RAD50 deficiency is a predictor of platinum sensitivity in sporadic epithelial ovarian cancers.

DNA repair Ovarian cancer Platinum therapy Predictive biomarker RAD50

Journal

Molecular biomedicine
ISSN: 2662-8651
Titre abrégé: Mol Biomed
Pays: Singapore
ID NLM: 9918283581406676

Informations de publication

Date de publication:
30 Dec 2020
Historique:
received: 26 11 2020
accepted: 30 11 2020
entrez: 10 1 2022
pubmed: 30 12 2020
medline: 30 12 2020
Statut: epublish

Résumé

Intrinsic or acquired resistance seriously limits the use of platinating agents in advanced epithelial ovarian cancers. Increased DNA repair capacity is a key route to platinum resistance. RAD50 is a critical component of the MRN complex, a 'first responder' to DNA damage and essential for the repair of DSBs and stalled replication forks. We hypothesised a role for RAD50 in ovarian cancer pathogenesis and therapeutics. Clinicopathological significance of RAD50 expression was evaluated in clinical cohorts of ovarian cancer at the protein level (n = 331) and at the transcriptomic level (n = 1259). Sub-cellular localization of RAD50 at baseline and following cisplatin therapy was tested in platinum resistant (A2780cis, PEO4) and sensitive (A2780, PEO1) ovarian cancer cells. RAD50 was depleted and cisplatin sensitivity was investigated in A2780cis and PEO4 cells. RAD50 deficiency was associated with better progression free survival (PFS) at the protein (p = 0.006) and transcriptomic level (p < 0.001). Basal level of RAD50 was higher in platinum resistant cells. Following cisplatin treatment, increased nuclear localization of RAD50 was evident in A2780cis and PEO4 compared to A2780 and PEO1 cells. RAD50 depletion using siRNAs in A2780cis and PEO4 cells increased cisplatin cytotoxicity, which was associated with accumulation of DSBs, S-phase cell cycle arrest and increased apoptosis. We provide evidence that RAD50 deficiency is a predictor of platinum sensitivity. RAD50 expression-based stratification and personalization could be viable clinical strategy in ovarian cancers.

Identifiants

pubmed: 35006434
doi: 10.1186/s43556-020-00023-y
pii: 10.1186/s43556-020-00023-y
pmc: PMC8607373
doi:

Types de publication

Journal Article

Langues

eng

Pagination

19

Informations de copyright

© 2020. The Author(s).

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Auteurs

Adel Alblihy (A)

Translational Oncology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.

Muslim L Alabdullah (ML)

Translational Oncology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.
Academic Pathology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.

Michael S Toss (MS)

Academic Pathology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.

Mashael Algethami (M)

Translational Oncology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.

Nigel P Mongan (NP)

Faculty of medicine and Health Sciences, Centre for Cancer Sciences, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD, UK.
Department of Pharmacology, Weill Cornell Medicine, New York, NY, 10065, USA.

Emad A Rakha (EA)

Academic Pathology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK.

Srinivasan Madhusudan (S)

Translational Oncology, Division of Cancer & Stem Cells, School of Medicine, University of Nottingham Biodiscovery Institute, Nottingham, NG51PB, UK. srinivasan.madhusudan@nottingham.ac.uk.
Department of Oncology, Nottingham University Hospitals, Nottingham, NG51PB, UK. srinivasan.madhusudan@nottingham.ac.uk.
Division of Cancer & Stem Cells, School of Medicine, Nottingham Biodiscovery Institute, University of Nottingham, University Park, Nottingham, NG7 3RD, UK. srinivasan.madhusudan@nottingham.ac.uk.

Classifications MeSH