Molecular and phenotypic characteristics influencing the degree of cytoreduction in high-grade serous ovarian carcinomas.

cancer genetics clinical observations gynaecological oncology mutations risk model surgery

Journal

Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310

Informations de publication

Date de publication:
07 2023
Historique:
revised: 23 04 2023
received: 12 10 2022
accepted: 05 05 2023
medline: 21 7 2023
pubmed: 16 5 2023
entrez: 16 5 2023
Statut: ppublish

Résumé

High-grade serous ovarian carcinoma (HGSOC) is the deadliest ovarian cancer subtype, and survival relates to initial cytoreductive surgical treatment. The existing tools for surgical outcome prediction remain inadequate for anticipating the outcomes of the complex relationship between tumour biology, clinical phenotypes, co-morbidity and surgical skills. In this genotype-phenotype association study, we combine phenotypic markers with targeted DNA sequencing to discover novel biomarkers to guide the surgical management of primary HGSOC. Primary tumour tissue samples (n = 97) and matched blood from a phenotypically well-characterised treatment-naïve HGSOC patient cohort were analysed by targeted massive parallel DNA sequencing (next generation sequencing [NGS]) of a panel of 360 cancer-related genes. Association analyses were performed on phenotypic traits related to complete cytoreductive surgery, while logistic regression analysis was applied for the predictive model. The positive influence of complete cytoreductive surgery (R0) on overall survival was confirmed (p = 0.003). Before surgery, low volumes of ascitic fluid, lower CA125 levels, higher platelet counts and relatively lower clinical stage at diagnosis were all indicators, alone and combined, for complete cytoreduction (R0). Mutations in either the chromatin remodelling SWI_SNF (p = 0.036) pathway or the histone H3K4 methylation pathway (p = 0.034) correlated with R0. The R0 group also demonstrated higher tumour mutational burden levels (p = 0.028). A predictive model was developed by combining two phenotypes and the mutational status of five genes and one genetic pathway, enabling the prediction of surgical outcomes in 87.6% of the cases in this cohort. Inclusion of molecular biomarkers adds value to the pre-operative stratification of HGSOC patients. A potential preoperative risk stratification model combining phenotypic traits and single-gene mutational status is suggested, but the set-up needs to be validated in larger cohorts.

Sections du résumé

BACKGROUND
High-grade serous ovarian carcinoma (HGSOC) is the deadliest ovarian cancer subtype, and survival relates to initial cytoreductive surgical treatment. The existing tools for surgical outcome prediction remain inadequate for anticipating the outcomes of the complex relationship between tumour biology, clinical phenotypes, co-morbidity and surgical skills. In this genotype-phenotype association study, we combine phenotypic markers with targeted DNA sequencing to discover novel biomarkers to guide the surgical management of primary HGSOC.
METHODS
Primary tumour tissue samples (n = 97) and matched blood from a phenotypically well-characterised treatment-naïve HGSOC patient cohort were analysed by targeted massive parallel DNA sequencing (next generation sequencing [NGS]) of a panel of 360 cancer-related genes. Association analyses were performed on phenotypic traits related to complete cytoreductive surgery, while logistic regression analysis was applied for the predictive model.
RESULTS
The positive influence of complete cytoreductive surgery (R0) on overall survival was confirmed (p = 0.003). Before surgery, low volumes of ascitic fluid, lower CA125 levels, higher platelet counts and relatively lower clinical stage at diagnosis were all indicators, alone and combined, for complete cytoreduction (R0). Mutations in either the chromatin remodelling SWI_SNF (p = 0.036) pathway or the histone H3K4 methylation pathway (p = 0.034) correlated with R0. The R0 group also demonstrated higher tumour mutational burden levels (p = 0.028). A predictive model was developed by combining two phenotypes and the mutational status of five genes and one genetic pathway, enabling the prediction of surgical outcomes in 87.6% of the cases in this cohort.
CONCLUSION
Inclusion of molecular biomarkers adds value to the pre-operative stratification of HGSOC patients. A potential preoperative risk stratification model combining phenotypic traits and single-gene mutational status is suggested, but the set-up needs to be validated in larger cohorts.

Identifiants

pubmed: 37191035
doi: 10.1002/cam4.6085
pmc: PMC10358208
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

