Departments of *Pathology †Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA Departments of ‡Pediatrics §Neurosurgery, University of Minnesota, Minneapolis, MN.
J Immunother. 2013 Nov-Dec;36(9):477-89. doi: 10.1097/01.cji.0000436722.46675.4a.
Immune profiling has been widely used to probe mechanisms of immune escape in cancer and identify novel targets for therapy. Two emerging uses of immune signatures are to identify likely responders to immunotherapy regimens among individuals with cancer and to understand the variable responses seen among subjects with cancer in immunotherapy trials. Here, the immune profiles of 6 murine solid tumor models (CT26, 4T1, MAD109, RENCA, LLC, and B16) were correlated to tumor regression and survival in response to 2 immunotherapy regimens. Comprehensive profiles for each model were generated using quantitative reverse transcriptase polymerase chain reaction, immunohistochemistry, and flow cytometry techniques, as well as functional studies of suppressor cell populations (regulatory T cells and myeloid-derived suppressor cells), to analyze intratumoral and draining lymphoid tissues. Tumors were stratified as highly or poorly immunogenic, with highly immunogenic tumors showing a significantly greater presence of T-cell costimulatory molecules and immune suppression in the tumor microenvironment. An absence of tumor-infiltrating cytotoxic T lymphocytes and mature dendritic cells was seen across all models. Delayed tumor growth and increased survival with suppressor cell inhibition and tumor-targeted chemokine+/-dendritic cells vaccine immunotherapy were associated with high tumor immunogenicity in these models. Tumor MHC class I expression correlated with the overall tumor immunogenicity level and was a singular marker to predict immunotherapy response with these regimens. By using experimental tumor models as surrogates for human cancers, these studies demonstrate how select features of an immune profile may be utilized to identify patients most likely to respond to immunotherapy regimens.
免疫分析已广泛用于探究癌症中免疫逃逸的机制，并鉴定新的治疗靶点。免疫特征的两个新用途是在癌症患者中识别可能对免疫治疗方案有反应的人，并了解癌症患者在免疫治疗试验中的不同反应。在这里，6 种鼠类实体瘤模型（CT26、4T1、MAD109、RENCA、LLC 和 B16）的免疫特征与对 2 种免疫治疗方案的肿瘤消退和生存相关联。使用定量逆转录聚合酶链反应、免疫组织化学和流式细胞术技术，以及抑制细胞群体（调节性 T 细胞和髓源抑制细胞）的功能研究，为每个模型生成了全面的特征，以分析肿瘤内和引流淋巴组织。将肿瘤分层为高度或低度免疫原性，高度免疫原性肿瘤在肿瘤微环境中表现出显著更多的 T 细胞共刺激分子和免疫抑制。所有模型均未见肿瘤浸润性细胞毒性 T 淋巴细胞和成熟树突状细胞。在这些模型中，抑制抑制细胞和肿瘤靶向趋化因子+/-树突状细胞疫苗免疫治疗可延迟肿瘤生长并提高生存率，与高肿瘤免疫原性相关。肿瘤 MHC 类 I 表达与肿瘤的整体免疫原性水平相关，是预测这些方案免疫治疗反应的单一标志物。通过将实验性肿瘤模型作为人类癌症的替代品，这些研究表明，免疫特征的某些特征如何用于识别最有可能对免疫治疗方案有反应的患者。
