Computational screen to identify potential targets for immunotherapeutic identification and removal of senescence cells

• Published in: Aging cell 2023-06, Vol.22 (6), p.e13809-n/a
• Main Authors: Deng, Eden Z., Fleishman, Reid H., Xie, Zhuorui, Marino, Giacomo B., Clarke, Daniel J. B., Ma'ayan, Avi
• Format: Article
• Language: English
• Subjects: Aged; Aging; Aging - genetics; antibody drug conjugates; bioinforatics; biomarkers; CAR T‐cell therapy; Cell cycle; Cell Line; Cellular Senescence - genetics; Gene expression; Gene Expression Profiling; Heart failure; Humans; Immunotherapy; neoantigens; omics integration; Proteins; Proteomics; Pulmonary fibrosis; Senescence; Short Communication; Short Communications; Software; Transcriptomics
• ISSN: 1474-9718; 1474-9726
• DOI: 10.1111/acel.13809

To prioritize gene and protein candidates that may enable the selective identification and removal of senescent cells, we compared gene expression signatures from replicative senescent cells to transcriptomics and proteomics atlases of normal human tissues and cell types. RNA‐seq samples from in vitro senescent cells (6 studies, 13 conditions) were analyzed for identifying targets at the gene and transcript levels that are highly expressed in senescent cells compared to their expression in normal human tissues and cell types. A gene set made of 301 genes called SenoRanger was established based on consensus analysis across studies and backgrounds. Of the identified senescence‐associated targets, 29% of the genes in SenoRanger are also highly differentially expressed in aged tissues from GTEx. The SenoRanger gene set includes previously known as well as novel senescence‐associated genes. Pathway analysis that connected the SenoRanger genes to their functional annotations confirms their potential role in several aging and senescence‐related processes. Overall, SenoRanger provides solid hypotheses about potentially useful targets for identifying and removing senescence cells. Data from published studies of senescence cells were used to identify genes and transcripts that are commonly upregulated in these cells compared to their expression levels across normal tissues and cell types processed from GTEx, ARCHS4, and Tabula Sapiens. Identified genes and transcripts were further filtered to include only genes and transcripts that give rise to membrane proteins and secreted proteins. These genes and transcripts may serve as useful targets for identifying and removing senescence cells.