Dataset Information

Genome-wide characterization of lncRNAs in acute myeloid leukemia.

ABSTRACT: Long noncoding RNAs (lncRNAs) are a large family of noncoding RNAs that play a critical role in various normal bioprocesses as well as tumorigenesis. However, the expression patterns and biological functions of lncRNAs in acute leukemia have not been well studied. Here, we performed transcriptome-wide lncRNA expression profiling of acute myeloid leukemia (AML) patient samples, along with non-leukemia control hematopoietic samples. We found that lncRNAs were differentially expressed in AML samples relative to control samples. Notably, we identified that lncRNAs upregulated in AML (relative to the control samples) are associated with a lower degree of DNA methylation and a higher ratio of being bound by transcription factors such as SP1, STAT4, ATF-2 and ELK-1 compared with those downregulated in AML. Moreover, an enrichment of H3K4me3 and a depletion of H3K27me3 were observed in upregulated lncRNAs in AML. Expression patterns of three types of lncRNAs (antisense, enhancer and intergenic lncRNAs) have previously been characterized. Of the identified lncRNAs, we found that high expression level lncRNA LOC285758 is associated with the poor prognosis in AML patients. Furthermore, we found that LOC285758 regulates proliferation of AML cell lines by enhancing the expression of HDAC2, a key factor in carcinogenesis. Collectively, our study depicts a landscape of important lncRNAs in AML and provides novel potential therapeutic targets and prognostic markers for AML treatment.

SUBMITTER: Lei L

PROVIDER: S-EPMC6355113 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Genome-wide characterization of lncRNAs in acute myeloid leukemia.

Lei Lijun L Xia Siyu S Liu Dan D Li Xiaoqing X Feng Jing J Zhu Yaqi Y Hu Jun J Xia Linjian L Guo Lieping L Chen Fei F Cheng Hui H Chen Ke K Hu Hanyang H Chen Xiaohua X Li Feng F Zhong Shan S Mittal Nupur N Yang Guohua G Qian Zhijian Z Han Leng L He Chunjiang C

Briefings in bioinformatics 20180701 4

Long noncoding RNAs (lncRNAs) are a large family of noncoding RNAs that play a critical role in various normal bioprocesses as well as tumorigenesis. However, the expression patterns and biological functions of lncRNAs in acute leukemia have not been well studied. Here, we performed transcriptome-wide lncRNA expression profiling of acute myeloid leukemia (AML) patient samples, along with non-leukemia control hematopoietic samples. We found that lncRNAs were differentially expressed in AML sample ...[more]

PMID: 28203711

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Project description:BackgroundAcute myeloid leukemia (AML) is a highly heterogeneous cluster of hematologic malignancies. Leukemic stem cells (LSCs) are one of the culprits for the persistence and relapse of AML. The discovery of copper-induced cell death, namely cuproptosis, gives bright insights into the treatment of AML. Analogous to copper ions, long non-coding RNAs (lncRNAs) are not bystanders for AML progression, especially for LSC physiology. Uncovering the involvement of cuproptosis-related lncRNAs in AML will benefit clinical management.MethodsDetection of prognostic relevant cuproptosis-related lncRNAs are carried out by Pearson correlation analysis and univariate Cox analysis with RNA sequencing data of The Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) cohort. After the least absolute shrinkage and selection operator (LASSO) regression and the subsequent multivariate Cox analysis, a cuproptosis-related risk score (CuRS) system was derived to weigh the risk of AML patients. Thereafter, AML patients were classified into two groups by their risk property which was validated with principal component analysis (PCA), risk curves, Kaplan-Meier survival analysis, the combined receiver operating characteristic (ROC) curves, and nomogram. Variations in biological pathways and divergences in immune infiltration and immune-related processes between groups were resolved by GSEA and CIBERSORT algorism, respectively. Response to chemotherapies were scrutinized as well. The expression profiles of the candidate lncRNAs were examined by real-time quantitative polymerase chain reaction (RT-qPCR) and the specific mechanisms of lncRNA FAM30A were determined by transcriptomic analysis.ResultsWe fabricated an efficient prognostic signature named CuRS incorporating 4 lncRNAs (TRAF3IP2-AS1, NBR2, TP53TG1, and FAM30A) relevant to immune environment and chemotherapy responsiveness. The relevance of lncRNA FAM30A with proliferation, migration ability, Daunorubicin resistance and its reciprocal action with AUF1 were demonstrated in an LSC cell line. Transcriptomic analysis suggested correlations between FAM30A and T cell differentiation and signaling, intercellular junction genes.ConclusionsThe prognostic signature CuRS can guide prognostic stratification and personalized AML therapy. Analysis of FAM30A offers a foundation for investigating LSC-targeted therapies.

Project description:Background:Acute myeloid leukemia (AML) is a type of cancer that consists of a group of hematological malignancies with high heterogeneity. DNA methyltransferase 3A (DNMT3A)-mutated AML patients have a poor prognosis. Some long non-coding RNAs (lncRNAs) have been reported to enhance therapeutic sensitivity, and so could affect the overall survival rate of elderly cytogenetically normal acute myeloid leukemia (CN-AML) patients; however, studies on the lncRNA signature in DNMT3A-mutated AML are rare. Method:The DNMT3A R878H conditional knock-in mouse model was constructed to explore the lncRNAs of DNMT3A mutation by using the Cuffcomparison method. Cis and trans regulation networks were used to predict candidate genes. The expression levels in leukemic cell lines and the prognostic index of these candidate genes were analyzed with the Broad Institute Cancer Cell Line Encyclopedia (CCLE) and OncoLnc databases. The data for each sample were statistically analyzed using GraphPad Prism. Results:In this study, we applied the DNMT3A R878H conditional knock-in mouse model to explore the lncRNA epigenetic landscape of DNMT3A mutation by using the Cuffcomparison method. Twenty-three differentially expressed lncRNAs were identified in Dnmt3aR878H/WTMx1-Cre+ mice. We next predicted the downstream targetable genes regulated by these lncRNAs through cis and trans regulation networks and found 124 candidate genes are related to these lncRNAs. In further analysis of 124 genes, we found that increased mRNA expression levels of interleukin 1 receptor type 2 (IL1R2), Krüppel-like factor 13 (KLF13), ATPase H+ transporting V1 subunit A (ATP6V1A), proteasome 26S Subunit, non-ATPase 3 (PSMD3), and pyrroline-5-carboxylate reductase 2 (PYCR2) were associated with poor prognosis in AML. Functional analysis of these genes demonstrated that the pathways involved in autophagy, cell cycle, and hematopoietic stem cell differentiation were more enriched in Dnmt3aR878H/WTMx1-Cre+ mice. Conclusion:Our study was the first to use DNMT3A R878H conditional knock-in mouse model to predict the specific lncRNAs regulated by the DNMT3A mutation in AML. Six candidate genes were found to be associated with DNMT3A mutation with poor prognosis. Our results provided a possible treatment strategy for this disease.

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Genome-wide characterization of lncRNAs in acute myeloid leukemia.

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Genome-wide characterization of lncRNAs in acute myeloid leukemia.

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