PO.CL01.03 · 临床研究

发现用于预测HRR驱动实体瘤治疗反应的循环蛋白质组学生物标志物

Discovery of predictive circulating proteomic biomarkers for therapy response in HRR-driven solid tumors

海报缩略图:发现用于预测HRR驱动实体瘤治疗反应的循环蛋白质组学生物标志物
编号 2438 展板 8 时间 4/20 09:00–12:00 区域 Section 40 主讲 Yuehan Feng, PhD
分会场 Biomarkers Predictive of Therapeutic Benefit 3
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作者与单位 Authors & Affiliations

Anamarija Pfeiffer1, Wouter van Bergen1, Martin Mehnert1, Polina Shichkova1, Vanessa Bühlmann1, Amaury Lachaud1, Yuehan Feng1, Takayuki Yoshino2, Norio Nonomura3, Taigo Kato3

1Biognosys AG, Schlieren, Switzerland,2Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center East, Kashiwa, Chiba, Japan,3Department of Urology, The University of Osaka, Graduate School of Medicine, Suita, Osaka, Japan

摘要 Abstract

中文摘要
背景 IMAGENE试验(jRCT2051210120)是一项多中心、泛肿瘤、II期篮子研究,评估PARP抑制剂niraparib与PD-1抑制剂联合用于既往免疫检查点抑制剂(ICI)治疗后进展且携带同源重组修复(HRR)基因突变患者的疗效。在这一泛肿瘤背景下,入组患者包括不可切除的局部晚期尿路上皮癌(UC)、肾细胞癌(RCC)、胃癌(GC)、食管癌(EC)、头颈癌(HNC)和黑色素瘤(MC),均携带HRR基因改变。2022年4月至2024年4月期间,共有45例患者入组主要队列。 现有的生物标志物如PD-L1表达和肿瘤突变负荷(TMB),在ICI治疗和HRR驱动的肿瘤中预测能力有限。为弥补这一不足,我们对IMAGENE试验中入组的HNC受试者的基线和治疗中样本进行了无偏倚的深度血浆蛋白质组学分析,并辅以靶向炎症标志物panel。 方法 在患者基线以及接受niraparib联合抗PD-1治疗后的两个给药后时间点采集枸橼酸血浆样本。为研究应答者与非应答者之间的蛋白质组学差异及其时间动态,我们采用了两种互补方法:(i) 使用P2富集系统结合质谱(DIA-MS)进行无偏倚血浆蛋白质组分析;(ii) 使用约250个标志物的邻近连接测定(NULISA)panel对炎症蛋白进行靶向定量。 结果 通过P2富集LC-MS/MS,在所有样本中共定量了4,875种蛋白和67,311条肽段。治疗后样本的比较分析识别出160种在应答者与非应答者之间丰度存在差异的蛋白,富集于补体激活和免疫相关通路。纵向分析揭示了应答者治疗前后有46种蛋白显著改变,再次凸显免疫和补体系统激活为关键特征。靶向NULISA分析证实了20个在应答者与非应答者之间存在差异的标志物,以及11个在应答过程中动态调控的标志物。总体而言,这些发现提示补体激活、体液免疫反应和B细胞介导的免疫是niraparib联合抗PD-1联合治疗疗效反应的关键决定因素。
查看英文原文 English abstract
Background The IMAGENE trial (jRCT2051210120) is a multicenter, tumor-agnostic, phase II basket study evaluating the combination of the PARP inhibitor niraparib and PD-1 inhibitors in patients with homologous recombination repair (HRR) gene mutations who have progressed following prior immune checkpoint inhibitor (ICI) therapy. In this tumor-agnostic setting, patients were enrolled with unresectable, locally advanced urothelial carcinoma (UC), renal cell carcinoma (RCC), gastric cancer (GC), esophageal cancer (EC), head and neck cancer (HNC), and melanoma (MC), all harboring HRR gene alterations. A total of 45 patients were enrolled in the primary cohort between April 2022 and April 2024. Existing biomarkers such as PD-L1 expression and tumor mutation burden (TMB) have shown limited predictive power in ICI-treated and HRR-driven tumors. To address this gap, we performed unbiased deep plasma proteomic profiling, complemented by a targeted inflammatory marker panel, on baseline and on-treatment samples from HNC participants enrolled in the IMAGENE trial. Methods Citrate plasma samples were collected from patients at baseline and two post-dose time points after treatment with niraparib plus anti-PD-1 therapy. To study proteomic differences between responders and non-responders, and their temporal dynamics, we employed two complementary approaches: (i) unbiased plasma proteome profiling using the P2 enrichment system combined with mass spectrometry (DIA-MS), and (ii) targeted quantification of inflammatory proteins using a proximity ligation assay (NULISA) panel of ~250 markers. Results A total of 4,875 proteins and 67,311 peptides were quantified by P2-enriched LC-MS/MS across all samples. Comparative analysis of post-treatment samples identified 160 proteins differentially abundant between responders and non-responders, with enrichment in complement activation and immune-related pathways. Longitudinal analysis revealed 46 proteins significantly altered between pre- and post-treatment samples in responders, again highlighting immune and complement system activation as key features. Targeted NULISA profiling confirmed 20 markers differing between responders and non-responders and 11 markers dynamically regulated during response. Collectively, these findings suggest that complement activation, humoral immune response, and B-cell-mediated immunity are critical determinants of therapeutic response to niraparib plus anti-PD-1 combination therapy.
利益披露 Disclosure
A. Pfeiffer, None.. W. van Bergen, None.. M. Mehnert, None.. P. Shichkova, None.. V. Bühlmann, None.. A. Lachaud, None.. Y. Feng, None.. T. Yoshino, None.. N. Nonomura, None.. T. Kato, None.

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