Objective:Lung adenocarcinoma(LUAD)is the most common subtype of lung cancer.Despite significant advances in immunotherapy,treatment responses vary substantially among individuals.Metabolic reprogramming,as a hallmark...Objective:Lung adenocarcinoma(LUAD)is the most common subtype of lung cancer.Despite significant advances in immunotherapy,treatment responses vary substantially among individuals.Metabolic reprogramming,as a hallmark of cancer,plays a crucial role in tumor progression and immune evasion.However,the interplay between metabolic features and tumor immune microenvironment in LUAD remains to be systematically elucidated.Methods:We analyzed data from 1,231 LUAD patients across seven global cohorts and developed an integrated Metabolism-Related Signature(iMRS)using machine learning approaches based on 114 metabolic features.The signature's ability to predict immunotherapy response was validated using 9 immunotherapy cohorts(n=712,including LUAD,melanoma,and glioma).An in-house LUAD tissue cohort(n=146)confirmed the prognostic significance of SLC25A1,a key gene within the signature,and its spatial relationship with immune cells.In vivo and in vitro experiments investigated SLC25A1's role in cancer promotion,immune exclusion,and its impact on programmed cell death protein 1(PD-1)therapy efficacy.Results:i MRS demonstrated superior prognostic performance in LUAD patients,outperforming 129 published LUAD signatures.In immunotherapy cohorts,responders showed significantly lower iMRS scores.High iMRS was associated with reduced immune activity and“cold”tumor characteristics.SLC25A1(correlation coefficient=0.54,P<0.05),a key gene in the signature,showed the highest expression in CD8 desert phenotype and correlated with poor prognosis.Multiplexed immunofluorescence revealed exclusion patterns between SLC25A1 and immune cells(CD4+T cells and CD20+B cells).SLC25A1 knockdown reduced lung metastasis and enhanced anti-PD-1 efficacy by increasing CD8+T cell abundance and cytotoxicity[increased interferon-γ(IFN-γ)+/GZMB+CD8+T cells].Conclusions:iMRS provides personalized immunotherapy prediction for LUAD patients.SLC25A1,identified as a novel immune-exclusion related oncogene,represents a promising therapeutic target for LUAD treatment.展开更多
Background:The immune response in the tumor microenvironment(TME)plays a crucial role in cancer progression and recurrence.We aimed to develop an immune-related gene(IRG)signature to improve prognostic predictive powe...Background:The immune response in the tumor microenvironment(TME)plays a crucial role in cancer progression and recurrence.We aimed to develop an immune-related gene(IRG)signature to improve prognostic predictive power and reveal the immune infiltration characteristics of pancreatic ductal adenocarcinoma(PDAC).Methods:The Cancer Genome Atlas(TCGA)PDAC was used to construct a prognostic model as a training cohort.The International Cancer Genome Consortium(ICGC)and the Gene Expression Omnibus(GEO)databases were set as validation datasets.Prognostic genes were screened by using univariate Cox regression.Then,a novel optimal prognostic model was developed by using least absolute shrinkage and selection operator(LASSO)Cox regression.Cell type identification by estimating the relative subsets of RNA transcripts(CIBERSORT)and estimation of stromal and immune cells in malignant tumors using expression data(ESTIMATE)algorithms were used to characterize tumor immune infiltrating patterns.The tumor immune dysfunction and exclusion(TIDE)algorithm was used to predict immunotherapy responsiveness.Results:A prognostic signature based on five IRGs(MET,ERAP2,IL20RB,EREG,and SHC2)was constructed in TCGA-PDAC and comprehensively validated in ICGC and GEO cohorts.Multivariate Cox regression analysis demonstrated that this signature had an independent prognostic value.The area under the curve(AUC)values of the receiver operating characteristic(ROC)curve at 1,3,and 5 years of survival were 0.724,0.702,and 0.776,respectively.We further demonstrated that our signature has better prognostic performance than recently published ones and is superior to traditional clinical factors such as grade and tumor node metastasis classification(TNM)stage in predicting survival.Moreover,we found higher abundance of CD8+T cells and lower M2-like macrophages in the low-risk group of TCGA-PDAC,and predicted a higher proportion of immunotherapeutic responders in the low-risk group.Conclusions:We constructed an optimal prognostic model which had independent prognostic value and was comprehensively validated in external PDAC databases.Additionally,this five-genes signature could predict immune infiltration characteristics.Moreover,the signature helped stratify PDAC patients who might be more responsive to immunotherapy.展开更多
