Quantitative assessment of markers for cell senescence

Conor Lawless, Chunfang Wang, Diana Jurk, Alina Merz, Thomas von Zglinicki, João F. Passos

Research output: Contribution to journalArticlepeer-review

153 Scopus citations


Cellular senescence, the irreversible loss of replicative capacity, might be a tumour suppressor and a contributor to age-related loss of tissue function. The absence of quantitative tests for reliability of candidate markers for senescent cells is a major drawback in cell population studies. Fibroblasts in culture constitute mixed populations of proliferation-competent and senescent cells, with transition between these with increasing population doublings (PD). We estimated senescent fraction in human and mouse fibroblasts with high precision from easily observed growth curves using a dynamic simulation model. We also determined senescent fractions, at various PD (over a wide range of senescent cell frequencies) using candidate senescence markers: Ki67, p21 (CDKN1A), γH2AX, SAHF and Sen-β-Gal either alone or in combination, and compared with those derived from growth curves. This comparison allowed ranking of candidate markers. High rankings were obtained for Sen-β-Gal, SAHFs and the combination of Ki67 negativity with high (>5 per nucleus) γH2A.X foci density in MRC5 fibroblasts. We demonstrate that this latter marker combination, which can easily be performed in paraffin-embedded tissue, gives quantitative senescent cell frequency estimates in mouse embryonic fibroblast cultures and in mouse intestinal sections. The technique presented is a framework for quantitative assessment of markers for senescence.

Original languageEnglish (US)
Pages (from-to)772-778
Number of pages7
JournalExperimental Gerontology
Issue number10
StatePublished - Oct 2010


  • Ageing
  • Bayesian inference
  • Dynamic model
  • Fibroblasts
  • Growth curves
  • Markers
  • Mathematical model
  • Population
  • Senescence
  • Simulation

ASJC Scopus subject areas

  • Biochemistry
  • Aging
  • Molecular Biology
  • Genetics
  • Endocrinology
  • Cell Biology


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