Literature DB >> 28428987

Microarray profiling and co-expression network analysis of the lncRNAs and mRNAs associated with acute leukemia in adults.

Hui Cheng1, Chong Mei Huang, Yang Wang, Xiao Xia Hu, Xiao Qian Xu, Xian Min Song, Gu Sheng Tang, Li Chen, Jian Min Yang.   

Abstract

Acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) are common types of acute leukemia in adults and cause low survival rate and poor outcome after 5 years despite high rates of complete remission (CR) with modern chemotherapeutic regimens. To understand the distinct mechanisms in leukemogenesis for ALL and AML and to identify markers for diagnosis and treatment, lncRNA and mRNA expression profiles of AML and ALL patients and healthy controls were generated using microarray analysis. For comparison, the differentially expressed mRNA functions were annotated using gene ontology (GO) and pathway analysis. The microarray revealed that 1011 lncRNAs and 2656 mRNAs differed in AML patients and 6069 lncRNAs and 5338 mRNAs differed in ALL patients from those in healthy controls. The GO terms and KEGG pathway annotation data revealed that the olfactory receptor activity, G-protein coupled receptor activity and olfactory transduction-related genes were significantly associated with AML and ALL. Co-expression network analysis indicated that 108 lncRNAs and 85 mRNAs were included in the co-expression network. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in AML and ALL using microarray technology and could provide basic information for new biomarkers or treatment targets to alleviate AML and ALL.

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Year:  2017        PMID: 28428987     DOI: 10.1039/c6mb00874g

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  6 in total

Review 1.  Linear and Circular Long Non-Coding RNAs in Acute Lymphoblastic Leukemia: From Pathogenesis to Classification and Treatment.

Authors:  Yasen Maimaitiyiming; Linyan Ye; Tao Yang; Wenjuan Yu; Hua Naranmandura
Journal:  Int J Mol Sci       Date:  2022-04-18       Impact factor: 6.208

2.  Identification of crucial long non-coding RNAs and mRNAs along with related regulatory networks through microarray analysis in esophageal carcinoma.

Authors:  Yaowen Zhang; Huitao Wang; Fuyou Zhou; Anlin Hao; Ningtao Dai; Haijun Yang; Anping Zheng
Journal:  Funct Integr Genomics       Date:  2021-04-16       Impact factor: 3.410

3.  LINC01255 combined with BMI1 to regulate human mesenchymal stromal senescence and acute myeloid leukemia cell proliferation through repressing transcription of MCP-1.

Authors:  Q Liu; H Zhang; J Dong; J Li; Y Duan; K Wang; Q Kong
Journal:  Clin Transl Oncol       Date:  2021-01-06       Impact factor: 3.405

4.  Prediction of Long Non-Coding RNAs Based on Deep Learning.

Authors:  Xiu-Qin Liu; Bing-Xiu Li; Guan-Rong Zeng; Qiao-Yue Liu; Dong-Mei Ai
Journal:  Genes (Basel)       Date:  2019-04-03       Impact factor: 4.096

5.  Identification and validation of inferior prognostic genes associated with immune signatures and chemotherapy outcome in acute myeloid leukemia.

Authors:  Jie Wang; Jian-Ping Hao; Md Nazim Uddin; Yun Wu; Rong Chen; Dong-Feng Li; Dai-Qin Xiong; Nan Ding; Jian-Hua Yang; Xuan-Sheng Ding
Journal:  Aging (Albany NY)       Date:  2021-06-18       Impact factor: 5.682

6.  Identification of long non-coding RNA competing interactions and biological pathways associated with prognosis in pediatric and adolescent cytogenetically normal acute myeloid leukemia.

Authors:  Xuejiao Yin; Sui Huang; Ruiqi Zhu; Fengjuan Fan; Chunyan Sun; Yu Hu
Journal:  Cancer Cell Int       Date:  2018-08-28       Impact factor: 5.722

  6 in total

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