Accepted_test

Single-cell transcriptomic analysis reveals a unique cluster and differences in gene expression in somatotroph adenomas
by Asaad W. | Deviatiiarov R. | Shcherbakova A. | Popov S. | Utkina M. | Department of General, Molecular and Population genetics, Endocrinology Research Centre, Moscow, Russia | 1 Department of General, Molecular and Population genetics, Endocrinology Research Centre, Moscow, Russia 2 Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia 3 Graduate School of Medicine, Juntendo University, Tokyo, Japan 4 Life Improvement by Future Technologies (LIFT) Center, Moscow, Russia | Department of General, Molecular and Population genetics, Endocrinology Research Centre, Moscow, Russia | Department of General, Molecular and Population genetics, Endocrinology Research Centre, Moscow, Russia | Department of General, Molecular and Population genetics, Endocrinology Research Centre, Moscow, Russia
Abstract ID: 197
Event: BGRS-abstracts
Sections: [Sym 9] Section “Gene expression and human diseases”

Pituitary adenomas (PAs) are benign tumors of the pituitary gland, accounting for approximately 15% of all primary brain tumors. These PAs can be either functioning (secreting) or non-functioning (silent) adenomas, and research is conducted to understand the differences between these two adenoma types. Single-cell RNA sequencing (scRNA-seq) is a powerful technique that allows us to understand different normal or tumoral tissue structures and regulation on the molecular level. This abstract describes the obtained results of our last study on somatotroph adenoma (SA) - a type of PA, where we compared silent and secreting SAs by scRNA-seq. Our data analysis indicated significant differences in gene expression levels and patterns between silent and functioning SAs, which reflects differences in the tumor progression, regulatory mechanisms, and microenvironment between these tumor types. In addition, we identified a novel cluster specifically expressed in silent SA with a distinct gene expression profile. Our data described in this abstract will promote a deeper understanding of SA pathology.