Cargando…

Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis

The role of CXC chemokine receptors in tumors has been an increasingly researched focus in recent years. However, significant prognostic values of CXCR members in acute myeloid leukemia are yet to be explored profoundly. In this study, we firstly made an analysis of the relationship of CXCR family m...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Cong, Zhu, Jiang, Chen, Xiangjun, Hu, Yanjie, Xie, Wei, Yao, Junxia, Huang, Shiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769120/
https://www.ncbi.nlm.nih.gov/pubmed/33381455
http://dx.doi.org/10.3389/fonc.2020.584766
_version_ 1783629261680148480
author Lu, Cong
Zhu, Jiang
Chen, Xiangjun
Hu, Yanjie
Xie, Wei
Yao, Junxia
Huang, Shiang
author_facet Lu, Cong
Zhu, Jiang
Chen, Xiangjun
Hu, Yanjie
Xie, Wei
Yao, Junxia
Huang, Shiang
author_sort Lu, Cong
collection PubMed
description The role of CXC chemokine receptors in tumors has been an increasingly researched focus in recent years. However, significant prognostic values of CXCR members in acute myeloid leukemia are yet to be explored profoundly. In this study, we firstly made an analysis of the relationship of CXCR family members and AML using samples from TCGA. Our results suggested that transcriptional expressions of CXCRs serve an important role in AML. CXCR transcript expressions, except CXCR1 expression, were significantly increased in AML. It displayed the expression pattern of CXCR members in different AML subtypes according to FAB classification. The correlations of CXCR transcript expression with different genotypes and karyotypes were also present. High CXCR2 expression was found to have a significantly worse prognosis compared with that of low CXCR2 expression, and CXCR2 was also found to be an independent prognostic factor. We also established a CXCR signature to identify high-risk subgroups of patients with AML. It was an independent prognostic factor and could become a powerful method to predict the survival rate of patients.
format Online
Article
Text
id pubmed-7769120
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-77691202020-12-29 Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis Lu, Cong Zhu, Jiang Chen, Xiangjun Hu, Yanjie Xie, Wei Yao, Junxia Huang, Shiang Front Oncol Oncology The role of CXC chemokine receptors in tumors has been an increasingly researched focus in recent years. However, significant prognostic values of CXCR members in acute myeloid leukemia are yet to be explored profoundly. In this study, we firstly made an analysis of the relationship of CXCR family members and AML using samples from TCGA. Our results suggested that transcriptional expressions of CXCRs serve an important role in AML. CXCR transcript expressions, except CXCR1 expression, were significantly increased in AML. It displayed the expression pattern of CXCR members in different AML subtypes according to FAB classification. The correlations of CXCR transcript expression with different genotypes and karyotypes were also present. High CXCR2 expression was found to have a significantly worse prognosis compared with that of low CXCR2 expression, and CXCR2 was also found to be an independent prognostic factor. We also established a CXCR signature to identify high-risk subgroups of patients with AML. It was an independent prognostic factor and could become a powerful method to predict the survival rate of patients. Frontiers Media S.A. 2020-10-30 /pmc/articles/PMC7769120/ /pubmed/33381455 http://dx.doi.org/10.3389/fonc.2020.584766 Text en Copyright © 2020 Lu, Zhu, Chen, Hu, Xie, Yao and Huang http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Lu, Cong
Zhu, Jiang
Chen, Xiangjun
Hu, Yanjie
Xie, Wei
Yao, Junxia
Huang, Shiang
Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title_full Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title_fullStr Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title_full_unstemmed Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title_short Risk Stratification in Acute Myeloid Leukemia Using CXCR Gene Signatures: A Bioinformatics Analysis
title_sort risk stratification in acute myeloid leukemia using cxcr gene signatures: a bioinformatics analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769120/
https://www.ncbi.nlm.nih.gov/pubmed/33381455
http://dx.doi.org/10.3389/fonc.2020.584766
work_keys_str_mv AT lucong riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT zhujiang riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT chenxiangjun riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT huyanjie riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT xiewei riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT yaojunxia riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis
AT huangshiang riskstratificationinacutemyeloidleukemiausingcxcrgenesignaturesabioinformaticsanalysis