Sidiropoulos Dimitrios N, Shin Sarah M, Wetzel Meredith, Girgis Alexander A, Bergman Daniel, Danilova Ludmila, Perikala Susheel, Shu Daniel, Montagne Janelle M, Deshpande Atul, Leatherman James, Dequiedt Lucie, Jacobs Victoria, Ogurtsova Aleksandra, Mo Guanglan, Yuan Xuan, Lvovs Dmitrijs, Stein-O'Brien Genevieve, Yarchoan Mark, Zhu Qingfeng, Harper Elizabeth I, Weeraratna Ashani T, Kiemen Ashley L, Jaffee Elizabeth M, Zheng Lei, Ho Won Jin, Anders Robert A, Fertig Elana J, Kagohara Luciane T
Johns Hopkins Medicine, Baltimore, United States.
Johns Hopkins Medicine, Baltimore, MD, United States.
Cancer Immunol Res. 2025 Aug 15. doi: 10.1158/2326-6066.CIR-25-0387.
Pancreatic adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. Herein, we report the generation of a spatial multi-omics atlas of PDAC tumors and tumor-adjacent lymph nodes from patients treated with combination neoadjuvant immunotherapies. Using machine learning-enabled hematoxylin and eosin image classification models, imaging mass cytometry, and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within and adjacent to TLS spanning across distinct spatial niches and pathologic responses. Unsupervised learning identified TLS-specific spatial gene expression signatures that significantly associated with improved survival in PDAC patients. We identified spatial features of pathologic immune responses, including intratumoral TLS-associated B-cell maturation colocalizing with IgG dissemination and extracellular matrix remodeling. Our findings offer insights into the cellular and molecular landscape of TLS in PDACs during immunotherapy treatment.
胰腺腺癌（PDAC）是一种进展迅速的癌症，对免疫疗法反应不佳。肿瘤内三级淋巴结构（TLS）与罕见的长期PDAC幸存者有关，但TLS在PDAC中的作用及其在更广泛肿瘤微环境背景下的空间关系仍不清楚。在此，我们报告了接受新辅助免疫联合疗法治疗的患者的PDAC肿瘤和肿瘤旁淋巴结的空间多组学图谱的生成。使用基于机器学习的苏木精和伊红图像分类模型、成像质谱流式细胞术以及用于空间转录组学的无监督基因表达矩阵分解方法，我们对跨越不同空间生态位和病理反应的TLS内部及相邻区域的细胞状态进行了表征。无监督学习确定了与PDAC患者生存率提高显著相关的TLS特异性空间基因表达特征。我们确定了病理免疫反应的空间特征，包括肿瘤内与TLS相关的B细胞成熟与IgG扩散和细胞外基质重塑共定位。我们的研究结果为免疫治疗期间PDAC中TLS的细胞和分子景观提供了见解。
