Evidence map›Paper›PMID 18266982›Full record

ReviewJournal of cellular and molecular medicine

Applications of SELDI-MS technology in oncology.

L C Whelan, K A R Power, D T McDowell, J Kennedy, W M Gallagher

Abstract readReview
In one paragraph

Review in Journal of cellular and molecular medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. The application of SELDI-TOF-MS in clinical diagnosis of cancers.Journal of biomedicine & biotechnology · 2011
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Challenges for biomarker discovery in body fluids using SELDI-TOF-MS.Journal of biomedicine & biotechnology · 2010
    Review
  16. Article
  17. 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

5 authors.

L C WhelanUCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Ireland.
K A R Power
D T McDowell
J Kennedy
W M Gallagher

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considerable interest, speculation and controversy have been generated utilising surface-enhanced laser desorption/ionization in conjunction with mass spectrometry (SELDI-MS) for the diagnosis, prognosis and therapeutic monitoring of cancer and offers an attractive approach to cancer biomarker discovery from tissues and biological fluids. This technology utilises a combination of mass spectrometry and chromatography to facilitate protein profiling of complex biological mixtures. Compared to some other more traditional proteomic platforms, such as 2D polyacrylamide gel electrophoresis, it has a high-throughput capability and can resolve low-mass proteins. However, a considerable number of challenging issues related to the design of studies, including reproducibility, sensitivity, specificity, variation in sample collection, processing and storage, have been reported as problematic with this technology; albeit some of these concerns could perhaps also be lauded against other proteomic approaches that have attempted to address complex protein mixtures, such as plasma. Applications, successes and limitations of SELDI-MS in both clinical and basic science arenas will be reviewed in this article.

Indexed as

Medical OncologyAnimalsDisease ProgressionDrug Resistance, NeoplasmHumansNeoplasmsNeoplasm StagingSpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Identifiers

PMID18266982
PMCPMC3918069

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.