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T Cell-Inflamed versus Non-T Cell-Inflamed Tumors: A Conceptual Framework for Cancer Immunotherapy Drug Development and Combination Therapy Selection

机译:T细胞发炎与非T细胞发炎的肿瘤:癌症免疫治疗药物开发和联合治疗选择的概念框架

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Immunotherapies such as checkpoint-blocking antibodies and adoptive cell transfer are emerging as treatments for a growing number of cancers. Despite clinical activity of immunotherapies across a range of cancer types, the majority of patients fail to respond to these treatments and resistance mechanisms remain incompletely defined. Responses to immunotherapy preferentially occur in tumors with a preexisting antitumor T-cell response that can most robustly be measured via expression of dendritic cell and CD8(+) T cell-associated genes. The tumor subset with high expression of this signature has been described as the T cell-"inflamed" phenotype. Segregating tumors by expression of the inflamed signature may help predict immunotherapy responsiveness. Understanding mechanisms of resistance in both the T cell-inflamed and noninflamed subsets of tumors will be critical in overcoming treatment failure and expanding the proportion of patients responding to current immunotherapies. To maximize the impact of immunotherapy drug development, pretreatment stratification of targets associated with either the T cell-inflamed or noninflamed tumor microenvironment should be employed. Similarly, biomarkers predictive of responsiveness to specific immunomodulatory therapies should guide therapy selection in a growing landscape of treatment options. Combination strategies may ultimately require converting non-T cell-inflamed tumors into T cell-inflamed tumors as a means to sensitize tumors to therapies dependent on T-cell killing. (C) 2018 AACR.
机译:免疫疗法,例如检查点阻断抗体和养护细胞转移是作为越来越多的癌症的治疗。尽管在一系列癌症类型上进行了免疫治疗的临床活动,但大多数患者未能应对这些治疗和抗性机制仍然保持不完整。对免疫疗法的反应优先发生在具有预先存在的抗肿瘤T细胞响应的肿瘤中,其可以通过表达树突细胞和CD8(+)T细胞相关基因来最鲁棒地测量。具有高表达该签名的肿瘤子集已被描述为T细胞 - “发炎”表型。通过发炎的签名表达分离肿瘤可能有助于预测免疫治疗反应性。理解在肿瘤的T细胞发炎和非血压亚群中的抵抗机制对于克服治疗失败并扩大对当前免疫治疗的患者的比例至关重要。为了最大限度地提高免疫疗法的影响,应采用与T细胞发炎或非荷瘤微环境相关的靶标的预处理分层。类似地,生物标志物预测对特定免疫调节疗法的反应性应该在越来越多的治疗选择景观中指导治疗选择。组合策略可能最终需要将非T细胞发炎的肿瘤转化为T细胞发炎的肿瘤,因为一种敏感肿瘤对依赖于T细胞杀伤的疗法的手段。 (c)2018年AACR。

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