Transcriptional Heterogeneity of Cellular Senescence in Cancer

Abstract

Cellular senescence plays a paradoxical role in tumorigenesis through the expression of diverse senescence-associated (SA) secretory phenotypes (SASPs). The heterogeneity of SA gene expression in cancer cells not only promotes cancer stemness but also protects these cells from chemotherapy. Despite the potential correlation between cancer and SA biomarkers, many transcriptional changes across distinct cell populations remain largely unknown. During the past decade, single-cell RNA sequencing (scRNA-seq) technologies have emerged as powerful experimental and analytical tools to dissect such diverse senescence-derived transcriptional changes. Here, we review the recent sequencing efforts that successfully characterized scRNA-seq data obtained from diverse cancer cells and elucidated the role of senescent cells in tumor malignancy. We further highlight the functional implications of SA genes expressed specifically in cancer and stromal cell populations in the tumor microenvironment. Translational research leveraging scRNA-seq profiling of SA genes will facilitate the identification of novel expression patterns underlying cancer susceptibility, providing new therapeutic opportunities in the era of precision medicine.

Keywords: cancer; cellular heterogeneity; senescence; single-cell RNA sequencing.

Fig. 1. Role of senescence-associated secretory phenotype (SASP) factors in tumor initiation and progression.

Chronic senescence leads to DNA damage that elicits a DNA damage response via key effector pathways to execute senescence and SASP, promoting tumorigenesis (Campisi, 2011; Kim and Park, 2019; Lee and Schmitt, 2019). Various types of senescent cells present in the tumor microenvironment produce SASP factors, which are involved not only in auto and paracrine-mediated cell cycle arrest but also in tumor progression and chemoresistance (Bochenek et al., 2016; Hansel et al., 2020; Hassona et al., 2014; Liu and Cao, 2016). IL, interleukin; PDGF, platelet-derived growth factor; TGFβ, transforming growth factor beta; VEGFs, vascular endothelial growth factors; FGF, fibroblast growth factor; CTGF, connective tissue growth factor; TIMP, tissue inhibitors of metalloproteinases; MMP, matrix metalloproteinase; CXCL, chemokine (C-X-C motif) ligand; EGF, epidermal growth factor; TNF, tumor necrosis factor; AREG, amphiregulin; CCL, chemokine (C-C motif) ligand.

Fig. 2. Mouse to human preclinical cancer models leveraging scRNA-seq technologies play leading roles in advancing precision medicine research.