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Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients

OBJECTIVE: In recent years, whole-genome sequencing and whole-exon sequencing have revealed the spectrum of gene mutations in multiple myeloma (MM). Gene mutations may play an important role in the pathogenesis, progression, and prognosis of this disease. On the basis of these studies, we establishe...

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Autores principales: Hu, Ying, Chen, Wenming, Wang, Jingbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877412/
https://www.ncbi.nlm.nih.gov/pubmed/31819496
http://dx.doi.org/10.2147/OTT.S216289
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author Hu, Ying
Chen, Wenming
Wang, Jingbo
author_facet Hu, Ying
Chen, Wenming
Wang, Jingbo
author_sort Hu, Ying
collection PubMed
description OBJECTIVE: In recent years, whole-genome sequencing and whole-exon sequencing have revealed the spectrum of gene mutations in multiple myeloma (MM). Gene mutations may play an important role in the pathogenesis, progression, and prognosis of this disease. On the basis of these studies, we established a box of mutations in 30 hotspot genes and analyzed the characteristics in newly diagnosed MM patients in China. METHODS: Bone marrow samples were collected. Mononuclear cells were isolated and plasma cells were separated using CD138 magnetic beads. Gene mutations were detected by PCR and Sanger sequencing. Fluorescence in situ hybridization (FISH) was used to analyze 1q21, 17p13.1, 14q32/16q23, 14q32/4p16, and 14q32/11q13.3. In the first part of this study, characterization of 30 genes and FISH analysis were performed in 40 patients. For economic reasons, in the second part of this study, 12 of 30 genes were characterized in another 46 patients. RESULTS: In the 40 patients of the first part of this study, single nucleotide polymorphisms (SNPs) were detected in 7 genes (CRBN, ATM, FAT4, FAM46C, RB1, NR3C1, and SPEN), while 16 genes were mutated (ATM, CUL4B, IRF4, CCND1, KRAS, DIS3, CRBN, TP53, FAT4, NR3C1, VCAN, RB1, SP140, NRAS, EGR1, and BRAF). Overall, 83 mutations of 30 genes were identified, including 54 intronic mutations, 18 missense mutations, 6 synonymous mutations, 3 5′/3′-UTR mutations, and 2 deletions mutations. Cytogenetic abnormalities were also screened in the 40 patients assayed, with 50% of the patients having 1q21(+), 12.5% having 17p(−), 15% having t(4;14), and 17.5% having t(11;14). DIS3 was mutated in 4/40, three of which involved t(4;14) or t(11;14). TP53 was mutated in two non-17p(−) patients, one of whom survived only 7 months, while the other survived 13 months. Three genes (ATM, CUL4B, and IRF4) with a high mutation rate were analyzed for an association with survival. There was no statistically significant difference in 2-year PFS (progress free survival) and 2-year OS (overall survival) between patients with or without ATM or CUL4B mutation (P>0.05). This finding was also obtained for IFR4 mutation, but patients with IFR4 mutation did show trends for longer PFS and OS. CONCLUSION: SNPs and other types of gene mutations are common in newly diagnosed Chinese multiple myeloma patients. The genes most commonly featuring SNPs are CRBN, ATM, FAT4, and FAM46C, while the genes most commonly featuring other mutation types are ATM, CUL4B, and IRF4. There were differences in the profiles of genes affected by SNPs and by other mutation types. Intronic mutations were the most common mutation type. Gene mutations may differ among patients with different cytogenetic abnormalities. Genetic mutations may be associated with prognosis.
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spelling pubmed-68774122019-12-09 Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients Hu, Ying Chen, Wenming Wang, Jingbo Onco Targets Ther Original Research OBJECTIVE: In recent years, whole-genome sequencing and whole-exon sequencing have revealed the spectrum of gene mutations in multiple myeloma (MM). Gene mutations may play an important role in the pathogenesis, progression, and prognosis of this disease. On the basis of these studies, we established a box of mutations in 30 hotspot genes and analyzed the characteristics in newly diagnosed MM patients in China. METHODS: Bone marrow samples were collected. Mononuclear cells were isolated and plasma cells were separated using CD138 magnetic beads. Gene mutations were detected by PCR and Sanger sequencing. Fluorescence in situ hybridization (FISH) was used to analyze 1q21, 17p13.1, 14q32/16q23, 14q32/4p16, and 14q32/11q13.3. In the first part of this study, characterization of 30 genes and FISH analysis were performed in 40 patients. For economic reasons, in the second part of this study, 12 of 30 genes were characterized in another 46 patients. RESULTS: In the 40 patients of the first part of this study, single nucleotide polymorphisms (SNPs) were detected in 7 genes (CRBN, ATM, FAT4, FAM46C, RB1, NR3C1, and SPEN), while 16 genes were mutated (ATM, CUL4B, IRF4, CCND1, KRAS, DIS3, CRBN, TP53, FAT4, NR3C1, VCAN, RB1, SP140, NRAS, EGR1, and BRAF). Overall, 83 mutations of 30 genes were identified, including 54 intronic mutations, 18 missense mutations, 6 synonymous mutations, 3 5′/3′-UTR mutations, and 2 deletions mutations. Cytogenetic abnormalities were also screened in the 40 patients assayed, with 50% of the patients having 1q21(+), 12.5% having 17p(−), 15% having t(4;14), and 17.5% having t(11;14). DIS3 was mutated in 4/40, three of which involved t(4;14) or t(11;14). TP53 was mutated in two non-17p(−) patients, one of whom survived only 7 months, while the other survived 13 months. Three genes (ATM, CUL4B, and IRF4) with a high mutation rate were analyzed for an association with survival. There was no statistically significant difference in 2-year PFS (progress free survival) and 2-year OS (overall survival) between patients with or without ATM or CUL4B mutation (P>0.05). This finding was also obtained for IFR4 mutation, but patients with IFR4 mutation did show trends for longer PFS and OS. CONCLUSION: SNPs and other types of gene mutations are common in newly diagnosed Chinese multiple myeloma patients. The genes most commonly featuring SNPs are CRBN, ATM, FAT4, and FAM46C, while the genes most commonly featuring other mutation types are ATM, CUL4B, and IRF4. There were differences in the profiles of genes affected by SNPs and by other mutation types. Intronic mutations were the most common mutation type. Gene mutations may differ among patients with different cytogenetic abnormalities. Genetic mutations may be associated with prognosis. Dove 2019-11-21 /pmc/articles/PMC6877412/ /pubmed/31819496 http://dx.doi.org/10.2147/OTT.S216289 Text en © 2019 Hu et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Hu, Ying
Chen, Wenming
Wang, Jingbo
Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title_full Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title_fullStr Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title_full_unstemmed Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title_short Mutations In Thirty Hotspot Genes In Newly Diagnosed Chinese Multiple Myeloma Patients
title_sort mutations in thirty hotspot genes in newly diagnosed chinese multiple myeloma patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877412/
https://www.ncbi.nlm.nih.gov/pubmed/31819496
http://dx.doi.org/10.2147/OTT.S216289
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