Glycoproteomics Approach for Identifying Glycobiomarker Candidate Molecules for Tissue Type Classification of Non-small Cell Lung Carcinoma

Histopathological
classification of lung cancer has important implications
in the application of clinical practice guidelines and the prediction
of patient prognosis. Thus, we focused on discovering glycobiomarker
candidates to classify the types of lung cancer tissue. First, we
performed lectin microarray analysis of lung cancer tissue specimens
and cell lines and identified Aleuria aurantia lectin (AAL), Hippeastrum hybrid lectin (HHL),
and Concanavalia ensiformis agglutinin
(ConA) as lectin probes specific to non-small cell lung carcinoma
(NSCLC). LC–MS-based analysis was performed for the comprehensive
identification of glycoproteins and N-linked glycosylation sites using
lectin affinity capture of NSCLC-specific glycoforms of glycoproteins.
This analysis identified 1092 AAL-bound glycoproteins (316 gene symbols)
and 948 HHL/ConA-bound glycoproteins (279 gene symbols). The lectin
microarray-assisted verification using 15 lung cancer cell lines revealed
the NSCLC-specific expression of fibronectin. The glycosylation profiling
of fibronectin indicated that the peanut agglutinin (PNA) signal appeared
to differentiate two NSCLC types, adenocarcinoma and large cell carcinoma,
whereas the protein expression level was similar between these types.
Our glycoproteomics approach together with the concurrent use of an
antibody and lectin is applicable to the quantitative and qualitative
monitoring of variations in glycosylation of fibronectin specific
to certain types of lung cancer tissue.