Characterization of the Tumor Immune Microenvironment in Soft Tissue Sarcoma Patients Undergoing Surgery
JOURNAL OF IMMUNOLOGY(2022)
摘要
Abstract Tumor infiltrating lymphocytes (TILs) have been shown to predict survival in soft tissue sarcomas (STS), but the specific contribution of natural killer (NK) and CD8+ T cells to outcomes is undefined. Therefore, we sought to characterize the extent of NK and CD8+ T cell infiltration in STS. Prospectively, we evaluated 15 patients using fresh tumor from surgery for flow cytometric analysis. Retrospectively, we evaluated archived tumor tissue from 90 STS patients by immunohistochemistry (IHC) for CD3, CD8, CD45RO, NKp46, TIGIT, MHC-I, and p53. We analyzed metastasis-free survival (MFS) and overall survival (OS) by Kaplan-Meier method and log-rank test. By flow cytometry, we observed significant variability in CD45+ leukocytes in the STS TME (mean 29±24% of total live cells) with low percentages of tumor-infiltrating CD3-CD56+ NK cells (1.7±1.9% of total live cells and 5.3±3.0% of live CD45+ cells) and CD8+ T cells (1.6±1.6% of total live cells and 29.6±30.5% of live CD45+ cells). By IHC, NK and T cell infiltrates were low (median H score 0, range 0–66.5 and 2.7, range 0–110, respectively). We confirmed a positive correlation between CD8+ T cell infiltration and significantly improved OS (P<0.05) and a trend for improved MFS. We also observed a trend for improved OS among patients with higher NKp46 scores (P=0.07). MHC-I expression positively correlated with both T and NK cell infiltration (P<0.05), whereas TIGIT expression positively correlated with T cell infiltration (P<0.05), but not NK infiltration. Infiltration of NK and CD8+ T cells is overall low in STS patients undergoing surgery but associated with superior OS. Further characterization of the immune infiltrate in STS may yield better biomarkers of prognosis and immune targeting. Supported by the following grants: NIH/NCI 1R03CA252793 NIH/NCI T32 CA251007-01
更多查看译文
关键词
tumor immune microenvironment,soft tissue sarcoma patients
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要