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空间分析确定树突状细胞生态位是头颈部鳞状细胞癌中帕博利珠单抗治疗疗效的预测指标。

Spatial analysis identifies DC niches as predictors of pembrolizumab therapy in head and neck squamous cell cancer.

作者信息

Oh Juhyun, Hoelzl Jan, Carlson Jonathan C T, Bill Ruben, Peterson Hannah M, Faquin William C, Pittet Mikael J, Pai Sara I, Weissleder Ralph

机构信息

Center for Systems Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA.

Center for Systems Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medical Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany.

出版信息

Cell Rep Med. 2025 May 20;6(5):102100. doi: 10.1016/j.xcrm.2025.102100. Epub 2025 Apr 30.

Abstract

Head and neck squamous cell carcinoma (HNSCC) shows variable response to anti-programmed cell death protein 1 (PD-1) therapy, which can be partially explained by a combined positive score (CPS) of tumor and immune cell expression of programmed death-ligand 1 (PD-L1) within the local tumor microenvironment (TME). To better define TME immune determinants associated with treatment efficacy, we conduct a study of n = 48 HNSCC tumors from patients prior to pembrolizumab therapy. Our investigation combines a rapid bioorthogonal multiplex staining method with computational analysis of whole-slide imaging to capture the single-cell spatial heterogeneity and complexity of the TME. Analyzing 6,316 fields of view (FOVs), we provide comprehensive PD-L1 phenotyping and cell proximity assays across the entirety of tissue sections. While none of the PD-L1 metrics adequately predict response, we find that the spatial organization of CCR7 dendritic cells (DCs) in niches better predicts overall patient survival than CPS alone. This study highlights the importance of understanding the spatial context of immune networks for immunotherapy.

摘要

头颈部鳞状细胞癌(HNSCC)对抗程序性细胞死亡蛋白1(PD-1)疗法的反应各不相同,局部肿瘤微环境(TME)中肿瘤和免疫细胞程序性死亡配体1(PD-L1)的联合阳性评分(CPS)可部分解释这种差异。为了更好地确定与治疗效果相关的TME免疫决定因素,我们对48例接受帕博利珠单抗治疗前患者的HNSCC肿瘤进行了研究。我们的研究将一种快速的生物正交多重染色方法与全切片成像的计算分析相结合,以捕捉TME的单细胞空间异质性和复杂性。通过分析6316个视野(FOV),我们在整个组织切片上提供了全面的PD-L1表型分析和细胞邻近性检测。虽然没有一个PD-L1指标能充分预测反应,但我们发现,生态位中CCR7树突状细胞(DC)的空间组织比单独的CPS更能预测患者的总体生存。这项研究强调了了解免疫网络空间背景对免疫治疗的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dc3/12147904/94d123c56a14/fx1.jpg

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