Cargando…

Analyzing the key gene expression and prognostics values for acute myeloid leukemia

BACKGROUND: Acute myeloid leukemia (AML) is one of the first tumor types sequenced at the whole genome level. However, numbers of the mutated genes expression levels, functions, and prognostics values still unclear. METHODS: To most ordinary mutated genes were analyzed via cancer virtual cohort disc...

Descripción completa

Detalles Bibliográficos
Autores principales: Shi, Lingling, Huang, Yan, Huang, Xunjun, Zhou, Weijie, Wei, Jie, Deng, Donghong, Lai, Yongrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797974/
https://www.ncbi.nlm.nih.gov/pubmed/35117330
http://dx.doi.org/10.21037/tcr-20-3177
_version_ 1784641683090046976
author Shi, Lingling
Huang, Yan
Huang, Xunjun
Zhou, Weijie
Wei, Jie
Deng, Donghong
Lai, Yongrong
author_facet Shi, Lingling
Huang, Yan
Huang, Xunjun
Zhou, Weijie
Wei, Jie
Deng, Donghong
Lai, Yongrong
author_sort Shi, Lingling
collection PubMed
description BACKGROUND: Acute myeloid leukemia (AML) is one of the first tumor types sequenced at the whole genome level. However, numbers of the mutated genes expression levels, functions, and prognostics values still unclear. METHODS: To most ordinary mutated genes were analyzed via cancer virtual cohort discovery analysis platform (CVCDAP), and further investigated the mutational conversions, variant allele frequencies (VAF), driver genes, and potential druggable mutated genes in AML. The top mutated gene mRNA expression levels and the relationship between gene expression levels and prognosis for AML patients were performed by Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the UALCAN dataset to confirm the association between gene expression levels and prognosis for AML patients. Enrichment functions of the top mutated genes of AML were analyzed through Metascape. Finally, the role of these defined genes in cancer pathways and potential drug targets were analyzed by gene set cancer analysis (GSCALite). RESULTS: The top 20 mutated genes for AML included FLT3, HPS3, ABCA6, PCLO, SLIT2, and other ones. Compared to normal control samples, NPM1 and GABRB3 were significantly downregulated in AML samples, but TP53, DNMT3A, HPS3, FLT3, SENP6, and RUNX1 were significantly overexpressed (all these genes P value <0.01). Overexpression of FLT3 and PCLO indicated a poor prognosis, but the overexpression of SLIT3 functioned as a protector for AML via GEPIA. HSP3 indicates the favorable factor for AML, but overexpression of ABCA6 (P=0.066) may act as the adverse factor by UALCAN analysis. Enrichment function analysis shows the functions of defining genes, including negative regulation of cell differentiation, small GTPase mediated signal transduction, and immune system process. Finally, these genes participate in apoptosis, cell cycle, PI3K/AKT, and RAS/MAPK signaling pathway, and FLT3 is sensitive to 5-Fluorouracil, Methotrexate, ATRA. DNMT3A and IDH2 are resistant to Trametinib. RUNX1 and TP53 were sensitive to I-BET-762 and Tubastatin A. CONCLUSIONS: Present study showed overexpression of FLT3, ABCA6, and PCLO indicated the poor prognosis of AML, but overexpression of SLIT3 and HSP3 functioned as an AML protector. There are several drugs and small molecules that target the top 20 mutated genes in AML.
format Online
Article
Text
id pubmed-8797974
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher AME Publishing Company
record_format MEDLINE/PubMed
spelling pubmed-87979742022-02-02 Analyzing the key gene expression and prognostics values for acute myeloid leukemia Shi, Lingling Huang, Yan Huang, Xunjun Zhou, Weijie Wei, Jie Deng, Donghong Lai, Yongrong Transl Cancer Res Original Article BACKGROUND: Acute myeloid leukemia (AML) is one of the first tumor types sequenced at the whole genome level. However, numbers of the mutated genes expression levels, functions, and prognostics values still unclear. METHODS: To most ordinary mutated genes were analyzed via cancer virtual cohort discovery analysis platform (CVCDAP), and further investigated the mutational conversions, variant allele frequencies (VAF), driver genes, and potential druggable mutated genes in AML. The top mutated gene mRNA expression levels and the relationship between gene expression levels and prognosis for AML patients were performed by Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the UALCAN dataset to confirm the association between gene expression levels and prognosis for AML patients. Enrichment functions of the top mutated genes of AML were analyzed through Metascape. Finally, the role of these defined genes in cancer pathways and potential drug targets were analyzed by gene set cancer analysis (GSCALite). RESULTS: The top 20 mutated genes for AML included FLT3, HPS3, ABCA6, PCLO, SLIT2, and other ones. Compared to normal control samples, NPM1 and GABRB3 were significantly downregulated in AML samples, but TP53, DNMT3A, HPS3, FLT3, SENP6, and RUNX1 were significantly overexpressed (all these genes P value <0.01). Overexpression of FLT3 and PCLO indicated a poor prognosis, but the overexpression of SLIT3 functioned as a protector for AML via GEPIA. HSP3 indicates the favorable factor for AML, but overexpression of ABCA6 (P=0.066) may act as the adverse factor by UALCAN analysis. Enrichment function analysis shows the functions of defining genes, including negative regulation of cell differentiation, small GTPase mediated signal transduction, and immune system process. Finally, these genes participate in apoptosis, cell cycle, PI3K/AKT, and RAS/MAPK signaling pathway, and FLT3 is sensitive to 5-Fluorouracil, Methotrexate, ATRA. DNMT3A and IDH2 are resistant to Trametinib. RUNX1 and TP53 were sensitive to I-BET-762 and Tubastatin A. CONCLUSIONS: Present study showed overexpression of FLT3, ABCA6, and PCLO indicated the poor prognosis of AML, but overexpression of SLIT3 and HSP3 functioned as an AML protector. There are several drugs and small molecules that target the top 20 mutated genes in AML. AME Publishing Company 2020-11 /pmc/articles/PMC8797974/ /pubmed/35117330 http://dx.doi.org/10.21037/tcr-20-3177 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Shi, Lingling
Huang, Yan
Huang, Xunjun
Zhou, Weijie
Wei, Jie
Deng, Donghong
Lai, Yongrong
Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title_full Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title_fullStr Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title_full_unstemmed Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title_short Analyzing the key gene expression and prognostics values for acute myeloid leukemia
title_sort analyzing the key gene expression and prognostics values for acute myeloid leukemia
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797974/
https://www.ncbi.nlm.nih.gov/pubmed/35117330
http://dx.doi.org/10.21037/tcr-20-3177
work_keys_str_mv AT shilingling analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT huangyan analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT huangxunjun analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT zhouweijie analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT weijie analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT dengdonghong analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia
AT laiyongrong analyzingthekeygeneexpressionandprognosticsvaluesforacutemyeloidleukemia