14183-14195

Informations de copyright

© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Références

Cancer Res. 2008 Jul 1;68(13):5478-86
pubmed: 18593951
Cancers (Basel). 2021 Feb 05;13(4):
pubmed: 33562443
Int J Cancer. 2019 Nov 15;145(10):2670-2681
pubmed: 30892690
N Engl J Med. 2011 Dec 29;365(26):2473-83
pubmed: 22204724
Nat Commun. 2020 Feb 5;11(1):729
pubmed: 32024854
N Engl J Med. 2018 Dec 27;379(26):2495-2505
pubmed: 30345884
Genome Biol. 2019 Oct 9;20(1):203
pubmed: 31597578
Ann Surg Oncol. 2006 Aug;13(8):1156-61
pubmed: 16791447
Am Soc Clin Oncol Educ Book. 2020 Mar;40:1-16
pubmed: 32364757
Cancer Cell Int. 2020 Aug 05;20:373
pubmed: 32774167
Ann Surg Oncol. 2019 Dec;26(Suppl 3):786-787
pubmed: 31605337
Int J Gynecol Cancer. 2011 Feb;21(2):289-95
pubmed: 21270612
Obstet Gynecol. 2011 Sep;118(3):537-547
pubmed: 21860281
J Natl Cancer Inst. 2014 Apr 03;106(5):
pubmed: 24700803
N Engl J Med. 1995 Mar 9;332(10):629-34
pubmed: 7845426
Science. 2015 Apr 3;348(6230):124-8
pubmed: 25765070
J Clin Oncol. 2014 May 1;32(13):1302-8
pubmed: 24637997
J Clin Oncol. 2002 Mar 1;20(5):1248-59
pubmed: 11870167
Gynecol Oncol. 2022 Jul;166(1):50-56
pubmed: 35599168
Ann Surg Oncol. 2019 Sep;26(9):2943-2951
pubmed: 31243666
Nature. 2011 Jun 29;474(7353):609-15
pubmed: 21720365
Facts Views Vis Obgyn. 2020 Oct 8;12(3):227-239
pubmed: 33123697
Clin Cancer Res. 2020 Jan 1;26(1):213-219
pubmed: 31527166
Gynecol Oncol. 2015 Dec;139(3):394-400
pubmed: 26348314
CA Cancer J Clin. 2020 Jan;70(1):7-30
pubmed: 31912902
Ann Oncol. 2021 Feb;32(2):240-249
pubmed: 33242536
Lancet Oncol. 2018 Dec;19(12):1680-1687
pubmed: 30413383
Quant Imaging Med Surg. 2020 Mar;10(3):743-753
pubmed: 32269933
Cancer. 2000 Oct 1;89(7):1532-40
pubmed: 11013368
Genes (Basel). 2019 Sep 05;10(9):
pubmed: 31491988
Clin Cancer Res. 2014 Jun 15;20(12):3280-8
pubmed: 24756370
Gynecol Oncol. 2017 Sep;146(3):491-497
pubmed: 28624153
Cancer Biol Ther. 2015;16(6):807-20
pubmed: 25894333
Gynecol Oncol. 2017 Dec;147(3):503-508
pubmed: 28964622
Cancer Med. 2023 Jul;12(13):14183-14195
pubmed: 37191035
Ann Surg Oncol. 2006 Dec;13(12):1702-10
pubmed: 17009163
Nat Genet. 2018 Sep;50(9):1262-1270
pubmed: 30104763
Int Immunopharmacol. 2020 Dec;89(Pt A):107126
pubmed: 33189611
N Engl J Med. 2011 Dec 29;365(26):2484-96
pubmed: 22204725
Radiology. 2015 Mar;274(3):742-51
pubmed: 25383459
Gynecol Oncol. 2022 Aug;166(2):334-343
pubmed: 35738917
Cancer. 2009 Mar 15;115(6):1234-44
pubmed: 19189349
Cancer. 2009 Jul 1;115(13):2891-902
pubmed: 19472394
CA Cancer J Clin. 2019 Jul;69(4):280-304
pubmed: 31099893
Clin Cancer Res. 2017 Aug 1;23(15):4077-4085
pubmed: 28280090
Cancer Cell. 2017 Aug 14;32(2):169-184.e7
pubmed: 28810143
Nat Med. 2015 Jul;21(7):751-9
pubmed: 26099045
Ann Oncol. 2003 Jan;14(1):74-7
pubmed: 12488296
Br J Cancer. 2017 May 9;116(10):1287-1293
pubmed: 28350786
J Gynecol Oncol. 2020 Jul;31(4):e57
pubmed: 32347021
Rev Obstet Gynecol. 2010 Summer;3(3):111-7
pubmed: 21364862
Ann Surg Oncol. 2012 Dec;19(13):4059-67
pubmed: 22766983
Lancet Oncol. 2017 Sep;18(9):1274-1284
pubmed: 28754483
Clin Cancer Res. 2008 Aug 15;14(16):5198-208
pubmed: 18698038
J Natl Cancer Inst. 2014 Sep 30;106(10):
pubmed: 25269487
Gynecol Oncol. 2007 Apr;105(1):211-7
pubmed: 17239941

Auteurs

Cecilie Fredvik Torkildsen (CF)

Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Obstetrics and Gynecology, Stavanger University Hospital, Stavanger, Norway.

Liv Cecilie Vestrheim Thomsen (LCV)

Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.

Ragnar Kvie Sande (RK)

Department of Obstetrics and Gynecology, Stavanger University Hospital, Stavanger, Norway.
Department of Clinical Science, University of Bergen, Bergen, Norway.

Camilla Krakstad (C)

Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.

Ingunn Stefansson (I)

Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Pathology, Haukeland University Hospital, Bergen, Norway.

Eva Karin Lamark (EK)

Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.

Stian Knappskog (S)

Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Oncology, Haukeland University Hospital, Bergen, Norway.

Line Bjørge (L)

Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.

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