Ma Jianli, Zhang Minghui, Yu Jinming
Department of Radiotherapy, Shandong University Cancer Center, Jinan, China.
Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Front Oncol. 2022 Jul 4;12:899925. doi: 10.3389/fonc.2022.899925. eCollection 2022.
Numerous studies have reported that long non-coding RNAs (lncRNAs) play important roles in immune-related pathways in cancer. However, immune-related lncRNAs and their roles in predicting immunotherapeutic response and prognosis of non-small cell lung cancer (NSCLC) patients treated with immunotherapy remain largely unexplored.
Transcriptomic data from NSCLC patients were used to identify novel lncRNAs by a custom pipeline. ImmuCellAI was utilized to calculate the infiltration score of immune cells. The marker genes of immunotherapeutic response-related (ITR)-immune cells were used to identify immune-related (IR)-lncRNAs. A co-expression network was constructed to determine their functions. LASSO and multivariate Cox analyses were performed on the training set to construct an immunotherapeutic response and immune-related (ITIR)-lncRNA signature for predicting the immunotherapeutic response and prognosis of NSCLC. Four independent datasets involving NSCLC and melanoma patients were used to validate the ITIR-lncRNA signature.
In total, 7,693 novel lncRNAs were identified for NSCLC. By comparing responders with non-responders, 154 ITR-lncRNAs were identified. Based on the correlation between the marker genes of ITR-immune cells and lncRNAs, 39 ITIR-lncRNAs were identified. A co-expression network was constructed and the potential functions of 38 ITIR-lncRNAs were annotated, most of which were related to immune/inflammatory-related pathways. Single-cell RNA-seq analysis was performed to confirm the functional prediction results of an ITIR-lncRNA, LINC01272. Four-ITIR-lncRNA signature was identified and verified for predicting the immunotherapeutic response and prognosis of NSCLC. Compared with non-responders, responders had a lower risk score in both NSCLC datasets (P<0.05). NSCLC patients in the high-risk group had significantly shorter PFS/OS time than those in the low-risk group in the training and testing sets (P<0.05). The AUC value was 1 of responsiveness in the training set. In melanoma validation datasets, patients in the high-risk group also had significantly shorter OS/PFS time than those in the low-risk group (P<0.05). The ITIR-lncRNA signature was an independent prognostic factor (P<0.001).
Thousands of novel lncRNAs in NSCLC were identified and characterized. In total, 39 ITIR-lncRNAs were identified, 38 of which were functionally annotated. Four ITIR-lncRNAs were identified as a novel ITIR-lncRNA signature for predicting the immunotherapeutic response and prognosis in NSCLC patients treated with immunotherapy.
大量研究报道长链非编码RNA(lncRNA)在癌症免疫相关通路中发挥重要作用。然而,免疫相关lncRNA及其在预测接受免疫治疗的非小细胞肺癌(NSCLC)患者免疫治疗反应和预后方面的作用仍基本未被探索。
利用NSCLC患者的转录组数据通过自定义流程鉴定新型lncRNA。使用ImmuCellAI计算免疫细胞浸润评分。利用免疫治疗反应相关(ITR)免疫细胞的标记基因鉴定免疫相关(IR)lncRNA。构建共表达网络以确定其功能。对训练集进行LASSO和多变量Cox分析,构建用于预测NSCLC免疫治疗反应和预后的免疫治疗反应及免疫相关(ITIR)lncRNA特征。使用四个涉及NSCLC和黑色素瘤患者的独立数据集验证ITIR-lncRNA特征。
总共为NSCLC鉴定出7693个新型lncRNA。通过比较反应者和无反应者,鉴定出154个ITR-lncRNA。基于ITR免疫细胞标记基因与lncRNA之间的相关性,鉴定出39个ITIR-lncRNA。构建了共表达网络并注释了38个ITIR-lncRNA的潜在功能,其中大多数与免疫/炎症相关通路有关。进行单细胞RNA测序分析以证实一种ITIR-lncRNA,即LINC01272的功能预测结果。鉴定并验证了四ITIR-lncRNA特征用于预测接受免疫治疗的NSCLC患者的免疫治疗反应和预后。与无反应者相比,反应者在两个NSCLC数据集中的风险评分较低(P<0.05)。在训练集和测试集中,高危组的NSCLC患者的无进展生存期/总生存期明显短于低危组(P<0.05)。训练集中反应性的AUC值为1。在黑色素瘤验证数据集中,高危组患者的总生存期/无进展生存期也明显短于低危组(P<0.05)。ITIR-lncRNA特征是一个独立的预后因素(P<0.001)。
鉴定并表征了NSCLC中的数千个新型lncRNA。总共鉴定出39个ITIR-lncRNA,其中38个进行了功能注释。鉴定出四个ITIR-lncRNA作为一种新型ITIR-lncRNA特征,用于预测接受免疫治疗的NSCLC患者的免疫治疗反应和预后。