Evidence map›Paper›PMID 17608509›Full record

ArticleJournal of proteome research2007

Identification of differentially secreted biomarkers using LC-MS/MS in isogenic cell lines representing a progression of breast cancer.

Flaubert Mbeunkui, Brandon J Metge, Lalita A Shevde, Lewis K Pannell

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
5.3field-weighted citation impact, top 4% 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

41 citing papers in PubMed, 116 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Silence of α1-Antitrypsin Inhibits Migration and Proliferation of Triple Negative Breast Cancer Cells.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  10. Proteomics in pediatric cystic craniopharyngioma.Brain pathology (Zurich, Switzerland) · 2017
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Analysis of the differences of serum protein mass spectrometry in patients with triple negative breast cancer and non-triple negative breast cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014
    Article
  16. Article
  17. Methodologies to decipher the cell secretome.Biochimica et biophysica acta · 2013
    Review
  18. Article
  19. Lysyl oxidase, extracellular matrix remodeling and cancer metastasis.Cancer microenvironment : official journal of the International Cancer Microenvironment Society · 2012
    Article
  20. 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

4 authors at 2 institutions in 1 country.

Flaubert MbeunkuiMitchell Cancer Institute, University of South Alabama, Mobile, Alabama 36688, USA.
Brandon J Metge
Lalita A Shevde
Lewis K Pannell
University of South Alabama · USUSA Mitchell Cancer Institute · US

Funding

Automated Glyco-Analysis of Cancer Related ProteinsR21CA116070 · NCI · UNIVERSITY OF SOUTH ALABAMA · PI PANNELL, LEWIS KENNETH · 2005 to 2006
$289k
NCI NIH HHS 5R21CA116070NCI NIH HHS R21 CA116070
6 · The paper itself

Abstract

Proteins secreted (the secretome) from cancer cells are potentially useful as biomarkers of the disease. Using LC-MS/MS, the secreted proteomes from a series of isogenic breast cancer cell lines varying in aggressiveness were analyzed by mass spectrometry: nontumorigenic MCF10A, premalignant/tumorigenic MCF10AT, tumorigenic/locally invasive MCF10 DCIS.com, and tumorigenic/metastatic MCF 10CA cl. D. Proteomes were obtained from conditioned serum-free media, partially fractionated using a small reverse phase C2 column, and digested with trypsin for analysis by LC-MS/MS, using a method previously shown to give highly enriched secreted proteomes (Mbeunkui et al. J. Proteome Res. 2006, 5, 899-906). The search files produced from five analyses (three separate preparations) were combined for database searching (Mascot) which produced a list of over 250 proteins from each cell line. The aim was to discover highly secreted proteins which changed significantly in abundance corresponding with aggressiveness. The most apparent changes were observed for alpha-1-antichymotrypsin and galectin-3-binding protein which were highly secreted proteins from MCF10 DCIS.com and MCF10CA cl. D, yet undetected in the MCF10A and MCF10AT cell lines. Other proteins showing increasing abundance in the more aggressive cell lines included alpha-1-antitrypsin, cathepsin D, and lysyl oxidase. The S100 proteins, often associated with metastasis, showed variable changes in abundance. While the cytosolic proteins were low (e.g., actin and tubulin), there was significant secretion of proteins often associated with the cytoplasm. These proteins were all predicted as products of nonclassical secretion (SecretomeP, Center for Biological Sequence Analysis). The LC-MS/MS results were verified for five selected proteins by western blot analysis, and the relevance of other significant proteins is discussed. Comparisons with two other aggressive breast cancer cell lines are included. The protein with consistent association with aggressiveness in all lines, and in unrelated cancer cells, was the galectin-3-binding protein which has been associated with breast, prostate, and colon cancer earlier, supporting the approach and findings. This analysis of an isogenic series of cell lines suggests the potential usefulness of the secretome for identifying prospective markers for the early detection and aggressiveness/progression of cancer.

Indexed as

Biomarkers, TumorBreast NeoplasmsCell LineChromatography, LiquidDisease ProgressionFemaleHumansProteomeTandem Mass SpectrometryBiomarkers, TumorProteome

Identifiers

PMID17608509
PMCPMC2584611
OpenAlexW1983981115

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.