Evidence map›Paper›PMID 24660652›Full record

ArticleOmics : a journal of integrative biology2014

Towards an animal model of ovarian cancer: cataloging chicken blood proteins using combinatorial peptide ligand libraries coupled with shotgun proteomic analysis for translational research.

Yingying Ma, Zeyu Sun, Ricardo de Matos, Jing Zhang, Kunle Odunsi, Biaoyang Lin

Open access · greenAbstract read
In one paragraph

Article in Omics : a journal of integrative biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
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

6 authors at 5 institutions in 3 countries.

Yingying Ma1 System Biology Division, Zhejiang-California International Nanosystem Institute (ZCNI), Zhejiang University , Hangzhou, China .
Zeyu Sun
Ricardo de Matos
Jing Zhang
Kunle Odunsi
Biaoyang Lin
Zhejiang University · CNCenter for Innovation · USCornell University · USRoswell Park Comprehensive Cancer Center · USSwedish Medical Center · US

Funding

Ovarian Cancer Detection Using H-NMR_Based MetabonomicsR21CA106949 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI ODUNSI, KUNLE O · 2005 to 2006
$364k
NCI NIH HHS R21CA106949-01A1
6 · The paper itself

Abstract

Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune- and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here the most comprehensive survey of the chicken blood proteome to date.

Indexed as

AnimalsAvian ProteinsBiomarkers, TumorBlood ProteinsCarcinoma, Ovarian EpithelialChickensDisease Models, AnimalFemaleHumansNeoplasms, Glandular and EpithelialOvarian NeoplasmsPeptide LibraryPoultry DiseasesProteomicsTranslational Research, BiomedicalAvian ProteinsBiomarkers, TumorBlood ProteinsPeptide Library

Identifiers

PMID24660652
PMCPMC4012627
OpenAlexW1557120091

What OpenQuestion holds

Textmetadata
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.