MASS SPECTROMETRY-BASED PROTEOME PROFILE DIFFERENTIATES ADENOID CYSTIC CARCINOMA FROM POLYMORPHOUS ADENOCARCINOMA

Abstract

Objective To determine the proteome profile of adenoid cystic carcinoma (AdCC) and polymorphous adenocarcinoma (PAc) and to identify a protein signature useful to differentiate both neoplasms. Study Design Ten cases of AdCC and 10 cases of PAc were retrospectively retrieved and submitted to laser microdissection for enrichment of neoplastic tissue. The samples were submitted to liquid chromatography-tandem mass spectrometry (LC-MS/MS) and the proteomics data were analyzed using the MaxQuant software. MS/MS spectra were searched against the Human UniProt database, whereas statistical analyses were performed with Perseus software. Results The LC-MS/MS analysis identified 1957 proteins. Among these, 261 proteins were exclusively identified in AdCC and 106 proteins only in PAc. Clustering analysis of the 394 statistically significant proteins identified in both tumors showed a clear separation of the tumors. A total of 16 proteins were upregulated in each tumor, 6 in AdCC and 10 in PAc, and their cluster analysis also revealed clear differences between both neoplasms. Conclusions Global proteome can effectively discriminate AdCC and PAc, and the use of a protein signature may represent a useful diagnostic auxiliary to differentiate both tumors in difficult cases. Support: FAPESP 2015/16056-0 and FAPEMIG. To determine the proteome profile of adenoid cystic carcinoma (AdCC) and polymorphous adenocarcinoma (PAc) and to identify a protein signature useful to differentiate both neoplasms. Ten cases of AdCC and 10 cases of PAc were retrospectively retrieved and submitted to laser microdissection for enrichment of neoplastic tissue. The samples were submitted to liquid chromatography-tandem mass spectrometry (LC-MS/MS) and the proteomics data were analyzed using the MaxQuant software. MS/MS spectra were searched against the Human UniProt database, whereas statistical analyses were performed with Perseus software. The LC-MS/MS analysis identified 1957 proteins. Among these, 261 proteins were exclusively identified in AdCC and 106 proteins only in PAc. Clustering analysis of the 394 statistically significant proteins identified in both tumors showed a clear separation of the tumors. A total of 16 proteins were upregulated in each tumor, 6 in AdCC and 10 in PAc, and their cluster analysis also revealed clear differences between both neoplasms. Global proteome can effectively discriminate AdCC and PAc, and the use of a protein signature may represent a useful diagnostic auxiliary to differentiate both tumors in difficult cases. Support: FAPESP 2015/16056-0 and FAPEMIG.