumor-derived DEFB1 can inhibit the maturation of DC and weaken the function of CD8+T cells,accounting for the immune tolerance in ESCC.The role of DEFB1 in ESCC deserves further exploration.
文摘Background:Cytotoxic T lymphocytes(CD8+T)cells function critically in mediating anti-tumor immune response in cancer patients.Characterizing the specific functions of CD8+T cells in lung adenocarcinoma(LUAD)could help better understand local anti-tumor immune responses and estimate the effect of immunotherapy.Methods:Gens related to CD8+T cells were identified by cluster analysis based on the single-cell sequencing data of three LUAD tissues and their paired normal tissues.Weighted gene co-expression network analysis(WGCNA),consensus clustering,differential expression analysis,least absolute shrinkage and selection operator(LASSO)and Cox regression analysis were conducted to classify molecular subtypes for LUAD and to develop a risk model using prognostic genes related to CD8+T cells.Expression of the genes in the prognostic model,their effects on tumor cell invasion,and interactions with CD8+T cells were verified by cell experiments.Results:This study defined two LUAD clusters(CD8+0 and CD8+1)based on CD8+T cells,with cluster CD8+0 being significantly associated with the prognosis of LUAD.Three heterogeneous subtypes(clusters 1,2,and 3)differing in prognosis,genome mutation events,and immune status were categorized using 42 prognostic genes.A prognostic model created based on 11 significant genes(including CD200R1,CLEC17A,ZC3H12D,GNG7,SNX30,CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2,and KRT81)was able to independently estimate the death risk for patients in different LUAD cohorts.Moreover,the model also showed general applicability in external validation cohorts.Low-risk patients could benefit more from taking immunotherapy and were significantly related to the resistance to anticancer drugs.The results from cell experiments demonstrated that the expression of CD200R1,CLEC17A,ZC3H12D,GNG7,and SNX30 was significantly downregulated,while that of CDCP1,NEIL3,IGF2BP1,RHOV,ABCC2 and KRT81 was upregulated in LUAD cells.Inhibition of CD200R1 greatly increased the invasiveness of the LUAD cells,but inhibiting CDCP1 expression weakened the invasion ability of LUAD cells.Conclusion:This study defined two prognostic CD8+T cell clusters and classified three heterogeneous molecular subtypes for LUAD.A prognostic model predictive of the potential effects of immunotherapy on LUAD patients was developed.
