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肿瘤内和肿瘤周围免疫浸润的预后和预测影响。

Prognostic and predictive impact of intra- and peritumoral immune infiltrates.

机构信息

INSERM U872, Centre de Recherche des Cordeliers, France.

出版信息

Cancer Res. 2011 Sep 1;71(17):5601-5. doi: 10.1158/0008-5472.CAN-11-1316. Epub 2011 Aug 16.

Abstract

Leukocyte infiltrates into or around tumor cell nests are found in the context of protumorigenic inflammation and anticancer immunosurveillance. Hence, the detailed composition, density, architecture, and function of leukocyte infiltrates must be analyzed to understand their prognostic impact. The ectopic presence within tumors of high endothelial venule cells, which are normally characteristic for secondary lymphoid organs, correlates with a more pronounced infiltration by T lymphocytes and has a positive predictive impact on local advanced breast cancer treated with neoadjuvant chemotherapy. Recent progress in the field indicates that immune infiltrates of the primary tumors, as well as of metastases, are not only independent prognostic biomarkers but can also constitute predictive factors, suggesting that the pretherapeutic immune response can determine the efficacy of conventional chemotherapies. Moreover, accumulating evidence indicates that chemotherapy can stimulate anticancer immune responses coupled with an increased intratumoral lymphoid infiltration, which correlates with tumor mass reduction and patient survival. Improved methods for the automation of immunohistochemistry and digitalized image analyses will pave the way to an improved understanding of the complex interplay between cancer parenchyma, stroma, and immune effectors, as well as to the routine evaluation of immune-related parameters to the clinical management of cancer patients.

摘要

肿瘤细胞巢内或周围的白细胞浸润存在于促肿瘤发生炎症和抗肿瘤免疫监视的背景下。因此,必须分析白细胞浸润的详细组成、密度、结构和功能,以了解其预后影响。肿瘤内异位存在高内皮静脉细胞,这些细胞通常是次级淋巴器官的特征,与 T 淋巴细胞的更明显浸润相关,并对接受新辅助化疗的局部晚期乳腺癌具有阳性预测影响。该领域的最新进展表明,原发肿瘤和转移瘤的免疫浸润不仅是独立的预后生物标志物,而且还可以构成预测因素,表明治疗前的免疫反应可以决定常规化疗的疗效。此外,越来越多的证据表明,化疗可以刺激抗肿瘤免疫反应,并伴有肿瘤内淋巴细胞浸润增加,这与肿瘤体积缩小和患者生存相关。免疫组织化学和数字化图像分析的自动化改进方法将为更好地理解癌症实质、基质和免疫效应器之间的复杂相互作用以及常规评估与癌症患者临床管理相关的免疫参数铺平道路。

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