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Network controllability-based algorithm to target personalized driver genes for discovering combinatorial drugs of individual patients.
Guo, Wei-Feng; Zhang, Shao-Wu; Feng, Yue-Hua; Liang, Jing; Zeng, Tao; Chen, Luonan.
  • Guo WF; Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian 710072, China.
  • Zhang SW; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.
  • Feng YH; Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian 710072, China.
  • Liang J; Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian 710072, China.
  • Zeng T; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.
  • Chen L; CAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Nucleic Acids Res ; 49(7): e37, 2021 04 19.
Article in English | MEDLINE | ID: covidwho-1066376
Semantic information from SemMedBD (by NLM)
1. Candidate Disease Gene PART_OF Drivers of Vehicles
Subject
Candidate Disease Gene
Predicate
PART_OF
Object
Drivers of Vehicles
2. Pharmaceutical Preparations TREATS Patients
Subject
Pharmaceutical Preparations
Predicate
TREATS
Object
Patients
3. Gene Modules PROCESS_OF Drivers of Vehicles
Subject
Gene Modules
Predicate
PROCESS_OF
Object
Drivers of Vehicles
4. Candidate Disease Gene INTERACTS_WITH Drug Combinations
Subject
Candidate Disease Gene
Predicate
INTERACTS_WITH
Object
Drug Combinations
5. Drug Combinations AFFECTS Gene Modules
Subject
Drug Combinations
Predicate
AFFECTS
Object
Gene Modules
6. Candidate Disease Gene PART_OF Drivers of Vehicles
Subject
Candidate Disease Gene
Predicate
PART_OF
Object
Drivers of Vehicles
7. Pharmaceutical Preparations TREATS Patients
Subject
Pharmaceutical Preparations
Predicate
TREATS
Object
Patients
8. Gene Modules PROCESS_OF Drivers of Vehicles
Subject
Gene Modules
Predicate
PROCESS_OF
Object
Drivers of Vehicles
9. Candidate Disease Gene INTERACTS_WITH Drug Combinations
Subject
Candidate Disease Gene
Predicate
INTERACTS_WITH
Object
Drug Combinations
10. Drug Combinations AFFECTS Gene Modules
Subject
Drug Combinations
Predicate
AFFECTS
Object
Gene Modules
ABSTRACT
Multiple driver genes in individual patient samples may cause resistance to individual drugs in precision medicine. However, current computational methods have not studied how to fill the gap between personalized driver gene identification and combinatorial drug discovery for individual patients. Here, we developed a novel structural network controllability-based personalized driver genes and combinatorial drug identification algorithm (CPGD), aiming to identify combinatorial drugs for an individual patient by targeting personalized driver genes from network controllability perspective. On two benchmark disease datasets (i.e. breast cancer and lung cancer datasets), performance of CPGD is superior to that of other state-of-the-art driver gene-focus methods in terms of discovery rate among prior-known clinical efficacious combinatorial drugs. Especially on breast cancer dataset, CPGD evaluated synergistic effect of pairwise drug combinations by measuring synergistic effect of their corresponding personalized driver gene modules, which are affected by a given targeting personalized driver gene set of drugs. The results showed that CPGD performs better than existing synergistic combinatorial strategies in identifying clinical efficacious paired combinatorial drugs. Furthermore, CPGD enhanced cancer subtyping by computationally providing personalized side effect signatures for individual patients. In addition, CPGD identified 90 drug combinations candidates from SARS-COV2 dataset as potential drug repurposing candidates for recently spreading COVID-19.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Breast Neoplasms / Drug Therapy, Combination / Precision Medicine / Lung Neoplasms Type of study: Etiology study / Prognostic study / Risk factors Limits: Humans Language: English Journal: Nucleic Acids Res Year: 2021 Document Type: Article Affiliation country: Nar

Full text: Available Collection: International databases Database: MEDLINE Main subject: Algorithms / Breast Neoplasms / Drug Therapy, Combination / Precision Medicine / Lung Neoplasms Type of study: Etiology study / Prognostic study / Risk factors Limits: Humans Language: English Journal: Nucleic Acids Res Year: 2021 Document Type: Article Affiliation country: Nar