Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer DOI Creative Commons
Ning Li, Li Xiu,

Yating Xu

и другие.

Frontiers in Genetics, Год журнала: 2025, Номер 16

Опубликована: Апрель 7, 2025

The role of immunogenic cell death (ICD) in cervical cancer (CESC) is not well understood. This study sought to investigate the significance ICD CESC and establish an ICDRs prognostic model improve immunotherapy efficacy for patients with cancer. ICD-associated genes were screened at single-cell transcriptome levels based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA) weighted co-expression network (WGCNA) analysis. Immunogenic death-related features (ICDRs) constructed using multiple machine algorithms, evaluated training validation sets provide quantitative tools predicting prognosis clinical practice. Predictive models used risk subgroups response immunotherapy, as drug sensitivity. Finally, expression ICD-related was verified by RT-qPCR. Through integrated data, transcriptomic profiling, computational modeling, seven identified highly patients. Multivariate demonstrated that low-risk had significantly better overall survival compared high-risk patients, confirming independent tool. Assessments tumor microenvironment (TME), mutation characteristics, sensitivity within indicated a stronger group.

Язык: Английский

Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer DOI Creative Commons
Ning Li, Li Xiu,

Yating Xu

и другие.

Frontiers in Genetics, Год журнала: 2025, Номер 16

Опубликована: Апрель 7, 2025

The role of immunogenic cell death (ICD) in cervical cancer (CESC) is not well understood. This study sought to investigate the significance ICD CESC and establish an ICDRs prognostic model improve immunotherapy efficacy for patients with cancer. ICD-associated genes were screened at single-cell transcriptome levels based on AddModuleScore, single-sample gene set enrichment analysis (ssGSEA) weighted co-expression network (WGCNA) analysis. Immunogenic death-related features (ICDRs) constructed using multiple machine algorithms, evaluated training validation sets provide quantitative tools predicting prognosis clinical practice. Predictive models used risk subgroups response immunotherapy, as drug sensitivity. Finally, expression ICD-related was verified by RT-qPCR. Through integrated data, transcriptomic profiling, computational modeling, seven identified highly patients. Multivariate demonstrated that low-risk had significantly better overall survival compared high-risk patients, confirming independent tool. Assessments tumor microenvironment (TME), mutation characteristics, sensitivity within indicated a stronger group.

Язык: Английский

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