Abstract A75: A radiosensitivity gene signature and PD-L1 expression are predictive of the clinical outcomes of patients with lower-grade glioma in The Cancer Genome Atlas dataset

B. Jang, I. Kim
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Abstract

Background: Identifying predictive factors for the clinical outcome of patients with low grade gliomas following radiotherapy could help optimize patient treatments. Here, we investigate the predictive efficacy of both a previously identified “31 gene signature” and programmed death ligand-1 (PD-L1) expression. Methods: We identified 516 patients with low grade glioma in The Cancer Genome Atlas dataset and divided them into two clusters: radiosensitive (RS) and radioresistant (RR). Patients were also classified as PD-L1-high or PD-L1-low based on CD274 mRNA expression. Five-year survival rates were compared across patient groups, and differentially expressed genes were identified via a gene enrichment analysis. Results: Patients in the RS group had a higher survival rate than in the RR group, but only when treated with radiotherapy (63% vs. 52%, p = 0.019; univariate analysis). Patients in the RR group who were also PD-L1-high had a lower survival rate than other patients (50% vs. 60%, p = 0.010). Furthermore, a Cox multivariate analysis demonstrated that both belonging to this patient population and expressing wild-type isocitrate dehydrogenase were predictive of lower survival rates (p = 0.048). Differentially expressed genes associated with this group were found to play a role in the immune response, including the T-cell receptor signaling pathway. Conclusions: We validated the predictive value of a 31 gene signature and PD-L1 expression in a dataset of patients with low-grade glioma. Our results suggest that the patient population classified as both RR and PD-L1 high may benefit most from radiotherapy combined with anti-PD1/PD-L1 treatment. This work was supported by a grant from the Ministry of Science, ICT & Future Planning (NRF#2017R1A2B4002710 & & 2017M2A2A7A01018438) to In Ah Kim. Citation Format: Bum Sup Jang, In Ah Kim. A radiosensitivity gene signature and PD-L1 expression are predictive of the clinical outcomes of patients with lower-grade glioma in The Cancer Genome Atlas dataset [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr A75.
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摘要A75:在Cancer Genome Atlas数据集中,放射敏感性基因标记和PD-L1表达可预测低级别胶质瘤患者的临床结局
背景:确定低级别胶质瘤患者放疗后临床预后的预测因素有助于优化患者治疗。在这里,我们研究了先前确定的“31基因标记”和程序性死亡配体-1 (PD-L1)表达的预测效果。方法:我们从癌症基因组图谱数据集中筛选出516例低级别胶质瘤患者,并将其分为两组:放射敏感(RS)和放射耐药(RR)。根据CD274 mRNA的表达将患者分为pd - l1高或pd - l1低。比较不同患者组的5年生存率,并通过基因富集分析鉴定差异表达基因。结果:RS组患者生存率高于RR组,但仅在放疗时(63% vs. 52%, p = 0.019;单变量分析)。pd - l1高的RR组患者的生存率低于其他患者(50%比60%,p = 0.010)。此外,Cox多变量分析表明,属于该患者群体和表达野生型异柠檬酸脱氢酶的患者的生存率较低(p = 0.048)。与这一组相关的差异表达基因被发现在免疫反应中发挥作用,包括t细胞受体信号通路。结论:我们验证了31个基因标记和PD-L1表达在低级别胶质瘤患者数据集中的预测价值。我们的研究结果表明,RR和PD-L1高的患者群体可能从放疗联合抗pd - 1/PD-L1治疗中获益最多。这项工作得到了科学,信息通信技术和未来规划部的资助(NRF#2017R1A2B4002710 & & 2017M2A2A7A01018438)给In Ah Kim的支持。引文格式:Bum Sup Jang, In Ah Kim。放射敏感性基因标记和PD-L1表达可预测癌症基因组图谱数据集中低级别胶质瘤患者的临床结局[摘要]。摘自:AACR肿瘤免疫学和免疫治疗特别会议论文集;2017年10月1-4日;波士顿,MA。费城(PA): AACR;癌症免疫学杂志,2018;6(9增刊):摘要第A75期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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