Table4_A glycosylation risk score comprehensively assists the treatment of bladder neoplasm in the real-world cohort, including the tumor microenvironment, molecular and clinical prognosis.XLSX

Background: Bladder cancer is a common urological cancer associated high significant morbidity and mortality rates. Immunotherapy has emerged as a promising treatment option, although response rates vary among patients. Glycosylation has been implicated in tumorigenesis and immune regulation. However, our current comprehensive understanding of the role of glycosylation in bladder cancer and its clinical implications is limited.Methods: We constructed a training cohort based on the downloaded TCGA-BLCA dataset, while additional datasets (Xiangya cohort, GSE32894, GSE48075, GSE31684, GSE69795 and E-MTAB-1803) from Xiangya hospital, GEO and ArrayExpress database were obtained and used as validation cohorts. To identify glycosylation-related genes associated with prognosis, univariate Cox regression and LASSO regression were performed. A Cox proportional hazards regression model was then constructed to develop a risk score model. The performance of the risk score was assessed in the training cohort using Kaplan-Meier survival curves and ROC curves, and further validated in multiple validation cohorts.Results: We classified patients in the training cohort into two groups based on glycosylation-related gene expression patterns: Cluster 1 and Cluster 2. Prognostic analysis revealed that Cluster 2 had poorer survival outcomes. Cluster 2 also showed higher levels of immune cell presence in the tumor microenvironment and increased activation in key steps of the cancer immune response cycle. We developed an independent prognostic risk score (p Conclusion: This multi-omics glycosylation score based on these genes reliably confirmed the heterogeneity of bladder cancer tumors, predicted the efficacy of immunotherapy and molecular subtypes, optimizing individual treatment decisions.</p

Table5_A glycosylation risk score comprehensively assists the treatment of bladder neoplasm in the real-world cohort, including the tumor microenvironment, molecular and clinical prognosis.XLSX

Background: Bladder cancer is a common urological cancer associated high significant morbidity and mortality rates. Immunotherapy has emerged as a promising treatment option, although response rates vary among patients. Glycosylation has been implicated in tumorigenesis and immune regulation. However, our current comprehensive understanding of the role of glycosylation in bladder cancer and its clinical implications is limited.Methods: We constructed a training cohort based on the downloaded TCGA-BLCA dataset, while additional datasets (Xiangya cohort, GSE32894, GSE48075, GSE31684, GSE69795 and E-MTAB-1803) from Xiangya hospital, GEO and ArrayExpress database were obtained and used as validation cohorts. To identify glycosylation-related genes associated with prognosis, univariate Cox regression and LASSO regression were performed. A Cox proportional hazards regression model was then constructed to develop a risk score model. The performance of the risk score was assessed in the training cohort using Kaplan-Meier survival curves and ROC curves, and further validated in multiple validation cohorts.Results: We classified patients in the training cohort into two groups based on glycosylation-related gene expression patterns: Cluster 1 and Cluster 2. Prognostic analysis revealed that Cluster 2 had poorer survival outcomes. Cluster 2 also showed higher levels of immune cell presence in the tumor microenvironment and increased activation in key steps of the cancer immune response cycle. We developed an independent prognostic risk score (p Conclusion: This multi-omics glycosylation score based on these genes reliably confirmed the heterogeneity of bladder cancer tumors, predicted the efficacy of immunotherapy and molecular subtypes, optimizing individual treatment decisions.</p

Table_4_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p

Table1_A glycosylation risk score comprehensively assists the treatment of bladder neoplasm in the real-world cohort, including the tumor microenvironment, molecular and clinical prognosis.XLSX

Background: Bladder cancer is a common urological cancer associated high significant morbidity and mortality rates. Immunotherapy has emerged as a promising treatment option, although response rates vary among patients. Glycosylation has been implicated in tumorigenesis and immune regulation. However, our current comprehensive understanding of the role of glycosylation in bladder cancer and its clinical implications is limited.Methods: We constructed a training cohort based on the downloaded TCGA-BLCA dataset, while additional datasets (Xiangya cohort, GSE32894, GSE48075, GSE31684, GSE69795 and E-MTAB-1803) from Xiangya hospital, GEO and ArrayExpress database were obtained and used as validation cohorts. To identify glycosylation-related genes associated with prognosis, univariate Cox regression and LASSO regression were performed. A Cox proportional hazards regression model was then constructed to develop a risk score model. The performance of the risk score was assessed in the training cohort using Kaplan-Meier survival curves and ROC curves, and further validated in multiple validation cohorts.Results: We classified patients in the training cohort into two groups based on glycosylation-related gene expression patterns: Cluster 1 and Cluster 2. Prognostic analysis revealed that Cluster 2 had poorer survival outcomes. Cluster 2 also showed higher levels of immune cell presence in the tumor microenvironment and increased activation in key steps of the cancer immune response cycle. We developed an independent prognostic risk score (p Conclusion: This multi-omics glycosylation score based on these genes reliably confirmed the heterogeneity of bladder cancer tumors, predicted the efficacy of immunotherapy and molecular subtypes, optimizing individual treatment decisions.</p

Table_11_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p

Table_10_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p

Table_3_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p

Table_7_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p

Table13_A glycosylation risk score comprehensively assists the treatment of bladder neoplasm in the real-world cohort, including the tumor microenvironment, molecular and clinical prognosis.XLSX

Background: Bladder cancer is a common urological cancer associated high significant morbidity and mortality rates. Immunotherapy has emerged as a promising treatment option, although response rates vary among patients. Glycosylation has been implicated in tumorigenesis and immune regulation. However, our current comprehensive understanding of the role of glycosylation in bladder cancer and its clinical implications is limited.Methods: We constructed a training cohort based on the downloaded TCGA-BLCA dataset, while additional datasets (Xiangya cohort, GSE32894, GSE48075, GSE31684, GSE69795 and E-MTAB-1803) from Xiangya hospital, GEO and ArrayExpress database were obtained and used as validation cohorts. To identify glycosylation-related genes associated with prognosis, univariate Cox regression and LASSO regression were performed. A Cox proportional hazards regression model was then constructed to develop a risk score model. The performance of the risk score was assessed in the training cohort using Kaplan-Meier survival curves and ROC curves, and further validated in multiple validation cohorts.Results: We classified patients in the training cohort into two groups based on glycosylation-related gene expression patterns: Cluster 1 and Cluster 2. Prognostic analysis revealed that Cluster 2 had poorer survival outcomes. Cluster 2 also showed higher levels of immune cell presence in the tumor microenvironment and increased activation in key steps of the cancer immune response cycle. We developed an independent prognostic risk score (p Conclusion: This multi-omics glycosylation score based on these genes reliably confirmed the heterogeneity of bladder cancer tumors, predicted the efficacy of immunotherapy and molecular subtypes, optimizing individual treatment decisions.</p

Table_9_An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer.xlsx

BackgroundEpithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.MethodsTCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.ResultsBased on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.ConclusionsEMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.</p