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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 50% |
Ireland | 1 | 17% |
United Kingdom | 1 | 17% |
Unknown | 1 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 50% |
Scientists | 2 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
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% |