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Spatial heterogeneity of tumor microenvironment influences the prognosis of clear cell renal cell carcinoma

肾透明细胞癌 肿瘤微环境 免疫系统 CD8型 癌症研究 生物 细胞 T细胞 表型 癌症 细胞毒性T细胞 病理 肾细胞癌 免疫学 医学 体外 基因 生物化学 遗传学
作者
Dawei Zhang,Yuanli Ni,Yongquan Wang,Juan Feng,Na Zhuang,Jiatao Li,Limei Liu,Wenhao Shen,Zheng Ji,Wei Zheng,Qian Cheng,Juanjuan Shan,Zhansong Zhou
出处
期刊:Journal of Translational Medicine [BioMed Central]
卷期号:21 (1) 被引量:13
标识
DOI:10.1186/s12967-023-04336-8
摘要

Abstract Background Clear cell renal cell carcinoma (ccRCC) is an immunologically and histologically diverse tumor. However, how the structural heterogeneity of tumor microenvironment (TME) affects cancer progression and treatment response remains unclear. Hence, we characterized the TME architectures of ccRCC tissues using imaging mass cytometry (IMC) and explored their associations with clinical outcome and therapeutic response. Methods Using IMC, we profiled the TME landscape of ccRCC and paracancerous tissue by measuring 17 markers involved in tissue architecture, immune cell and immune activation. In the ccRCC tissue, we identified distinct immune architectures of ccRCC tissue based on the mix score and performed cellular neighborhood (CN) analysis to subdivide TME phenotypes. Moreover, we assessed the relationship between the different TME phenotypes and ccRCC patient survival, clinical features and treatment response. Results We found that ccRCC tissues had higher levels of CD8 + T cells, CD163 − macrophages, Treg cells, endothelial cells, and fibroblasts than paracancerous tissues. Immune infiltrates in ccRCC tissues distinctly showed clustered and scattered patterns. Within the clustered pattern, we identified two subtypes with different clinical outcomes based on CN analysis. The TLS-like phenotype had cell communities resembling tertiary lymphoid structures, characterized by cell–cell interactions of CD8 + T cells-B cells and GZMB + CD8 + T cells-B cells, which exhibited anti-tumor features and favorable outcomes, while the Macrophage/T-clustered phenotype with macrophage- or T cell-dominated cell communities had a poor prognosis. Patients with scattered immune architecture could be further divided into scattered-CN-hot and scattered-CN-cold phenotypes based on the presence or absence of immune CNs, but both had a better prognosis than the macrophage/T-clustered phenotype. We further analyzed the relationship between the TME phenotypes and treatment response in five metastatic ccRCC patients treated with sunitinib, and found that all three responders were scattered-CN-hot phenotype while both non-responders were macrophage/T-clustered phenotype. Conclusion Our study revealed the structural heterogeneity of TME in ccRCC and its impact on clinical outcome and personalized treatment. These findings highlight the potential of IMC and CN analysis for characterizing TME structural units in cancer research.
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