1. Multi-omics and single cell characterization of cancer immunosenescence landscape
- Author
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Qiuxia Wei, Ruizhi Chen, Xue He, Yanan Qu, Changjian Yan, Xiaoni Liu, Jing Liu, Jiahao Luo, Zining Yu, Wenping Hu, Liqun Wang, Xiaoya Lin, Chaoling Wu, Jinyuan Xiao, Haibo Zhou, Jing Wang, Mingxia Zhu, Ping Yang, Yingtong Chen, Qilong Tan, Xiaoliang Yuan, Hongmei Jing, and Weilong Zhang
- Subjects
Science - Abstract
Abstract Cellular senescence (CS) is closely related to tumor progression. However, the studies about CS genes across human cancers have not explored the relationship between cancer senescence signature and telomere length. Additionally, single-cell analyses have not revealed the evolutionary trends of malignant cells and immune cells at the CS level. We defined a CS-associated signature, called “senescence signature”, and found that patients with higher senescence signature had worse prognosis. Higher senescence signature was related to older age, higher genomic instability, longer telomeres, increased lymphocytic infiltration, higher pro-tumor immune infiltrates (Treg cells and MDSCs), and could predict responses to immune checkpoint inhibitor therapy. Single-cell analysis further reveals malignant cells and immune cells share a consistent evolutionary trend at the CS level. MAPK signaling pathway and apoptotic processes may play a key role in CS, and senescence signature may effectively predict sensitivity of MEK1/2 inhibitors, ERK1/2 inhibitors and BCL-2 family inhibitors. We also developed a new CS prediction model of cancer survival and established a portal website to apply this model ( https://bio-pub.shinyapps.io/cs_nomo/ ).
- Published
- 2024
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