Integrated analysis of the immunological and genetic status in and across cancer types: impact of mutational signatures beyond tumor mutational burden
Integrated analysis of the immunological and genetic status in and across cancer types: impact of mutational signatures beyond tumor mutational burden
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DOI：
10.1080/2162402x.2018.1526613
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发表时间：
2018-12-02
期刊：
影响因子：
7.2
通讯作者：
Denkert, Carsten
中科院分区：
文献类型：
--
作者：
Budczies, Jan;Seidel, Anja;Denkert, Carsten
通过检查点阻断来利用免疫系统，极大地扩展了晚期癌症的治疗选择。由于免疫疗法的疗效受肿瘤的分子组成及其与免疫系统的相互作用的影响，因此对遗传和免疫肿瘤特征的综合分析对于深入了解治疗反应和耐药性的机制至关重要。我们使用来自21种癌症类型的5722个肿瘤样本的TCGA数据研究了免疫细胞结构与肿瘤遗传学的关联，包括肿瘤突变负荷（TMB）、拷贝数改变（CNA）负荷、突变等位基因异质性（MATH）和特异性突变特征（MutSigs）。在所有遗传变量中，与DNA修复缺陷和AID/APOBEC基因活性相关的MutSigs与免疫参数呈最强的正相关。对于吸烟相关和UV光暴露相关的MutSig，确定了一些正相关性，而MutSig 1（时钟样过程）与大多数癌症类型中的主要免疫参数无显著或负相关。高TMB与一些但不是所有癌症类型中的高免疫细胞浸润相关，相反，高CNA负荷和高MATH主要与低免疫细胞浸润相关。虽然在结直肠癌、胃癌和子宫内膜癌中观察到TMB的双峰或多峰分布，其中其水平与POLE/POLD 1突变和MSI状态相关，但TMB在大多数其他癌症类型（包括NSCLC和黑色素瘤）中呈单峰分布。总之，这项研究揭示了主要癌症类型中的特定遗传免疫学关联，并建议应进一步研究突变特征作为TMB以外的反应预测的有趣候选者。
Harnessing the immune system by checkpoint blockade has greatly expanded the therapeutic options for advanced cancer. Since the efficacy of immunotherapies is influenced by the molecular make-up of the tumor and its crosstalk with the immune system, comprehensive analysis of genetic and immunologic tumor characteristics is essential to gain insight into mechanisms of therapy response and resistance. We investigated the association of immune cell contexture and tumor genetics including tumor mutational burden (TMB), copy number alteration (CNA) load, mutant allele heterogeneity (MATH) and specific mutational signatures (MutSigs) using TCGA data of 5722 tumor samples from 21 cancer types. Among all genetic variables, MutSigs associated with DNA repair deficiency and AID/APOBEC gene activity showed the strongest positive correlations with immune parameters. For smoking-related and UV-light-exposure associated MutSigs a few positive correlations were identified, while MutSig 1 (clock-like process) correlated non-significantly or negatively with the major immune parameters in most cancer types. High TMB was associated with high immune cell infiltrates in some but not all cancer types, in contrast, high CNA load and high MATH were mostly associated with low immune cell infiltrates. While a bi- or multimodal distribution of TMB was observed in colorectal, stomach and endometrial cancer where its levels were associated with POLE/POLD1 mutations and MSI status, TMB was unimodal distributed in the most other cancer types including NSCLC and melanoma. In summary, this study uncovered specific genetic-immunology associations in major cancer types and suggests that mutational signatures should be further investigated as interesting candidates for response prediction beyond TMB.