Cancer patients have difficulties in seeking remedies for treating symptoms based on Traditional Korean Medicine (TKM) because of its lack of standardized diagnosis. This study is a preliminary research using a proteomics approach to pattern identification of lung cancer patients for patient-specific TKM. Glycoproteins are well-known to be associated with diseases and can be used as disease biomarkers. Six plasma groups (EX, ES, EN, RX, RS and RN) from Lung cancer patients are independently analyzed through glycoproteomics approach based on the pattern identification in TKM. Glycoproteins are separated from human plasma via Lycopersicon esculentum Lectin (LEL) affinity selection on HPLC system. The separated glycoproteins are first trypsin-digested and then deglycosylated with PNGase F. The resulting deglycosylated peptides are analyzed with nLC-MS/MS and the corresponding parent proteins from the each groups are categorized for protein classification. This leads to (1) establish the standardized proteomics methodology for the pattern identification in the lung cancers patients under the framework of TKM; (2) discover lung cancer biomarkers based on the patients’ pattern identification in TKM and then develop in vitro diagnostic kits for lung cancers that optimize these biomarkers to establish patient-specific TKM for further treatment.