基于口腔癌数据库数据富集的免疫治疗对腭部黏液表皮样癌的有效性

Palate mucoepidermoid carcinoma (PMEC) is an infrequent but tough subtype of oral carcinoma. Due to the lack of independent and comprehensive database for PMEC, the selection or screening of targeted protein on PMEC might be inaccurate. However, several databases of gene expression based on oral cancers having been constructed and uploaded. With the help of combining data enrichment and lab experiments, the target protein choosing against PMEC could be available. METHOD: We firstly searched multiple databases, which being relevant with oral cancers, and compared the gene expression property between tumor tissues and normal tissues. From the overlapped differential genes, we chose several candidates. Meanwhile, we cultured different in vitro and ex vivo models for the targeted protein verification, to ascertain its effectiveness to the immunotherapy. RESULT: 744 genes were in the overlapped region from the 4 different databases. Among those genes, we further enriched 12 for the protein expression profiling. Then two target proteins, CD276 and CD6, were selected and constructed on the CAR-NK cells. Based on the killing efficiency analysis with cell line, tumor primary cells and organoids. The final targeted protein CD276 had been confirmed.

This research provided a new mentality that the target of immunotherapy on such infrequent carcinoma, PMEC, could still be determined with the data enrichment from its upper category. More importantly, the combination of database analysis with multi-model's verification in lab helped the targeted protein selection more precisely.