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Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation
Induced granulocytic differentiation of human leukemic cells under all-trans-retinoid acid (ATRA) treatment underlies differentiation therapy of acute myeloid leukemia. Knowing the regulation of this process it is possible to identify potential targets for antileukemic drugs and develop novel approa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233756/ https://www.ncbi.nlm.nih.gov/pubmed/34207065 http://dx.doi.org/10.3390/biom11060907 |
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author | Novikova, Svetlana Tikhonova, Olga Kurbatov, Leonid Farafonova, Tatiana Vakhrushev, Igor Lupatov, Alexey Yarygin, Konstantin Zgoda, Victor |
author_facet | Novikova, Svetlana Tikhonova, Olga Kurbatov, Leonid Farafonova, Tatiana Vakhrushev, Igor Lupatov, Alexey Yarygin, Konstantin Zgoda, Victor |
author_sort | Novikova, Svetlana |
collection | PubMed |
description | Induced granulocytic differentiation of human leukemic cells under all-trans-retinoid acid (ATRA) treatment underlies differentiation therapy of acute myeloid leukemia. Knowing the regulation of this process it is possible to identify potential targets for antileukemic drugs and develop novel approaches to differentiation therapy. In this study, we have performed transcriptomic and proteomic profiling to reveal up- and down-regulated transcripts and proteins during time-course experiments. Using data on differentially expressed transcripts and proteins we have applied upstream regulator search and obtained transcriptome- and proteome-based regulatory networks of induced granulocytic differentiation that cover both up-regulated (HIC1, NFKBIA, and CASP9) and down-regulated (PARP1, VDR, and RXRA) elements. To verify the designed network we measured HIC1 and PARP1 protein abundance during granulocytic differentiation by selected reaction monitoring (SRM) using stable isotopically labeled peptide standards. We also revealed that transcription factor CEBPB and LYN kinase were involved in differentiation onset, and evaluated their protein levels by SRM technique. Obtained results indicate that the omics data reflect involvement of the DNA repair system and the MAPK kinase cascade as well as show the balance between the processes of the cell survival and apoptosis in a p53-independent manner. The differentially expressed transcripts and proteins, predicted transcriptional factors, and key molecules such as HIC1, CEBPB, LYN, and PARP1 may be considered as potential targets for differentiation therapy of acute myeloid leukemia. |
format | Online Article Text |
id | pubmed-8233756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82337562021-06-27 Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation Novikova, Svetlana Tikhonova, Olga Kurbatov, Leonid Farafonova, Tatiana Vakhrushev, Igor Lupatov, Alexey Yarygin, Konstantin Zgoda, Victor Biomolecules Article Induced granulocytic differentiation of human leukemic cells under all-trans-retinoid acid (ATRA) treatment underlies differentiation therapy of acute myeloid leukemia. Knowing the regulation of this process it is possible to identify potential targets for antileukemic drugs and develop novel approaches to differentiation therapy. In this study, we have performed transcriptomic and proteomic profiling to reveal up- and down-regulated transcripts and proteins during time-course experiments. Using data on differentially expressed transcripts and proteins we have applied upstream regulator search and obtained transcriptome- and proteome-based regulatory networks of induced granulocytic differentiation that cover both up-regulated (HIC1, NFKBIA, and CASP9) and down-regulated (PARP1, VDR, and RXRA) elements. To verify the designed network we measured HIC1 and PARP1 protein abundance during granulocytic differentiation by selected reaction monitoring (SRM) using stable isotopically labeled peptide standards. We also revealed that transcription factor CEBPB and LYN kinase were involved in differentiation onset, and evaluated their protein levels by SRM technique. Obtained results indicate that the omics data reflect involvement of the DNA repair system and the MAPK kinase cascade as well as show the balance between the processes of the cell survival and apoptosis in a p53-independent manner. The differentially expressed transcripts and proteins, predicted transcriptional factors, and key molecules such as HIC1, CEBPB, LYN, and PARP1 may be considered as potential targets for differentiation therapy of acute myeloid leukemia. MDPI 2021-06-18 /pmc/articles/PMC8233756/ /pubmed/34207065 http://dx.doi.org/10.3390/biom11060907 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Novikova, Svetlana Tikhonova, Olga Kurbatov, Leonid Farafonova, Tatiana Vakhrushev, Igor Lupatov, Alexey Yarygin, Konstantin Zgoda, Victor Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title | Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title_full | Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title_fullStr | Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title_full_unstemmed | Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title_short | Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation |
title_sort | omics technologies to decipher regulatory networks in granulocytic cell differentiation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233756/ https://www.ncbi.nlm.nih.gov/pubmed/34207065 http://dx.doi.org/10.3390/biom11060907 |
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