Evidence map›Paper›PMID 24262153›Full record

ArticleJournal of proteomics2014

Using a cell line breast cancer progression system to identify biomarker candidates.

Ten-Yang Yen, Nicole Haste, Leslie C Timpe, Christina Litsakos-Cheung, Roger Yen, Bruce A Macher

Abstract read
In one paragraph

Article in Journal of proteomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

7 citing papers in PubMed, 22 citations in OpenAlex.

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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 1 institution in 1 country.

Ten-Yang YenDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States.
Nicole HasteDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States.
Leslie C TimpeDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States.
Christina Litsakos-CheungDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States.
Roger YenDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States.
Bruce A MacherDepartment of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, United States. Electronic address: macher@sfsu.edu.
San Francisco State University · US

Funding

Student EnrichmentP20MD000544 · NIMHD · SAN FRANCISCO STATE UNIVERSITY · PI BAIRD, TEASTER T · 2003 to 2012
$9.4M
Glycoprotein Signatures as Biomarkers for Breast CancerR15CA164929 · NCI · SAN FRANCISCO STATE UNIVERSITY · PI MACHER, BRUCE A., TIMPE, LESLIE CHARLES · 2012 to 2012
$462k
NCI NIH HHS R15 CA164929NCI NIH HHS R15CA164929NIMHD NIH HHS P20 MD000544
6 · The paper itself

Abstract

Secreted and plasma membrane glycoproteins are considered excellent candidates for disease biomarkers. Herein we describe the identification of secreted and plasma membrane glycoproteins that are differentially expressed among a family of three breast cancer cell lines that models the progression of breast cancer. Using two-dimensional liquid chromatography-tandem mass spectrometry we identified more than 40 glycoproteins that were differentially expressed in either the premalignant (MCF10AT) or the fully malignant (MCF10CA1a) cell lines of this model system. Comparative analysis revealed that the differentially expressed breast cancer progression-associated glycoproteins were among the most highly expressed in the malignant (MCF10CA1a) breast cancer cell line; a subset of these was detected only in the malignant line; and others were detected in the malignant line at levels 25 to 50 times greater than in the benign (MCF10A) line. Using the results from this model cell system as a guide, we then carried out glycoproteomic analyses of normal and cancerous breast tissue lysates. Eleven of the glycoproteins differentially expressed in the breast cell lines were identified in the tissue lysates. Among these glycoproteins, collagen alpha-1 (XII) chain was expressed at dramatically higher (~10-fold) levels in breast cancer than in normal tissue. BIOLOGICAL SIGNIFICANCE: Identifying glycoproteins differentially expressed during cancer progression results in information on the biological processes and key pathways associated with cancer. In addition, new hypotheses and potential biomarkers result from these glycoproteomic studies. Our glycoproteomic analysis of this model of breast cancer provides a roadmap for future experimental interventions to further tease apart critical components of tumor progression.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorBreast NeoplasmsCell Line, TumorCollagen Type XIIDisease ProgressionFemaleHumansNeoplasm ProteinsBiomarkers, TumorCOL12A1 protein, humanCollagen Type XIINeoplasm ProteinsBreast cancerDifferential expressionGlycoproteomicsLabel-free quantitationNon-malignant vs. malignantSpectral counts

Identifiers

PMID24262153
PMCPMC3920745
OpenAlexW2044524126

What OpenQuestion holds

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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.