Evidence map›Paper›PMID 34656146›Full record

ArticleJournal of experimental & clinical cancer research : CR2021

Replication catastrophe is responsible for intrinsic PAR glycohydrolase inhibitor-sensitivity in patient-derived ovarian cancer models.

Camilla Coulson-Gilmer, Robert D Morgan, Louisa Nelson, Bethany M Barnes, Anthony Tighe, René Wardenaar, Diana C J Spierings, Helene Schlecht, George J Burghel, Floris Foijer and 3 more

Open access · goldAbstract read
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

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  15. PARG inhibitor sensitivity correlates with accumulation of single-stranded DNA gaps in preclinical models of ovarian cancer.Proceedings of the National Academy of Sciences of the United States of America · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 2 countries.

Camilla Coulson-GilmerDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
Robert D MorganDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
Louisa NelsonDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
Bethany M BarnesDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
Anthony TigheDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
René WardenaarEuropean Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, 9713, AV, The Netherlands.
Diana C J SpieringsEuropean Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, 9713, AV, The Netherlands.
Helene SchlechtManchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
George J BurghelManchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
Floris FoijerEuropean Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, 9713, AV, The Netherlands.
Sudha DesaiDepartment of Histopathology, The Christie NHS Foundation Trust, Wilmslow Rd, Manchester, M20 4BX, UK.
Joanne C McGrailDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK.
Stephen S TaylorDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, Oglesby Cancer Research Building, 555 Wilmslow Road, Manchester, M20 4GJ, UK. stephen.taylor@manchester.ac.uk.
Cancer Research UK Manchester Institute · GBCancer Research UK Manchester CentreSt Mary's Hospital · GBThe Christie NHS Foundation Trust · GBUniversity of Groningen · NLUniversity Medical Center Groningen · NL

Funding

Cancer Research UK C1422/A19842Cancer Research UK C147/A25254
6 · The paper itself

Abstract

backgroundPatients with ovarian cancer often present at advanced stage and, following initial treatment success, develop recurrent drug-resistant disease. PARP inhibitors (PARPi) are yielding unprecedented survival benefits for women with BRCA-deficient disease. However, options remain limited for disease that is platinum-resistant and/or has inherent or acquired PARPi-resistance. PARG, the PAR glycohydrolase that counterbalances PARP activity, is an emerging target with potential to selectively kill tumour cells harbouring oncogene-induced DNA replication and metabolic vulnerabilities. Clinical development of PARG inhibitors (PARGi) will however require predictive biomarkers, in turn requiring an understanding of their mode of action. Furthermore, differential sensitivity to PARPi is key for expanding treatment options available for patients.

methodsA panel of 10 ovarian cancer cell lines and a living biobank of patient-derived ovarian cancer models (OCMs) were screened for PARGi-sensitivity using short- and long-term growth assays. PARGi-sensitivity was characterized using established markers for DNA replication stress, namely replication fibre asymmetry, RPA foci, KAP1 and Chk1 phosphorylation, and pan-nuclear γH2AX, indicating DNA replication catastrophe. Finally, gene expression in sensitive and resistant cells was also examined using NanoString or RNAseq.

resultsPARGi sensitivity was identified in both ovarian cancer cell lines and patient-derived OCMs, with sensitivity accompanied by markers of persistent replication stress, and a pre-mitotic cell cycle block. Moreover, DNA replication genes are down-regulated in PARGi-sensitive cell lines consistent with an inherent DNA replication vulnerability. However, DNA replication gene expression did not predict PARGi-sensitivity in OCMs. The subset of patient-derived OCMs that are sensitive to single-agent PARG inhibition, includes models that are PARPi- and/or platinum-resistant, indicating that PARG inhibitors may represent an alternative treatment strategy for women with otherwise limited therapeutic options.

conclusionsWe discover that a subset of ovarian cancers are intrinsically sensitive to pharmacological PARG blockade, including drug-resistant disease, underpinned by a common mechanism of replication catastrophe. We explore the use of a transcript-based biomarker, and provide insight into the design of future clinical trials of PARGi in patients with ovarian cancer. However, our results highlight the complexity of developing a predictive biomarker for PARGi sensitivity.

Indexed as

Cell Line, TumorFemaleGlycoside HydrolasesHumansOvarian NeoplasmsGlycoside HydrolasesDNA replicationGene expression signatureHigh-grade serous ovarian cancerPARG inhibitorPredictive biomarkersReplication stress

Identifiers

PMID34656146
PMCPMC8520217
OpenAlexW3205799333

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.