Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida, USA.
Department of Statistics, Florida State University, Tallahassee, Florida, USA.
BMC Cancer. 2020 Jun 18;20(1):572. doi: 10.1186/s12885-020-07058-y.
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.
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.
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.
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.
尽管癌症免疫疗法最近取得了进展,但由于前列腺癌复杂的免疫逃逸机制(IEMs)和缺乏预测患者反应的生物标志物,这些疗法对人类前列腺癌患者的疗效较低。
为了了解前列腺癌中的 IEMs 并将这种理解应用于个性化免疫疗法的设计,我们使用了双聚类、差异表达分析、免疫细胞分型和机器学习方法组合,分析了来自癌症基因组图谱(TCGA)的前列腺腺癌的 RNA-seq 数据。
综合分析确定了八个具有不同免疫逃逸组合和每个免疫逃逸簇预测生物标志物的簇。前列腺肿瘤采用不同的 IEM 组合。大多数前列腺癌患者被鉴定为免疫忽视(89.8%)、细胞毒性 T 淋巴细胞相关蛋白 4(CTLA4)上调(58.8%)和诱饵受体 3(DcR3)上调(51.6%)。在免疫忽视患者中,41.4%显示出 DcR3 表达上调,43.26%具有 CTLA4 上调,11.4%具有这三种机制的组合。由于上调的程序性细胞死亡 1(PD-1)和/或 CTLA4 通常与其他 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失败提供了合理的解释。
这些发现表明,人类前列腺癌标本大多是免疫冷肿瘤,对单免疫治疗反应不佳。有了这些鉴定的生物标志物,可以通过更深入地了解患者的免疫逃逸机制,制定更精确的治疗策略,以提高治疗效果。