Predicting candidate therapeutic drugs for sepsis-induced acute respiratory distress syndrome based on transcriptome profiling

ABSTRACT

Sepsis-induced acute respiratory distress syndrome (ARDS) remains a major threat to human health without effective therapeutic drugs. Previous studies demonstrated the power of gene expression profiling to reveal pathological changes associated with sepsis-induced ARDS. However, there is still a lack of systematic data mining framework for identifying potential targets for treatment. In this study, we demonstrated the feasibility of druggable targets prediction based on gene expression data. Through the functional enrichment analysis of microarray-based expression profiles between sepsis-induced ARDS and non-sepsis ARDS samples, we revealed genes involved in anti-microbial infection immunity were significantly altered in sepsis-induced ARDS. Protein–protein interaction (PPI) network analysis highlighted TOP2A gene as the key regulator in the dysregulated gene network of sepsis-induced ARDS. We were also able to predict several therapeutic drug candidates for sepsis-induced ARDS using Connectivity Map (Cmap) database, among which doxorubicin was identified to interact with TOP2A with a high affinity similar to its endogenous ligand. Overall, our findings suggest that doxorubicin could be a potential therapeutic for sepsis-induced ARDS by targeting TOP2A, which requires further investigation and validation. The whole study relies on publicly available dataset and publicly accessible database or bioinformatic tools for data mining. Therefore, our study benchmarks a workflow for druggable target prediction which can be widely applicable in the search of targets in other pathological conditions.

Graphical Abstract

KEYWORDS:

• Sepsis-induced ARDS
• functional enrichment analysis
• protein-protein interaction (PPI)
• connectivity map
• molecular docking

Highlights

(1) Transcriptome profiling identified signature genes dysregulated in sepsis-induced ARDS.

(2) GSEA revealed that genes in anti-microbial response is dysregulated in sepsis-induced ARDS.

(3) TOP2A was at the center of dysregulated gene network in sepsis-induced ARDS.

(4) Doxorubicin as a strong candidate targeting TOP2A for reversing transcriptome signature.

Abbreviation

ARDS	=	acute respiratory distress syndrome;
PPI	=	protein-protein interaction
Cmap	=	Connectivity map
SIRS	=	Systemic Inflammatory Response Syndrome
DAVID	=	the Database for annotation, visualization and integrated discovery
GESA	=	Gene Set Enrichment Analysis
TOP2A	=	DNA topoisomerase 2-alpha;

Authors’ Contributions

LL conceived of the study.

QL, DJ and HL carried out sample selection from the publicly available data.

JM did statistical analyses of all data and drafted the manuscript.

All authors read and approved the final manuscript.

Declaration

Ethics approval and consent to participate

Not applicable

Acknowledgements

None

Consent to publish

Not applicable

Availability of data and materials

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Disclosure statement

The authors declare that they have no competing interests.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This study was supported by Major Project of Wuxi Municipal Commission For Health and Family Planning (Z201601), The 13th” Top six talent peaks” project of jiangsu (WSN-184), Suzhou Science and Technology Development Plan (no. SYS2019017) and General Project of Science and technology development fund of Nanjing Medical University (NMUB2019302).