PO.CL06.02 · 临床研究

质子诱导的外泌体特征揭示儿童弥漫性中线胶质瘤的放射反应通路

Proton-induced exosomal signatures reveal radiation response pathways in pediatric diffuse midline glioma

海报缩略图:质子诱导的外泌体特征揭示儿童弥漫性中线胶质瘤的放射反应通路
编号 1170 展板 23 时间 4/19 02:00–05:00 区域 Section 45 主讲 Ann Morcos, BS
分会场 Mechanistic Insights for Targeted Therapies in Pediatric Cancer
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作者与单位 Authors & Affiliations

Ann Morcos1, Yeonkyu Jung1, Nathan R. Wall2

1James M. Slater, MD Proton Treatment & Research Center Department of Radiation Medicine, Loma Linda University, Loma Linda, CA,2Assistant Professor of Basic Sciences, Pediatrics & Rad. Med., Loma Linda University, Loma Linda, CA

摘要 Abstract

中文摘要
弥漫性内生型脑桥胶质瘤(DIPG)主要影响5至10岁的儿童,预后不良,中位生存期为9至12个月。标准治疗选择有限,通常包括放射治疗,但仅提供暂时性改善,而化疗和靶向治疗试验仍在进行中。DIPG仍是最致命的儿童脑肿瘤之一,新出现的证据提示外泌体等细胞外囊泡可能通过携带调控凋亡、DNA损伤信号和细胞间存活通路的货物促成治疗耐药。尽管对外泌体介导的通讯兴趣日益增长,但DIPG中外泌体释放的放射依赖性动态仍研究不足且定义不清。本研究旨在通过比较质子照射后DIPG1和DIPG16A的增殖行为、细胞周期分布以及凋亡和坏死模式来表征其放射反应特征,同时通过定量外泌体释放和粒径分布来建立早期和晚期外泌体动态。在此,我们提供了早期证据,表明质子放射诱导出独特的细胞应激表型,并伴有可测量的、时间依赖性的外泌体输出,提示存在一个活跃的放射响应性囊泡程序。DIPG16A源自未经治疗的治疗前活检标本,而DIPG1获自经放射及多种化疗方案治疗后的治疗后尸检标本。两种细胞系均在标准条件下培养,暴露于梯度质子剂量,并使用纳米颗粒追踪对外泌体进行分离和分析。对全局治疗反应的汇总分析揭示了模型特异性差异,这可能反映了先前的治疗暴露和内在肿瘤生物学特性。增殖实验表明DIPG16A比DIPG1对放射更敏感。DIPG16A照射后显示出更高的凋亡群体,而两种模型均表现出极少的坏死,且两种细胞系均未显示可检测的细胞周期停滞。纳米颗粒追踪分析证实每种细胞系在早期和晚期间隔均有可测量的外泌体释放,为未来研究外泌体内凋亡抑制蛋白如何促成弥漫性中线胶质瘤中外泌体介导的放射耐药奠定了基础。总的来说,这些发现凸显了质子诱导的外泌体信号作为儿童弥漫性中线胶质瘤治疗反应中一个潜在重要且此前未受重视的组成部分,并支持对外泌体携带的存活因子进行进一步机制探索。生成式人工智能仅用于文本编辑和清晰化,所有科学内容均由作者产生和验证。
查看英文原文 English abstract
Diffuse intrinsic pontine glioma (DIPG) primarily affects children between five and ten years of age and carries a poor prognosis, with median survival of nine to twelve months. Standard treatment options are limited and typically include radiation therapy, which provides only temporary improvement, while chemotherapy and targeted therapy trials remain ongoing. DIPG remains one of the most lethal pediatric brain tumors, and emerging evidence suggests that extracellular vesicles such as exosomes may contribute to treatment resistance by carrying cargo that regulates apoptosis, DNA damage signaling, and intercellular survival pathways. Despite growing interest in exosome-mediated communication, the radiation-dependent dynamics of exosome release in DIPG remain understudied and poorly defined. This study aims to characterize radiation response features in DIPG1 and DIPG16A by comparing proliferation behavior, cell cycle distribution, and apoptosis and necrosis patterns after proton exposure, while establishing early and late exosomal dynamics through quantification of exosome release and size distribution. Here, we provide early evidence that proton radiation induces distinct cellular stress phenotypes accompanied by measurable and time-dependent exosomal output, suggesting an active radiation-responsive vesicle program. DIPG16A was derived from a treatment-naïve pretreatment biopsy specimen, whereas DIPG1 was obtained from a post-treatment autopsy specimen following exposure to radiation and multiple chemotherapeutic regimens. Both cell lines were cultured under standard conditions, exposed to graded proton doses, and exosomes were isolated and analyzed using nanoparticle tracking. A summary analysis of global treatment response revealed model-specific differences that may reflect prior therapeutic exposure and intrinsic tumor biology. Proliferation assays demonstrated that DIPG16A was more sensitive to radiation than DIPG1. DIPG16A showed a higher apoptotic population after irradiation, while both models displayed minimal necrosis and neither line showed detectable cell cycle arrest. Nanoparticle tracking analysis confirmed measurable exosome release at both early and late intervals in each line, establishing the foundation for future work investigating how apoptosis inhibitor proteins within exosomes may contribute to exosome-mediated radiation resistance in diffuse midline glioma. Collectively, these findings highlight proton-induced exosomal signaling as a potentially important and previously underappreciated component of treatment response in pediatric diffuse midline glioma and support further mechanistic exploration of exosome-carried survival factors. Generative artificial intelligence was used only for text editing and clarity, and all scientific content was produced and verified by the authors.
利益披露 Disclosure
A. Morcos, None.. Y. Jung, None.

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