Hybrid phenotype mining method for investigating off-target protein and underlying side effects of anti-tumor immunotherapy.

Background: It is of utmost importance to investigate novel therapies for cancer, as it is a major cause of death. In recent years, immunotherapies, especially those against immune checkpoints, have been developed and brought significant improvement in cancer management. However, on the other hand,...

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Publicado en:BMC Medical Informatics & Decision Making Vol. 20; pp. 1 - 12
Autores principales: Zheng, Yuyu, Meng, Xiangyu, Zweigenbaum, Pierre, Chen, Lingling, Xia, Jingbo
Formato: research Journal Article
Publicado: BioMed Central 7/9/2020 Supplement 3
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 7/9/2020 Supplement 3
      vid: 20
      pid: 24147
      pub: BioMed Central
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        144473169
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        144473169
        10.1186/s12911-020-1105-4
        NLM32646421
        144473169
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        atl: Hybrid phenotype mining method for investigating off-target protein and underlying side effects of anti-tumor immunotherapy.
      aug:
        au:
          Zheng, Yuyu
          Meng, Xiangyu
          Zweigenbaum, Pierre
          Chen, Lingling
          Xia, Jingbo
        affil: Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, 430070, Wuhan, China
      sug:
        subj:
          Neoplasms Drug Therapy
          Adverse Drug Event
          Neoplasms
          Human
          Proteins
          Immunotherapy Adverse Effects
          Phenotype
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
      ab: Background: It is of utmost importance to investigate novel therapies for cancer, as it is a major cause of death. In recent years, immunotherapies, especially those against immune checkpoints, have been developed and brought significant improvement in cancer management. However, on the other hand, immune checkpoints blockade (ICB) by monoclonal antiboties may cause common and severe adverse reactions (ADRs), the cause of which remains largely undetermined. We hypothesize that ICB-agents may induce adverse reactions through off-target protein interactions, similar to the ADR-causing off-target effects of small molecules. In this study, we propose a hybrid phenotype mining approach which integrates molecular level information and provides new mechanistic insights for ICB-associated ADRs.Methods: We trained a conditional random fields model on the TAC 2017 benchmark training data, then used it to extract all drug-centric phenotypes for the five anti-PD-1/PD-L1 drugs from the drug labels of the DailyMed database. Proteins with structure similar to the drugs were obtained by using BlastP, and the gene targets of drugs were obtained from the STRING database. The target-centric phenotypes were extracted from the human phenotype ontology database. Finally, a screening module was designed to investigate off-target proteins, by making use of gene ontology analysis and pathway analysis.Results: Eventually, through the cross-analysis of the drug and target gene phenotypes, the off-target effect caused by the mutation of gene BTK was found, and the candidate side-effect off-target site was analyzed.Conclusions: This research provided a hybrid method of biomedical natural language processing and bioinformatics to investigate the off-target-based mechanism of ICB treatment. The method can also be applied for the investigation of ADRs related to other large molecule drugs.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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