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>