Zheng Sikuan, Luo Mengliang, Huang Hong, Huang Xuanxuan, Peng Zhidong, Zheng Shaowei, Tan Jianye
Department of Orthopaedics, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
Department of Joint and Orthopedics, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
Cell Commun Signal. 2024 Dec 18;22(1):592. doi: 10.1186/s12964-024-01989-w.
Osteosarcoma (OSA), the most common primary bone malignancy, poses significant challenges due to its aggressive nature and propensity for metastasis, especially in adolescents. Mitophagy analysis can help identify new therapeutic targets and combined treatment strategies.
This study integrates single-cell sequencing (scRNA-seq) data and bulk-seq to identify mitophagy-related genes (MRGs) associated with the progression of OSA metastasis and analyze their clinical significance. scRNA-seq data elucidates the relationship between mitophagy and OSA metastasis, employing "CellChat" R package to explore intercellular communications and report on hundreds of ligand-receptor interactions. Subsequently, the combination of bulk-seq and CRISPR-Cas9 gene editing identifies mitophagy-related biomarker associated with metastatic prognosis. Finally, validation of the relationship between mitophagy and OSA metastasis is achieved through cellular biology experiments and animal studies.
The distinct mitophagy activity of various mitochondria manifests in diverse spatial localization, cellular developmental trajectories, and intercellular interactions. OSA tissue exhibits notable heterogeneity in mitophagy within osteoblastic OSA cells. However, high mitophagy activity correlates consistently with high metastatic potential. Subsequently, we identified three critical genes associated with mitophagy in OSA, namely RPS27A, TOMM20 and UBB. According to the aforementioned queue of genes, we have constructed a mitophagy_score (MIP_score). We observed that it consistently predicts patient prognosis in both internal and external datasets, demonstrating strong robustness and stability. Furthermore, we have found that MIP_score can also guide chemotherapy, with varying sensitivities to chemotherapeutic agents based on different MIP_score. It is noteworthy that, through the integration of CRISPR-Cas9 genome-wide screening and validation via cellular and animal experiments, we have identified RPS27A as a potential novel biomarker for OSA.
Our comprehensive analysis elucidated the profile of mitophagy throughout the OSA metastasis process, forming the basis for a mitophagy-related prognostic model that addresses clinical outcomes and drug sensitivity following OSA metastasis. Additionally, an online interactive platform was established to assist clinicians in decision-making ( https://mip-score.shinyapps.io/labtan/ ). These findings lay the groundwork for developing targeted therapies aimed at improving the prognosis of OSA patients.
骨肉瘤(OSA)是最常见的原发性骨恶性肿瘤,因其侵袭性和转移倾向,尤其是在青少年中,带来了重大挑战。线粒体自噬分析有助于识别新的治疗靶点和联合治疗策略。
本研究整合单细胞测序(scRNA-seq)数据和批量测序,以识别与OSA转移进展相关的线粒体自噬相关基因(MRGs),并分析其临床意义。scRNA-seq数据阐明了线粒体自噬与OSA转移之间的关系,使用“CellChat”R包探索细胞间通讯,并报告数百种配体-受体相互作用。随后,批量测序与CRISPR-Cas9基因编辑相结合,确定与转移预后相关的线粒体自噬相关生物标志物。最后,通过细胞生物学实验和动物研究验证线粒体自噬与OSA转移之间的关系。
不同线粒体的独特线粒体自噬活性体现在不同的空间定位、细胞发育轨迹和细胞间相互作用中。OSA组织在成骨OSA细胞内的线粒体自噬方面表现出显著的异质性。然而,高线粒体自噬活性始终与高转移潜能相关。随后,我们在OSA中鉴定出三个与线粒体自噬相关的关键基因,即RPS27A、TOMM20和UBB。根据上述基因队列,我们构建了一个线粒体自噬评分(MIP_score)。我们观察到,它在内部和外部数据集中均能持续预测患者预后,显示出很强的稳健性和稳定性。此外,我们发现MIP_score还可以指导化疗,根据不同的MIP_score对化疗药物具有不同的敏感性。值得注意的是,通过整合CRISPR-Cas9全基因组筛选并通过细胞和动物实验进行验证,我们已将RPS27A确定为OSA的潜在新型生物标志物。
我们的综合分析阐明了整个OSA转移过程中的线粒体自噬概况,为一个与线粒体自噬相关的预后模型奠定了基础,该模型可解决OSA转移后的临床结果和药物敏感性问题。此外,还建立了一个在线互动平台,以协助临床医生进行决策(https://mip-score.shinyapps.io/labtan/)。这些发现为开发旨在改善OSA患者预后的靶向治疗奠定了基础。