Journal
PHARMACOLOGICAL RESEARCH
Volume 177, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.phrs.2022.106096
Keywords
Machine learning; Ingenol; Megakaryocyte differentiation; Thrombocytopenia; Platelets
Categories
Funding
- National Key Research and Development Program of China [2018ZX09721004-006004]
- National Natural Science Foundation of China [81774013, 81804221, 82074129]
- Science and Technology Planning Project of Sichuan Province, China [2019JDPT0010, 2019YFSY0014, 2019LZXNYDJ11, 2019YJ0484, 2019YJ0473]
- Educational Commission of Sichuan Province, China [18TD0051, 18ZA0525]
- Joint project of Luzhou Municipal People's Government and Southwest Medical University, China [2018LZXNYD-ZK31, 2019LZXNYDJ05, 2018LZXNYD-ZK41, 2018LZXNYD-PT02, 2020LZXNYDZ03, 2020LZXNYDP01, 2018LZXNYD-YL05]
- Luzhou Science and Technology Project, China [2017-S-39(3/5)]
- School-level Fund of Southwest Medical University, China [2021ZKMS044, 2021ZKQN022, 2021ZKMS041, 2018-ZRZD-001, 2019ZZD006, 2017-ZRZD-017, 2017-ZRQN-081]
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In this study, a drug screening model was established using machine learning to predict the potential active compound ingenol for the treatment of radiation- and chemotherapy-induced thrombocytopenia. In vitro experiments and animal models were used to demonstrate that ingenol promoted megakaryocyte differentiation and platelet production. The activation of the PI3K/Akt signaling pathway was found to be involved in ingenol-induced megakaryocyte differentiation.
Thrombocytopenia, a most common complication of radiotherapy and chemotherapy, is an important cause of morbidity and mortality in cancer patients. However, there are still no approved agents for the treatment of radiation- and chemotherapy-induced thrombocytopenia (RIT and CIT, respectively). In this study, a drug screening model for predicting compounds with activity in promoting megakaryocyte (MK) differentiation and platelet production was established based on machine learning (ML), and a natural product ingenol was predicted as a potential active compound. Then, in vitro experiments showed that ingenol significantly promoted MK differentiation in K562 and HEL cells. Furthermore, a RIT mice model and c-MPL knock-out (c-MPL-/-) mice constructed by CRISPR/Cas9 technology were used to assess the therapeutic action of ingenol on thrombocytopenia. The results showed that ingenol accelerated megakaryopoiesis and thrombopoiesis both in RIT mice and c-MPL-/- mice. Next, RNA-sequencing (RNA-seq) was carried out to analyze the gene expression profile induced by ingenol during MK differentiation. Finally, through experimental verifications, we demonstrated that the activation of PI3K/Akt signaling pathway was involved in ingenol-induced MK differentiation. Blocking PI3K/Akt signaling pathway abolished the promotion of ingenol on MK differentiation. Nevertheless, inhibition of TPO/c-MPL signaling pathway could not suppress ingenol-induced MK differentiation. In conclusion, our study builds a drug screening model to discover active compounds against thrombocytopenia, reveals the critical roles of ingenol in promoting MK differentiation and platelet production, and provides a promising avenue for the treatment of RIT.
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