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An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts.
Deng, Hao; Deng, Dingshan; Qi, Tiezheng; Liu, Zhi; Wu, Longxiang; Yuan, Junbin.
Afiliação
  • Deng H; Department of Urology, Xiangya Hospital, Central South University, Changsha, China.
  • Deng D; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
  • Qi T; Department of Urology, Xiangya Hospital, Central South University, Changsha, China.
  • Liu Z; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
  • Wu L; Xiangya School of Medicine, Central South University, Changsha, China.
  • Yuan J; Department of Urology, Xiangya Hospital, Central South University, Changsha, China.
Front Genet ; 13: 1100317, 2022.
Article em En | MEDLINE | ID: mdl-36685901
ABSTRACT
Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article