Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
by
, , , , , ,
Ulf Gyllensten
1,2, 
Julia Hedlund-Lindberg
1,
Johanna Svensson
3,
Johanna Manninen
3,
Torbjörn Öst
3,
Jon Ramsell
3,
Matilda Åslin
3,
Emma Ivansson
1,
Marta Lomnytska
4,
Maria Lycke
5,
Tomas Axelsson
3,
Ulrika Liljedahl
3,
Jessica Nordlund
3
,
Per-Henrik Edqvist
1,
Tobias Sjöblom
1,
Mathias Uhlén
6,
Karin Stålberg
4,
Karin Sundfeldt
5,
Mikael Åberg
3 and
Stefan Enroth
1,7,* 1
Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
2
Stellenbosch Institute for Advanced Study (STIAS), Marais Rd., Mostertsdrift, Stellenbosch 7600, South Africa
3
Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden
4
Department of Women’s and Children’s Health, Uppsala University, SE-75185 Uppsala, Sweden
5
Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-41685 Gothenburg, Sweden
6
Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17165 Stockholm, Sweden
7
Swedish Collegium for Advanced Study, Thunbergsvägen 2, SE-752 38 Uppsala, Sweden
*
Author to whom correspondence should be addressed.
Cancers 2022, 14(7), 1757; https://doi.org/10.3390/cancers14071757
Submission received: 4 March 2022
/
Revised: 22 March 2022
/
Accepted: 25 March 2022
/
Published: 30 March 2022
(This article belongs to the Special Issue Ovarian Cancer Biomarkers, Diagnostic and Therapeutic Technologies)
Simple Summary
Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4–7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort.
Abstract
Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
Keywords:
ovarian cancer; protein biomarkers; early detection
