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Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma

BACKGROUND: With the rapid development of next-generation sequencing (NGS) technologies, researchers are making efforts to reveal the genomic landscape of multiple myeloma (MM). However, the clinical significance of many mutations remains poorly defined due to the genetic heterogeneity of MM. To sys...

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Autores principales: Zhang, Lina, Zhang, Run, Wang, Jing, Chen, Ying, Qiao, Chun, Shi, Qinglin, Jin, Yuanyuan, Shen, Xuxing, Li, Jianyong, Chen, Lijuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308335/
https://www.ncbi.nlm.nih.gov/pubmed/35870987
http://dx.doi.org/10.1186/s13148-022-01314-7
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author Zhang, Lina
Zhang, Run
Wang, Jing
Chen, Ying
Qiao, Chun
Shi, Qinglin
Jin, Yuanyuan
Shen, Xuxing
Li, Jianyong
Chen, Lijuan
author_facet Zhang, Lina
Zhang, Run
Wang, Jing
Chen, Ying
Qiao, Chun
Shi, Qinglin
Jin, Yuanyuan
Shen, Xuxing
Li, Jianyong
Chen, Lijuan
author_sort Zhang, Lina
collection PubMed
description BACKGROUND: With the rapid development of next-generation sequencing (NGS) technologies, researchers are making efforts to reveal the genomic landscape of multiple myeloma (MM). However, the clinical significance of many mutations remains poorly defined due to the genetic heterogeneity of MM. To systematically explore the clinical implications of gene mutations and build practical prognostic models, we performed DNA sequencing in newly diagnosed MM patients. METHODS: MM cells were purified from bone marrow aspirates using CD138 microbeads and subjected to sequencing with a 387-gene Panel. Nomogram was developed using Cox’s proportional hazards model, and candidate variables were screened by stepwise regression. Internal validation was carried out by the bootstrap method. RESULTS: Between July 2016 and December 2020, a total of 147 patients were included in our study. We found patients with a higher mutational load had a significantly shorter progress-free survival (PFS) (19.0 vs. 32.0 months, P = 0.0098) and overall survival (OS) (3-year OS rates were 66.1% and 80.0%, P = 0.0290). Mutations in chromatin regulators (CRs) including KMT2C (14.3%), KMT2D (14.3%), EP300 (11.6%) and ARID gene family (31.3%) were highly frequent in newly diagnosed MM patients. Interestingly, proteins encoded by these genes could form a complex called KMT2C/D COMPASS (K(CD)COMs). Patients with mutations of ARID gene family had a significantly shorter PFS (15.5 vs. 34.0 months, P = 0.0003) and OS (3-year OS rates were 64.9% and 81.0%, P = 0.0351) than patients without ARID gene mutations. Incorporating ARID gene mutations into the current staging system could successfully improve their prognostic performance. The PFS and OS nomogram models (including 1q21 copies, ARID gene mutations, extramedullary disease, mutational load and TP53 mutations) showed good predicting performance in both training and validation sets. CONCLUSION: Our findings emphasized the importance of CRs mutations in newly diagnosed MM patients and indicated the mutations affecting K(CD)COMs might promote the development of MM. High mutational load and harboring mutations in the ARID gene family were novel predictors of adverse prognosis in MM. Prognostic models based on gene mutations were commendably prognostic evaluation methods that could provide a reference for clinical practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01314-7.
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spelling pubmed-93083352022-07-24 Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma Zhang, Lina Zhang, Run Wang, Jing Chen, Ying Qiao, Chun Shi, Qinglin Jin, Yuanyuan Shen, Xuxing Li, Jianyong Chen, Lijuan Clin Epigenetics Research BACKGROUND: With the rapid development of next-generation sequencing (NGS) technologies, researchers are making efforts to reveal the genomic landscape of multiple myeloma (MM). However, the clinical significance of many mutations remains poorly defined due to the genetic heterogeneity of MM. To systematically explore the clinical implications of gene mutations and build practical prognostic models, we performed DNA sequencing in newly diagnosed MM patients. METHODS: MM cells were purified from bone marrow aspirates using CD138 microbeads and subjected to sequencing with a 387-gene Panel. Nomogram was developed using Cox’s proportional hazards model, and candidate variables were screened by stepwise regression. Internal validation was carried out by the bootstrap method. RESULTS: Between July 2016 and December 2020, a total of 147 patients were included in our study. We found patients with a higher mutational load had a significantly shorter progress-free survival (PFS) (19.0 vs. 32.0 months, P = 0.0098) and overall survival (OS) (3-year OS rates were 66.1% and 80.0%, P = 0.0290). Mutations in chromatin regulators (CRs) including KMT2C (14.3%), KMT2D (14.3%), EP300 (11.6%) and ARID gene family (31.3%) were highly frequent in newly diagnosed MM patients. Interestingly, proteins encoded by these genes could form a complex called KMT2C/D COMPASS (K(CD)COMs). Patients with mutations of ARID gene family had a significantly shorter PFS (15.5 vs. 34.0 months, P = 0.0003) and OS (3-year OS rates were 64.9% and 81.0%, P = 0.0351) than patients without ARID gene mutations. Incorporating ARID gene mutations into the current staging system could successfully improve their prognostic performance. The PFS and OS nomogram models (including 1q21 copies, ARID gene mutations, extramedullary disease, mutational load and TP53 mutations) showed good predicting performance in both training and validation sets. CONCLUSION: Our findings emphasized the importance of CRs mutations in newly diagnosed MM patients and indicated the mutations affecting K(CD)COMs might promote the development of MM. High mutational load and harboring mutations in the ARID gene family were novel predictors of adverse prognosis in MM. Prognostic models based on gene mutations were commendably prognostic evaluation methods that could provide a reference for clinical practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01314-7. BioMed Central 2022-07-23 /pmc/articles/PMC9308335/ /pubmed/35870987 http://dx.doi.org/10.1186/s13148-022-01314-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Lina
Zhang, Run
Wang, Jing
Chen, Ying
Qiao, Chun
Shi, Qinglin
Jin, Yuanyuan
Shen, Xuxing
Li, Jianyong
Chen, Lijuan
Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title_full Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title_fullStr Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title_full_unstemmed Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title_short Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
title_sort identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308335/
https://www.ncbi.nlm.nih.gov/pubmed/35870987
http://dx.doi.org/10.1186/s13148-022-01314-7
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