Implications of time‐series gene expression profiles of replicative senescence. Issue 4 (7th May 2013)

• Record Type: Journal Article
• Authors: Kim, You‐Mi; Byun, Hae‐Ok; Jee, Byul A.; Cho, Hyunwoo; Seo, Yong‐Hak; Kim, You‐Sun; Park, Min Hi; Chung, Hae‐Young; Woo, Hyun Goo; Yoon, Gyesoon
• Is Part Of: Aging cell. Volume 12:Issue 4(2013:Aug.)
• Page Start: 622
• Page End: 634
• Publication Date: 2013-05-07
• Subjects: gene expression -- human diploid fibroblasts -- replicative senescence -- senescence‐associated secretory phenotype; Cells -- Aging -- Periodicals; 571.8783605
• DOI: 10.1111/acel.12087
• Languages: English
• ISSNs: 1474-9718

Abstract

Summary: Although senescence has long been implicated in aging‐associated pathologies, it is not clearly understood how senescent cells are linked to these diseases. To address this knowledge gap, we profiled cellular senescence phenotypes and mRNA expression patterns during replicative senescence in human diploid fibroblasts. We identified a sequential order of gain‐of‐senescence phenotypes: low levels of reactive oxygen species, cell mass/size increases with delayed cell growth, high levels of reactive oxygen species with increases in senescence‐associated β‐galactosidase activity (SA‐β‐gal), and high levels of SA‐β‐gal activity. Gene expression profiling revealed four distinct modules in which genes were prominently expressed at certain stages of senescence, allowing us to divide the process into four stages: early, middle, advanced, and very advanced. Interestingly, the gene expression modules governing each stage supported the development of the associated senescence phenotypes. Senescence‐associated secretory phenotype–related genes also displayed a stage‐specific expression pattern with three unique features during senescence: differential expression of interleukin isoforms, differential expression of interleukins and their receptors, and differential expression of matrix metalloproteinases and their inhibitory proteins. We validated these phenomena at the protein level using human diploid fibroblasts and aging Sprague‐Dawley rat skin tissues. Finally, disease‐association analysis of the modular genes also revealed stage‐specific patterns. Taken together, our results reflect a detailed process of cellular senescence and provide diverse genome‐wide information of cellular backgrounds for senescence.