SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu and M. J. Thun, “Cancer Statistics,” CA Cancer Journal for Clinicians, Vol. 57, No. 1, 2007, pp. 43-66. doi:10.3322/canjclin.57.1.43

has been cited by the following article:

  • TITLE: Comparative Proteomics Analysis of Exhaled Breath Condensate in Lung Cancer Patients

    AUTHORS: Zujian Cheng, Craig R. Lewis, Paul S. Thomas, Mark J. Raftery

    KEYWORDS: Lung Cancer, Exhaled Breath Condensate, Mass Spectrometry, Proteomics

    JOURNAL NAME: Journal of Cancer Therapy, Vol.2 No.1, March 2, 2011

    ABSTRACT: The prognosis for patients with non-small cell lung cancer (NSCLC) remains poor in spite of better treatments. This relates mainly to the fact that the majority of patients present with advanced disease. There is a need to identify tools which can improve screening for lung cancer in the at risk patient population. The aim of this study was to compare the breath proteomic profile of NSCLC patients with healthy control subjects to explore the potential of new biomarkers of lung cancer. Comparative proteomic analysis of exhaled breath condensate (EBC) between 14 patients with NSCLC and 13 healthy control subjects were carried out using LTQ FT Ultra mass spectrometry and database searching to determine any unique proteins. In total, 29 unique proteins were identified using multiple protein identification algorithms. A comparison of lung cancer, smoker, and ex-smoker proteomes showed that 18 proteins were shared among the three groups. While one unique protein was found in smokers and lung cancer patients, four proteins were unique to ex-smokers. This data set provides a foundation for evaluation of these proteins from EBC as potential biomarkers for non-invasive lung cancer diagnosis.