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Protein Signature of Lung Cancer Tissues

Overview of attention for article published in PLOS ONE, April 2012
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Title
Protein Signature of Lung Cancer Tissues
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0035157
Pubmed ID
Authors

Michael R. Mehan, Deborah Ayers, Derek Thirstrup, Wei Xiong, Rachel M. Ostroff, Edward N. Brody, Jeffrey J. Walker, Larry Gold, Thale C. Jarvis, Nebojsa Janjic, Geoffrey S. Baird, Sheri K. Wilcox

Abstract

Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan) to compare protein expression signatures of non small-cell lung cancer (NSCLC) tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.

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Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Italy 1 <1%
Switzerland 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 99 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 34%
Student > Ph. D. Student 18 17%
Other 8 7%
Student > Master 8 7%
Professor 7 7%
Other 15 14%
Unknown 15 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 22%
Medicine and Dentistry 19 18%
Biochemistry, Genetics and Molecular Biology 10 9%
Chemistry 9 8%
Engineering 8 7%
Other 15 14%
Unknown 22 21%