D'Assoro, Tony

3022 Background: Pharmacological blockade of Aurora-A mitotic kinase (AURKA) oncogenic pathway represents a promising therapeutic strategy to inhibit breast cancer plasticity and progression. However, treatment with the selective AURKA inhibitor alisertib is followed by acquired on-target mutations in a subset of patients that are linked to alisertib resistance and tumor progression. Current resistance mechanisms are typically identified retrospectively after therapeutic failure. We evaluated whether Dynaptive, a structure- and evolution-aware artificial intelligence (AI) platform, could prospectively predict treatment-induced AURKA resistance mutations prior to experimental observation. Methods: We identified acquired on-target mutations in patients from the alisertib Phase-II clinical trial. These mutations were cross-matched against Dynaptive predictions that had been generated independently of any experimental resistance data. Dynaptive integrates protein conformational ensembles and evolutionary sequence constraints to predict mutational hotspots and assess their functional and drug-binding impact. Identified mutations were evaluated against large-scale population datasets to determine natural occurrence. Results: Several AURKA mutations observed in patients that showed resistance to alisertib were prospectively predicted by Dynaptive despite being entirely absent from prior population datasets. These mutations were not observed previously in either healthy or cancer cohorts described in the public domain. Significantly, the most frequently occurring AURKA resistance mutation occurred at a residue ranked second among predicted mutational hotspots and were predicted to reduce alisertib binding affinity by ≥10-fold. Across all variants, absence from population datasets and emergence only following treatment support a treatment-induced resistance mechanism. Conclusions: A structure-aware AI platform prospectively identified clinically relevant, treatment-induced AURKA resistance mutations prior to experimental detection. These findings demonstrate the feasibility of predictive modeling to anticipate resistance mechanisms and support the development of next-generation AURKA inhibitors optimized to overcome mutations-driven resistance and to improve therapeutic efficacy, safety and durability.

Abstract Introduction: Eicosanoid mediated mechanisms of hormone therapy resistance in ER+HER2- breast cancer are poorly understood. Cytochrome P450 arachidonic acid (AA) epoxygenase-derived epoxyeicosatrienoic acids (EETs) contribute to breast cancer progression by promoting mitochondrial oxidative phosphorylation (OXPHOS). However, it remains unclear how EETs contribute to hormonal therapy resistance. In this study, the well-known letrozole resistant (LR) MCF-7 AC1 cell line overexpressing aromatase was selected for fulvestrant resistance (FR). A clonal cell line resistant to letrozole and fulvestrant (LR/FR) also exhibited resistance to palbociclib (PR) (MCF-7 AC1 LR/FR/PR). Xenograft tumors of this cell line were resistant to letrozole, fulvestrant, and palbociclib. Structure activity studies and modeling led to the development of CYP3A4 AA epoxygenase inhibiting biguanides hexyl cuban-1-yl biguanide (HCB) and fluorinated hexyl derivatives C5F2-HCB and C6F3-HCB. Fluorination on the hexyl moiety led to broader inhibition of EET regioisomer biosynthesis. These agents were tested for inhibition of proliferation, signaling, and OXPHOS/glycolysis balance in the MCF-7 AC1 LR/FR/PR cell line. Results: In the MCF-7 AC1 LR/FR/PR clonal cell line cyclin D1 and estrogen receptor (ER) expression were undetectable, while cyclin E1, CDK4, CDK6, CYP3A4, and c-MYC were upregulated 11, 40, 13, 10, and 12- fold (n=3, p<0.001) compared to the MCF-7 cell line. LC-MS analysis demonstrated 1.8, 1.4, and 1.2- fold higher total cellular levels of (±)8,9, (±)11,12, and (±)14,15-EET in the MCF-7 AC1 LR/FR/PR cell line compared to the MCF-7 cell line (n=3, p<0.05). C6F3-HCB suppressed cellular levels of EETs: (±)8,9-EET by 55% (n=3, p<0.031), (±)11,12-EET by 53% (n=3, p<0.029), and (±)14,15-EET by 60% (n=3, P<0.0001). The MCF-7 AC1 LR/FR/PR cell line was more potently inhibited by hexyl-cuban-1-yl biguanides compared to the MCF-7 cell line, exhibiting lower IC50 values (MCF-7 AC1 LR/FR/PR IC50 vs. MCF-7 IC50; HCB 4.1 vs. 7.0 uM; for C5F2-HCB 10 vs. 25 uM; C6F3-HCB: 5.4 vs. 12 uM; P values all <0.05). Measurement of spare respiratory capacity revealed that the MCF-7 AC1 LR/FR/PR cell line had 4.2% spare respiratory capacity compared to 34% for MCF-7, indicating a lower OXPHOS reserve for the resistant cells. Additionally, the MCF-7 AC1 LR/FR/PR cell line displayed a 2.4-fold higher extracellular acidification rate (ECAR) than the MCF-7 cell line, indicating a higher glycolysis rate (Warburg effect) in the resistant cells. Conclusion: Selection for fulvestrant resistance of MCF-7 AC1 cells resulted in upregulation of CYP3A4 and biosynthesis of hormone therapy resistance associated EETs while correlating with greater sensitivity to fluorinated hexyl-cuban-1-yl biguanides that inhibit EET biosynthesis. Citation Format: Zhijun Guo, Jianxun Lei, Allison Makovec, Swaathi Jayaraman, John R. Hawse, Carol Lange, Elizabeth Ambrose, Gunda I. Georg, Tony D'Assoro, Goetz P. Matthew, David A. Potter. Mechanisms of endocrine resistance to letrozole, fulvestrant, and palbociclib are associated with increased sensitivity to hexyl-cuban-1-yl biguanide inhibitors of CYP3A4 mediated epoxyeicosatrienoic acid biosynthesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB334.