Evidence map›Paper›PMID 34681879›Full record

ArticleInternational journal of molecular sciences2021

Identification of Tumor Antigens in Ovarian Cancers Using Local and Circulating Tumor-Specific Antibodies.

Jessica Da Gama Duarte, Luke T Quigley, Anna Rachel Young, Masaru Hayashi, Mariko Miyazawa, Alex Lopata, Nunzio Mancuso, Mikio Mikami, Andreas Behren, Els Meeusen

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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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

10 authors at 5 institutions in 2 countries.

Jessica Da Gama DuarteOlivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084, Australia.ORCID 0000-0003-4289-5204
Luke T QuigleyOlivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084, Australia.ORCID 0000-0003-4975-7779
Anna Rachel YoungLa Trobe Institute for Molecular Science, La Trobe University, Bundoora, VIC 3086, Australia.
Masaru HayashiSchool of Medicine, Tokai University, Isehara-City 259-1193, Japan.ORCID 0000-0001-6187-9563
Mariko MiyazawaSchool of Medicine, Tokai University, Isehara-City 259-1193, Japan.
Alex LopataCancerProbe Pty Ltd., Prahran, VIC 3181, Australia.
Nunzio MancusoCancerProbe Pty Ltd., Prahran, VIC 3181, Australia.
Mikio MikamiSchool of Medicine, Tokai University, Isehara-City 259-1193, Japan.ORCID 0000-0002-7496-3518
Andreas BehrenOlivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084, Australia.ORCID 0000-0001-5329-280X
Els MeeusenCancerProbe Pty Ltd., Prahran, VIC 3181, Australia.ORCID 0000-0003-1239-6287
La Trobe University · AUTokai University · JPCancer Australia · AUFederation University · AUThe University of Melbourne · AU

Funding

Cure Cancer Australia Foundation 1187815Global Connections Fund NAVictorian Cancer Agency NAVictorian Government Operational Infrastructure Support Program NA
6 · The paper itself

Abstract

Ovarian cancers include several disease subtypes and patients often present with advanced metastatic disease and a poor prognosis. New biomarkers for early diagnosis and targeted therapy are, therefore, urgently required. This study uses antibodies produced locally in tumor-draining lymph nodes (ASC probes) of individual ovarian cancer patients to screen two separate protein microarray platforms and identify cognate tumor antigens. The resulting antigen profiles were unique for each individual cancer patient and were used to generate a 50-antigen custom microarray. Serum from a separate cohort of ovarian cancer patients encompassing four disease subtypes was screened on the custom array and we identified 28.8% of all ovarian cancers, with a higher sensitivity for mucinous (50.0%) and serous (40.0%) subtypes. Combining local and circulating antibodies with high-density protein microarrays can identify novel, patient-specific tumor-associated antigens that may have diagnostic, prognostic or therapeutic uses in ovarian cancer.

Indexed as

Adenocarcinoma, Clear CellAdenocarcinoma, MucinousAdultAgedAged, 80 and overAntigens, NeoplasmAutoantibodiesBiomarkers, TumorCase-Control StudiesCohort StudiesCystadenocarcinoma, SerousFemaleFollow-Up StudiesGene Expression Regulation, NeoplasticHumansMiddle AgedAntigens, NeoplasmAutoantibodiesBiomarkers, Tumorantibody-secreting B cellsbiomarkerscirculating antibodiesdiagnosisovarian cancerprotein microarrays

Identifiers

PMID34681879
PMCPMC8538754
OpenAlexW3205952197

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.