Evidence map›Paper›PMID 22084687›Full record

ArticleInternational journal of proteomics2011

Clinical utility of serum autoantibodies detected by protein microarray in melanoma.

Michael S Sabel, Yashu Liu, Kent A Griffith, Jintang He, Xaiolei Xie, David M Lubman

Open access · hybridAbstract read
In one paragraph

Article in International journal of proteomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Michael S SabelDepartment of Surgery, University of Michigan Health Systems Biostatistics Core, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI 48109, USA.
Yashu Liu
Kent A Griffith
Jintang He
Xaiolei Xie
David M Lubman
University of Michigan–Ann Arbor · USMichigan Medicine · US

Funding

Protein Microarrays for the Humoral Response in CancerR01CA106402 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUBMAN, DAVID M. · 2004 to 2008
$1.4M
A Lectin Glycoarray Approach for Markers of Pancreatic CancerR21CA124441 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUBMAN, DAVID M. · 2007 to 2008
$334k
NCI NIH HHS R01 CA106402NCI NIH HHS R21 CA124441
6 · The paper itself

Abstract

Better prognostic and predictive markers in melanoma are needed to select patients for therapy. We utilized a dual-lectin affinity chromatography and a natural protein microarray-based analysis to select a subproteome of target glycoproteins to profile serum antibodies against melanoma associated antigens that may predict nodal positivity. We identified 5 melanoma-associated antigens using this microarray coupled to mass spectrometry; GRP75, GRP94, ASAH1, CTSD and LDHB. We evaluated their predictive value for nodal status adjusting for age, gender, Breslow thickness, mitotic rate and ulceration using standard logistic regression. After adjustment, ASAH1, CTSD and LDHB were significantly negatively associated with nodal status (P = 0.0008) and GRP94 was significantly positively associated (P = 0.014). Our best multivariate model for nodal positivity included Breslow thickness, presence of serum anti-ASAH1, anti-LDHB or anti-CTSD, and presence of serum anti-GRP94, with an area under the ROC curve of 0.869. If validated, these results show promise for selecting clinically node negative patients for SLN biopsy. In addition, there is strong potential for glycoprotein microarray to screen serum autoantibodies that may identify patients at high risk of distant metastases or those likely or unlikely to respond to treatment, and these proteins may serve as targets for intervention.

Identifiers

PMID22084687
PMCPMC3199061
OpenAlexW2103859238

What OpenQuestion holds

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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.