Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model
BackgroundNecroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear.MethodsWe classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related g...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Surgery |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsurg.2022.860857/full |
| _version_ | 1811279425986101248 |
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| author | Shiwen Nie Youlong Huili Yadong He Junchao Hu Shaosan Kang Fenghong Cao |
| author_facet | Shiwen Nie Youlong Huili Yadong He Junchao Hu Shaosan Kang Fenghong Cao |
| author_sort | Shiwen Nie |
| collection | DOAJ |
| description | BackgroundNecroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear.MethodsWe classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related genes) and analyzed the relationship between necroptosis subtypes of bladder cancer and TME, then extracted differentially expressed genes (DEGS) of necroptosis subtypes, classified patients into different gene subtypes according to DEGS, and performed univariate COX analysis on DEGS to obtain prognosis-related DEGS. All patients included in the analysis were randomized into the Train and Test groups in a 1:1 ratio, and the prognostic model was obtained using the LASSO algorithm and multivariate COX analysis with the Train group as the sample, and external validation of the model was conducted using the GSE32894.ResultsTwo necroptosis subtypes and three gene subtypes were obtained by clustering analysis and the prognosis-related DEGS was subjected to the LASSO algorithm and multivariate COX analysis to determine six predictors to construct the prognostic model using the formula: riskScore = CERCAM × 0.0035 + POLR1H × −0.0294 + KCNJ15 × −0.0172 + GSDMB × −0.0109 + EHBP1 × 0.0295 + TRIM38 × −0.0300. The results of the survival curve, roc curve, and risk curve proved the reliability of the prognostic model by validating the model with the test group and the results of the calibration chart of the Nomogram applicable to the clinic also showed its good accuracy. Necroptosis subtype A with high immune infiltration had a higher risk score than necroptosis subtype B, gene subtype B with low immune infiltration had a lower risk score than gene subtypes A and C, CSC index was negatively correlated with the risk score and drug sensitivity prediction showed that commonly used chemotherapeutic agents were highly sensitive to the high-risk group.ConclusionOur analysis of NRGS in bladder cancer reveals their potential role in TME, immunity, and prognosis. These findings may improve our understanding of necroptosis in bladder cancer and provide some reference for predicting prognosis and developing immunotherapies. |
| first_indexed | 2024-04-13T00:55:25Z |
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| id | doaj.art-823d4082c13d4fc8816a5bddaa6c2e17 |
| institution | Directory Open Access Journal |
| issn | 2296-875X |
| language | English |
| last_indexed | 2024-04-13T00:55:25Z |
| publishDate | 2022-04-01 |
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| series | Frontiers in Surgery |
| spelling | doaj.art-823d4082c13d4fc8816a5bddaa6c2e172022-12-22T03:09:43ZengFrontiers Media S.A.Frontiers in Surgery2296-875X2022-04-01910.3389/fsurg.2022.860857860857Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic ModelShiwen Nie0Youlong Huili1Yadong He2Junchao Hu3Shaosan Kang4Fenghong Cao5Department of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaDepartment of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaDepartment of General Practice, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaDepartment of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaDepartment of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaDepartment of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan, ChinaBackgroundNecroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear.MethodsWe classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related genes) and analyzed the relationship between necroptosis subtypes of bladder cancer and TME, then extracted differentially expressed genes (DEGS) of necroptosis subtypes, classified patients into different gene subtypes according to DEGS, and performed univariate COX analysis on DEGS to obtain prognosis-related DEGS. All patients included in the analysis were randomized into the Train and Test groups in a 1:1 ratio, and the prognostic model was obtained using the LASSO algorithm and multivariate COX analysis with the Train group as the sample, and external validation of the model was conducted using the GSE32894.ResultsTwo necroptosis subtypes and three gene subtypes were obtained by clustering analysis and the prognosis-related DEGS was subjected to the LASSO algorithm and multivariate COX analysis to determine six predictors to construct the prognostic model using the formula: riskScore = CERCAM × 0.0035 + POLR1H × −0.0294 + KCNJ15 × −0.0172 + GSDMB × −0.0109 + EHBP1 × 0.0295 + TRIM38 × −0.0300. The results of the survival curve, roc curve, and risk curve proved the reliability of the prognostic model by validating the model with the test group and the results of the calibration chart of the Nomogram applicable to the clinic also showed its good accuracy. Necroptosis subtype A with high immune infiltration had a higher risk score than necroptosis subtype B, gene subtype B with low immune infiltration had a lower risk score than gene subtypes A and C, CSC index was negatively correlated with the risk score and drug sensitivity prediction showed that commonly used chemotherapeutic agents were highly sensitive to the high-risk group.ConclusionOur analysis of NRGS in bladder cancer reveals their potential role in TME, immunity, and prognosis. These findings may improve our understanding of necroptosis in bladder cancer and provide some reference for predicting prognosis and developing immunotherapies.https://www.frontiersin.org/articles/10.3389/fsurg.2022.860857/fullnecroptosisbladder cancerprognostic modeltumor microenvironmentTCGA |
| spellingShingle | Shiwen Nie Youlong Huili Yadong He Junchao Hu Shaosan Kang Fenghong Cao Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model Frontiers in Surgery necroptosis bladder cancer prognostic model tumor microenvironment TCGA |
| title | Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model |
| title_full | Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model |
| title_fullStr | Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model |
| title_full_unstemmed | Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model |
| title_short | Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model |
| title_sort | identification of bladder cancer subtypes based on necroptosis related genes construction of a prognostic model |
| topic | necroptosis bladder cancer prognostic model tumor microenvironment TCGA |
| url | https://www.frontiersin.org/articles/10.3389/fsurg.2022.860857/full |
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