Proteogenomic landscape and clinical characterization of GH-producing pituitary adenomas/somatotroph pituitary neuroendocrine tumors

生长激素分泌垂体腺瘤/生长激素垂体神经内分泌肿瘤的蛋白质组学概况和临床特征

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作者:Azusa Yamato #, Hidekazu Nagano #, Yue Gao, Tatsuma Matsuda, Naoko Hashimoto, Akitoshi Nakayama, Kazuyuki Yamagata, Masataka Yokoyama, Yingbo Gong, Xiaoyan Shi, Siti Nurul Zhahara, Takashi Kono, Yuki Taki, Naoto Furuki, Motoi Nishimura, Kentaro Horiguchi, Yasuo Iwadate, Masaki Fukuyo, Bahityar Rahmu

Abstract

The clinical characteristics of growth hormone (GH)-producing pituitary adenomas/somatotroph pituitary neuroendocrine tumors (GHomas/somatotroph PitNETs) vary across patients. In this study, we aimed to integrate the genetic alterations, protein expression profiles, transcriptomes, and clinical characteristics of GHomas/somatotroph PitNETs to identify molecules associated with acromegaly characteristics. Targeted capture sequencing and copy number analysis of 36 genes and nontargeted proteomics analysis were performed on fresh-frozen samples from 121 sporadic GHomas/somatotroph PitNETs. Targeted capture sequencing revealed GNAS as the only driver gene, as previously reported. Classification by consensus clustering using both RNA sequencing and proteomics revealed many similarities between the proteome and the transcriptome. Gene ontology analysis was performed for differentially expressed proteins between wild-type and mutant GNAS samples identified by nontargeted proteomics and involved in G protein-coupled receptor (GPCR) pathways. The results suggested that GNAS mutations impact endocrinological features in acromegaly through GPCR pathway induction. ATP2A2 and ARID5B correlated with the GH change rate in the octreotide loading test, and WWC3, SERINC1, and ZFAND3 correlated with the tumor volume change rate after somatostatin analog treatment. These results identified a biological connection between GNAS mutations and the clinical and biochemical characteristics of acromegaly, revealing molecules associated with acromegaly that may affect medical treatment efficacy.

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