PO.CL01.23 · 临床研究
空间免疫特征预测HPV阳性口咽癌的预后:一项临床试验的结果
Spatial immune signatures predict outcomes in HPV-positive oropharyngeal cancer: Results of a clinical trial
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摘要 Abstract
中文摘要
背景:近年来,人乳头瘤病毒(HPV)相关口咽癌(OPC)的发病率一直在上升。虽然HPV阳性OPC患者的预后通常比HPV阴性疾病患者更好,但仍有一部分患者会出现局部区域复发和远处转移。这些临床挑战凸显了更好地理解肿瘤微环境(TME)及其在调节治疗反应中作用的必要性。我们假设完全缓解者与部分缓解/无反应者之间TME的组成和空间动态存在差异,而这些差异可能作为预测性生物标志物。
方法:这项回顾性研究纳入了2010年至2023年间在蒙特利尔两家主要癌症中心接受治疗的p16阳性OPC患者。检索了福尔马林固定石蜡包埋(FFPE)组织块,并构建了组织微阵列(TMAs),使用成像质谱流式细胞术(IMC)进行高维免疫分析。跨治疗反应类别(完全缓解者与部分缓解者)和治疗阶段(治疗前与治疗后)分析了免疫细胞群体。应用基于深度学习的细胞分割来量化免疫细胞亚群、评估空间结构,并对TME进行网络和邻域分析,以识别潜在的预测性和预后性免疫特征。
结果:从HPV阳性(p16+)OPC患者获取组织标本,其中79.6%为男性,平均年龄62.5岁。IMC揭示了各反应组之间存在不同的免疫图谱。在完全缓解者中,治疗诱导了抗肿瘤免疫细胞(如CD8+ T细胞和B细胞)的强力募集,提示治疗后呈现活化的免疫表型。相比之下,无反应者在治疗后表现出免疫抑制性或促肿瘤细胞类型的富集。空间共定位和细胞-细胞相互作用分析进一步表明,B细胞与T细胞的相互作用可能有助于治疗成功。
结论与影响:本研究为HPV阳性OPC治疗前后免疫微环境的空间和细胞重塑提供了新的见解。我们的发现凸显了基于IMC的免疫分析的预后潜力,并支持开发预测性生物标志物,以指导选择可能从新辅助化疗或免疫调节干预中获益的患者。
查看英文原文 English abstract
Background: The incidence of Human Papillomavirus (HPV)-associated oropharyngeal cancer (OPC) has been increasing in recent years. While patients with HPV-positive OPC generally demonstrate more favorable outcomes compared to those with HPV-negative disease, a subset still experiences locoregional recurrence and distant metastasis. These clinical challenges underscore the need for a better understanding of the tumor microenvironment (TME) and its role in modulating treatment response. We hypothesized that the composition and spatial dynamics of the TME differ between complete responders and partial/non-responders, and these differences may serve as predictive biomarkers.
Methods: This retrospective study included patients with p16-positive OPC treated at two major cancer centers in Montreal between 2010 and 2023. Formalin-Fixed Paraffin-Embedded (FFPE) tissue blocks were retrieved, and tissue microarrays (TMAs) were constructed for high-dimensional immune profiling using imaging mass cytometry (IMC). Immune cell populations were analyzed across treatment response categories (complete vs. partial responders) and treatment stages (pre- vs. post-treatment). Deep learning-based cell segmentation was applied to quantify immune cell subsets, assess spatial architecture, and perform network and neighborhood analyses of the TME to identify potential predictive and prognostic immune signatures.
Results: Tissue specimens were obtained from HPV-positive (p16+) OPC patients, of whom 79.6% were male, with a mean age of 62.5 years. IMC revealed distinct immune landscapes between response groups. In complete responders, treatment induced a robust recruitment of anti-tumor immune cells (e.g., CD8+ T cells and B cells), suggesting an activated immune phenotype post-treatment. In contrast, non-responders exhibited enrichment of immunosuppressive or tumor-promoting cell types following therapy. Spatial co-localization and cell-cell interaction analyses further indicated that B and T cells interactions may contribute to therapeutic success.
Conclusion and Impact: This study provides novel insights into the spatial and cellular remodeling of the immune microenvironment in HPV-positive OPC before and after treatment. Our findings highlight the prognostic potential of IMC-based immune profiling and support the development of predictive biomarkers to guide the selection of patients who may benefit from neoadjuvant chemotherapy or immunomodulatory interventions.
利益披露 Disclosure
S. Landais, None..
S. Wurzba, None.