Budczies Jan, Seidel Anja, Christopoulos Petros, Endris Volker, Kloor Matthias, Győrffy Balázs, Seliger Barbara, Schirmacher Peter, Stenzinger Albrecht, Denkert Carsten
Institute of Pathology, Charité University Hospital, Berlin, Germany.
Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Oncoimmunology. 2018 Oct 19;7(12):e1526613. doi: 10.1080/2162402X.2018.1526613. eCollection 2018.
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 / 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.
通过检查点阻断来利用免疫系统已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相互作用的影响，因此对肿瘤的遗传和免疫特征进行全面分析对于深入了解治疗反应和耐药机制至关重要。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之间的关联，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）和特定的突变特征（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与免疫参数显示出最强的正相关。对于与吸烟相关和紫外线暴露相关的MutSigs，发现了一些正相关，而MutSig 1（类似时钟的过程）在大多数癌症类型中与主要免疫参数的相关性不显著或呈负相关。在某些但并非所有癌症类型中，高TMB与高免疫细胞浸润相关，相反，高CNA负荷和高MATH大多与低免疫细胞浸润相关。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，其水平与/突变和微卫星不稳定性（MSI）状态相关，而在包括非小细胞肺癌（NSCLC）和黑色素瘤在内的大多数其他癌症类型中，TMB呈单峰分布。总之，本研究揭示了主要癌症类型中特定的遗传-免疫学关联，并表明突变特征应作为TMB之外有趣的反应预测候选因素进行进一步研究。
