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. 2019 Apr;18(4):735-743.
doi: 10.1074/mcp.RA118.001208. Epub 2019 Jan 28.

Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay

Malin Berggrund  1 , Stefan Enroth  1 , Martin Lundberg  2 , Erika Assarsson  2 , Karin Stålberg  3 , David Lindquist  4 , Göran Hallmans  5 , Kjell Grankvist  6 , Matts Olovsson  3 , Ulf Gyllensten  7
Affiliations

Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay

Malin Berggrund et al. Mol Cell Proteomics. 2019 Apr.

Abstract

Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.

Keywords: Blood*; Cancer biomarker(s); Cervical cancer; Clinical proteomics; Human Papillomavirus; Personalized medicine; Screening.

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Conflict of interest statement

The study was co-funded by OLINK Proteomics AB

Figures

None
Graphical abstract
Fig. 1.
Fig. 1.
Replication of univariate analyses. A, Distribution of days to diagnosis for samples in the replication cohort. The gray dotted vertical lines indicate the cut-offs used in the binned analysis. B, Distribution of normalized protein abundance levels in the cohorts used for PTX3. The top and the bottom of the box represents the 25th and 75th percentile and the band inside the box the median value. The whiskers are calculated as 1.5× the interquartile range. Cohorts ordered as in (A). The dotted gray line indicates the mean of the groups used to determine normalization coefficients, e.g. the control samples from the discovery cohort and the samples from the replication cohort collected at least 3 years before diagnosis (See Methods for details).
Fig. 2.
Fig. 2.
Multivariate analyses. A, Aggregated ROC-curve for the test-samples in the cross-validation training of the model using the full discovery data with 80 proteins. AUC given with 95% confidence interval. B, Performance of the trained model in the withheld discovery validation set. The red-cross represent the performance at the cut-off determined using the training data. C, Distribution of model-output (log(p)) when applied to the replication cohort in bins. The black line represents median value in each bin. D, Median (dot) and median absolute deviation (lines) of probabilities (model output) in the same bins as in (C). The dotted vertical line indicates the median in the bin with samples collected 6166 to 1328 days before diagnosis. E, AUCs for discriminations of the samples collected 6166 to 1328 days before diagnosis and the subsequent bins. Horizontal black lines indicate 95% confidence interval. The dotted vertical line indicates and AUC = 0.5. F, ROC-curves in the same bins as in (E). The red crosses indicate performance at the cut-off determined in the training proportion of the discovery data. The width and breadth of the cross represent 95% confidence interval of the sensitivity and specificity. G–I, Same as (D–F) but for the 11-protein signature. J–L, As (G–I) but for the 11-protein signature retrained as in (A–B) but with samples used for normalization in the replication cohort as controls and the samples taken at diagnosis in the replication cohort as cases.
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