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Glycoproteomics approach for identifying Glycobiomarker candidate molecules for tissue type classification of non-small cell lung carcinoma.
J Proteome Res. 2014 Nov 07; 13(11):4705-16.JP

Abstract

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.

Authors+Show Affiliations

Research Center for Medical Glycoscience (RCMG), National Institute of Advanced Industrial Science and Technology (AIST) , Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

25244057

Citation

Hirao, Yoshitoshi, et al. "Glycoproteomics Approach for Identifying Glycobiomarker Candidate Molecules for Tissue Type Classification of Non-small Cell Lung Carcinoma." Journal of Proteome Research, vol. 13, no. 11, 2014, pp. 4705-16.
Hirao Y, Matsuzaki H, Iwaki J, et al. Glycoproteomics approach for identifying Glycobiomarker candidate molecules for tissue type classification of non-small cell lung carcinoma. J Proteome Res. 2014;13(11):4705-16.
Hirao, Y., Matsuzaki, H., Iwaki, J., Kuno, A., Kaji, H., Ohkura, T., Togayachi, A., Abe, M., Nomura, M., Noguchi, M., Ikehara, Y., & Narimatsu, H. (2014). Glycoproteomics approach for identifying Glycobiomarker candidate molecules for tissue type classification of non-small cell lung carcinoma. Journal of Proteome Research, 13(11), 4705-16. https://doi.org/10.1021/pr5006668
Hirao Y, et al. Glycoproteomics Approach for Identifying Glycobiomarker Candidate Molecules for Tissue Type Classification of Non-small Cell Lung Carcinoma. J Proteome Res. 2014 Nov 7;13(11):4705-16. PubMed PMID: 25244057.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Glycoproteomics approach for identifying Glycobiomarker candidate molecules for tissue type classification of non-small cell lung carcinoma. AU - Hirao,Yoshitoshi, AU - Matsuzaki,Hideki, AU - Iwaki,Jun, AU - Kuno,Atsushi, AU - Kaji,Hiroyuki, AU - Ohkura,Takashi, AU - Togayachi,Akira, AU - Abe,Minako, AU - Nomura,Masaharu, AU - Noguchi,Masayuki, AU - Ikehara,Yuzuru, AU - Narimatsu,Hisashi, Y1 - 2014/09/22/ PY - 2014/9/23/entrez PY - 2014/9/23/pubmed PY - 2015/7/15/medline KW - Biomarker KW - glycoproteomics KW - glycosylation KW - lectin microarray KW - lung cancer KW - tissue SP - 4705 EP - 16 JF - Journal of proteome research JO - J. Proteome Res. VL - 13 IS - 11 N2 - 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. SN - 1535-3907 UR - https://www.unboundmedicine.com/medline/citation/25244057/Glycoproteomics_approach_for_identifying_Glycobiomarker_candidate_molecules_for_tissue_type_classification_of_non_small_cell_lung_carcinoma_ L2 - https://dx.doi.org/10.1021/pr5006668 DB - PRIME DP - Unbound Medicine ER -