AI-powered omics-based drug pair discovery for pyroptosis therapy targeting triple-negative breast cancer

Boshu Ouyang, Caihua Shan, Shun Shen, Xinnan Dai, Qingwang Chen, Xiaomin Su, Yongbin Cao, Xifeng Qin, Ying He, Siyu Wang, Ruizhe Xu, Ruining Hu, Leming Shi, Tun Lu, Wuli Yang, Shaojun Peng (), Jun Zhang (), Jianxin Wang (), Dongsheng Li () and Zhiqing Pang ()
Additional contact information
Boshu Ouyang: Fudan University
Caihua Shan: Microsoft Research Asia
Shun Shen: Fudan University Pudong Medical Center
Xinnan Dai: Microsoft Research Asia
Qingwang Chen: Fudan University
Xiaomin Su: Fudan University
Yongbin Cao: Fudan University
Xifeng Qin: Fudan University
Ying He: Fudan University
Siyu Wang: Fudan University
Ruizhe Xu: Fudan University
Ruining Hu: Fudan University
Leming Shi: Fudan University
Tun Lu: Fudan University
Wuli Yang: Fudan University
Shaojun Peng: Zhuhai People’s Hospital (Zhuhai Hospital Affiliated with Jinan University); Zhuhai
Jun Zhang: Fudan University
Jianxin Wang: Fudan University
Dongsheng Li: Microsoft Research Asia
Zhiqing Pang: Fudan University

Nature Communications, 2024, vol. 15, issue 1, 1-20

Abstract: Abstract 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.

Date: 2024
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DOI: 10.1038/s41467-024-51980-9

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