Evidence map›Paper›PMID 19349484›Full record

ReviewProceedings of the American Thoracic Society2009

Mass spectrometry-based proteomic profiling of lung cancer.

Sebahat Ocak, Pierre Chaurand, Pierre P Massion

Abstract readReview
In one paragraph

Review in Proceedings of the American Thoracic Society, 2009. 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. Article
  3. Review
  4. Article
  5. The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    Review
  6. Article
  7. Review
  8. Discovery of new membrane-associated proteins overexpressed in small-cell lung cancer.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2014
    Article
  9. Significance of combined detection of LunX mRNA and tumor markers in diagnosis of lung carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2014
    Article
  10. Review
  11. Proteomic biomarkers in lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2013
    Review
  12. The state of molecular biomarkers for the early detection of lung cancer.Cancer prevention research (Philadelphia, Pa.) · 2012
    Review
  13. Article
  14. Article
  15. Advances in proteomic strategies toward the early detection of lung cancer.Proceedings of the American Thoracic Society · 2011
    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

3 authors.

Sebahat OcakDivision of Allergy, Pulmonary and Critical Care Medicine, Thoracic Oncology Center Vanderbilt-Ingram Cancer Center, Nashville TN 37232-6838, USA.
Pierre Chaurand
Pierre P Massion

Funding

TARGETING NOTCH 3 IN LUNG CANCERP50CA090949 · NCI · VANDERBILT UNIVERSITY · PI MASSION, PIERRE P. · 2001 to 2011
$24.1M
Spatial Analysis of Molecules in Tissue using MALDI-MSR01GM058008 · NIGMS · VANDERBILT UNIVERSITY · PI CAPRIOLI, RICHARD M · 1998 to 2015
$5.8M
Molecular Approaches to Early Detection of Lung CancerR01CA102353 · NCI · VANDERBILT UNIVERSITY · PI MASSION, PIERRE P. · 2005 to 2014
$2.4M
NCI NIH HHS CA102353NCI NIH HHS CA90949NIGMS NIH HHS 2R01 GM58008-09NIGMS NIH HHS R01 GM058008
6 · The paper itself

Abstract

In an effort to further our understanding of lung cancer biology and to identify new candidate biomarkers to be used in the management of lung cancer, we need to probe these tissues and biological fluids with tools that address the biology of lung cancer directly at the protein level. Proteins are responsible of the function and phenotype of cells. Cancer cells express proteins that distinguish them from normal cells. Proteomics is defined as the study of the proteome, the complete set of proteins produced by a species, using the technologies of large-scale protein separation and identification. As a result, new technologies are being developed to allow the rapid and systematic analysis of thousands of proteins. The analytical advantages of mass spectrometry (MS), including sensitivity and high-throughput, promise to make it a mainstay of novel biomarker discovery to differentiate cancer from normal cells and to predict individuals likely to develop or recur with lung cancer. In this review, we summarize the progress made in clinical proteomics as it applies to the management of lung cancer. We will focus our discussion on how MS approaches may advance the areas of early detection, response to therapy, and prognostic evaluation.

Indexed as

ProteomicsBiomarkersHumansLung NeoplasmsMass SpectrometryBiomarkers

Identifiers

PMID19349484
PMCPMC2674226

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.