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Curr Biol. 2017 Sep 11;27(17):2652-2660.e4. doi: 10.1016/j.cub.2017.07.033. Epub 2017 Aug 30.

Unmasking Transcriptional Heterogeneity in Senescent Cells.

Author information

1
European Research Institute for the Biology of Aging, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, the Netherlands.
2
Buck Institute for Research on Aging, 8001 Redwood Boulevard, 94945 Novato CA, USA.
3
Buck Institute for Research on Aging, 8001 Redwood Boulevard, 94945 Novato CA, USA; Lawrence Berkeley National Laboratory, Life Sciences Division, 1 Cyclotron Road, Berkeley, CA 94720, USA.
4
European Research Institute for the Biology of Aging, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, the Netherlands. Electronic address: m.demaria@umcg.nl.

Abstract

Cellular senescence is a state of irreversibly arrested proliferation, often induced by genotoxic stress [1]. Senescent cells participate in a variety of physiological and pathological conditions, including tumor suppression [2], embryonic development [3, 4], tissue repair [5-8], and organismal aging [9]. The senescence program is variably characterized by several non-exclusive markers, including constitutive DNA damage response (DDR) signaling, senescence-associated β-galactosidase (SA-βgal) activity, increased expression of the cyclin-dependent kinase (CDK) inhibitors p16INK4A (CDKN2A) and p21CIP1 (CDKN1A), increased secretion of many bio-active factors (the senescence-associated secretory phenotype, or SASP), and reduced expression of the nuclear lamina protein LaminB1 (LMNB1) [1]. Many senescence-associated markers result from altered transcription, but the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking [10]. Here, we characterize the heterogeneity of the senescence program using numerous whole-transcriptome datasets generated by us or publicly available. We identify transcriptome signatures associated with specific senescence-inducing stresses or senescent cell types and identify and validate genes that are commonly differentially regulated. We also show that the senescent phenotype is dynamic, changing at varying intervals after senescence induction. Identifying novel transcriptome signatures to detect any type of senescent cell or to discriminate among diverse senescence programs is an attractive strategy for determining the diverse biological roles of senescent cells and developing specific drug targets.

KEYWORDS:

DNA damage; RNA-seq; SASP; cell-cycle arrest; cellular senescence; primary cells; qPCR; transcriptional signatures; tumor suppression; whole-transcriptome sequencing

PMID:
28844647
PMCID:
PMC5788810
DOI:
10.1016/j.cub.2017.07.033
[Indexed for MEDLINE]
Free PMC Article

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