PO.TB04.01 · 肿瘤生物学
利用离体人体组织和活细胞生物传感器的非动物平台实现肾细胞癌的功能性药物检测
Non-animal platforms using ex-vivo human tissue and live-cell biosensors enable functional drug testing in renal cell carcinoma
该海报暂无可下载的资料
AACR 官方页面
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:动物模型常常无法重现肾细胞癌(RCC)的免疫和代谢复杂性。为解决这一问题,我们开发了两个互补的非动物平台:一个患者来源离体组织系统和一个生物传感器平台,以实现快速、机制性且具临床相关性的药物检测。
实验:i)将新鲜RCC标本切成精密切割组织切片(PCTS),并与自体外周血单个核细胞(PBMC)共培养(5x10^5个与一个PCTS共培养)六天。治疗组包括:a)单用cabozantinib(cabo),b)cabo联合cemiplimab(cemi,一种PD-1抑制剂),c)cemi联合fianlimab(fin,一种LAG-3抑制剂)。使用H&E染色和Live-Dead染色对共培养的PCTS进行分析,以评估细胞活力。ii)使用能够重现透明细胞RCC典型代谢表型(高糖酵解通量和HIF1A稳定)的RCC细胞系786O,我们进行了时程实验以评估生物传感器信号的动态变化。将细胞接种于生物传感器兼容的微孔板上,并用代谢抑制剂(2-DG、oligomycin)和与RCC相关的药理靶向药物[(PI103——PI3K/mTOR抑制剂)、sunitinib和cabozantinib(酪氨酸激酶抑制剂)以及linsitinib(IGF1R抑制剂)]进行处理。在12小时内每30分钟记录一次生物传感器输出,以生成高分辨率动力学曲线。
结果:i)共培养PCTS的活力评估表明,与单药或cemi+fin双药策略相比,cabo+cemi组的死细胞比例显著更高。此外,共培养六天后评估的有活力PBMC数量在cabo+cemi处理的肿瘤中也最高。MxIF分析正在进行中。
ii)在生物传感器实验中,786O RCC细胞对oligomycin的AMPK反应极小,提示其依赖糖酵解。此外,这些细胞在用Linsitinib和PI103处理后,诱导了HYLIGHT(糖酵解)信号强度快速而持续的降低。cabozantinib引起的降低更为渐进,而sunitinib几乎无效,提示部分代谢抑制或通路代偿。正在进行的工作使用了一种改良方案SCENITH(通过翻译抑制分析的单细胞能量代谢),该方案能够利用基于puromycin的标记以单细胞分辨率评估细胞能量代谢,量化在代谢抑制剂存在下的蛋白质合成。
结论:这一整合的、完全非动物策略通过将保存的人体肿瘤微环境与高分辨率代谢生物传感相结合,克服了动物模型的关键局限。总之,这些平台能够对RCC的治疗易感性进行快速、基于机制的分析。
查看英文原文 English abstract
Background: Animal models frequently fail to recapitulate the immune and metabolic complexity of renal cell carcinoma (RCC). To address this, we developed two complementary non-animal platforms, a patient-derived ex vivo tissue system and a biosensor platform to enable rapid, mechanistic, and clinically relevant drug testing.
Experiments: i) Fresh RCC specimens were sectioned into precision-cut tissue slices (PCTS) and co-cultured with autologous peripheral blood mononuclear cells (PBMCs) (5x10^5 co-cultured with one PCTS) for six days. Treatment groups included: a) cabozantinib (cabo) alone, b) cabo with cemiplimab (cemi, a PD-1 inhibitor), c) cemi with fianlimab (fin, a LAG-3 inhibitor). The co-cultured PCTS were analyzed using H&E staining and a Live-Dead stain to assess cell viability. ii) Using RCC cell line 786O, which recapitulates the canonical metabolic phenotype of clear cell RCC (high glycolytic flux and HIF1A stabilization), we performed time-course experiments to assess dynamic changes in biosensor signal. Cells were plated on biosensor-compatible microplates and treated with metabolic inhibitors (2-DG, oligomycin) and pharmacological targeted drugs relevant to RCC [(PI103- PI3K/mTOR inhibitor), sunitinib and cabozantinib (tyrosine kinase inhibitors), and linsitinib (IGF1R inhibitor)]. Biosensor output was recorded at 30-minute intervals over 12 hours to generate high-resolution kinetic profiles.
Results: i) Viability assessment of co-cultured PCTS indicated a significantly higher proportion of dead cells in the cabo+cemi compared with either a single agent or cemi+fin doublet strategy. Additionally, the number of viable PBMCs, assessed six days post-co-culture, was also highest in the cabo+cemi-treated tumors. MxIF analysis is ongoing.
ii) In the biosensor experiment, 786O RCC cells showed minimal AMPK response to oligomycin, suggesting reliance on glycolysis. Further, these cells, upon treatment with Linsitinib and PI103, induced a rapid and sustained reduction in HYLIGHT (glycolysis) signal intensity. A more gradual decrease was observed with cabozantinib, whereas sunitinib showed almost no effect, suggesting partial metabolic inhibition or pathway compensation. Ongoing work is using a modified protocol, SCENITH (Single-Cell ENergetic metabolism by profiling Translation Inhibition), which allows evaluation of cellular energy metabolism at single-cell resolution using puromycin-based labeling to quantify protein synthesis in the presence of metabolic inhibitors.
Conclusion: This integrated, fully non-animal strategy overcomes key limitations of animal models by combining preserved human tumor microenvironments with high-resolution metabolic biosensing. Together, these platforms enable rapid and mechanism-based profiling of therapeutic vulnerabilities in RCC.
利益披露 Disclosure
S. Gulati,
Eisai Other, advisory board.
Aveo Other, Advisory board.
E. Kofke, None..
M. Pargett, None..
D. Oberbauer, None..
C. Chen, None.