Evidence map›Paper›PMID 28427776›Full record

ArticleGynecologic oncology2017

Autoantibody biomarkers for the detection of serous ovarian cancer.

Benjamin A Katchman, Diego Chowell, Garrick Wallstrom, Allison F Vitonis, Joshua LaBaer, Daniel W Cramer, Karen S Anderson

Abstract read
In one paragraph

Article in Gynecologic oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
10.0field-weighted citation impact, top 2% 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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.

  1. Pooled it
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  9. Molecular Biomarkers for the Early Detection of Ovarian Cancer.International journal of molecular sciences · 2022
    Review
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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

7 authors at 2 institutions in 1 country.

Benjamin A KatchmanVirginia G. Piper Center for Personal Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Diego ChowellVirginia G. Piper Center for Personal Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Garrick WallstromVirginia G. Piper Center for Personal Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Allison F VitonisDepartment of Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, MA, USA.
Joshua LaBaerVirginia G. Piper Center for Personal Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Daniel W CramerDepartment of Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, MA, USA.
Karen S AndersonVirginia G. Piper Center for Personal Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA. Electronic address: Karen.Anderson.1@asu.edu.
Arizona State University · USBrigham and Women's Hospital · US

Funding

Biomarker Detection Using NAPPA Tumor Antigen ArraysU01CA117374 · NCI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ANDERSON, KAREN SUE, LABAER, JOSHUA · 2005 to 2015
$6.2M
Novel approaches to study immune responses to post translational modifications for cancer detectionU01CA214201 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI ANDERSON, KAREN SUE, LABAER, JOSHUA · 2016 to 2021
$2.6M
NCI NIH HHS U01 CA117374NCI NIH HHS U01 CA214201
6 · The paper itself

Abstract

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer.

methodsTo detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n=30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n=30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n=63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed.

resultsWe identified 11-TAAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity.

conclusionThese are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts.

Indexed as

Antibodies, NeoplasmAntigens, NeoplasmAutoantibodiesBiomarkers, TumorCase-Control StudiesCystadenocarcinoma, SerousFemaleHumansMiddle AgedOvarian NeoplasmsProtein Array AnalysisAntibodies, NeoplasmAntigens, NeoplasmAutoantibodiesBiomarkers, TumorAutoantibodyBiomarkerDiagnosticsOvarian cancerProteomics

Identifiers

PMID28427776
PMCPMC5519143
OpenAlexW2605684940

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.