Novel classification based on immunohistochemistry combined with hierarchical clustering analysis in non-functioning neuroendocrine tumor patients

基于免疫组织化学结合层次聚类分析的无功能神经内分泌肿瘤患者新分类

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作者:Shinya Iida, Yasuhiro Miki, Katsuhiko Ono, Jun-ichi Akahira, Takashi Suzuki, Kazuyuki Ishida, Mika Watanabe, Hironobu Sasano

Abstract

Somatostatin analogues ameliorated many symptoms caused by neuroendocrine tumors (NET), but their antitumor activities are limited especially in non-functioning cases. An overactivation of signaling pathways under receptor tyrosine-kinase (RTK) has been recently demonstrated in some NET patients, but its details have remained largely unknown. Therefore, in this study, we immunolocalized therapeutic factors and evaluated the data to study the clinical significance of the molecules in non-functioning Japanese gastrointestinal NET. Fifty-two NET cases were available for examination in this study and expression of somatostatin receptor (sstr) 1, 2A, 2B, 3 and 5, activated form of mammalian target of rapamycin (mTOR), eukaryotic initiation factor 4-binding protein 1 (4EBP1), ribosomal protein s6 (S6), extracellular signal-regulated kinase (ERK) and insulin-like growth factor 1 receptor (IGF-1R) was evaluated using immunohistochemistry. We then studied the correlation among the immunohistochemical results of the individual cases using hierarchical clustering analysis. Results of clustering analysis demonstrated that NET cases were basically classified into Cluster I and II. Cluster I was associated with higher expression of sstr1, 2B and 3 and Cluster II was characterized by an activation of the PI3K/Akt pathway and IGF-1R and higher proliferative status. Cluster II was further classified into Cluster IIa and IIb. Cluster IIa was associated with higher expression of sstr1 and 5 and higher proliferative status and Cluster IIb was characterized by ERK activation. Hierarchical clustering analysis of immunoreactivity of the therapeutic factors can classify NET cases into three distinctive groups and the medical treatment may be determined according to this novel classification method for non-functioning NET patients.

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