AI-powered omics-based drug pair discovery for pyroptosis therapy targeting triple-negative breast cancer
Due to low success rates and long cycles of traditional drug development, the clinical tendency is to apply omics techniques to reveal patient-level disease characteristics and individualized responses to treatment. However, the heterogeneous form of data and uneven distribution of targets make drug discovery and precision medicine a non-trivial task. This study takes pyroptosis therapy for triple-negative breast cancer (TNBC) as a paradigm and uses data mining of a large TNBC cohort and drug databases to establish a biofactor-regulated neural network for rapidly screening and optimizing compound pyroptosis drug pairs. Subsequently, biomimetic nanococrystals are prepared using the preferred combination of mitoxantrone and gambogic acid for rational drug delivery. The unique mechanism of obtained nanococrystals regulating pyroptosis genes through ribosomal stress and triggering pyroptosis cascade immune effects are revealed in TNBC models. In this work, a target omics-based intelligent compound drug discovery framework explores an innovative drug development paradigm, which repurposes existing drugs and enables precise treatment of refractory diseases.
Authors
- Xiaomin Su (ORCID: https://orcid.org/0000-0002-1621-4009)
- Qingwang Chen (ORCID: https://orcid.org/0000-0002-7191-5801)
- Xinnan Dai
- Leming Shi (ORCID: https://orcid.org/0000-0002-2981-4150)
- Ruining Hu
- Tun Lu
- Boshu Ouyang (ORCID: https://orcid.org/0000-0002-0934-434X)
- Shun-Qing Shen (ORCID: https://orcid.org/0000-0002-1954-5882)
- Jianxin Wang (ORCID: https://orcid.org/0000-0002-8444-1537)
- Dongsheng Li (ORCID: https://orcid.org/0000-0003-3103-8442)
- Yongbin Cao (ORCID: https://orcid.org/0009-0001-1795-042X)
- Ruizhe Xu (ORCID: https://orcid.org/0009-0007-8193-4292)
- Caihua Shan (ORCID: https://orcid.org/0000-0003-2607-1598)
- Wuli Yang (ORCID: https://orcid.org/0000-0003-0384-9213)
- Zhiqing Pang (ORCID: https://orcid.org/0000-0003-0228-904X)
- Shaojun Peng (ORCID: https://orcid.org/0000-0003-2273-0234)
- Jun Zhang (ORCID: https://orcid.org/0000-0003-1849-9199)
- Ying He
- Xifeng Qin
- Siyu Wang (ORCID: https://orcid.org/0009-0001-2719-9748)
Institutions
- Fudan University (CN)
- Zhuhai People's Hospital (CN)
- Microsoft Research Asia (China) (CN)
- Ministry of Education (KR)
- Pudong Medical Center (CN)
- Huashan Hospital (CN)
- State Key Laboratory of Genetic Engineering
Publication Details
- Journal
- Nature Communications
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1038/s41467-024-51980-9
- Citations
- 45
- Primary Topic
- Ferroptosis and cancer prognosis
- Type
- article
- Field-Weighted Citation Impact
- 18.85
Funders
- National Science Foundation
- Microsoft Research
- National Natural Science Foundation of China
- Microsoft Research Asia
- Program of Shanghai Academic Research Leader
- Basic and Applied Basic Research Foundation of Guangdong Province