Connectivity Map Analysis of a Single-Cell RNA-Sequencing -Derived Transcriptional Signature of mTOR Signaling.
Int J Mol Sci
; 22(9)2021 Apr 22.
Article
em En
| MEDLINE
| ID: mdl-33922083
ABSTRACT
In the connectivity map (CMap) approach to drug repositioning and development, transcriptional signature of disease is constructed by differential gene expression analysis between the diseased tissue or cells and the control. The negative correlation between the transcriptional disease signature and the transcriptional signature of the drug, or a bioactive compound, is assumed to indicate its ability to "reverse" the disease process. A major limitation of traditional CMaP analysis is the use of signatures derived from bulk disease tissues. Since the key driver pathways are most likely dysregulated in only a subset of cells, the "averaged" transcriptional signatures resulting from bulk analysis lack the resolution to effectively identify effective therapeutic agents. The use of single-cell RNA-seq (scRNA-seq) transcriptomic assay facilitates construction of disease signatures that are specific to individual cell types, but methods for using scRNA-seq data in the context of CMaP analysis are lacking. Lymphangioleiomyomatosis (LAM) mutations in TSC1 or TSC2 genes result in the activation of the mTOR complex 1 (mTORC1). The mTORC1 inhibitor Sirolimus is the only FDA-approved drug to treat LAM. Novel therapies for LAM are urgently needed as the disease recurs with discontinuation of the treatment and some patients are insensitive to the drug. We developed methods for constructing disease transcriptional signatures and CMaP analysis using scRNA-seq profiling and applied them in the analysis of scRNA-seq data of lung tissue from naïve and sirolimus-treated LAM patients. New methods successfully implicated mTORC1 inhibitors, including Sirolimus, as capable of reverting the LAM transcriptional signatures. The CMaP analysis mimicking standard bulk-tissue approach failed to detect any connection between the LAM signature and mTORC1 signaling. This indicates that the precise signature derived from scRNA-seq data using our methods is the crucial difference between the success and the failure to identify effective therapeutic treatments in CMaP analysis.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biomarcadores Tumorais
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Regulação Neoplásica da Expressão Gênica
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Linfangioleiomiomatose
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Serina-Treonina Quinases TOR
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Análise de Célula Única
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Conectoma
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Neoplasias Pulmonares
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Int J Mol Sci
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos