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Updated: Jan 19, 2026
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Expression profile analysis of prognostic long non-coding RNA in adult acute myeloid leukemia by weighted gene
Cun-Te Chen1, Pei-Pei Wang2, Wen-Jian Mo1
1Department of Hematology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
Abstract:
Background: Long non-coding RNAs (lncRNAs), which are over 200 nt in length, have a key role in tumorigenesis and disease progression. To explore the role of prognostic lncRNAs in adult acute myeloid leukemia (AML), the expression profiles of lncRNAs and mRNAs in AML were analyzed. Methods: The RNAseq data of 167 adult AML patients and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA), which is a publicly available database. The RPKM values of the RNAseq data were subjected to weighted gene co-expression network analysis (WGCNA) in modularization. Results: We identified survival specific lncRNAs and mRNAs, which were divided into modules by coexpression analysis. The lncRNAs were mainly annotated into "Fc gamma R-mediated phagocytosis". The hub lncRNA and co-expressed mRNAs were further selected for analysis of risk stratification. LncRNA-LOC646762 may contribute to AML through the "endocytosis" signaling pathway. Finally, the expression levels of LOC646762 and co-expressed CCND3, CBR1, C10orf54, CD97 and BLOC1S1 in the adult AML patients and healthy volunteers were validated by qRT-PCR, and then their roles in prognosis and risk stratification were identified. Conclusions: Prognostic lncRNA-LOC646762, which may contribute to AML through the "endocytosis" signaling pathway, may act as a biomarker for predicting the survival of adult AML patients, as well as for risk stratification.
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