LBPO.ET02 · 实验与分子治疗 · Late-Breaking

单细胞DNA测序揭示芳香化酶抑制新辅助临床试验中的克隆选择、激素适应和治疗耐药

Single cell DNA sequencing reveals clonal selection, hormonal adaptation and treatment resistance in neoadjuvant clinical trial of Aromatase inhibition

编号 LB190 展板 12 时间 4/20 02:00–05:00 区域 Section 53 主讲 Vessela Kristensen, PhD

分会场 Late-Breaking Research: Experimental and Molecular Therapeutics 2

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作者与单位 Authors & Affiliations

Vessela N. Kristensen¹, Denise G. O`Mahony¹, Tom Lesluyes², Ina S. Brorson¹, Patrik H. Vernhoff¹, Ksenia Sokolova³, Miriam R. Aure¹, Grethe G. Alnæs¹, Rebecca M. Hoøen¹, Arvind Y. M. Sundaram¹, Chandra Theesfeld⁴, Stephanie B. Geisler⁵, Torill Sauer Sauer⁵, Nazli Bahrami⁵, Andliena Tahiri⁵, Torben Lüders⁵, Olga Troyanskaya⁶, Charles Vaske⁷, Peter Van Loo⁸, Jürgen Geisler⁵

¹Oslo University Hospital, Oslo, Norway,²Cancer Genomics Laboratory, Francis Crick Institute,, London, United Kingdom,³Princeton Precision Health, Princeton, NJ,⁴Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ,⁵Akershus University Hospital, Oslo, Norway,⁶Center for Computational Biology, Flatiron Institute, New York, NY,⁷Nantomics LLC, Santa Cruz, CA,⁸The University of Texas MD Anderson Cancer Center, Houston, TX

摘要 Abstract

中文摘要

背景。芳香化酶抑制剂（AI）letrozole和exemestane常被序贯用于靶向ER+乳腺癌。然而，对AI的耐药性构成了持续临床获益的主要障碍，而这一现象背后的生物学机制在很大程度上仍属未知。在本研究中，我们基于我们的NeoLetExe临床试验，旨在通过分析序贯治疗期间的亚克隆进化动态，探究对AI耐药的分子基础。方法。我们使用来自11例ER+乳腺癌患者以及NeoLetExe试验3个时间点的全外显子组测序（WES）数据，重建基于癌细胞比例的亚克隆组成。在MissionBio平台上对配对肿瘤样本进行单细胞DNA测序，以验证所鉴定的克隆和变异。通过整合公共数据和ExpectoSc的证据，将亚克隆变异注释到基因。使用Human Base进行通路富集分析。结果。较高癌细胞比例的克隆轨迹与治疗反应降低显著相关（p = 0.023）。通过WES重建的克隆经单细胞DNA测序验证的一致率为81%。对letrozole和exemestane均耐药的克隆表现出PIK3CA/AKT/mTOR信号激活、KRAS通路失调、hedgehog信号和雄激素受体通路，同时伴有广泛的免疫激活和代谢重编程。药物特异性耐药模式显示，exemestane耐药克隆富集于表观遗传调控和miRNA介导的沉默，而letrozole耐药克隆表现出代谢失调，但显著缺乏免疫通路激活。相比之下，治疗敏感克隆维持协调的细胞周期调控、保留DNA损伤反应并保有免疫信号能力。对FDA批准的乳腺癌靶点的分析鉴定出在AI治疗中持续存在的PIK3CA（4例患者）和AKT1（1例患者）的可干预改变，RNA表达分析揭示了48个额外的治疗靶点，涵盖PI3K/AKT/mTOR、CDK4/6、DNA修复（BRCA1/2、ATM）和免疫检查点通路。结论。基于WES的癌细胞比例分析成功捕获了AI治疗期间的亚克隆进化轨迹，揭示了药物特异性机制并鉴定出内分泌治疗耐药中的关键分子参与者。这项工作通过提供可干预的治疗靶点并推进我们对耐药机制的理解，建立了精准肿瘤学方法的框架，以改善序贯AI治疗的临床结局。

查看英文原文 English abstract

Background. The aromatase inhibitors (AI) letrozole and exemestane are often used in sequence in targeting ER+ breast cancers. However, resistance to AI poses a major barrier to sustained clinical benefit, while the biological mechanisms underlying the phenomenon remain largely unknown. In this study, we build on our clinical NeoLetExe trial, with the aim to investigate the molecular basis of resistance to AI, by analysing subclonal evolutionary dynamics during sequential treatment. Methods. We use whole-exome sequencing (WES) data from 11 ER + breast cancer patients and 3 timepoints of the Neoletexe trial to reconstruct cancer cell fraction-based subclonal composition. Single-cell DNA sequencing from matched tumour samples is generated on the MissionBio platform to validate the identified clones and variants. Subclonal variants were annotated to genes by integrating evidence from public data and ExpectoSc. Pathway enrichment analysis using Human Base was conducted. Results. Higher cancer cell fraction clone trajectories were significantly associated with reduced treatment response (p = 0.023). Clones reconstructed by WES were validated at 81% using single-cell DNA sequencing. Clones resistant to both letrozole and exemestane demonstrated PIK3CA/AKT/mTOR signaling activation, KRAS pathway dysregulation, hedgehog signaling, and androgen receptor pathways, alongside extensive immune activation and metabolic reprogramming. Drug-specific resistance patterns showed exemestane-resistant clones enriched for epigenetic control and miRNA-mediated silencing, while letrozole-resistant clones displayed metabolic dysregulation but notably lacked immune pathway activation. In contrast, treatment-sensitive clones maintained coordinated cell cycle control, preserved DNA damage responses, and retained immune signaling capacity. Analysis of FDA-approved breast cancer targets identified actionable alterations in PIK3CA (4 patients) and AKT1 (1 patient) that persisted through AI treatment, with RNA expression analysis revealing 48 additional therapeutic targets spanning PI3K/AKT/mTOR, CDK4/6, DNA repair (BRCA1/2, ATM), and immune checkpoint pathways. Conclusion. WES-based cancer cell fraction analysis successfully captured subclonal evolutionary trajectories during AI treatment, revealing drug-specific mechanisms and identifying key molecular players in endocrine therapy resistance. This work establishes a framework for precision oncology approaches by providing actionable therapeutic targets and advancing our understanding of resistance mechanisms to improve clinical outcomes in sequential AI therapy.

利益披露 Disclosure

V. N. Kristensen, None.. D. G. O`Mahony, None.. T. Lesluyes, None.. I. S. Brorson, None.. P. H. Vernhoff, None.. K. Sokolova, None.. M. R. Aure, None.. G. G. Alnæs, None.. R. M. Hoøen, None.. A. Y. M. Sundaram, None.. C. Theesfeld, None.. S. B. Geisler, None.. T. Sauer, None.. N. Bahrami, None.. A. Tahiri, None.. T. Lüders, None.. O. Troyanskaya, None.. C. Vaske, None.. P. V. Loo, None.. J. Geisler, None.

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