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贝叶斯优化的深度学习用于识别线粒体自噬的必需基因并促进对抗人类癌症耐药性的治疗。

Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.

作者信息

Jin Wenyi, Chen Junwen, Li Zhongyi, Yubiao Zhang, Peng Hao

机构信息

Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.

Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China.

出版信息

J Cell Mol Med. 2025 Jan;29(2):e18254. doi: 10.1111/jcmm.18254.

Abstract

Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and developing mitophagy-based treatments to combat drug resistance remains challenging. Herein, BayeDEM (Bayesian-optimized Deep learning for identifying Essential genes of Mitophagy) was proposed for such a task. After Bayesian optimization, BayeDEM demonstrated its excellent performance in identifying critical genes regulating mitophagy of osteosarcoma (area under curve [AUC] of ROC: 98.96%; AUC of PR curve: 100%). CERS1 was identified as the most essential gene regulating mitophagy (mean (|SHAP value|): 4.14). Inhibition of CERS1 sensitized cisplatin-resistant osteosarcoma cells to cisplatin, restricting their growth, proliferation, invasion, migration and colony formation and inducing apoptosis. Mechanistically, inhibition of CERS1 restricted mitophagy to destroy the mitochondrial quality control in cisplatin-resistant osteosarcoma cells, including mitochondrial membrane potential loss and unfavourable mitochondrial dynamics, rendering them susceptible to cisplatin-induced apoptosis. More importantly, mitophagy facilitated the immunosuppressive microenvironment formation by significantly modulating T-cell differentiation, adhesion and antigen presentation, and mitophagy mainly affects malignant osteoblasts in the early-mid developmental stage. Immunologically, mitophagy potentially modulated the MIF signalling transmission between malignant osteoblasts and B cells, DCs, CD8+ T cells, NK cells and monocytes through the MIF-(CD74 + CXCR4) receptor-ligand interaction, thereby modulating the biological functions of these immune cells. Collectively, BayeDEM emerged as a promising tool for oncologists to identify pivotal genes governing mitophagy, thereby enabling mitophagy-centric therapeutic strategies to counteract drug resistance.

摘要

线粒体自噬失调对人类癌症中的线粒体质量控制至关重要。然而,识别调控线粒体自噬的关键基因并开发基于线粒体自噬的治疗方法以对抗耐药性仍然具有挑战性。在此,我们提出了BayeDEM(用于识别线粒体自噬关键基因的贝叶斯优化深度学习方法)来完成这项任务。经过贝叶斯优化后,BayeDEM在识别调控骨肉瘤线粒体自噬的关键基因方面表现出优异的性能(ROC曲线下面积[AUC]:98.96%;PR曲线下面积:100%)。CERS1被确定为调控线粒体自噬的最关键基因(平均(|SHAP值|):4.14)。抑制CERS1可使顺铂耐药的骨肉瘤细胞对顺铂敏感,限制其生长、增殖、侵袭、迁移和集落形成,并诱导细胞凋亡。从机制上讲,抑制CERS1会限制线粒体自噬,破坏顺铂耐药骨肉瘤细胞中的线粒体质量控制,包括线粒体膜电位丧失和不利的线粒体动力学,使其易受顺铂诱导的细胞凋亡影响。更重要的是,线粒体自噬通过显著调节T细胞分化、黏附和抗原呈递促进免疫抑制微环境的形成,并且线粒体自噬主要影响发育早中期的恶性成骨细胞。在免疫方面,线粒体自噬可能通过MIF-(CD74 + CXCR4)受体-配体相互作用调节恶性成骨细胞与B细胞、树突状细胞、CD8+ T细胞、自然杀伤细胞和单核细胞之间的MIF信号传递,从而调节这些免疫细胞的生物学功能。总的来说,BayeDEM成为肿瘤学家识别调控线粒体自噬的关键基因的一个有前景的工具,从而使以线粒体自噬为中心的治疗策略能够对抗耐药性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a7/11747347/1e3f7834c37d/JCMM-29-e18254-g008.jpg

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