Trem2-expressing multinucleated giant macrophages are a biomarker of good prognosis in head and neck squamous cell carcinoma

IF 29.7 1区 医学 Q1 ONCOLOGY
Gregoire Gessain, Ahmed-Amine Anzali, Marvin Lerousseau, Kevin Mulder, Mathilde Bied, Anne Auperin, Daniel Stockholm, Nicolas Signolle, Farah Sassi, Maria Eugenia Marques Da Costa, Antonin Marchais, Alexandre Sayadi, Daniela Weidner, Stefan Uderhardt, Quentin Blampey, Sumanth Reddy Nakkireddy, Sophie Broutin, Charles-Antoine Dutertre, Pierre Busson, Thomas Walter, Alix Marhic, Antoine Moya-Plana, Joanne Guerlain, Ingrid Breuskin, Odile Casiraghi, Philippe Gorphe, Marion Classe, Jean-Yves Scoazec, Camille Bleriot, Florent Ginhoux
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引用次数: 0

Abstract

Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk-management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC) – a type of macrophages – in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative-chemotherapy-treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the anti-tumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor associated macrophages, which co-localized in keratin tumor niches.
表达 Trem2 的多核巨型巨噬细胞是头颈部鳞状细胞癌良好预后的生物标志物
头颈部鳞状细胞癌(HNSCC)患者的预后往往不佳,原因是他们的风险管理和治疗策略不够理想;然而,将新型预后生物标志物纳入临床实践是一项挑战。在这里,我们报告了多核巨细胞(MGC)--巨噬细胞的一种--在HNSCC患者的肿瘤中的存在,这与未经治疗和术前化疗患者的良好预后有关。重要的是,术前治疗后肿瘤中的巨噬细胞密度增加,表明这些细胞在抗肿瘤反应中发挥作用。为了将 MGC 密度作为一种预后标志物进行临床转化,我们开发了一种深度学习模型,用于在常规染色的病理切片图像上自动量化 MGC 密度。最后,我们利用空间转录组学和蛋白质组学方法描述了与 MGC 相关的肿瘤微环境,并观察到中心记忆 CD4 T 细胞的增加。我们定义了一种 MGC 特异性特征,类似于表达 TREM2 的单核肿瘤相关巨噬细胞,它们共同定位在角蛋白肿瘤龛中。
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来源期刊
Cancer discovery
Cancer discovery ONCOLOGY-
CiteScore
22.90
自引率
1.40%
发文量
838
审稿时长
6-12 weeks
期刊介绍: Cancer Discovery publishes high-impact, peer-reviewed articles detailing significant advances in both research and clinical trials. Serving as a premier cancer information resource, the journal also features Review Articles, Perspectives, Commentaries, News stories, and Research Watch summaries to keep readers abreast of the latest findings in the field. Covering a wide range of topics, from laboratory research to clinical trials and epidemiologic studies, Cancer Discovery spans the entire spectrum of cancer research and medicine.
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