Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy.
Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy.
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DOI：
10.1126/science.aaf8399
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发表时间：
2017-01-20
期刊：
影响因子：
--
通讯作者：
Elledge SJ
中科院分区：
文献类型：
--
作者：
Davoli T;Uno H;Wooten EC;Elledge SJ
非整倍性，也称为体细胞拷贝数改变（SCNAs），在人类癌症中广泛存在，并已被提出驱动肿瘤发生。SCNA与癌症的特征性功能特征或“标志”之间的关系尚未得到很好的理解。这些癌症标志之一是免疫逃避，这是通过新抗原编辑、抗原呈递缺陷和肿瘤浸润抑制和/或免疫细胞的细胞毒性活性来实现的。肿瘤SCNA水平是否以及如何影响免疫逃避特别令人感兴趣，因为这些信息可能用于提高免疫检查点阻断的疗效，这种疗法在癌症患者的子集中产生了持久的反应。了解SCNAs和突变负荷如何影响肿瘤演变，以及通过何种机制，是癌症研究的一个关键目标。为了探索SCNA水平、肿瘤突变和癌症标志之间的关系，我们检查了来自癌症基因组图谱项目的代表12种癌症类型的5255个肿瘤/正常样本的数据。我们给每个肿瘤分配了一个SCNA评分，并寻找与肿瘤突变数量和类型的相关性。我们还比较了高SCNA水平与低SCNA水平肿瘤的基因表达谱，以确定细胞信号传导途径的差异。首先，我们发现，对于大多数肿瘤，SCNA水平与突变总数之间呈正相关。第二，在受体酪氨酸激酶-RAS-磷脂酰肌醇3-激酶途径中携带激活致癌突变的肿瘤显示出较少的SCNA，这一发现与致癌基因驱动的基因组不稳定性的假设不一致。第三，我们发现具有高水平SCNA的肿瘤显示细胞周期和细胞增殖标志物（细胞周期特征）的表达升高，以及细胞毒性免疫细胞浸润标志物（免疫特征）的表达降低。细胞周期特征的表达水平增加主要由局灶性SCNA预测，臂和全染色体SCNA的贡献较小。相比之下，免疫特征的较低表达水平主要由高水平的臂和全染色体SCNA预测。SCNA水平是比肿瘤突变负荷更强的细胞毒性免疫细胞浸润标志物的预测因子。最后，通过对两项已发表的黑色素瘤患者免疫治疗临床试验数据的分析，我们发现肿瘤中高SCNA水平与患者生存率较差相关。肿瘤SCNA评分和肿瘤突变负荷的组合比单独的生物标志物更好地预测免疫治疗后的生存率。我们发现癌症的两个标志，细胞增殖和免疫逃避，是由不同类型的非整倍体预测的，这些非整倍体可能通过不同的机制起作用。增殖标记物主要与局灶性SCNA相关，这意味着与这些SCNA靶向的特定基因的作用相关的机制。免疫逃避标记主要与臂和染色体水平SCNA相关，与一般基因剂量失衡相关的机制一致，而不是特定基因的作用。对接受免疫检查点阻断抗CTLA-4（细胞毒性T淋巴细胞相关蛋白4）治疗的黑色素瘤患者进行的回顾性分析显示，高SCNA水平与较差的反应相关，这表明肿瘤非整倍性可能是预测哪些患者最有可能从这种治疗中获益的有用生物标志物。与两个癌症标志相关的遗传事件：细胞增殖和免疫逃避。在几种人类肿瘤类型中，高SCNA水平与细胞周期标志物表达增加和细胞毒性免疫细胞浸润标志物表达减少相关。高负荷的肿瘤新抗原（反映高水平的点突变）促进免疫系统对肿瘤的检测，限制免疫逃避。显示了病灶、臂/染色体和新抗原负荷对增殖和免疫逃避预测的相对贡献。
Aneuploidy, also known as somatic copy number alterations (SCNAs), is widespread in human cancers and has been proposed to drive tumorigenesis. The relationship between SCNAs and the characteristic functional features or “hallmarks” of cancer is not well understood. Among these cancer hallmarks is immune evasion, which is accomplished by neoantigen editing, defects in antigen presentation and inhibition of tumor infiltration, and/or cytotoxic activities of immune cells. Whether and how tumor SCNA levels influence immune evasion is of particular interest as this information could potentially be used to improve the efficacy of immune checkpoint blockade, a therapy that has produced durable responses in a subset of cancer patients. Understanding how SCNAs and mutation load affect tumor evolution, and through what mechanisms, is a key objective in cancer research. To explore the relationships between SCNA levels, tumor mutations, and cancer hallmarks, we examined data from 5255 tumor/normal samples representing 12 cancer types from The Cancer Genome Atlas project. We assigned each tumor an SCNA score and looked for correlations with the number and types of tumor mutations. We also compared the gene expression profiles of tumors with high versus low SCNA levels to identify differences in cellular signaling pathways. First, we found that, for most tumors, there was a positive correlation between SCNA levels and the total number of mutations. Second, tumors harboring activating oncogenic mutations in the receptor tyrosine kinase–RAS–phosphatidylinositol 3-kinase pathway showed fewer SCNAs, a finding at odds with the hypothesis of oncogene-driven genomic instability. Third, we found that tumors with high levels of SCNAs showed elevated expression of cell cycle and cell proliferation markers (cell cycle signature) and reduced expression of markers for cytotoxic immune cell infiltrates (immune signature). The increased expression level of the cell cycle signature was primarily predicted by focal SCNAs, with a lesser contribution of arm and whole-chromosome SCNAs. In contrast, the lower expression level of the immune signature was primarily predicted by high levels of arm and whole-chromosome SCNAs. SCNA levels were a stronger predictor of markers of cytotoxic immune cell infiltration than tumor mutational load. Finally, through analysis of data from two published clinical trials of immunotherapy in melanoma patients, we found that high SCNA levels in tumors correlated with poorer survival of patients. The combination of the tumor SCNA score and the tumor mutational load was a better predictor of survival after immunotherapy than either biomarker alone. We found that two hallmarks of cancer, cell proliferation and immune evasion, are predicted by distinct types of aneuploidy that likely act through distinct mechanisms. Proliferation markers mainly correlated with focal SCNAs, implying a mechanism related to the action of specific genes targeted by these SCNAs. Immune evasion markers mainly correlated with arm- and chromosome-level SCNAs, consistent with a mechanism related to general gene dosage imbalance rather than the action of specific genes. A retrospective analysis of melanoma patients treated with immune checkpoint blockade anti–CTLA-4 (cytotoxic T lymphocyte–associated protein 4) therapy revealed that high SCNA levels were associated with a poorer response, suggesting that tumor aneuploidy might be a useful biomarker for predicting which patients are most likely to benefit from this therapy. Genetic events associated with two cancer hallmarks: cell proliferation and immune evasion. Across several human tumor types, high SCNA levels correlate with increased expression of cell cycle markers and decreased expression of markers of cytotoxic immune cell infiltrates. A high load of tumor neoantigens (reflecting a high level of point mutations) promotes the detection of tumors by the immune system, limiting immune evasion. The relative contribution of focal, arm/chromosome, and neoantigen load to the prediction of proliferation and immune evasion is shown.
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影响因子：
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作者：
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