Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators

Tao, Wanyu; Yu, Zhengqing; Han, Jing-Dong J.

doi:10.1016/j.cmet.2024.03.009

Cited by 21 publications

(1 citation statement)

References 141 publications

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“…Recent studies have demonstrated the notion of molecular subtypes of senescence 13,28 . In light of these studies and other studies defining molecular signatures of senescence 8,9 , it would be interesting to see what extent these molecular profiles associate with and map onto our morphology-defined subtypes.…”

Section: Discussionmentioning

confidence: 99%

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts

Kamat,

Macaluso,

Min

et al. 2024

Preprint

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Cellular senescence is an established driver of aging, exhibiting context-dependent phenotypes across multiple biological length-scales. Despite its mechanistic importance, profiling senescence within cell populations is challenging. This is in part due to the limitations of current biomarkers to robustly identify senescent cells across biological settings, and the heterogeneous, non-binary phenotypes exhibited by senescent cells. Using a panel of primary dermal fibroblasts, we combined live single-cell imaging, machine learning, multiple senescence induction conditions, and multiple protein-based senescence biomarkers to show the emergence of functional subtypes of senescence. Leveraging single-cell morphologies, we defined eleven distinct morphology clusters, with the abundance of cells in each cluster being dependent on the mode of senescence induction, the time post-induction, and the age of the donor. Of these eleven clusters, we identified three bona-fide senescence subtypes (C7, C10, C11), with C10 showing the strongest age-dependence across a cohort of fifty aging individuals. To determine the functional significance of these senescence subtypes, we profiled their responses to senotherapies, specifically focusing on Dasatinib + Quercetin (D+Q). Results indicated subtype-dependent responses, with senescent cells in C7 being most responsive to D+Q. Altogether, we provide a robust single-cell framework to identify and classify functional senescence subtypes with applications for next-generation senotherapy screens, and the potential to explain heterogeneous senescence phenotypes across biological settings based on the presence and abundance of distinct senescence subtypes.

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Section: Discussionmentioning

confidence: 99%

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts

Kamat,

Macaluso,

Min

et al. 2024

Preprint

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Biomarkers of Cellular Senescence and Aging: Current State‐of‐the‐Art, Challenges and Future Perspectives

Muthamil,

Kim,

Jang

et al. 2024

Advanced Biology

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Population aging has increased the global prevalence of aging‐related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence‐associated β‐galactosidase staining, telomere shortening, cell‐cycle arrest, DNA methylation, and senescence‐associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging‐associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi‐omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging‐associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.

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Integration of single-cell and spatial transcriptome sequencing identifies CDKN2A as a senescent biomarker in endothelial cells implicating hepatocellular carcinoma malignancy

Ma,

Yi,

Cai

et al. 2024

J Cancer Res Clin Oncol

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Purpose Highly complex tumor microenvironment makes hepatocellular carcinoma (HCC) as one of the most malignant tumors worldwide. The role of cellular senescence in HCC has been gradually recognized. The present study aimed to comprehensively elucidate the senescence-related features of HCC in single-cell and spatial dimension. Methods Single-cell RNA sequencing (scRNA-Seq) data was used to clarify the heterogeneity of senescence-related genes (SRGs) among multiple cell types within HCC. Spatial transcriptome RNA sequencing (stRNA-Seq) data was used for depicting SRGs features in spatial dimension. A prognostic model based on SRGs was constructed by using of bulk sequencing (bulk-Seq) data of HCC. The cell-cell interaction of senescent endothelial cells (ECs) in tumor microenvironment was analyzed. Then, the role of senescent ECs was verified through in vitro and in vivo experiments. Results The level of senescence demonstrated substantial heterogeneity among different cell types within tumor microenvironment of HCC, where ECs exhibited the most prominent senescent phenotype. Senescent ECs activated specific regulatory pathways through communicating with other cell types, with a potential impact on tumor progression. Spatial analysis revealed senescent ECs mainly located in the core region of HCC. The interaction of senescent ECs and immune cells implicated their role in tumor progression and immunotherapeutic response. In addition, CDKN2A was identified as an independent risk factor for HCC prognosis by constructing a prognostic model. Patients with high risk displayed an even worse outcome. The experimental verification indicated senescence of ECs determined by CDKN2A exhibited a secretory phenotype. Furthermore, senescent ECs with CDKN2A overexpression promote the proliferation and migration of HCC. Conclusion The present study recognizes the critical effect of senescent ECs defined by CDKN2A in the promotion of tumor progression, which sheds new light on the investigation of ECs senescence in HCC. Supplementary Information The online version contains supplementary material available at 10.1007/s00432-024-06017-5.

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Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators

Cited by 21 publications

References 141 publications

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts

Biomarkers of Cellular Senescence and Aging: Current State‐of‐the‐Art, Challenges and Future Perspectives

Integration of single-cell and spatial transcriptome sequencing identifies CDKN2A as a senescent biomarker in endothelial cells implicating hepatocellular carcinoma malignancy

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