Abstract 2964: Identification of synergistic dual payload combinations for antibody-drug conjugates to overcome resistance through resistance modeling.

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 CI0.9) 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 Citation Format: Lili Chai, Yue Zhai, Yan Zhang, Ying Bi, Xue Yang, Zhengtai Li, Tiejun Bing. Identification of synergistic dual payload combinations for antibody-drug conjugates to overcome resistance through resistance modeling abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2964.