Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma

作者全名："Zhang, Hao; Zhang, Nan; Wu, Wantao; Zhou, Ran; Li, Shuyu; Wang, Zeyu; Dai, Ziyu; Zhang, Liyang; Liu, Zaoqu; Zhang, Jian; Luo, Peng; Liu, Zhixiong; Cheng, Quan"

作者地址："[Zhang, Hao; Wu, Wantao; Wang, Zeyu; Dai, Ziyu; Zhang, Liyang; Liu, Zhixiong; Cheng, Quan] Xiangya Hosp, Dept Neurosurg, Changsha, Peoples R China; [Zhang, Hao] Chongqing Med Univ, Affiliated Hosp 6, Affiliated Hosp 2, Dept Neurosurg, Chongqing, Peoples R China; [Zhang, Nan] Huazhong Univ Sci & Technol, COLL Life Sci & Technol, Wuhan, Peoples R China; [Wu, Wantao] Xiangya Hosp, Dept Oncol, Changsha, Peoples R China; [Zhou, Ran] Univ Manchester, Div Neurosci & Expt Psychol, Manchester, Lancs, England; [Li, Shuyu] Huazhong Univ Sci & Technol, Tongji Med Coll, Tongji Hosp, Dept Thyroid & Breast Surg, Wuhan, Peoples R China; [Liu, Zaoqu] First Affiliated Hosp Zhengzhou, Dept Oncol, Zhengzhou, Peoples R China; [Zhang, Jian; Luo, Peng] Zhujiang Hosp, Dept Neurosurg, Guangzhou, Peoples R China"

通信作者："Liu, ZX; Cheng, Q (通讯作者)，Ctr South Univ, Xiangya Hosp, Dept Neurosurg, Changsha 410008, Hunan, Peoples R China."

来源：BRIEFINGS IN BIOINFORMATICS

ESI学科分类：COMPUTER SCIENCE

WOS号：WOS:000858597700001

JCR分区：Q1

影响因子：9.5

年份：2022

卷号：　

期号：　

开始页：　

结束页：　

文献类型：Article; Early Access

关键词：immunotherapy; glioblastoma; lncRNA; immune checkpoint; immune infiltration; prognosis

摘要："Long noncoding ribonucleic acids (RNAs; lncRNAs) have been associated with cancer immunity regulation. However, the roles of immune cell-specific lncRNAs in glioblastoma (GBM) remain largely unknown. In this study, a novel computational framework was constructed to screen the tumor-infiltrating immune cell-associated lncRNAs (TIIClnc) for developing TIIClnc signature by integratively analyzing the transcriptome data of purified immune cells, GBM cell lines and bulk GBM tissues using six machine learning algorithms. As a result, TIIClnc signature could distinguish survival outcomes of GBM patients across four independent datasets, including the Xiangya in-house dataset, and more importantly, showed superior performance than 95 previously established signatures in gliomas. TIIClnc signature was revealed to be an indicator of the infiltration level of immune cells and predicted the response outcomes of immunotherapy. The positive correlation between TIIClnc signature and CD8, PD-1 and PD-L1 was verified in the Xiangya in-house dataset. As a newly demonstrated predictive biomarker, the TIIClnc signature enabled a more precise selection of the GBM population who would benefit from immunotherapy and should be validated and applied in the near future."

基金机构：Hunan Provincial Natural Science Foundation of China [2022JJ20095]; Hunan Provincial Health Committee Foundation of China [202204044869]

基金资助正文：Hunan Provincial Natural Science Foundation of China (No. 2022JJ20095); Hunan Provincial Health Committee Foundation of China (No. 202204044869).