Evidence map›Paper›PMID 42310533›Full record

ArticleClinical proteomics2026

Repurposing the liquid-based Pap test for the detection of ovarian cancer protein biomarkers.

Amy P N Skubitz, Kristin L M Boylan, Limeng Liu, Ashley Petersen, Yuqian Gao, Joshua R Hansen, Jesse B Trejo, Thomas L Fillmore, Yang Wang, Melissa A Geller and 5 more

Abstract read
In one paragraph

Article in Clinical proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Amy P N SkubitzDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, 55455, United States of America. skubi002@umn.edu.
Kristin L M BoylanDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, 55455, United States of America.
Limeng LiuDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.
Ashley PetersenDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States of America.
Yuqian GaoBiological Sciences Division, Pacific Northwest National Laboratories, Richland, WA, United States of America.
Joshua R HansenBiological Sciences Division, Pacific Northwest National Laboratories, Richland, WA, United States of America.
Jesse B TrejoBiological Sciences Division, Pacific Northwest National Laboratories, Richland, WA, United States of America.
Thomas L FillmoreEnvironmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States of America.
Yang WangAbbVie, Inc, North Chicago, IL, United States of America.
Melissa A GellerDepartment of Obstetrics, Gynecology & Women's Health, University of Minnesota, Minneapolis, MN, 55455, United States of America.
Peter A ArgentaDepartment of Obstetrics, Gynecology & Women's Health, University of Minnesota, Minneapolis, MN, 55455, United States of America.
Samantha HoffmanDepartment of Obstetrics, Gynecology & Women's Health, University of Minnesota, Minneapolis, MN, 55455, United States of America.
Karin RodlandDepartment of Cell, Developmental, and Cancer Biology, Oregon Health and Science University, Portland, OR, United States of America.
Tao LiuBiological Sciences Division, Pacific Northwest National Laboratories, Richland, WA, United States of America.
Paul D PiehowskiEnvironmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States of America.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Department of Defense Ovarian Cancer Research Program Pilot Award W81XWH-16-1-0070Department of Defense Ovarian Cancer Research Program Teal Award W81XWH-22-1-0486National Center for Advancing Translational Sciences of the National Institutes of Health Award UM1TR004405National Institutes of Health National Cancer Institute 5R01CA262153NIH P30 grant for the Biostatistics Core shared resource of the Masonic Cancer Center CA77598University of Minnesota's NIH Clinical and Translational Science Award (BioNet Tissue Procurement Facility) UM1TR004405
6 · The paper itself

Abstract

backgroundEarlier detection is strongly associated with increased survival for women with ovarian cancer. Unfortunately, current screening strategies, employing serial serum or ultrasound assessments, lack adequate sensitivity and specificity for use in the low-prevalence general population. In contrast, screening for cervical cancer by Pap tests has been routinely performed for over 50 years. Since ovarian cancer cells have been observed in Pap tests, ovarian cancer protein biomarkers may also be present; yet Pap samples have not been rigorously examined for diagnostic proteins. Assessment of cervical effluent, as can be collected in a Pap test, has the potential to differentiate ovarian cancer cases from healthy controls, and thereby demonstrate that intra-abdominal pathology may be detected using this commonly acquired specimen. We hypothesize that proteins shed by ovarian cancer cells can be detected in the SurePath™ liquid-based Pap test fixative using mass spectrometry (MS)-based proteomics, making it possible to distinguish women with ovarian cancer from healthy women.

methodsCandidate ovarian cancer biomarkers were successfully identified in liquid-based Pap test samples from 20 cases of high grade serous ovarian cancer, 10 benign ovarian conditions, and 10 healthy control samples, by performing Tandem Mass Tag™ isobaric labeling, 2D liquid chromatography-MS/MS, and bioinformatics integration. Selected reaction monitoring (SRM) MS-based targeted proteomics was then performed using a panel of candidate biomarkers to quantify their abundance in an expanded patient cohort of 90 liquid-based Pap tests.

resultsA multi-protein classifier was developed using the SRM-MS data comprised of 6 proteins and achieving an AUC of 0.880 (95% CI: 0.738-0.989); sensitivity at 90% specificity was 0.800.

conclusionThis pilot study provides evidence that the cervical effluent collected in SurePath™ fixative from Pap tests has the potential to be used as a biospecimen for the detection of ovarian cancer proteins. Our long-term goal is to develop a noninvasive screening test that can be incorporated into a routine Pap test or a self-administered home test, so that women can be screened simultaneously for cervical and ovarian cancer.

Indexed as

BiomarkerMass spectrometry-based proteomicsOvarian cancer detectionPap test

Identifiers

PMID42310533
PMCPMC13282856

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.