PO.CL01.12 · 临床研究
空间转录组学揭示乳腺癌对trastuzumab deruxtecan耐药的药代动力学屏障和肿瘤内在决定因素
Spatial transcriptomics uncovers pharmacokinetic barriers and tumor-intrinsic determinants of resistance to trastuzumab deruxtecan in breast cancer
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
引言：Trastuzumab deruxtecan（T-DXd）是一种抗体药物偶联物（ADC），对HER2阳性和HER2低表达转移性乳腺癌（MBC）均有效。虽然已发现HER2表达水平与T-DXd应答之间的相关性，但有效的生物标志物及敏感或耐药机制仍难以捉摸，部分原因在于T-DXd复杂的药代动力学。我们的目标是阐明与T-DXd治疗应答和耐药相关的空间转录组（ST）特征。
方法：我们使用10x Genomics Visium HD对接受T-DXd治疗的MBC患者的福尔马林固定石蜡包埋肿瘤组织进行ST。T-DXd应答者定义为出现客观缓解或疾病稳定超过6个月的患者，非应答者定义为其他情况。将应答者的治疗前活检样本片段指定为“敏感片段”，而将非应答者的治疗前活检样本或应答者进展后活检样本的片段定义为“耐药片段”。进行了多种转录组分析，包括基于房室模型的方法，从T-DXd药代动力学谱估算抗体和载荷浓度。
结果：共有来自13例患者的20份肿瘤组织可用，包括5例患者的治疗前后配对活检。质控后，纳入11份T-DXd敏感组织（19个片段）和7份耐药组织样本（27个片段）进行分析。利用自相关相关指数，ERBB2基因表达的空间异质性影响结局，癌细胞ERBB2基因表达分布越分散，应答越好。在HER2阳性肿瘤中，耐药片段显示ERBB2基因表达下调及PI3K和EGFR通路激活，自分泌amphiregulin-EGFR信号成为候选耐药机制。在HER2低表达肿瘤中，耐药显著与药代动力学屏障相关：耐药片段表现出癌-血管距离增加、ERBB2表达与cathepsin接头切割酶的共定位减少以及预测的肿瘤-非肿瘤载荷浓度比降低。对配对治疗前后样本的探索性纵向分析揭示了耐药时血管-癌距离随时间增加。
结论：这些发现凸显了T-DXd疗效的潜在决定因素。我们的研究证明了ST在临床样本中揭示ADC应答机制及潜在新型治疗策略方面的实用性。
查看英文原文 English abstract
Introduction: Trastuzumab deruxtecan (T-DXd) is an antibody-drug conjugate (ADC) that is effective for both HER2-positive and HER2-low metastatic breast cancers (MBC). While correlation between HER2 expression levels and response to T-DXd was identified, effective biomarkers and mechanisms of sensitivity or resistance remain elusive, partly due to complex pharmacokinetics of T-DXd. Our goal is to delineate spatial transcriptomic (ST) features which is associated with therapeutic response and resistance to T-DXd.
Methods: We performed ST with the 10x Genomics Visium HD on formalin-fixed paraffin-embedded tumor tissues from patients with MBC treated with T-DXd. Responders to T-DXd were defined as patients who experienced objective response or stable disease for more than 6 months, and non-responders were defined as otherwise. Fragments of pre-treatment biopsy samples from patients classified as responders were designated as "sensitive fragment” while that of pre-treatment biopsy samples from non-responders or post-progression biopsy samples from responders were defined as “resistant fragment”. Various transcriptome analyses were performed including the compartment modeling-based methods for estimating antibody and payload concentrations from T-DXd pharmacokinetic profiles.
Results: A total of 20 tumor tissues from 13 patients were available including matched pre- and post-treatment biopsied in 5 patients. After quality check, 11 T-DXd-sensitive (19 fragments) and 7 resistant tissue samples (27 fragments) were included for analysis. Utilizing autocorrelation-related indices, spatial heterogeneity of ERBB2 gene expression influenced outcomes, with more dispersed ERBB2 gene expression distributions by cancer cells correlating with improved response. In HER2-positive tumors, resistant fragments showed downregulation of ERBB2 gene expression and activation of PI3K and EGFR pathways, with autocrine amphiregulin-EGFR signaling emerging as a candidate resistance mechanism. In HER2-low tumors, resistance was notably associated with pharmacokinetic barriers: resistant fragments exhibited increased cancer-vessel distance, reduced colocalization of ERBB2 expression with cathepsin linker-cleaving enzymes and diminished predicted tumor-to-non-tumor payload concentration ratio. Exploratory longitudinal analyses of paired pre- and post-treatment samples revealed temporal increases in vessel-cancer distance at resistance.
Conclusion: These findings highlight potential determinants of T-DXd efficacy. Our study demonstrates the utility of ST for uncovering ADC response mechanisms in clinical samples and potential novel therapeutic strategies.
利益披露 Disclosure
C. Park,
has received consulting fees from AstraZeneca ).
has received consulting fees from Samsung Bioepis ).
M. Choi, None..
J. Koh, None..
S. Bae, None..
H. Choi, None..
K. Na, None..
D. Lee, None.
K. Lee,
received research funding from Roche ).
reported honoraria from AstraZeneca ).
reported honoraria from Eisai ).
reported honoraria from Lilly ).
reported honoraria from Novartis ).
reported honoraria from Roche ).
reported honoraria from Pfizer ).
H. Ryu, None.
S. Im,
received research grants from Daiichi Sankyo ).
received research grants from AstraZeneca ).
received research grants from Eisai ).
received research grants from Daewoong Pharm ).
received research grants from Pfizer ).
received research grants from Roche ).
received research grants from Boryung Pharm ).
received consulting fees from Daiichi Sankyo ).
received consulting fees from AstraZeneca ).
received consulting fees from Hanmi ).
received consulting fees from Eisai ).
received consulting fees from Lilly ).
received consulting fees from MSD ).
received consulting fees from Idience ).
received consulting fees from Novartis ).
received consulting fees from Pfizer ).
received consulting fees from Roche ).
received consulting fees from GSK ).