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Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification
BACKGROUND: Enoyl-CoA hydratase domain containing 3 (ECHDC3) increased in CD34(+) progenitor cells of acute myeloid leukemia (AML) cells after chemotherapy. However, the prognostic significance and function of ECHDC3 in AML remain to be clarified. METHODS: In the training cohort, 24 AML (non-acute p...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511173/ https://www.ncbi.nlm.nih.gov/pubmed/36172164 http://dx.doi.org/10.3389/fonc.2022.947492 |
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author | Zhao, Yijing Niu, Li-Ting Hu, Li-Juan Lv, Meng |
author_facet | Zhao, Yijing Niu, Li-Ting Hu, Li-Juan Lv, Meng |
author_sort | Zhao, Yijing |
collection | PubMed |
description | BACKGROUND: Enoyl-CoA hydratase domain containing 3 (ECHDC3) increased in CD34(+) progenitor cells of acute myeloid leukemia (AML) cells after chemotherapy. However, the prognostic significance and function of ECHDC3 in AML remain to be clarified. METHODS: In the training cohort, 24 AML (non-acute promyelocytic leukemia, APL) patients were enrolled in Peking University People’s Hospital and tested for ECHDC3 in enriched CD34(+) cells at diagnosis. In the validation set, 351 bone marrow RNA-seq data of non-APL AML were obtained by two independent online datasets (TCGA-LAML and BEAT-AML). LASSO regression model was conducted to a new prediction model of ECHDC3-related genes. In addition, the ECHDC3 signature was further explored by GO, KEGG, GSEA, and immuno-infiltration analysis. By RNA interference, the function of ECHDC3 in mitochondrial DNA (mt-DNA) transcriptome and chemoresistance was further explored, and the GSE52919 database re-verified the ECHDC3 chemoresistance feature. RESULTS: By Kaplan-Meier analysis, patients with ECHDC3(high) demonstrated inferior overall survival (OS) compared to those with ECHDC3(low) both in the training (2-year OS, 55.6% vs. 100%, p = 0.011) and validation cohorts (5-year OS, 9.6% vs. 24.3%, p = 0.002). In addition, ECHDC3(high) predicted inferior OS in the subgroup of patients with ELN 2017 intermediated (int) risk (5-year OS, 9.5% vs. 26.3%, p = 0.039) or FLT3+NPM1− adverse (adv) risk (4-year OS, 6.4% vs. 31.8%, p = 0.003). In multivariate analysis, ECHDC3 was an independent risk factor of inferior OS (HR 1.159, 95% CI 1.013–1.326, p = 0.032). In the prediction model combining ECHDC3 and nine selected genes (RPS6KL1, RELL2, FAM64A, SPATS2L, MEIS3P1, CDCP1, CD276, IL1R2, and OLFML2A) by Lasso regression, patients with high risk showed inferior 5-year OS (9.3% vs. 23.5%, p < 0.001). Bioinformatic analysis suggested that ECHDC3 alters the bone marrow microenvironment by inducing NK, resting mast cell, and monocyte differentiation. Knocking down ECHDC3 in AML cells by RNAi promoted the death of leukemia cells with cytarabine and doxorubicin. CONCLUSION: These bioinformatic analyses and experimental verification indicated that high ECHDC3 expression might be a poor prognostic biomarker for non-APL AML, which might be a potential target for reverting chemoresistance. |
format | Online Article Text |
id | pubmed-9511173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95111732022-09-27 Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification Zhao, Yijing Niu, Li-Ting Hu, Li-Juan Lv, Meng Front Oncol Oncology BACKGROUND: Enoyl-CoA hydratase domain containing 3 (ECHDC3) increased in CD34(+) progenitor cells of acute myeloid leukemia (AML) cells after chemotherapy. However, the prognostic significance and function of ECHDC3 in AML remain to be clarified. METHODS: In the training cohort, 24 AML (non-acute promyelocytic leukemia, APL) patients were enrolled in Peking University People’s Hospital and tested for ECHDC3 in enriched CD34(+) cells at diagnosis. In the validation set, 351 bone marrow RNA-seq data of non-APL AML were obtained by two independent online datasets (TCGA-LAML and BEAT-AML). LASSO regression model was conducted to a new prediction model of ECHDC3-related genes. In addition, the ECHDC3 signature was further explored by GO, KEGG, GSEA, and immuno-infiltration analysis. By RNA interference, the function of ECHDC3 in mitochondrial DNA (mt-DNA) transcriptome and chemoresistance was further explored, and the GSE52919 database re-verified the ECHDC3 chemoresistance feature. RESULTS: By Kaplan-Meier analysis, patients with ECHDC3(high) demonstrated inferior overall survival (OS) compared to those with ECHDC3(low) both in the training (2-year OS, 55.6% vs. 100%, p = 0.011) and validation cohorts (5-year OS, 9.6% vs. 24.3%, p = 0.002). In addition, ECHDC3(high) predicted inferior OS in the subgroup of patients with ELN 2017 intermediated (int) risk (5-year OS, 9.5% vs. 26.3%, p = 0.039) or FLT3+NPM1− adverse (adv) risk (4-year OS, 6.4% vs. 31.8%, p = 0.003). In multivariate analysis, ECHDC3 was an independent risk factor of inferior OS (HR 1.159, 95% CI 1.013–1.326, p = 0.032). In the prediction model combining ECHDC3 and nine selected genes (RPS6KL1, RELL2, FAM64A, SPATS2L, MEIS3P1, CDCP1, CD276, IL1R2, and OLFML2A) by Lasso regression, patients with high risk showed inferior 5-year OS (9.3% vs. 23.5%, p < 0.001). Bioinformatic analysis suggested that ECHDC3 alters the bone marrow microenvironment by inducing NK, resting mast cell, and monocyte differentiation. Knocking down ECHDC3 in AML cells by RNAi promoted the death of leukemia cells with cytarabine and doxorubicin. CONCLUSION: These bioinformatic analyses and experimental verification indicated that high ECHDC3 expression might be a poor prognostic biomarker for non-APL AML, which might be a potential target for reverting chemoresistance. Frontiers Media S.A. 2022-09-12 /pmc/articles/PMC9511173/ /pubmed/36172164 http://dx.doi.org/10.3389/fonc.2022.947492 Text en Copyright © 2022 Zhao, Niu, Hu and Lv https://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 Zhao, Yijing Niu, Li-Ting Hu, Li-Juan Lv, Meng Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title | Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title_full | Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title_fullStr | Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title_full_unstemmed | Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title_short | Comprehensive analysis of ECHDC3 as a potential biomarker and therapeutic target for acute myeloid leukemia: Bioinformatic analysis and experimental verification |
title_sort | comprehensive analysis of echdc3 as a potential biomarker and therapeutic target for acute myeloid leukemia: bioinformatic analysis and experimental verification |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511173/ https://www.ncbi.nlm.nih.gov/pubmed/36172164 http://dx.doi.org/10.3389/fonc.2022.947492 |
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