Background:Tumor-derived exosomes are involved in tumor progression and immune invasion and might func-tion as promising noninvasive approaches for clinical management.However,there are few reports on exosom-based mar...Background:Tumor-derived exosomes are involved in tumor progression and immune invasion and might func-tion as promising noninvasive approaches for clinical management.However,there are few reports on exosom-based markers for predicting the progression and adjuvant therapy response rate among patients with clear cell renal cell carcinoma(ccRCC).Methods:The signatures differentially expressed in exosomes from tumor and normal tissues from ccRCC pa-tients were correspondingly deregulated in ccRCC tissues.We adopted a two-step strategy,including Lasso and bootstrapping,to construct a novel risk stratification system termed the TDERS(Tumor-Derived Exosome-Related Risk Score).During the testing and validation phases,we leveraged multiple external datasets containing over 2000 RCC cases from eight cohorts and one inhouse cohort to evaluate the accuracy of the TDERS.In addition,enrichment analysis,immune infiltration signatures,mutation landscape and therapy sensitivity between the high and low TDERS groups were compared.Finally,the impact of TDERS on the tumor microenvironment(TME)was also analysed in our single-cell datasets.Results:TDERS consisted of 12 mRNAs deregulated in both exosomes and tissues from patients with ccRCC.TDERS achieved satisfactory performance in both prognosis and immune checkpoint inhibitor(ICI)response across all ccRCC cohorts and other pathological types,since the average area under the curve(AUC)to predict 5-year overall survival(OS)was larger than 0.8 across the four cohorts.Patients in the TDERS high group were resistant to ICIs,while mercaptopurine might function as a promising agent for those patients.Patients with a high TDERS were characterized by coagulation and hypoxia,which induced hampered tumor antigen presentation and relative resistance to ICIs.In addition,single cells from 12 advanced samples validated this phenomenon since the interaction between dendritic cells and macrophages was limited.Finally,PLOD2,which is highly expressed in fibro-and epi-tissue,could be a potential therapeutic target for ccRCC patients since inhibiting PLOD2 altered the malignant phenotype of ccRCC in vitro.Conclusion:As a novel,non-invasive,and repeatable monitoring tool,the TDERS could work as a robust risk stratification system for patients with ccRCC and precisely inform treatment decisions about ICI therapy.展开更多
文摘Objective:Lung adenocarcinoma(LUAD)is the most common subtype of lung cancer.Despite significant advances in immunotherapy,treatment responses vary substantially among individuals.Metabolic reprogramming,as a hallmark of cancer,plays a crucial role in tumor progression and immune evasion.However,the interplay between metabolic features and tumor immune microenvironment in LUAD remains to be systematically elucidated.Methods:We analyzed data from 1,231 LUAD patients across seven global cohorts and developed an integrated Metabolism-Related Signature(iMRS)using machine learning approaches based on 114 metabolic features.The signature's ability to predict immunotherapy response was validated using 9 immunotherapy cohorts(n=712,including LUAD,melanoma,and glioma).An in-house LUAD tissue cohort(n=146)confirmed the prognostic significance of SLC25A1,a key gene within the signature,and its spatial relationship with immune cells.In vivo and in vitro experiments investigated SLC25A1's role in cancer promotion,immune exclusion,and its impact on programmed cell death protein 1(PD-1)therapy efficacy.Results:i MRS demonstrated superior prognostic performance in LUAD patients,outperforming 129 published LUAD signatures.In immunotherapy cohorts,responders showed significantly lower iMRS scores.High iMRS was associated with reduced immune activity and“cold”tumor characteristics.SLC25A1(correlation coefficient=0.54,P<0.05),a key gene in the signature,showed the highest expression in CD8 desert phenotype and correlated with poor prognosis.Multiplexed immunofluorescence revealed exclusion patterns between SLC25A1 and immune cells(CD4+T cells and CD20+B cells).SLC25A1 knockdown reduced lung metastasis and enhanced anti-PD-1 efficacy by increasing CD8+T cell abundance and cytotoxicity[increased interferon-γ(IFN-γ)+/GZMB+CD8+T cells].Conclusions:iMRS provides personalized immunotherapy prediction for LUAD patients.SLC25A1,identified as a novel immune-exclusion related oncogene,represents a promising therapeutic target for LUAD treatment.
基金funded by the National Natural Science Foundation of China(Grants No.30972610 and 81273240)National Key Research and Development Program(Grants No.2017YFC0910000 and 2017YFD0501300)Jilin Province Science and Technology Agency(Grants No.JJKH20211210KJ,JJKH20211164KJ,20200403084SF,JLSWSRCZX2020-009,20200901025SF,20190101022JH,and 2019J026).
