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癌症患者的外周和肿瘤内免疫细胞格局:肿瘤生物学的替代指标和预后预测工具。

The Peripheral and Intratumoral Immune Cell Landscape in Cancer Patients: A Proxy for Tumor Biology and a Tool for Outcome Prediction.

作者信息

Schnell Annette, Schmidl Christian, Herr Wolfgang, Siska Peter J

机构信息

Department of Internal Medicine III, Hematology and Oncology, University Hospital Regensburg, 93053 Regensburg, Germany.

Regensburg Centre for Interventional Immunology and University Medical Center of Regensburg, 93053 Regensburg, Germany.

出版信息

Biomedicines. 2018 Feb 24;6(1):25. doi: 10.3390/biomedicines6010025.

DOI:10.3390/biomedicines6010025
PMID:29495308
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5874682/
Abstract

Functional systemic and local immunity is required for effective anti-tumor responses. In addition to an active engagement with cancer cells and tumor stroma, immune cells can be affected and are often found to be dysregulated in cancer patients. The impact of tumors on local and systemic immunity can be assessed using a variety of approaches ranging from low-dimensional analyses that are performed on large patient cohorts to multi-dimensional assays that are technically and logistically challenging and are therefore confined to a limited sample size. Many of these strategies have been established in recent years leading to exciting findings. Not only were analyses of immune cells in tumor patients able to predict the clinical course of the disease and patients' survival, numerous studies also detected changes in the immune landscape that correlated with responses to novel immunotherapies. This review will provide an overview of established and novel tools for assessing immune cells in tumor patients and will discuss exemplary studies that utilized these techniques to predict patient outcomes.

摘要

有效的抗肿瘤反应需要功能性的全身和局部免疫。除了与癌细胞和肿瘤基质积极相互作用外,免疫细胞也会受到影响,并且在癌症患者中经常发现其功能失调。肿瘤对局部和全身免疫的影响可以通过多种方法进行评估,从对大量患者队列进行的低维分析到技术和后勤方面具有挑战性、因此仅限于有限样本量的多维度检测。近年来已经建立了许多这些策略,带来了令人兴奋的发现。对肿瘤患者免疫细胞的分析不仅能够预测疾病的临床进程和患者的生存情况,大量研究还检测到了与新型免疫疗法反应相关的免疫格局变化。本综述将概述评估肿瘤患者免疫细胞的既定和新型工具,并将讨论利用这些技术预测患者预后的示例性研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/522c/5874682/46127e241b5a/biomedicines-06-00025-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/522c/5874682/46127e241b5a/biomedicines-06-00025-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/522c/5874682/46127e241b5a/biomedicines-06-00025-g001.jpg

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