Detection of lung cancer at an early stage is necessary for successful therapy and improved survival rates. We performed a bottom-up proteomic analysis employing a two-dimensional LC-MS/MS strategy on the conditioned media (CM) of 4 lung cancer cell lines of different histological backgrounds [non-small cell lung cancer: H23 (adenocarcinoma), H520 (squamous cell carcinoma), H460 (large cell carcinoma) and small cell lung cancer (H1688)] to identify secreted or membrane-bound proteins that could be useful as novel lung cancer biomarkers. Proteomic analysis of the four CM allowed identification of 1,830 different proteins (965, 871, 726 and 847 from H1688, H23, H460 and H520, respectively). All proteins were assigned a subcellular localization and 38% were classified as extracellular or membrane-bound. We successfully identified the internal control proteins (also detected by ELISA), kallikrein-related peptidases 14 and 11 and IGFBP2. We also identified known or putative lung cancer tumor markers such as squamous cell carcinoma antigen, CEA, chromogranin A, creatine kinase BB, progastrin-releasing peptide, neural cell adhesion molecule and tumor M2-PK. To select the most promising candidates for validation, we performed tissue specificity, functional classifications, association to cancer based on literature searches, and comparison of our proteome with the proteome of lung-related diseases and serum. Five novel lung cancer candidates, ADAM-17, Osteoprotegerin, Pentraxin 3, Follistatin and sTNF RI were preliminarily validated in the serum of patients with lung cancer and healthy controls. Our results demonstrate the utility of this cell culture proteomic approach to identify secreted and shed proteins that are potentially useful as serological markers for lung cancer.