A Human Tissue-Specific Transcriptomic Analysis Reveals that Ageing Hinders Cancer and Boosts Cellular Senescence

Abstract

Ageing is the biggest risk factor for cancer, but the mechanisms linking these two processes remain unclear. We compared genes differentially expressed with age and genes differentially expressed in cancer among nine human tissues. In most tissues, ageing and cancer gene expression surprisingly changed in the opposite direction. These overlapping gene sets were related to several processes, mainly cell cycle and the immune system.Moreover, cellular senescence signatures derived from a meta-analysis changed in the same direction as ageing and in the opposite direction of cancer signatures. Therefore, transcriptomic changes in ageing and cellular senescence might relate to a decrease in cell proliferation, while cancer transcriptomic changes shift towards an increase in cell division.Our results highlight the complex relationship between ageing, cancer and cellular senescence and suggest that in most human tissues ageing processes and senescence act in tandem while being detrimental to cancer. Our work challenges the traditional view concerning the relationship between cancer and ageing and suggests that ageing processes may hinder cancer development.

A Multidimensional Systems Biology Analysis of Cellular Senescence in Ageing and Disease

“…There was the opposite trend in the inhibitors of CS, where there was noticeably less overexpression of CS inhibitors with age, although these overlaps were also not significant after FDR correction. 1,240 differentially expressed signatures of CS were also overlapped with the GTEx ageing DEGs in 26 human tissues, including 9 tissues previously analysed ( Figure 2B) (Chatsirisupachai et al, 2019). The overexpressed signatures of CS were significantly overexpressed across multiple tissues with age, and only significantly underexpressed with age in the brain and uterus (p<0.05, Fisher's exact test with BH correction) (SI Table 12).…”

“…Then, we examined the differential expression of CS genes with age in different tissues. Using a previously generated gene set of differentially expressed genes (DEGs) with age in 26 tissues on GTEx (Chatsirisupachai et al, 2019;Consortium, 2013), we found overlaps with 268 CellAge promoters and inhibitors of CS present in the gene expression data (Figure 2A). The process of finding DEGs with age filters out lowly expressed genes, which explains the 11 missing CellAge CS regulators.…”

“…The genes in the dataset are also classified according to the experimental context used to determine these associations. We have also performed a meta-analysis to identify the genetic signatures of replicative CS, and found 526 overexpressed and 734 underexpressed genes (Chatsirisupachai et al, 2019). These gene signatures are also available on the CellAge website.…”

“…The Genotype-Tissue Expression (GTEx) project (v7, January 2015 release) contains expression data from 53 different tissue sites collected from 714 donors ranging from 20 to 79 years of age which can be grouped into 26 tissue classes (Consortium, 2013). We asked if CellAge genes and differentially expressed signatures of CS were expressed in a tissue-specific manner (Palmer et al, manuscript in preparation), and determined how CS gene expression changes across different tissues with age (Chatsirisupachai et al, 2019).…”

“…We generated a list of genes that are coexpressed with the CellAge SIPS (SI Table 41). A previous paper published a set of gene signatures that are overexpressed and underexpressed in replicative cell senescence (RS) (Chatsirisupachai et al, 2019). We chose to validate five additional genes that were both co-expressed with the CellAge SIPS and are present as underexpressed in our gene signatures in RS.…”