Capturing functional long non-coding RNAs through integrating large-scale causal relations from gene perturbation experimentsResearch in context
Jinyuan Xu,
Aiai Shi,
Zhilin Long,
Liwen Xu,
Gaoming Liao,
Chunyu Deng,
Min Yan,
Aiming Xie,
Tao Luo,
Jian Huang,
Yun Xiao,
Xia Li
Affiliations
Jinyuan Xu
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Aiai Shi
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Zhilin Long
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Liwen Xu
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Gaoming Liao
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Chunyu Deng
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Min Yan
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Aiming Xie
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Tao Luo
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
Jian Huang
Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China
Yun Xiao
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Harbin, Heilongjiang 150086, China
Xia Li
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China; Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Harbin, Heilongjiang 150086, China; Corresponding author at: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Characterizing functions of long noncoding RNAs (lncRNAs) remains a major challenge, mostly due to the lack of lncRNA-involved regulatory relationships. A wide array of genome-wide expression profiles generated by gene perturbation have been widely used to capture causal links between perturbed genes and response genes. Through annotating >600 gene perturbation profiles, over 354,000 causal relationships between perturbed genes and lncRNAs were identified. This large-scale resource of causal relations inspired us to develop a novel computational approach LnCAR for inferring lncRNAs' functions, which showed a higher accuracy than the co-expression based approach. By application of LnCAR to the cancer hallmark processes, we identified 38 lncRNAs involved in distinct carcinogenic processes. The “activating invasion & metastasis” related lncRNAs were strongly associated with metastatic progression in various cancer types and could act as a predictor of cancer metastasis. Meanwhile, the “evading immune destruction” related lncRNAs showed significant associations with immune infiltration of various immune cells and, importantly, can predict response to anti-PD-1 immunotherapy, suggesting their potential roles as biomarkers for immune therapy. Taken together, our approach provides a novel way to systematically reveal functions of lncRNAs, which will be helpful for further experimental exploration and clinical translational research of lncRNAs. Keywords: lncRNA, Function, Gene perturbation, Cancer, Immunotherapy
