PO.ET09.03 · 实验与分子治疗
整合的类器官筛选方法可实现对蛋白降解剂疗效和靶点结合的临床前评估
Integrated organoid screening approaches enable preclinical assessment of protein degrader efficacy and target engagement
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
引言:蛋白水解靶向嵌合体(PROTAC)和分子胶是为选择性蛋白降解而设计的新型疗法,为靶向癌症治疗提供了新途径。使用患者来源的类器官评估了两种cereblon(CRBN)介导的蛋白降解剂候选物——CC-885(GSPT1降解剂;分子胶)和ARV-471(雌激素受体(ER)降解剂;PROTAC),以满足临床前蛋白降解剂开发中对生理相关平台的未满足需求。
方法:使用OrganoidXplore™ CellTiterGlo检测,对CC-885进行6个剂量的筛选,涵盖98个经NGS表征的类器官,这些类器官来源于六种组织类型(结直肠癌、宫颈癌、胃癌、头颈癌、肺癌和胰腺癌),包括非患病模型。在高内涵成像(HCI)检测中,于十个ER敏感适应症(乳腺癌、卵巢癌)的类器官模型中评估了ARV-471的疗效。在HCI检测中对部分模型验证了CC-885的敏感性,并在免疫荧光(IF)检测中评估了GSPT1和ER的降解。选择CC-885敏感的模型来生成CRISPR/Cas9介导的CRBN敲除类器官模型。将(患者配对的)PDX模型皮下移植到免疫缺陷小鼠中,并通过肿瘤生长抑制(TGI)测量评估体内疗效。
结果:CC-885的大规模类器官筛选揭示了异质性的肿瘤反应(IC50范围约为0.1nM至50nM),这与GSPT1或CRBN mRNA表达水平无关。在同基因KO类器官模型中,CRBN缺失消除了CC-885的反应,证实了E3连接酶依赖性。HCI研究验证了CC-885的反应,并通过IF染色量化了靶点结合和降解。通过HCI对ER阳性类器官进行的ARV-471疗效测试表明其既具有强健的活性又有ER降解。通过HCI整合疗效与靶点结合,为观察到的反应与分子作用模式之间提供了机制联系。最后,将类器官筛选的结果与配对的患者来源异种移植(PDX)模型中的反应进行了比较。
结论:类器官提供了基因组稳定、患者来源的模型,能够捕捉患者多样性和肿瘤异质性,从而为精准医学提供可临床转化的见解。我们的结果确立了基于类器官的筛选平台(OrganoidXplore™),结合CTG和HCI两种模式,作为临床前蛋白降解剂评估的可靠工具。这些平台独特地能够识别可能对靶向降解产生反应的肿瘤亚型,并有可能通过同步的疗效和机制读数促进转化生物标志物的发现。PDXO到PDX的后续研究机会进一步凸显了这些平台在指导肿瘤学早期治疗开发和靶点选择方面的实用性。
查看英文原文 English abstract
Introduction Proteolysis-targeting chimeras (PROTACs) and molecular glues are novel therapeutics designed for selective protein degradation, offering new avenues for targeted cancer treatment. Two cereblon (CRBN)-mediated protein degrader candidates, CC-885 (GSPT1 degrader; molecular glue) and ARV-471 (estrogen receptor (ER) degrader; PROTAC), were evaluated using patient-derived organoids to address the unmet need for physiologically relevant platforms in preclinical protein degrader development.
Methods: CC-885 was screened using the OrganoidXplore™ CellTiterGlo assay at 6 doses across 98 NGS characterized organoids derived from six tissue types (colorectal, cervical, gastric, head and neck, lung, and pancreatic cancer), including non-diseased models. ARV-471 efficacy was assessed in ten organoid models of ER-sensitive indications (breast, ovarian) in high content imaging (HCI) assays. CC-885 sensitivity was validated in HCI assay for a selection of models, and GSPT1 and ER degradation were assessed in immuno-fluorescent (IF) assays. CC-885-sensitive models were selected to generate CRISPR/Cas9-mediated CRBN knockout organoid models. (Patient-matched) PDX models were subcutaneously engrafted in immunodeficient mice, and in vivo efficacy was evaluated by tumor growth inhibition (TGI) measurement.
Results: Large panel organoid screening of CC-885 revealed heterogeneous tumor responses (IC50s ranging from ~0.1nM to 50nM) that did not correlate to GSPT1 or CRBN mRNA expression levels. In isogenic KO organoid models, loss of CRBN abrogated CC-885 responses, confirming E3-ligase dependency. HCI studies validated CC-885 responses and quantified target engagement and degradation through IF staining. ARV-471 efficacy testing in ER positive organoids by HCI demonstrated both robust activity and ER degradation. The integration of efficacy and target engagement through HCI provided a mechanistic link between observed responses and molecular mode-of-action. Lastly, findings from organoid screens were compared to responses in matched patient-derived xenograft (PDX) models.
Conclusion: Organoids offer genomically stable, patient-derived models that capture patient diversity and tumor heterogeneity, enabling clinically translatable insights for precision medicine. Our results establish organoid-based screening platforms (OrganoidXploreTM), combining CTG and HCI modalities, as robust tools for preclinical protein degrader evaluation. These platforms uniquely enable identification of tumor subtypes likely to respond to targeted degradation and will potentially facilitate translational biomarker discovery through simultaneous efficacy and mechanistic readouts. PDXO to PDX follow-up opportunities further underscore the utility of these platforms for guiding early therapeutic development and target selection in oncology.
利益披露 Disclosure
M. Hornsveld, None..
D. van der Grinten, None..
D. Verstegen, None..
S. Kouters, None..
E. Kingma, None..
T. Veenendaal, None..
M. Madej, None..
A. Hua, None..
J. Wang, None..
L. Krenning, None..
J. Wang, None..
M. Putker, None..
L. Bourre, None.