Immune-related genes and gene sets for predicting the response to anti-programmed death 1 therapy in patients with primary or metastatic non-small cell lung cancer

用于预测原发性或转移性非小细胞肺癌患者对抗程序性死亡1疗法反应的免疫相关基因和基因集

阅读:7
作者:Bolin Chen, Min Yang, Kang Li, Jia Li, Li Xu, Fang Xu, Yan Xu, Dandan Ren, Jiao Zhang, Liyu Liu

Abstract

Although antibodies targeting the immune checkpoint protein programmed death-1 (PD-1) exert therapeutic effects in patients with primary or metastatic non-small cell lung cancer (NSCLC), the majority of patients exhibit partial or complete resistance to anti-PD1 treatment. Thus, the aim of the present study was to identify reliable biomarkers for predicting the response to anti-PD-1 therapy. The present study analyzed tumor specimens isolated from 24 patients (13 with primary and 11 with metastatic NSCLC) prior to treatment with approved PD1-targeting antibodies. The expression profile of 395 immune-related genes was examined using RNA immune-oncology panel sequencing. The results demonstrated that six immune-related differently expressed genes (DEGs), including HLA-F-AS1, NCF1, RORC, DMBT1, KLRF1 and IL-18, and five DEGs, including HLA-A, HLA-DPA1, TNFSF18, IFI6 and PTK7, may be used as single biomarkers for predicting the efficacy of anti-PD-1 treatment in patients with primary and with metastatic NSCLC, respectively. In addition, two DEG sets comprising either six (HLA-F-AS1, NCF1, RORC, DMBT1, KLRF and IL-18) or two (HLA-A and TNFSF18) DEGs as potential combination biomarkers for predicting the efficacy of anti-PD-1 therapy in patients with NSCLC. Patients with a calculated expression level of the DEG sets >6.501 (primary NSCLC) or >6.741 (metastatic NSCLC) may benefit from the anti-PD-1 therapy. Overall, these findings provided a basis for the identification of additional biomarkers for predicting the response to anti-PD-1 treatment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。