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      lncNBAT1/APOBEC3A is a mediator of HBX-induced chemoresistance in diffuse large B cell lymphoma cells

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          Abstract

          Individuals with diffuse large B cell lymphoma (DLBCL) infected with hepatitis B virus (HBV) have worse chemotherapy efficacy and poorer outcomes. It is still unclear whether long noncoding RNAs (lncRNAs) serve as prognostic and therapeutic targets in the chemotherapy resistance of individuals with DLBCL and HBV infection. Here we found that the core component of HBV (HBX) directly upregulated the expression of lncNBAT1, which was closely associated with the chemotherapy outcomes of HBV-infected individuals with DLBCL. Upregulation of lncNBAT1 reduced the sensitivity of DLBCL cells to chemotherapeutic agents (methotrexate [MTX] or cytarabine [Ara-C]) that induced S phase arrest, whereas knockdown of lncNBAT1 significantly relieved the chemoresistance of HBX-expressing DLBCLs. Mechanistically, lncNBAT1 could interact with the signal transducer and activator of transcription 1 (STAT1) to prevent its enrichment at the promoter region of the functional target gene apolipoprotein B mRNA editing enzyme catalytic subunit 3A (APOBEC3A), inhibiting expression of APOBEC3A and inducing resistance to MTX in DLBCL cells. Furthermore, clinical data analysis showed that lncNBAT1 and APOBEC3A expression was closely related to the poor prognosis and short survival of individuals with DLBCL. Our findings suggest a potential prognostic marker and a candidate lncRNA target for treating HBV-infected individuals with DLBCL.

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          Abstract

          Li et al. identified lncNBAT1 as a crucial mediator of HBX-induced chemoresistance in DLBCL. lncNBAT1 interacted with STAT1 and prevented its binding at the APOBEC3A promoter region, inhibiting APOBEC3A transcription. These findings suggested lncNBAT1 as a potential prognostic marker and a candidate lncRNA target for treating HBV-infected individuals with DLBCL.

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          Most cited references50

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          The Molecular Signatures Database (MSigDB) hallmark gene set collection.

          The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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            Long Noncoding RNAs in Cancer Pathways.

            Genome-wide cancer mutation analyses are revealing an extensive landscape of functional mutations within the noncoding genome, with profound effects on the expression of long noncoding RNAs (lncRNAs). While the exquisite regulation of lncRNA transcription can provide signals of malignant transformation, we now understand that lncRNAs drive many important cancer phenotypes through their interactions with other cellular macromolecules including DNA, protein, and RNA. Recent advancements in surveying lncRNA molecular mechanisms are now providing the tools to functionally annotate these cancer-associated transcripts, making these molecules attractive targets for therapeutic intervention in the fight against cancer.
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              The landscape of long noncoding RNAs in the human transcriptome.

              Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.
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                Author and article information

                Contributors
                Journal
                Mol Ther Nucleic Acids
                Mol Ther Nucleic Acids
                Molecular Therapy. Nucleic Acids
                American Society of Gene & Cell Therapy
                2162-2531
                25 January 2022
                08 March 2022
                25 January 2022
                : 27
                : 1064-1077
                Affiliations
                [1 ]Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, National Stem Cell Translational Resource Center, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
                [2 ]Department of Hematology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China
                [3 ]Institute for Advanced Study, Tongji University, Shanghai 200092, China
                Author notes
                []Corresponding author Xudong Guo, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, National Stem Cell Translational Resource Center, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China 19504@ 123456tongji.edu.cn
                [∗∗ ]Corresponding author Jie Chen, Department of Hematology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China chenjiedoctor@ 123456163.com
                [∗∗∗ ]Corresponding author Jiuhong Kang, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, National Stem Cell Translational Resource Center, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China jhkang@ 123456tongji.edu.cn
                [4]

                These authors contributed equally

                Article
                S2162-2531(22)00020-8
                10.1016/j.omtn.2022.01.015
                8850662
                35228900
                a6df2b8e-01d0-4b43-a15f-df8e52c5b3a4
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 7 May 2021
                : 21 January 2022
                Categories
                Original Article

                Molecular medicine
                dlbcl,hbv,lncnbat1,chemoresistance,apobec3a
                Molecular medicine
                dlbcl, hbv, lncnbat1, chemoresistance, apobec3a

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