Biomarker-based early detection of epithelial ovarian cancer based on a five-protein signature in patient's plasma - a prospective trial.


Journal

BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800

Informations de publication

Date de publication:
16 Sep 2021
Historique:
received: 07 03 2021
accepted: 13 08 2021
entrez: 17 9 2021
pubmed: 18 9 2021
medline: 16 10 2021
Statut: epublish

Résumé

Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors. In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses. Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor. The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort. Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.

Sections du résumé

BACKGROUND BACKGROUND
Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors.
METHODS METHODS
In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses.
RESULTS RESULTS
Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor.
CONCLUSIONS CONCLUSIONS
The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort.
TRIAL REGISTRATION BACKGROUND
Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.

Identifiants

pubmed: 34530759
doi: 10.1186/s12885-021-08682-y
pii: 10.1186/s12885-021-08682-y
pmc: PMC8447799
doi:

Substances chimiques

Biomarkers, Tumor 0
CA-125 Antigen 0
Leptin 0
WAP Four-Disulfide Core Domain Protein 2 0
WFDC2 protein, human 0
Osteopontin 106441-73-0
Prolactin 9002-62-4

Banques de données

ClinicalTrials.gov
['NCT01763125']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1037

Informations de copyright

© 2021. The Author(s).

Références

Lancet. 2016 Mar 5;387(10022):945-956
pubmed: 26707054
Gynecol Oncol. 2010 Jun;117(3):440-5
pubmed: 20334903
J Obstet Gynaecol Res. 2013 Nov;39(11):1518-25
pubmed: 23875677
Gynecol Oncol. 2005 Nov;99(2):267-77
pubmed: 16061277
Int J Gynecol Cancer. 2008 May-Jun;18(3):414-20
pubmed: 17645503
J Exp Med. 1999 Nov 15;190(10):1375-82
pubmed: 10562313
JAMA. 2002 Apr 3;287(13):1671-9
pubmed: 11926891
Clin Chem. 1998 Jul;44(7):1379-80
pubmed: 9665412
CA Cancer J Clin. 2017 Mar;67(2):100-121
pubmed: 28170086
Fam Cancer. 2016 Apr;15(2):221-30
pubmed: 26458935
Am J Obstet Gynecol. 2020 Jan;222(1):56.e1-56.e17
pubmed: 31351062
Clin Cancer Res. 2004 May 15;10(10):3474-8
pubmed: 15161704
Proc Natl Acad Sci U S A. 2005 May 24;102(21):7677-82
pubmed: 15890779
Cancer Res. 2004 Aug 15;64(16):5882-90
pubmed: 15313933
Lancet Oncol. 2009 Apr;10(4):327-40
pubmed: 19282241
J Stat Softw. 2010;33(1):1-22
pubmed: 20808728
Am J Obstet Gynecol. 2012 Apr;206(4):351.e1-8
pubmed: 22284961
Cancer Prev Res (Phila). 2011 Mar;4(3):365-74
pubmed: 21372036
Int J Gynecol Cancer. 2014 Sep;24(7):1222-31
pubmed: 25078339
Clin Chem. 1996 Nov;42(11):1881-2
pubmed: 8906098
Am J Obstet Gynecol. 2002 Aug;187(2):385-92
pubmed: 12193930
Facts Views Vis Obgyn. 2018 Mar;10(1):5-18
pubmed: 30510663
Acta Inform Med. 2015 Apr;23(2):86-9
pubmed: 26005273
Contemp Oncol (Pozn). 2014;18(5):318-22
pubmed: 25477753
Ultrasound Obstet Gynecol. 2013 Jan;41(1):9-20
pubmed: 23065859
Am J Obstet Gynecol. 2008 Sep;199(3):215-23
pubmed: 18468571
Clin Cancer Res. 2008 Feb 15;14(4):1065-72
pubmed: 18258665
Cancer Res. 2009 Jun 15;69(12):5226-33
pubmed: 19491263
PLoS One. 2013 Jun 27;8(6):e67349
pubmed: 23826274
BMC Cancer. 2013 Apr 03;13:178
pubmed: 23551967
Am J Obstet Gynecol. 2007 Apr;196(4):348.e1-5
pubmed: 17403417
Tumour Biol. 2011 Dec;32(6):1087-95
pubmed: 21863264
Int J Gynaecol Obstet. 1999 Jan;64(1):5-10
pubmed: 10190664
Am J Obstet Gynecol. 2016 Apr;214(4):424-437
pubmed: 26800772
Am J Epidemiol. 2014 Aug 1;180(3):318-24
pubmed: 24966219
Gynecol Oncol. 2009 Jan;112(1):40-6
pubmed: 18851871

Auteurs

A Hasenburg (A)

Department of Obstetrics and Gynecology, University Medical Center, Mainz, Germany.

D Eichkorn (D)

Department of Obstetrics and Gynecology, Schwarzwald-Baar Clinics, Villingen-Schwenningen, Germany.

F Vosshagen (F)

Department of Anesthesiology, Ortenau Clinics, Lahr-Ettenheim, Germany.

E Obermayr (E)

Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria.

A Geroldinger (A)

Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.

R Zeillinger (R)

Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria.

M Bossart (M)

Department of Obstetrics and Gynecology, University Medical Center, Freiburg, Germany. Michaela.Bossart@uniklinik-freiburg.de.

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Classifications MeSH