决定异体 CAR T 细胞排斥与扩增的细胞和分子机制
Cellular and molecular mechanisms determining allogeneic CAR T cell rejection and expansion.
我们评估了11例接受单一批次cemacabtagene ansegedleucel(cema-cel)治疗的大B细胞淋巴瘤患者,cemacabtagene ansegedleucel是一种异体抗CD19 CAR T产品。
英文原题:Prognostic value of various immune cells and Immunoscore in triple-negative breast cancer.
Prognostic value of various immune cells and Immunoscore in triple-negative breast cancer.
计算图像分析是评估TNBC中免疫调节细胞密度和分布以及计算Immunoscore的可靠工具。Immunoscore在IIB期之后的TNBC中仍保持其预后意义。需要未来研究来确认其预测肿瘤对化疗和免疫治疗反应的潜力。
本研究旨在评估三阴性乳腺癌(TNBC)中多种免疫调节细胞和检测指标的表达状态及预后作用。
回顾性分析68例连续TNBC病例的肿瘤切片,采用免疫组化评估肿瘤免疫细胞五种标志物(CD3/CD4/CD8/CD19/CD163)的表达。使用计算机图像分析量化每个免疫标志物在肿瘤区域、肿瘤浸润边缘和表达热点内的密度和分布。采用自动化方法计算免疫评分。同时分析其他临床特征。
对于所有患者,Kaplan-Meier生存分析显示,肿瘤区域高CD3+信号(无病生存期(DFS),P=0.0014;总生存期(OS),P=0.0031)和总区域高CD3+信号(DFS,P=0.0014;OS,P=0.0031)与更好的生存显著相关。肿瘤区域和总区域高CD4+水平与更好的生存显著相关(P<0.05)。对于Hotspot分析,CD3+在所有Top1、Top2和Top3密度下均与显著更好的生存相关(DFS和OS,P<0.05)。高CD4+水平在Top1和Top3密度下与更好的预后显著相关(DFS和OS,P<0.05)。对于IIB和IIIC期患者,肿瘤区域和所有Top hotspots中的CD3+被发现与生存显著相关(DFS和OS,P<0.05)。CD4+细胞在肿瘤区域、总区域和Top3密度下与生存显著相关(DFS,P=0.0213;OS,P=0.0728)。CD8+细胞在浸润边缘、Top2密度和Top3密度下与生存显著相关。空间参数分析显示,肿瘤细胞与免疫细胞(CD3+、CD4+或CD8+)的高共定位与患者生存显著相关。
BACKGROUND: This study aimed to evaluate the expression status and prognostic role of various immunoregulatory cells and test in triple-negative breast cancer (TNBC). METHODS: The expression of five markers (CD3/CD4/CD8/CD19/CD163) of tumor immune cells was evaluated retrospectively in tumor sections from 68 consecutive cases of TNBC by immunohistochemistry. Computational image analysis was used to quantify the density and distribution of each immune marker within the tumor region, tumor invasive margin, and expression hotspots. Immunoscores were calculated using an automated approach. Other clinical characteristics were also analyzed. RESULTS: For all patients, Kaplan-Meier survival analysis showed that high CD3+ signals in the tumor region (disease-free survival (DFS), P =0.0014; overall survival (OS), P= 0.0031) and total region (DFS, P= 0.0014; OS, P= 0.0031) were significantly associated with better survival. High CD4+ levels in the tumor region and total regions were significantly associated with better survival ( P< 0.05). For Hotspot analysis, CD3+ was associated with significantly better survival for all Top1, Top2, and Top3 densities (DFS and OS, P< 0.05). High CD4+ levels were significantly associated with better prognosis for Top1 and Top3 densities (DFS and OS, P< 0.05). For stage IIB and IIIC patients, CD3+ in the tumor region and all Top hotspots was found to be significantly correlated with survival (DFS and OS, P< 0.05). CD4+ cells were significantly associated with survival in the tumor region, total region, and Top3 density (DFS, P= 0.0213; OS, P= 0.0728). CD8+ cells were significantly associated with survival in the invasive margin, Top2 density, and Top3 density. Spatial parameter analysis showed that high colocalization of tumor cells and immune cells (CD3+, CD4+, or CD8+) was significantly associated with patient survival. CONCLUSION: Computational image analysis is a reliable tool for evaluating the density and distribution of immune regulatory cells and for calculating the Immunoscore in TNBC. The Immunoscore retains its prognostic significance in TNBC later than IIB stage breast cancer. Future studies are required to confirm its potential to predict tumor responses to chemotherapy and immune therapy.
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