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Updated: Dec 15, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Hybrid phenotype mining method for investigating off-target protein and underlying side effects of anti-tumor
Yuyu Zheng1, Xiangyu Meng2,3, Pierre Zweigenbaum4
1Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China.
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.
Insights
Investigating novel cancer immunotherapies, this study explores adverse drug reactions (ADRs) from immune checkpoint blockade (ICB). A hybrid approach identified off-target protein interactions, revealing a potential mechanism involving BTK gene mutations in ICB-associated ADRs.
Area of Science:
- Biomedical Natural Language Processing
- Bioinformatics
- Cancer Immunotherapy
Background:
- Cancer immunotherapy, particularly immune checkpoint blockade (ICB), has advanced cancer treatment.
- However, ICB therapies can cause severe adverse drug reactions (ADRs) with undetermined causes.
- This study hypothesizes that off-target protein interactions contribute to ICB-associated ADRs.
Purpose of the Study:
- To investigate the off-target mechanisms underlying adverse drug reactions (ADRs) associated with immune checkpoint blockade (ICB) therapies.
- To develop and apply a hybrid approach integrating molecular and phenotypic data for mechanistic insights into ICB-associated ADRs.
Main Methods:
- A conditional random fields model was trained to extract drug-centric phenotypes from drug labels.
- Proteins with structural similarity to ICB drugs were identified, and gene targets were retrieved.
- Off-target proteins were screened using gene ontology and pathway analyses, integrating drug and target gene phenotypes.
Main Results:
- A hybrid phenotype mining approach was developed and applied to ICB drugs.
- Cross-analysis revealed an off-target effect linked to BTK gene mutation as a candidate mechanism for ADRs.
- The study identified a potential off-target site contributing to ICB-related side effects.
Conclusions:
- A novel hybrid method combining biomedical NLP and bioinformatics was established to investigate off-target mechanisms in ICB treatment.
- This approach provides mechanistic insights into ICB-associated ADRs.
- The methodology is applicable to studying ADRs of other large molecule drugs.
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