PO.ET03.06 · 实验与分子治疗
通过耐药建模鉴定抗体-药物偶联物的协同双有效载荷组合以克服耐药
Identification of synergistic dual payload combinations for antibody-drug conjugates to overcome resistance through resistance modeling
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：抗体-药物偶联物（ADC）是强效的癌症治疗药物，但对ADC或其单一有效载荷的耐药仍是一个关键的临床障碍。双有效载荷ADC——通过单一抗体共递送两种不同的有效载荷——通过利用互补机制提供了一种有前景的解决方案。临床进展和在研候选药物验证了这一方法。然而，用于鉴定针对耐药的协同有效载荷组合并解析其机制的系统性框架尚不成熟。
方法：我们通过长期筛选建立了10余株针对临床ADC/有效载荷的耐药细胞系。为阐明耐药机制并预测协同组合，我们对耐药/亲本配对进行了RNA-seq和WES，随后进行通路富集和合成致死预测。我们筛选了100余种双有效载荷组合（耐药/亲本细胞组，活力实验）以鉴定命中组合。通过生物信息学分析研究命中组合的机制，并通过Western blot/免疫荧光（DDR标志物和细胞周期标志物）进行验证。
结果：生物信息学分析鉴定出关键的耐药机制，包括P-gp转运体升高和抗原表达降低。我们筛选了100余种组合（TOPO1抑制剂与DDR抑制剂、CDK抑制剂、TYR激酶抑制剂、毒素配对），并鉴定出三种协同命中组合，包括TOPO1抑制剂与DDR相关靶点及细胞周期靶点的组合。所有命中组合在耐药细胞中均表现出显著的协同效应（IC50位移>3倍且CI<0.9），而单一有效载荷疗效极小。生物信息学表明增强的DNA损伤和细胞周期失调是核心机制，并通过通路实验得到验证。
结论：我们的研究建立了一个系统性框架（耐药建模、生物信息学、高通量筛选）以鉴定ADC的协同双有效载荷组合。三种基于TOPO1的命中组合通过已验证的DDR/细胞周期机制强效克服耐药。这项工作为新一代双有效载荷ADC的开发提供了合理依据，并为加速在各种癌症治疗中发现克服耐药的方案提供了一种可推广的策略。
查看英文原文 English abstract
Background: Antibody-Drug Conjugates (ADCs) are potent cancer therapeutics, but resistance to ADCs or their single payloads remains a critical clinical barrier. Dual payload ADCs-co-delivering two distinct payloads via a single antibody-offer a promising solution by leveraging complementary mechanisms. Clinical progress and pipeline candidates validate this approach. However, a systematic framework to identify resistance-tailored synergistic payload combinations and decipher their mechanisms is underdeveloped.
Methods: We established 10+ drug-resistant cell lines against clinical ADCs/payloads via long-term selection. To elucidate resistance mechanisms and predict synergistic combinations, we performed RNA-seq and WES on resistant/parental pairs, followed by pathway enrichment and synthetic lethality prediction. We screened 100+ dual payload combinations (resistant/parental cell panel, viability assay) to identify hits. Mechanisms of hit combinations were investigated via bioinformatics analysis and validated by Western blotting/immunofluorescence (DDR markers and cell cycle markers).
Results: bioinformatics analysis identified key resistance mechanisms including elevated P-gp transporter and reduced antigen expression. We screened 100+ combinations (TOPO1 inhibitors paired with DDR inhibitors, CDK inhibitors, TYR kinase inhibitors, toxins) and identified three synergistic hits including TOPO1 inhibitor combined with DDR related targets and cell cycle targets. All hits showed significant synergistic effect (IC50 shifts >3 folds and CI<0.9) in resistant cells, while single payloads had minimal efficacy. Bioinformatics implicated enhanced DNA damage and cell cycle dysregulation as core mechanisms, validated by pathway assays.
Conclusions: Our study establishes a systematic framework (resistance modeling, bioinformatics, high-throughput screening) to identify synergistic dual payload combinations for ADCs. The three TOPO1-based hit combinations potently overcome resistance via validated DDR/cell cycle mechanisms. This work provides a rational basis for next-generation dual-payload ADC development and a generalizable strategy to accelerate resistance-overcoming regimen discovery across cancer therapies
利益披露 Disclosure
L. Chai, None..
Y. Zhai, None..
Y. Zhang, None..
Y. Bi, None..
X. Yang, None..
Z. Li, None..
T. Bing, None.