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      Molecular mechanism of lncRNA SNHG12 in immune escape of non-small cell lung cancer through the HuR/PD-L1/USP8 axis

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          Abstract

          Background

          The pivotal role of long noncoding RNAs (lncRNAs) in cancer immune responses has been well established. This study was conducted with the aim of exploring the molecular mechanism of lncRNA small nucleolar RNA host gene 12 (SNHG12) in immune escape of non-small cell lung cancer (NSCLC).

          Methods

          Expression of lncRNA SNHG12, programmed cell death receptor ligand 1 (PD-L1), ubiquitin-specific protease 8 (USP8), and human antigen R (HuR) in NSCLC tissues and cells was measured, and their binding relationship was determined. NSCLC cell proliferation and apoptosis were assessed. Peripheral blood mononuclear cells (PBMCs) were co-cultured with NSCLC cells. The ratio of CD8 + T cells, PBMC proliferation, and inflammatory factors were determined. lncRNA SNHG12 localization was assessed via subcellular fractionation assay. The half-life period of mRNA was determined using actinomycin D. Xenograft tumor models were established to confirm the role of lncRNA SNHG12 in vivo.

          Results

          LncRNA SNHG12 was found to be prominently expressed in NSCLC tissues and cells, which was associated with a poor prognosis. Silencing lncRNA SNHG12 resulted in the reduction in proliferation and the promotion of apoptosis of NSCLC cells, while simultaneously increasing PBMC proliferation and the ratio of CD8 + T cells. Mechanically, the binding of lncRNA SNHG12 to HuR improved mRNA stability and expression of PD-L1 and USP8, and USP8-mediated deubiquitination stabilized the protein level of PD-L1. Overexpression of USP8 or PD-L1 weakened the inhibition of silencing lncRNA SNHG12 on the immune escape of NSCLC. Silencing lncRNA SNHG12 restricted tumor growth and upregulated the ratio of CD8 + T cells by decreasing USP8 and PD-L1.

          Conclusion

          LncRNA SNHG12 facilitated the immune escape of NSCLC by binding to HuR and increasing PD-L1 and USP8 levels.

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          Most cited references53

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

            Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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              starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data

              Although microRNAs (miRNAs), other non-coding RNAs (ncRNAs) (e.g. lncRNAs, pseudogenes and circRNAs) and competing endogenous RNAs (ceRNAs) have been implicated in cell-fate determination and in various human diseases, surprisingly little is known about the regulatory interaction networks among the multiple classes of RNAs. In this study, we developed starBase v2.0 (http://starbase.sysu.edu.cn/) to systematically identify the RNA–RNA and protein–RNA interaction networks from 108 CLIP-Seq (PAR-CLIP, HITS-CLIP, iCLIP, CLASH) data sets generated by 37 independent studies. By analyzing millions of RNA-binding protein binding sites, we identified ∼9000 miRNA-circRNA, 16 000 miRNA-pseudogene and 285 000 protein–RNA regulatory relationships. Moreover, starBase v2.0 has been updated to provide the most comprehensive CLIP-Seq experimentally supported miRNA-mRNA and miRNA-lncRNA interaction networks to date. We identified ∼10 000 ceRNA pairs from CLIP-supported miRNA target sites. By combining 13 functional genomic annotations, we developed miRFunction and ceRNAFunction web servers to predict the function of miRNAs and other ncRNAs from the miRNA-mediated regulatory networks. Finally, we developed interactive web implementations to provide visualization, analysis and downloading of the aforementioned large-scale data sets. This study will greatly expand our understanding of ncRNA functions and their coordinated regulatory networks.
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                Author and article information

                Contributors
                lixizi19620716@163.com
                yangzhenzhou@sohu.com
                Journal
                Cell Mol Biol Lett
                Cell Mol Biol Lett
                Cellular & Molecular Biology Letters
                BioMed Central (London )
                1425-8153
                1689-1392
                3 June 2022
                3 June 2022
                2022
                : 27
                : 43
                Affiliations
                [1 ]GRID grid.412461.4, ISNI 0000 0004 9334 6536, Department of Cancer Center, , The Second Affiliated Hospital of Chongqing Medical University, ; Tianwen Avenue No. 288, Nan’an District, Chongqing, 400010 China
                [2 ]GRID grid.190737.b, ISNI 0000 0001 0154 0904, Chongqing University, Three Gorges Hospital, ; No. 165 Xincheng Road, Wanzhou District, Chongqing, 404100 China
                Author information
                http://orcid.org/0000-0001-9766-0280
                Article
                343
                10.1186/s11658-022-00343-7
                9164758
                35658874
                bb13ec18-7be5-4e3f-ac8d-bdc25e893649
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 January 2022
                : 5 May 2022
                Funding
                Funded by: Chongqing Talents Program
                Award ID: CQYC20200303151
                Award Recipient :
                Funded by: Kuanren Talents Program of the second affiliated hospital of Chongqing Medical University
                Award ID: 202007
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                non-small cell lung cancer,lncrna snhg12,pd-l1,usp8,immune escape,hur,peripheral blood mononuclear cells,cd8+ t

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