ISENICS: a model for identifying senescent immune cells and samples and characterization of their roles in tumor microenvironment

Senescent immune cells secrete varied inflammatory factors that weaken the systemic anti-tumor ability and promote the proliferation and metastasis of tumor cells. Tumor cells could also accelerate the immune cellular senescence through diverse mechanisms. However, there has been a lack of indicators to quantify the senescence levels of different immune cell types. A model for Identifying Senescent Immune Cells and Samples was developed to explore the role of senescent immune cells in the tumor immune microenvironment (TIME). By integrating bulk and single-cell RNA-seq data, we constructed immune cell gene expression profiles for 23 cancer types using a deconvolution algorithm. By calculating the cellular senescence scores, we found that tumor samples exhibited higher senescence levels than normal samples. Monocytes/macrophages were prone to co-senescence with other cell subtypes. Differentially expressed genes in the high- and low-immune cellular senescence scores groups were enriched in the senescence pathway. Patients with higher levels of immunosenescence were associated with better prognosis. At the single-cell level, the number and strength of cell-to-cell interactions increased following immune cellular senescence in most cancers. Samples with senescent immune cells exhibited poorer immunotherapy response. Our study advances our understanding of senescent immune cells in the TIME, provides insights into cancer-specific relationships between immune cellular senescence and immune characteristics, and offers a model for identifying these senescent immune cells.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2025-08-22
DOI
https://doi.org/10.1093/bib/bbaf469
Citations
1
Primary Topic
Immune cells in cancer
Type
article
Field-Weighted Citation Impact
0.80

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article

ISENICS: a model for identifying senescent immune cells and samples and characterization of their roles in tumor microenvironment

Shangwei Ning, Longlong Dong, Hui Zhi, Xinyu Wang et al.
1 citations
Briefings in Bioinformatics
Immune cells in cancer
0.80
article

ISENICS: a model for identifying senescent immune cells and samples and characterization of their roles in tumor microenvironment

Shangwei Ning, Longlong Dong, Hui Zhi, Xinyu Wang, Yue Gao, Hao Cui, Changfan Qu, Song Xiao, Miaomiao Tian, Peng Wang, Huading Hu
article en
1 citations

Abstract

Senescent immune cells secrete varied inflammatory factors that weaken the systemic anti-tumor ability and promote the proliferation and metastasis of tumor cells. Tumor cells could also accelerate the immune cellular senescence through diverse mechanisms. However, there has been a lack of indicators to quantify the senescence levels of different immune cell types. A model for Identifying Senescent Immune Cells and Samples was developed to explore the role of senescent immune cells in the tumor immune microenvironment (TIME). By integrating bulk and single-cell RNA-seq data, we constructed immune cell gene expression profiles for 23 cancer types using a deconvolution algorithm. By calculating the cellular senescence scores, we found that tumor samples exhibited higher senescence levels than normal samples. Monocytes/macrophages were prone to co-senescence with other cell subtypes. Differentially expressed genes in the high- and low-immune cellular senescence scores groups were enriched in the senescence pathway. Patients with higher levels of immunosenescence were associated with better prognosis. At the single-cell level, the number and strength of cell-to-cell interactions increased following immune cellular senescence in most cancers. Samples with senescent immune cells exhibited poorer immunotherapy response. Our study advances our understanding of senescent immune cells in the TIME, provides insights into cancer-specific relationships between immune cellular senescence and immune characteristics, and offers a model for identifying these senescent immune cells.

Briefings in BioinformaticsVol. 26(5)
Harbin Medical University (CN), Second Affiliated Hospital of Harbin Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 24%
Immune cells in cancer
0.80
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