Systems Biology-Based Drug Repositioning Identifies Extracellular Matrix Module as a Therapeutic Target in Lung Squamous Cell Carcinoma

Systematic proteomic comparisons across cancer subtypes provide insights into tumor heterogeneity and accelerate discovery of therapeutic targets and drug repositioning. Here, we present a novel computational framework, signature-network-perturbation- based drug repositioning (SnpDR), integrating proteomic and pharmacogenomic data through differential modular analysis, drug response network construction, and multiscale perturbation response scanning. Applying SnpDR to compare the proteomic landscapes of lung adenocarcinoma and lung squamous cell carcinoma (LSCC), we identified the extracellular matrix (ECM) module as a central hub in LSCC, while LAMA1 emerged as a novel drug target. <i>In vitro</i> and <i>in vivo</i> experiments validated two repositioned drugs, Fingolimod and Piperlongumine, both targeting ECM components, significantly inhibited LSCC cell growth, proliferation and migration at concentrations below 10 μM. These results provide compelling evidence for the power of systems biology to identify subtype-specific therapeutic vulnerabilities. Our findings highlight a promising framework for precision oncology and underscore the potential of ECM-targeted interventions in LSCC.

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Publication Details

Journal
Journal of Medicinal Chemistry
Published
2025-10-17
DOI
https://doi.org/10.1021/acs.jmedchem.5c01495
Citations
2
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
2.09
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article

Systems Biology-Based Drug Repositioning Identifies Extracellular Matrix Module as a Therapeutic Target in Lung Squamous Cell Carcinoma

Shuo Wang, Bin Yang, Zeyi Liu, Guang Hu et al.
2 citations
Journal of Medicinal Chemistry
Cancer Cells and Metastasis
2.09
article

Systems Biology-Based Drug Repositioning Identifies Extracellular Matrix Module as a Therapeutic Target in Lung Squamous Cell Carcinoma

Shuo Wang, Bin Yang, Zeyi Liu, Guang Hu, Ziyun Zhou, Yuna Shao
article en
2 citations

Abstract

Systematic proteomic comparisons across cancer subtypes provide insights into tumor heterogeneity and accelerate discovery of therapeutic targets and drug repositioning. Here, we present a novel computational framework, signature-network-perturbation- based drug repositioning (SnpDR), integrating proteomic and pharmacogenomic data through differential modular analysis, drug response network construction, and multiscale perturbation response scanning. Applying SnpDR to compare the proteomic landscapes of lung adenocarcinoma and lung squamous cell carcinoma (LSCC), we identified the extracellular matrix (ECM) module as a central hub in LSCC, while LAMA1 emerged as a novel drug target. <i>In vitro</i> and <i>in vivo</i> experiments validated two repositioned drugs, Fingolimod and Piperlongumine, both targeting ECM components, significantly inhibited LSCC cell growth, proliferation and migration at concentrations below 10 μM. These results provide compelling evidence for the power of systems biology to identify subtype-specific therapeutic vulnerabilities. Our findings highlight a promising framework for precision oncology and underscore the potential of ECM-targeted interventions in LSCC.

Journal of Medicinal ChemistryVol. 68(21)
Soochow University (CN), Precision Therapeutics (United States) (US), First Affiliated Hospital of Soochow University (CN), Institute of Infection and Immunity (CA), Nano Carbon (Poland) (PL)
Openalex Percentile: Top 10%
Cancer Cells and Metastasis
2.09
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