Cargando…

Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis

BACKGROUND: RUNXl plays a key regulatory role in the process of hematopoiesis and is a common target for multiple chromosomal translocations in human acute leukemia. Mutations of RUNX1 gene can lead to acute leukemia and affect the prognosis of AML patients. We aimed to identify pivotal genes and pa...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Fangxiao, Huang, Rui, Li, Jing, Liao, Xiwen, Huang, Yumei, Lai, Yongrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186152/
https://www.ncbi.nlm.nih.gov/pubmed/30289875
http://dx.doi.org/10.12659/MSM910916
_version_ 1783362821829951488
author Zhu, Fangxiao
Huang, Rui
Li, Jing
Liao, Xiwen
Huang, Yumei
Lai, Yongrong
author_facet Zhu, Fangxiao
Huang, Rui
Li, Jing
Liao, Xiwen
Huang, Yumei
Lai, Yongrong
author_sort Zhu, Fangxiao
collection PubMed
description BACKGROUND: RUNXl plays a key regulatory role in the process of hematopoiesis and is a common target for multiple chromosomal translocations in human acute leukemia. Mutations of RUNX1 gene can lead to acute leukemia and affect the prognosis of AML patients. We aimed to identify pivotal genes and pathways involved in RUNX1-mutated patients of with acute myeloid leukemia (AML) and to explore possible molecular markers for novel therapeutic targets of the disease. MATERIAL/METHODS: The RNA sequencing datasets of 151 cases of AML were obtained from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified using edgeR of the R platform. PPI (protein–protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS: A total of 379 genes were identified as DEGs. The KEGG enrichment analysis of DEGs showed significantly enriched pathways in cancer, extracellular matrix (ECM)-receptor interaction pathway, and cyclic adenosine monophosphate (cAMP) signaling pathway. The top 10 genes ranked by degree were PRKACG, ANKRD7, RNFL7, ROPN11, TEX14, PRMT8, OTOA, CFAP99, NRXN1, and DMRT1, which were identified as hub genes from the protein–protein interaction network (PPI). Statistical analysis revealed that RUNX1-mutated patients with AML had a shorter median survival time (MST) with poor clinical outcome and an increased risk of death when compared with those without RUNX1 mutations. CONCLUSIONS: DEGs and pathways identified in the present study will help understand the molecular mechanisms underlying RUNX1 mutations in AML and develop effective therapeutic strategies for RUNX1-mutation AML.
format Online
Article
Text
id pubmed-6186152
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher International Scientific Literature, Inc.
record_format MEDLINE/PubMed
spelling pubmed-61861522018-10-18 Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis Zhu, Fangxiao Huang, Rui Li, Jing Liao, Xiwen Huang, Yumei Lai, Yongrong Med Sci Monit Lab/In Vitro Research BACKGROUND: RUNXl plays a key regulatory role in the process of hematopoiesis and is a common target for multiple chromosomal translocations in human acute leukemia. Mutations of RUNX1 gene can lead to acute leukemia and affect the prognosis of AML patients. We aimed to identify pivotal genes and pathways involved in RUNX1-mutated patients of with acute myeloid leukemia (AML) and to explore possible molecular markers for novel therapeutic targets of the disease. MATERIAL/METHODS: The RNA sequencing datasets of 151 cases of AML were obtained from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified using edgeR of the R platform. PPI (protein–protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS: A total of 379 genes were identified as DEGs. The KEGG enrichment analysis of DEGs showed significantly enriched pathways in cancer, extracellular matrix (ECM)-receptor interaction pathway, and cyclic adenosine monophosphate (cAMP) signaling pathway. The top 10 genes ranked by degree were PRKACG, ANKRD7, RNFL7, ROPN11, TEX14, PRMT8, OTOA, CFAP99, NRXN1, and DMRT1, which were identified as hub genes from the protein–protein interaction network (PPI). Statistical analysis revealed that RUNX1-mutated patients with AML had a shorter median survival time (MST) with poor clinical outcome and an increased risk of death when compared with those without RUNX1 mutations. CONCLUSIONS: DEGs and pathways identified in the present study will help understand the molecular mechanisms underlying RUNX1 mutations in AML and develop effective therapeutic strategies for RUNX1-mutation AML. International Scientific Literature, Inc. 2018-10-05 /pmc/articles/PMC6186152/ /pubmed/30289875 http://dx.doi.org/10.12659/MSM910916 Text en © Med Sci Monit, 2018 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Lab/In Vitro Research
Zhu, Fangxiao
Huang, Rui
Li, Jing
Liao, Xiwen
Huang, Yumei
Lai, Yongrong
Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title_full Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title_fullStr Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title_full_unstemmed Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title_short Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis
title_sort identification of key genes and pathways associated with runx1 mutations in acute myeloid leukemia using bioinformatics analysis
topic Lab/In Vitro Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186152/
https://www.ncbi.nlm.nih.gov/pubmed/30289875
http://dx.doi.org/10.12659/MSM910916
work_keys_str_mv AT zhufangxiao identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis
AT huangrui identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis
AT lijing identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis
AT liaoxiwen identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis
AT huangyumei identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis
AT laiyongrong identificationofkeygenesandpathwaysassociatedwithrunx1mutationsinacutemyeloidleukemiausingbioinformaticsanalysis