Evidence map›Paper›PMID 23606351›Full record

ReviewClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2013

Proteomic biomarkers in lung cancer.

M D Pastor, A Nogal, S Molina-Pinelo, A Carnero, L Paz-Ares

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. The value of proteomics in lung cancer.Annals of translational medicine · 2015
    Article
  10. Article
  11. Article
  12. Article
  13. Integrating omics technologies to study pulmonary physiology and pathology at the systems level.Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology · 2014
    Review
  14. 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.

M D PastorServicio de Oncología Médica, Instituto de Biomedicina de Sevilla (IBIS), University Hospital Virgen del Rocío, Av. Manuel Siurot s/n, 41013, Seville, Spain.
A Nogal
S Molina-Pinelo
A Carnero
L Paz-Ares

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The correct understanding of tumour development relies on the comprehensive study of proteins. They are the main orchestrators of vital processes, such as signalling pathways, which drive the carcinogenic process. Proteomic technologies can be applied to cancer research to detect differential protein expression and to assess different responses to treatment. Lung cancer is the number one cause of cancer-related death in the world. Mostly diagnosed at late stages of the disease, lung cancer has one of the lowest 5-year survival rates at 15 %. The use of different proteomic techniques such as two-dimensional gel electrophoresis (2D-PAGE), isotope labelling (ICAT, SILAC, iTRAQ) and mass spectrometry may yield new knowledge on the underlying biology of lung cancer and also allow the development of new early detection tests and the identification of changes in the cancer protein network that are associated with prognosis and drug resistance.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorElectrophoresis, Gel, Two-DimensionalHumansIsotope LabelingLung NeoplasmsMass SpectrometryProteomeProteomicsBiomarkers, TumorProteome

Identifiers

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.