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Updated: Jul 15, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Identifying immune checkpoint-related lncRNA biomarkers for immunotherapy response and prognosis in cancers
Yue Gao1, Xinyue Wang1, Longlong Dong1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Abstract:
Long non-coding RNAs (lncRNAs) could modulate expression of immune checkpoints (ICPs) in tumor-immune. However, precise functions in immunity and potential for predicting ICP inhibitors (ICI) response have been described for only a few lncRNAs. Here, a multiple-step pipeline was developed to identify cancer- and immune-context ICP and lncRNA cooperative regulation pairs (ICPaLncCRPs) across cancers. Immune-related ICPs and lncRNAs were extracted follow immune cell lines and immunologic constant of rejection groups. ICPaLncCRP networks were constructed, which likely to modulate tumor-immune by specific patterns. Common and specific hub ICPaLncs such as MIR155HG, TRG-AS1 and PCED1B-AS1 maybe play central roles in prognosis and circulating. Moreover, these hub ICPaLncs were significantly correlated with immune cell infiltration based on bulk and single-cell RNA sequencing data. Some ICPaLncCRPs such as IDO1-MIR155HG could predict three- and five-year prognosis of melanoma in two independent datasets. We also validated that some ICPaLncCRPs could effectively predict ICI-response follow six independent datasets. Collectively, this study will enhance our understanding of lncRNA functions and accelerate discovery of lncRNA-based biomarkers in ICI treatment.
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