Evidence map›Paper›PMID 23528302›Full record

ArticleClinical biochemistry2013

Folate-receptor 1 (FOLR1) protein is elevated in the serum of ovarian cancer patients.

F Leung, A Dimitromanolakis, H Kobayashi, E P Diamandis, V Kulasingam

Open access · greenAbstract read
In one paragraph

Article in Clinical biochemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
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

40 citing papers in PubMed, 123 citations in OpenAlex.

  1. Article
  2. Folate receptor alpha in platinum-resistant ovarian cancer: prevalence in a multicenter Polish cohort and review of the evidence.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  3. Review
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  7. Article
  8. Folate Receptor Alpha-A Secret Weapon in Ovarian Cancer Treatment?International journal of molecular sciences · 2024
    Review
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  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Molecular Biomarkers for the Early Detection of Ovarian Cancer.International journal of molecular sciences · 2022
    Review
  19. Article
  20. Nucleic acid vaccination strategies for ovarian cancer.Frontiers in bioengineering and biotechnology · 2022
    Review
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

5 authors at 3 institutions in 2 countries.

F LeungDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada; Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.
A Dimitromanolakis
H Kobayashi
E P Diamandis
V Kulasingam
University of Toronto · CAMount Sinai Hospital · CANara Medical University · JP

Funding

An integrated systems biology approach for ovarian cancer biomarker discoveryU01CA152755 · NCI · SINAI HEALTH SYSTEM · PI DIAMANDIS, ELEFTHERIOS P · 2010 to 2015
$1.4M
NCI NIH HHS 5U01CA152755NCI NIH HHS U01 CA152755
6 · The paper itself

Abstract

objectivesOvarian cancer is the most lethal gynecological malignancy in North America. Although survival rates are high when the disease is diagnosed at an early stage, this decreases exponentially in late-stage diagnoses. As such, there is a need for novel early detection biomarkers. Through an integrated approach to ovarian cancer biomarker discovery that combines proteomics with transcriptomics and bioinformatics, our laboratory has identified folate-receptor 1 (FOLR1) and Dickkopf-related protein 3 (Dkk-3) as putative biomarkers. The objective of this study was to measure the levels of FOLR1 and Dkk-3 in the serum of patients with ovarian cancer, benign gynecological conditions and healthy women. DESIGN AND

methodsFOLR1 and Dkk-3 were analyzed in serum of 100 ovarian cancer patients, 100 patients with benign gynecological conditions, and 100 healthy women using enzyme-linked immunosorbent assays (ELISAs). All specimens were analyzed in triplicate.

resultsFOLR1 was significantly elevated in the serum of ovarian cancer patients compared to serum of both healthy controls (P<0.0001) and patients with benign gynecological conditions (P<0.0001). Furthermore, FOLR1 was strongly correlated with CA125 as both were elevated in the serous histotype and in late-stage disease. FOLR1 did not outperform CA125 in receiver operating characteristic curve analysis and there was no significant complementarity between the two markers. Dkk-3 was not significantly different between the three serum cohorts and was not correlated with CA125.

conclusionsFOLR1 is a new biomarker for ovarian cancer which correlates closely with CA125. The role of FOLR1 in the pathogenesis of ovarian cancer warrants further investigation.

Indexed as

Adaptor Proteins, Signal TransducingAdultBiomarkers, TumorCA-125 AntigenCarcinomaCase-Control StudiesChemokinesFemaleFolate Receptor 1Gene ExpressionHumansIntercellular Signaling Peptides and ProteinsMembrane ProteinsMiddle AgedNeoplasmsNeoplasm StagingAdaptor Proteins, Signal TransducingBiomarkers, TumorCA-125 AntigenChemokinesDKK3 protein, humanFolate Receptor 1FOLR1 protein, humanIntercellular Signaling Peptides and ProteinsMembrane ProteinsMUC16 protein, humanarea under the curveAUCBiomarkerCA125carbohydrate antigen 125CIconfidence intervalDiagnosticDickkopf-related protein 3Dkk-3ELISAenzyme-linked immunosorbent assayFDAfolate-receptor 1FOLR1Food and Drug AdministrationNID2nidogen-2odds ratioOROvarian cancerreceiver operating characteristicRisk of Malignancy AlgorithmROCROMA

Identifiers

PMID23528302
PMCPMC4130215
OpenAlexW2066588182

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.