文摘Background:The immune response in the tumor microenvironment(TME)plays a crucial role in cancer progression and recurrence.We aimed to develop an immune-related gene(IRG)signature to improve prognostic predictive power and reveal the immune infiltration characteristics of pancreatic ductal adenocarcinoma(PDAC).Methods:The Cancer Genome Atlas(TCGA)PDAC was used to construct a prognostic model as a training cohort.The International Cancer Genome Consortium(ICGC)and the Gene Expression Omnibus(GEO)databases were set as validation datasets.Prognostic genes were screened by using univariate Cox regression.Then,a novel optimal prognostic model was developed by using least absolute shrinkage and selection operator(LASSO)Cox regression.Cell type identification by estimating the relative subsets of RNA transcripts(CIBERSORT)and estimation of stromal and immune cells in malignant tumors using expression data(ESTIMATE)algorithms were used to characterize tumor immune infiltrating patterns.The tumor immune dysfunction and exclusion(TIDE)algorithm was used to predict immunotherapy responsiveness.Results:A prognostic signature based on five IRGs(MET,ERAP2,IL20RB,EREG,and SHC2)was constructed in TCGA-PDAC and comprehensively validated in ICGC and GEO cohorts.Multivariate Cox regression analysis demonstrated that this signature had an independent prognostic value.The area under the curve(AUC)values of the receiver operating characteristic(ROC)curve at 1,3,and 5 years of survival were 0.724,0.702,and 0.776,respectively.We further demonstrated that our signature has better prognostic performance than recently published ones and is superior to traditional clinical factors such as grade and tumor node metastasis classification(TNM)stage in predicting survival.Moreover,we found higher abundance of CD8+T cells and lower M2-like macrophages in the low-risk group of TCGA-PDAC,and predicted a higher proportion of immunotherapeutic responders in the low-risk group.Conclusions:We constructed an optimal prognostic model which had independent prognostic value and was comprehensively validated in external PDAC databases.Additionally,this five-genes signature could predict immune infiltration characteristics.Moreover,the signature helped stratify PDAC patients who might be more responsive to immunotherapy.
基金funded by grants from the National Natural Science Foundation of China(grant numbers:82002664,81872074,81772740,82173345 and 82373154)the Hanghai Jiading District Health Commission Scientific Research Project Youth Fund(grant num-ber:2020-QN-02)the Meng Chao Talent Training Plan-Youth Re-search Talent Training Program of Eastern Hepatobiliary Surgery Hos-pital and the Foundation for Distinguished Youths of Jiangsu Province(grant number:BK20200006).
文摘Background:Tumor-derived exosomes are involved in tumor progression and immune invasion and might func-tion as promising noninvasive approaches for clinical management.However,there are few reports on exosom-based markers for predicting the progression and adjuvant therapy response rate among patients with clear cell renal cell carcinoma(ccRCC).Methods:The signatures differentially expressed in exosomes from tumor and normal tissues from ccRCC pa-tients were correspondingly deregulated in ccRCC tissues.We adopted a two-step strategy,including Lasso and bootstrapping,to construct a novel risk stratification system termed the TDERS(Tumor-Derived Exosome-Related Risk Score).During the testing and validation phases,we leveraged multiple external datasets containing over 2000 RCC cases from eight cohorts and one inhouse cohort to evaluate the accuracy of the TDERS.In addition,enrichment analysis,immune infiltration signatures,mutation landscape and therapy sensitivity between the high and low TDERS groups were compared.Finally,the impact of TDERS on the tumor microenvironment(TME)was also analysed in our single-cell datasets.Results:TDERS consisted of 12 mRNAs deregulated in both exosomes and tissues from patients with ccRCC.TDERS achieved satisfactory performance in both prognosis and immune checkpoint inhibitor(ICI)response across all ccRCC cohorts and other pathological types,since the average area under the curve(AUC)to predict 5-year overall survival(OS)was larger than 0.8 across the four cohorts.Patients in the TDERS high group were resistant to ICIs,while mercaptopurine might function as a promising agent for those patients.Patients with a high TDERS were characterized by coagulation and hypoxia,which induced hampered tumor antigen presentation and relative resistance to ICIs.In addition,single cells from 12 advanced samples validated this phenomenon since the interaction between dendritic cells and macrophages was limited.Finally,PLOD2,which is highly expressed in fibro-and epi-tissue,could be a potential therapeutic target for ccRCC patients since inhibiting PLOD2 altered the malignant phenotype of ccRCC in vitro.Conclusion:As a novel,non-invasive,and repeatable monitoring tool,the TDERS could work as a robust risk stratification system for patients with ccRCC and precisely inform treatment decisions about ICI therapy.
