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Integrating LINCS Data to Evaluate Cancer Transcriptome Modifying Potential of Small-molecule Compounds for Drug Repositioning

Author(s):

Yachao Zhao*, Yang Liu and Hui Bai   Pages 1 - 12 ( 12 )

Abstract:


Background: Conventional high-throughput chemical screens in conjunction with genome-wide gene expression profiling proves to be successful in novel anti-cancer agent discovery and provides comprehensive insights into the mechanisms of action and off-target effects of single small-molecule compound. However, systematic evaluation on heterogeneous transcriptional responses of different cancer cell types to thousands of independent perturbations in a bioinformatics way is still limited.

Method: Here, we introduce cancer transcriptome modifying potential (CTMP) which uses “Connectivity Score” to quantify and compare the effects of approved antineoplastic drugs on transcriptionally restoring dysregulated (both up- and down-) gene expressions at cancer state towards normal state. As a proof-of-concept, we applied this CTMP computational evaluation on > 10,000 small-molecule compounds using >200,000 Library of Integrated Network-based Cellular Signatures (LINCS) expression profiles generated upon 4 different cancer cell lines. We screened and proposed a candidate list of cancer transcriptome modifying therapeutics (CTMTs), among which the approved on-market drugs are further validated using GDSC drug sensitivity data, highlighting their potential to facilitate direct antineoplastic repositioning.

Results: In total, we calculated CTMPs of 85 on-market antineoplastic drugs and ~15,000 small-molecule compounds using 253,813 transcriptomes across four cancer cell lines of lung, melanoma, prostate, and colon. Our results reveal that regardless of chemical structure and targeted proteins majority of approved antineoplastic drugs present significant bilateral CTMPs across all 4 cancer cell lines. Bilateral CTMP-based systematic screen further indicates that candidate CTMTs are limited and most notably cancer-type specific. In particular, for each cancer cell type we proposed 3~5 CTMTs that are approved drugs with potent sensitivity data to support development in antineoplastic indications.

Conclusion: Our work establishes CTMP to evaluate the antineoplastic property of small-molecule compounds and suggests CTMP-based systematic screen of cancer type-specific CTMTs as a feasible strategy in drug repositioning for precise anticancer purposes.

Keywords:

gene signatures, library of integrated network-based cellular signatures, cancer modifying therapeutics, drug sensitivity

Affiliation:

The Eighth Medical Center of PLA General Hospital, Beijing, Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People’s Hospital, Shenzhen, Guangdong Province, Department of Biochemistry and Molecular Biology, Beijing Institute of Radiation Medicine, Beijing



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