Year: 2024
Type: article
Abstract: BACKGROUND: correlates with a poor prognosis in non-small cell lung cancer (NSCLC) and, in non-transformed cells, p21 promotes quiescence after replication stress. We tested whether NSCLC cells enter p21-dependent quiescence and if this is advantageous to NSCLC cells. METHODS: Through analysis of patient data and quantitative, single-cell, timelapse imaging of genetically-engineered NSCLC reporter cell lines we investigated the role of p21 in NSCLC during normal proliferation and after chemotherapy. RESULTS: High p21 expression correlates with a poor prognosis in TP53 wild-type, but not TP53 mutant, NSCLC patients and TP53 wild-type NSCLC cells can enter p21-dependent quiescence, downstream of replication stress. Without p21, unrepaired DNA damage propagates into S-phase and cells display increased genomic instability. p21 expression confers survival advantages to TP53 wild-type NSCLC cells, during proliferation and after chemotherapy. p21 can promote tumour relapse by allowing recovery from both G1 and G2 arrests after chemotherapy. CONCLUSIONS: p21-dependent quiescence exists in TP53 wild-type NSCLC cells and provides survival advantages to these cells. Targeting p21 function in TP53 wild-type tumours could lead to better outcomes for chemotherapy treatment in NSCLC patients.
Source: British Journal of Cancer
Authors: SJ Cutty, FA Hughes, P. Ortega-Prieto, S. Desai, P. Thomas, LV Fets, M. Secrier, AR Barr
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,990
Funders: Wellcome Trust, UK Research and Innovation, Cancer Research UK, National Institute for Health and Care Research, Research Councils UK, University of Oxford, Medical Research Council, Engineering and Physical Sciences Research Council, Biotechnology and Biological Sciences Research Council, NIHR Imperial Biomedical Research Centre
Awards: G1418667172, G1427787581, G1988919693, G2453345397, G2782040499, UCL Biosciences Big Data, G3974205725, G4477160695, G5279000102, G5346331429, G5403519449, G561437257, G5831157471, G615387187, G6206488694, G6600006132, Institutional Strategic Support Fund, G6976145177, G7225549451, EPSRC Centre for Mathematics of Precision Healthcare, G7747780707, G850745309, From bacteria to mammalian cells: Interrogating single-cell dynamics using agent-based stochastic models
OpenAlex ID: W4405621614