Evidence map›Paper›PMID 16117833›Full record

ArticleBMC cancer2005

Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis.

Wei-Min Gao, Rork Kuick, Randal P Orchekowski, David E Misek, Ji Qiu, Alissa K Greenberg, William N Rom, Dean E Brenner, Gilbert S Omenn, Brian B Haab and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
8.1field-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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 173 citations in OpenAlex.

  1. Pooled it
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  15. Article
  16. Purification, identification and profiling of serum amyloid A proteins from sera of advanced-stage cancer patients.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2012
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  17. 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

11 authors at 5 institutions in 1 country.

Wei-Min GaoDepartment of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA. gaow@upmc.edu
Rork Kuick
Randal P Orchekowski
David E Misek
Ji Qiu
Alissa K Greenberg
William N Rom
Dean E Brenner
Gilbert S Omenn
Brian B Haab
Samir M Hanash
University of Michigan–Ann Arbor · USVan Andel Institute · USMichigan Medicine · USNew York University · USUniversity of Pittsburgh · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer serum protein profiling by mass spectrometry has uncovered mass profiles that are potentially diagnostic for several common types of cancer. However, direct mass spectrometric profiling has a limited dynamic range and difficulties in providing the identification of the distinctive proteins. We hypothesized that distinctive profiles may result from the differential expression of relatively abundant serum proteins associated with the host response.

methodsEighty-four antibodies, targeting a wide range of serum proteins, were spotted onto nitrocellulose-coated microscope slides. The abundances of the corresponding proteins were measured in 80 serum samples, from 24 newly diagnosed subjects with lung cancer, 24 healthy controls, and 32 subjects with chronic obstructive pulmonary disease (COPD). Two-color rolling-circle amplification was used to measure protein abundance.

resultsSeven of the 84 antibodies gave a significant difference (p < 0.01) for the lung cancer patients as compared to healthy controls, as well as compared to COPD patients. Proteins that exhibited higher abundances in the lung cancer samples relative to the control samples included C-reactive protein (CRP; a 13.3 fold increase), serum amyloid A (SAA; a 2.0 fold increase), mucin 1 and alpha-1-antitrypsin (1.4 fold increases). The increased expression levels of CRP and SAA were validated by Western blot analysis. Leave-one-out cross-validation was used to construct Diagonal Linear Discriminant Analysis (DLDA) classifiers. At a cutoff where all 56 of the non-tumor samples were correctly classified, 15/24 lung tumor patient sera were correctly classified.

conclusionOur results suggest that a distinctive serum protein profile involving abundant proteins may be observed in lung cancer patients relative to healthy subjects or patients with chronic disease and may have utility as part of strategies for detecting lung cancer.

Indexed as

Gene Expression Regulation, Neoplasticalpha 1-AntitrypsinAntibodiesAntibodies, NeoplasmBlood ProteinsBlotting, WesternCase-Control StudiesCollodionC-Reactive ProteinElectrophoresis, Polyacrylamide GelHumansLung NeoplasmsMass SpectrometryMicroarray AnalysisMucinsProtein Array Analysisalpha 1-AntitrypsinAntibodiesAntibodies, NeoplasmBlood ProteinsCollodionC-Reactive ProteinMucinsSerum Amyloid A Protein

Identifiers

PMID16117833
PMCPMC1198221
OpenAlexW1505550212

What OpenQuestion holds

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LicenceCC BY
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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.