Lung cancer is the leading cause of cancer death worldwide. Currently, lung cancer is classified into two major types, small-cell lung cancer carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC), based on the histological appearance. The histological classification has important implications in the clinical practice guideline and the prediction of the patient prognosis. However, conventional serum markers used in clinical tests are insufficient for clinical demands due to the low sensitivity and the low specificity to distinguish them. We have identified a number of glyco-biomarker candidate molecules from lung cancer cell lines using our developed glycoproteomics technologies such as lectin microarray and LC/MS-based protein analysis. On the validation studies, we found out that the selected molecules showed characteristic lectin biding profiles depending on either SCLC or NSCLC. Therefore, combination of these glyco-biomarkers could be expected to improve the diagnostic accuracy for histological classification in lung cancer compared to protein expression alone.