Methods of identification and diagnosis of lung diseases using classification systems and kits thereof

1. A method of determining the existence of non-small cell lung cancer early in disease progression by measuring expression levels of a set of biomarkers in a subject comprising:

determining biomarker measures of a set of biomarkers by immunoassay in a physiological sample,

wherein the biomarkers are peptides, proteins, peptides bearing post-translational modifications, proteins bearing post-translational modification, or a combination thereof;

wherein the physiological sample is whole blood, blood plasma, blood serum, or a combination thereof;

wherein the set of biomarkers comprise at least four of the following biomarkers: Leukemia Inhibiting Factor (“LIF”), Monocyte Chemotactic Protein 1 (“MCP-1”), IL-9, IL-16, Platelet-derived growth factor subunit B homodimer (“PDGFBB”), Regulated upon Activation, Normal T-cell Expressed, and Secreted (“RANTES”), or Soluble Fas Ligand (“sFasL”);

classifying the sample with respect to the presence or development of non-small cell lung cancer in the subject using the set of biomarker measures in a classification system,

wherein the classification system is a machine learning system comprising classification and regression trees selected from the group consisting of Random Forest and AdaBoost or an ensemble thereof.

2. The method of claim 1 , wherein the physiological sample is blood plasma.

3. The method of claim 1 , wherein the immunoassay is a multiplexed immunoassay.

4. The method of claim 1 , wherein the set of biomarkers further comprises at least one of the following biomarkers: Resistin (“RETN”), Myeloperoxidase (“MPO”), IL-2, MMP 9, Chemokine (C-X-C motif) ligand 1 (“GRO-1”), IL-8, Serum Amyloid A (“SAA”), Regulated upon Activation, IL-4, IL-12(p70), MMP 7, IL-10, Hepatocyte Growth Factor (“HGF”), IL-5, IL-7, Leptin (“LEP”), or Macrophage Migration Inhibitory Factor (“MIF”).

5. The method of claim 1 , wherein the set of biomarkers further comprises at least one of the following biomarkers: Apolipoprotein (“Apo”) A1, ApoA2, ApoB, ApoC2, ApoE, CD40, D-Dimer, Factor-VII, Factor-VIII, Factor-X, Protein-C, Tissue Plasminogen Activator (“TPA”), Brain Derived Neurotrophic Factor (“BDNF”), B Lymphocyte Chemoattractant (“BLC”), Chemokine (C-X-C motif) ligand 1 (“GRO-1”), Cutaneous T-cell Attracting Chemokine (“CTACK”), Eotaxin-2, Eotaxin-3, Granzyme-B, I-TAC (“CXCL11”; “Chemokine (C-X-C motif) ligand 11, interferon-inducible T-cell alpha chemoattractant, Monocyte-specific Chemokine 3 (“MMP-3”), Macrophage colony-stimulating factor (“MCSF”), Macrophage Inflammatory Protein-3α (“MIP-3α”), Matrix Metalloproteinase (“MMP”) 1, MMP 2, MMP3, MMP 7, MMP 8, MMP 9, MMP 12, MMP 13, CD40, Nerve Growth Factor β (“NGF-β”), Epidermal Growth Factor (“EFG”), Eotaxin (“CCL11”), Fractalkine, Fibroblast Growth Factor Basic (“FGF-basic”), Granulocyte Colony Stimulating Factor (“G-CSF”), Granulocyte Macrophage Colony Stimulating Factor (“GM-CSF”), Interferon γ (“IFN γ”), IFN-ω, IFN-α2, IFN-β, Interleukin (“IL”) 1a, IL-1β, IL-1ra, IL-2, IL-2ra, IL-3, IL-6, IL-12(p40), IL-13, IL-15, IL-17, IL-17a, IL-17F, IL-20, IL-21, IL-2 2 , IL-23(p19), IL-27, IL-31, IP-10, Macrophage Inflammatory Protein (“MIP”) 1a, MIP-1β, Neutrophil-Activating Peptide 78 (“ENA-78”), Osteoprotegrin (“OPG”), Placenta Growth Factor (“PIGF”), Stem Cell Growth Factor (“SCGF”), Stromal Cell Derived Factor 1 (“SDF-1”), soluble Receptor activator of nuclear factor ϰ-B ligand (“sRANKL”), Survivin, Transforming Growth Factor α (“TGF α”), TGF-β, Tumor Necrosis Factor α (“TNF α”), TNF-(β, TNF Receptor 1(“TNFR-I”), TNFR-II, TNF-related apoptosis-inducing ligand (“TRAIL”), Thrombopoietin (“TPO”), Vascular Endothelial Growth Factor (“VEGF”), Insulin (“Ins”), C-peptide, Glucagon Like Protein-1/amyline (“GLP-1amylin”), Amylin (total), Glucagon, Adiponectin, Plasminogen Activator Inhibitor 1 (“PAI-1”; “Serpin”) (active/total), sFas, sE-Selectin, Soluble Vascular Cell Adhesion Molecule (“sVCAM”), C-Reactive Protein (“CRP”), or Serum Amyloid P (“SAP”).

6. The method of claim 1 , wherein the subject is at risk for non-small cell lung cancer.

7. The method of claim 1 , wherein the classification system uses a training set comprising measurements of the set of biomarkers from a patient who is free of non-small cell lung cancer.

8. The method of claim 1 , wherein the classification system is AdaBoost.

9. The method of claim 1 , wherein the classification system is Random Forest.

10. The method of claim 1 , wherein the classification system is an ensemble of AdaBoost and Random Forest.