Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry

Xuemei Zeng, Brian L. Hood, Ting Zhao, Thomas P. Conrads, Mai Sun, Vanathi Gopalakrishnan, Himanshu Grover, Roger S. Day, Joel L. Weissfeld, David O. Wilson, Jill M. Siegfried, William L. Bigbee

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Introduction: Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer and the relatively favorable survival associated with early-stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods: We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry in a set of pooled non-small cell lung cancer case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by liquid chromatography-tandem mass spectrometry. The tandem mass spectrum data were searched against the human proteome database, and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting-derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring mass spectrometry assays. Results: A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (p < 0.01). Functional analysis with Ingenuity Pathway Analysis tools showed significant enrichment of inflammatory response proteins, key molecules in cell-cell signaling and interaction network, and differential physiological responses for the two common non-small cell lung cancer subtypes. Conclusions: We identified a set of candidate serum biomarkers with statistically significant differential abundance across the lung cancer case/control pools, which, when validated, could improve lung cancer early detection.

Original languageEnglish
Pages (from-to)725-734
Number of pages10
JournalJournal of Thoracic Oncology
Issue number4
StatePublished - Apr 2011
Externally publishedYes


  • Lung cancer
  • Serum biomarkers
  • liquid chromatographymass spectrometry/mass spectrometry


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