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The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome

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The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome. / Walker, Thomas D. J.; Faraahi, Zahra F.; Price, Marcus J. et al.
In: British Journal of Cancer, Vol. 128, 21.02.2023, p. 1765–1776.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Walker, TDJ, Faraahi, ZF, Price, MJ, Hawarden, A, Waddell, CA, Russell, B, Jones, DM, McCormick, A, Gavrielides, N, Tyagi, S, Woodhouse, LC, Whalley, B, Roberts, C, Crosbie, EJ & Edmondson, R 2023, 'The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome', British Journal of Cancer, vol. 128, pp. 1765–1776. https://doi.org/10.1038/s41416-023-02168-3

APA

Walker, T. D. J., Faraahi, Z. F., Price, M. J., Hawarden, A., Waddell, C. A., Russell, B., Jones, D. M., McCormick, A., Gavrielides, N., Tyagi, S., Woodhouse, L. C., Whalley, B., Roberts, C., Crosbie, E. J., & Edmondson, R. (2023). The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome. British Journal of Cancer, 128, 1765–1776. https://doi.org/10.1038/s41416-023-02168-3

Vancouver

Walker TDJ, Faraahi ZF, Price MJ, Hawarden A, Waddell CA, Russell B et al. The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome. British Journal of Cancer. 2023 Feb 21;128:1765–1776. doi: 10.1038/s41416-023-02168-3

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Bibtex

@article{e9552a329f3b4c56911587466de691f6,
title = "The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome",
abstract = "Background Ovarian cancers are hallmarked by chromosomal instability. New therapies deliver improved patient outcomes in relevant phenotypes, however therapy resistance and poor long-term survival signal requirements for better patient preselection. An impaired DNA damage response (DDR) is a major chemosensitivity determinant. Comprising five pathways, DDR redundancy is complex and rarely studied alongside chemoresistance influence from mitochondrial dysfunction. We developed functional assays to monitor DDR and mitochondrial states and trialled this suite on patient explants. Methods We profiled DDR and mitochondrial signatures in cultures from 16 primary-setting ovarian cancer patients receiving platinum chemotherapy. Explant signature relationships to patient progression-free (PFS) and overall survival (OS) were assessed by multiple statistical and machine-learning methods. ResultsDDR dysregulation was wide-ranging. Defective HR (HRD) and NHEJ were near-mutually exclusive. HRD patients (44%) had increased SSB abrogation. HR competence was associated with perturbed mitochondria (78% vs 57% HRD) while every relapse patient harboured dysfunctional mitochondria. DDR signatures classified explant platinum cytotoxicity and mitochondrial dysregulation. Importantly, explant signatures classified patient PFS and OS. Conclusions Whilst individual pathway scores are mechanistically insufficient to describe resistance, holistic DDR and mitochondrial states accurately predict patient survival. Our assay suite demonstrates promise for translational chemosensitivity prediction. ",
author = "Walker, {Thomas D. J.} and Faraahi, {Zahra F.} and Price, {Marcus J.} and Amy Hawarden and Waddell, {Caitlin A.} and Bryn Russell and Jones, {Dominique M.} and Aiste McCormick and N. Gavrielides and S. Tyagi and Woodhouse, {Laura C.} and Bethany Whalley and Connor Roberts and Crosbie, {Emma J.} and Richard Edmondson",
year = "2023",
month = feb,
day = "21",
doi = "10.1038/s41416-023-02168-3",
language = "English",
volume = "128",
pages = "1765–1776",
journal = "British Journal of Cancer",
issn = "0007-0920",
publisher = "Nature Publishing Group",

}

RIS

TY - JOUR

T1 - The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome

AU - Walker, Thomas D. J.

AU - Faraahi, Zahra F.

AU - Price, Marcus J.

AU - Hawarden, Amy

AU - Waddell, Caitlin A.

AU - Russell, Bryn

AU - Jones, Dominique M.

AU - McCormick, Aiste

AU - Gavrielides, N.

AU - Tyagi, S.

AU - Woodhouse, Laura C.

AU - Whalley, Bethany

AU - Roberts, Connor

AU - Crosbie, Emma J.

AU - Edmondson, Richard

PY - 2023/2/21

Y1 - 2023/2/21

N2 - Background Ovarian cancers are hallmarked by chromosomal instability. New therapies deliver improved patient outcomes in relevant phenotypes, however therapy resistance and poor long-term survival signal requirements for better patient preselection. An impaired DNA damage response (DDR) is a major chemosensitivity determinant. Comprising five pathways, DDR redundancy is complex and rarely studied alongside chemoresistance influence from mitochondrial dysfunction. We developed functional assays to monitor DDR and mitochondrial states and trialled this suite on patient explants. Methods We profiled DDR and mitochondrial signatures in cultures from 16 primary-setting ovarian cancer patients receiving platinum chemotherapy. Explant signature relationships to patient progression-free (PFS) and overall survival (OS) were assessed by multiple statistical and machine-learning methods. ResultsDDR dysregulation was wide-ranging. Defective HR (HRD) and NHEJ were near-mutually exclusive. HRD patients (44%) had increased SSB abrogation. HR competence was associated with perturbed mitochondria (78% vs 57% HRD) while every relapse patient harboured dysfunctional mitochondria. DDR signatures classified explant platinum cytotoxicity and mitochondrial dysregulation. Importantly, explant signatures classified patient PFS and OS. Conclusions Whilst individual pathway scores are mechanistically insufficient to describe resistance, holistic DDR and mitochondrial states accurately predict patient survival. Our assay suite demonstrates promise for translational chemosensitivity prediction.

AB - Background Ovarian cancers are hallmarked by chromosomal instability. New therapies deliver improved patient outcomes in relevant phenotypes, however therapy resistance and poor long-term survival signal requirements for better patient preselection. An impaired DNA damage response (DDR) is a major chemosensitivity determinant. Comprising five pathways, DDR redundancy is complex and rarely studied alongside chemoresistance influence from mitochondrial dysfunction. We developed functional assays to monitor DDR and mitochondrial states and trialled this suite on patient explants. Methods We profiled DDR and mitochondrial signatures in cultures from 16 primary-setting ovarian cancer patients receiving platinum chemotherapy. Explant signature relationships to patient progression-free (PFS) and overall survival (OS) were assessed by multiple statistical and machine-learning methods. ResultsDDR dysregulation was wide-ranging. Defective HR (HRD) and NHEJ were near-mutually exclusive. HRD patients (44%) had increased SSB abrogation. HR competence was associated with perturbed mitochondria (78% vs 57% HRD) while every relapse patient harboured dysfunctional mitochondria. DDR signatures classified explant platinum cytotoxicity and mitochondrial dysregulation. Importantly, explant signatures classified patient PFS and OS. Conclusions Whilst individual pathway scores are mechanistically insufficient to describe resistance, holistic DDR and mitochondrial states accurately predict patient survival. Our assay suite demonstrates promise for translational chemosensitivity prediction.

U2 - 10.1038/s41416-023-02168-3

DO - 10.1038/s41416-023-02168-3

M3 - Journal article

VL - 128

SP - 1765

EP - 1776

JO - British Journal of Cancer

JF - British Journal of Cancer

SN - 0007-0920

ER -