10.6084/m9.figshare.4872881.v1 Yoshimoto T. Yoshimoto T. Motoi N. Motoi N. Yamamoto N. Yamamoto N. Nagano H. Nagano H. Ushijima M. Ushijima M. Matsuura M. Matsuura M. Okumura S. Okumura S. Yamaguchi T. Yamaguchi T. Fukayama M. Fukayama M. Ishikawa Y. Ishikawa Y. Supplementary Material for: Pulmonary Carcinoids and Low-Grade Gastrointestinal Neuroendocrine Tumors Show Common MicroRNA Expression Profiles, Different from Adenocarcinomas and Small Cell Carcinomas Karger Publishers 2017 Carcinoids (carcinoid tumors) MicroRNA Microarray analysis Hierarchical clustering Consensus clustering with nonnegative matrix factorization 2017-04-13 10:39:16 Dataset https://karger.figshare.com/articles/dataset/Supplementary_Material_for_Pulmonary_Carcinoids_and_Low-Grade_Gastrointestinal_Neuroendocrine_Tumors_Show_Common_MicroRNA_Expression_Profiles_Different_from_Adenocarcinomas_and_Small_Cell_Carcinomas/4872881 <p><b><i>Background:</i></b> It is still uncertain whether small cell lung carcinomas (SCLCs), pulmonary carcinoids, and the gastrointestinal neuroendocrine tumors (GI-NETs) have a common origin. MicroRNA (miRNA) expression may clarify their genetic relationships and origin. <b><i>Methods:</i></b> First, we compared the miRNA expression signature of formalin-fixed paraffin-embedded (FFPE) samples with frozen samples to verify the applicability of microarray analysis. Second, we compared the comprehensive miRNA expression patterns of pulmonary carcinoids and GI-NETs as well as other types of tumors and normal tissues from each organ using FFPE samples. These data were analyzed by hierarchical clustering and consensus clustering with nonnegative matrix factorization. <b><i>Results:</i></b> We confirmed that FFPE samples retained the miRNA signatures. In the first hierarchical clustering comparing carcinoids/NETs with adenocarcinomas and normal tissues, most of the carcinoids (48/50) formed 1 major cluster with loose subpartitioning into each organ type, while all the adenocarcinomas (9/9) and normal tissues (15/15) formed another major cluster. The nonnegative matrix factorization approach largely matched the classification of the hierarchical clustering. In the additional cluster analysis comparing carcinoids/NETs with SCLCs, most carcinoids/NETs (17/22) formed a major cluster, while SCLCs (9/9) grouped together with pulmonary adenocarcinomas (3/3) and normal tissues (6/6) in another major cluster. Furthermore, a subset of miRNAs was successfully identified that exhibited significant expression in carcinoids/NETs. <b><i>Conclusion:</i></b> Carcinoids/NETs had a characteristic pattern of miRNA expression, suggesting a common origin for pulmonary carcinoids and GI-NETs. The expression profiles of pulmonary carcinoids and SCLCs were quite different, indicating the distinct histogenesis of these neuroendocrine neoplasms.</p>