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Immune landscape of human prostate cancer: immune evasion mechanisms and biomarkers for personalized immunotherapy.
人类前列腺癌的免疫景观: 个性化免疫治疗的免疫逃避机制和生物标志物。
- 影响因子:3.29
- DOI:10.1186/s12885-020-07058-y
- 作者列表:"Bou-Dargham MJ","Sha L","Sang QA","Zhang J
- 发表时间:2020-06-18
Abstract
BACKGROUND:Despite recent advances in cancer immunotherapy, the efficacy of these therapies for the treatment of human prostate cancer patients is low due to the complex immune evasion mechanisms (IEMs) of prostate cancer and the lack of predictive biomarkers for patient responses. METHODS:To understand the IEMs in prostate cancer and apply such understanding to the design of personalized immunotherapies, we analyzed the RNA-seq data for prostate adenocarcinoma from The Cancer Genome Atlas (TCGA) using a combination of biclustering, differential expression analysis, immune cell typing, and machine learning methods. RESULTS:The integrative analysis identified eight clusters with different IEM combinations and predictive biomarkers for each immune evasion cluster. Prostate tumors employ different combinations of IEMs. The majority of prostate cancer patients were identified with immunological ignorance (89.8%), upregulated cytotoxic T lymphocyte-associated protein 4 (CTLA4) (58.8%), and upregulated decoy receptor 3 (DcR3) (51.6%). Among patients with immunologic ignorance, 41.4% displayed upregulated DcR3 expression, 43.26% had upregulated CTLA4, and 11.4% had a combination of all three mechanisms. Since upregulated programmed cell death 1 (PD-1) and/or CTLA4 often co-occur with other IEMs, these results provide a plausible explanation for the failure of immune checkpoint inhibitor monotherapy for prostate cancer. CONCLUSION:These findings indicate that human prostate cancer specimens are mostly immunologically cold tumors that do not respond well to mono-immunotherapy. With such identified biomarkers, more precise treatment strategies can be developed to improve therapeutic efficacy through a greater understanding of a patient's immune evasion mechanisms.
摘要
背景: 尽管肿瘤免疫治疗取得了最新进展,但由于复杂的免疫逃避机制 (IEMs),这些疗法对人类前列腺癌患者的治疗效果较低前列腺癌和患者反应的预测生物标志物的缺乏。 方法: 为了了解前列腺癌中的 IEMs,并将其应用于个性化免疫疗法的设计,我们分析了来自癌症基因组图谱 (TCGA) 的前列腺腺癌的 RNA-seq 数据使用双聚类、差异表达分析、免疫细胞分型和机器学习方法的组合。 结果: 整合分析确定了 8 个具有不同 IEM 组合的簇和每个免疫逃避簇的预测生物标志物。前列腺肿瘤采用不同的 IEMs 组合。大多数前列腺癌患者被确定为免疫无知 (89.8%),细胞毒性 T 淋巴细胞相关蛋白 4 (CTLA4) 上调 (58.8%),诱饵受体 3 (DcR3) 上调 (51.6%)。在免疫无知的患者中,41.4% 的患者显示 DcR3 表达上调,43.26% 的患者 CTLA4 表达上调,11.4% 的患者联合三种机制。由于上调的程序性细胞死亡 1 (PD-1) 和/或 CTLA4 经常与其他 IEMs 共同发生,这些结果为免疫检查点抑制剂单药治疗前列腺癌的失败提供了一个合理的解释。 结论: 这些发现表明,人类前列腺癌标本大多是免疫冷肿瘤,对单一免疫治疗反应不佳。有了这样确定的生物标志物,可以通过更好地了解患者的免疫逃避机制来开发更精确的治疗策略来提高治疗疗效。
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