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PMID: 14573703 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Protein profiles associated with survival in lung adenocarcinoma.

Chen G, Gharib TG, Wang H, Huang CC, Kuick R, Thomas DG, Shedden KA, Misek DE, Taylor JM, Giordano TJ, Kardia SL, Iannettoni MD, Yee J, Hogg PJ, Orringer MB, Hanash SM, Beer DG

Abstract

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer.

MeSH Terms
Adenocarcinoma/metabolism,mortality Blotting, Western Electrophoresis, Gel, Two-Dimensional Enzyme-Linked Immunosorbent Assay Glycolysis Humans Immunohistochemistry Lung Neoplasms/metabolism,mortality Mass Spectrometry Models, Biological Oligonucleotide Array Sequence Analysis Oligonucleotides/chemistry Proportional Hazards Models Protein Array Analysis RNA, Messenger/metabolism Treatment Outcome
Chemicals
Oligonucleotides RNA, Messenger
Authors & Affiliations
17 authors, click to expand affiliations / ORCID
Chen Guoan
Department of Surgery, University of Michigan, Ann Arbor, MI 48109, USA.
Gharib Tarek G
Wang Hong
Huang Chiang-Ching
Kuick Rork
Thomas Dafydd G
Shedden Kerby A
Misek David E
Taylor Jeremy M G
Giordano Thomas J
Kardia Sharon L R
Iannettoni Mark D
Yee John
Hogg Philip J
Orringer Mark B
Hanash Samir M
Beer David G
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Article Info
Journal
Proceedings of the National Academy of Sciences of the United States of America
Abbr.
Proc Natl Acad Sci U S A
ISSN
0027-8424
Published
2003-11-11
Epub
2003-00-22
Pages
13537-42
Language
English
Region
United States
NLM ID
7505876
PMCID
PMC263849
Subset
IM
Grants
NCI NIH HHS · R01 CA085953 · United States
NCI NIH HHS · CA-46952 · United States
NCI NIH HHS · U19 CA-85953 · United States
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