Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, Texas; Caris Life Sciences, Phoenix, Arizona; Departments of Biostatistics, Neuro-Pathology, Neuro-Oncology, Pediatrics, and Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Neuro Oncol. 2017 Aug 1;19(8):1047-1057. doi: 10.1093/neuonc/nox026.
Despite a multiplicity of clinical trials testing immune checkpoint inhibitors, the frequency of expression of potential predictive biomarkers is unknown in glioma.
In this study, we profiled the frequency of shared biomarker phenotypes. To clarify the relationships among tumor mutational load (TML), mismatch repair (MMR), and immune checkpoint expression, we profiled patients with glioma (n = 327), including glioblastoma (GBM) (n = 198), whose samples had been submitted for analysis from 2009 to 2016. The calculation algorithm for TML included nonsynonymous mutation counts per tumor, with germline mutations filtered out. Immunohistochemical analysis and next-generation sequencing were used to determine tumor-infiltrating lymphocyte expression positive for programmed cell death protein 1 (PD-1), PD ligand 1 (PD-L1) expression on tumor cells, MMR (MLH1, MSH2, MSH6, and PMS2) protein expression and mutations, and DNA polymerase epsilon (POLE) mutations.
High TML was only found in 3.5% of GBM patients (7 of 198) and was associated with the absence of protein expression of mutL homolog 1 (MLH1) (P = .0345), mutS homolog 2 (MSH2) (P = .0099), MSH6 (P = .0022), and postmeiotic segregation increased 2 (PMS2) (P = .0345) and the presence of DNA MMR mutations. High and moderate TML GBMs did not have an enriched influx of CD8+ T cells, PD-1+ T cells, or tumor-expressed PD-L1. IDH1 mutant gliomas were not enriched for high TML, PD-1+ T cells, or PD-L1 expression.
To clarify the relationships among TML, MMR, and immune checkpoint expression, we profiled the frequency of shared biomarker phenotypes. On the basis of a variety of potential biomarkers of response to immune checkpoints, only small subsets of glioma patients are likely to benefit from monotherapy immune checkpoint inhibition.
尽管有多项临床试验测试了免疫检查点抑制剂,但在神经胶质瘤中,潜在预测生物标志物的表达频率尚不清楚。
在这项研究中,我们对共享生物标志物表型的频率进行了分析。为了阐明肿瘤突变负荷(TML)、错配修复(MMR)和免疫检查点表达之间的关系,我们对 2009 年至 2016 年间提交分析的 327 例包括胶质母细胞瘤(GBM)患者的样本进行了分析,其中 198 例为 GBM。TML 的计算算法包括每个肿瘤的非同义突变计数,并过滤掉种系突变。免疫组织化学分析和下一代测序用于确定肿瘤浸润淋巴细胞程序性细胞死亡蛋白 1(PD-1)阳性表达、肿瘤细胞 PD-配体 1(PD-L1)表达、MMR(MLH1、MSH2、MSH6 和 PMS2)蛋白表达和突变以及 DNA 聚合酶 epsilon(POLE)突变。
高 TML 仅在 3.5%的 GBM 患者(198 例中的 7 例)中发现,与 mutL 同源物 1(MLH1)(P=0.0345)、mutS 同源物 2(MSH2)(P=0.0099)、MSH6(P=0.0022)和减数分裂后增加 2 (PMS2)(P=0.0345)和 DNA MMR 突变的蛋白表达缺失相关。高和中 TML 的 GBM 没有富含 CD8+T 细胞、PD-1+T 细胞或肿瘤表达的 PD-L1。IDH1 突变型神经胶质瘤也没有富集高 TML、PD-1+T 细胞或 PD-L1 表达。
为了阐明 TML、MMR 和免疫检查点表达之间的关系,我们对共享生物标志物表型的频率进行了分析。基于对免疫检查点反应的多种潜在生物标志物,只有少数胶质细胞瘤患者可能受益于单药免疫检查点抑制。