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A gene signature can predict risk of MGUS progressing to multiple myeloma
Multiple myeloma is preceded by monoclonal gammopathy of undetermined significance (MGUS). Serum markers are currently used to stratify MGUS patients into clinical risk groups. A molecular signature predicting MGUS progression has not been produced. We have explored the use of gene expression profil...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308756/ https://www.ncbi.nlm.nih.gov/pubmed/37386588 http://dx.doi.org/10.1186/s13045-023-01472-y |
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author | Sun, Fumou Cheng, Yan Ying, Jun Mery, David Al Hadidi, Samer Wanchai, Visanu Siegel, Eric R. Xu, Hongwei Gai, Dongzheng Ashby, Timothy Cody Bailey, Clyde Chen, Jin-Ran Schinke, Carolina Thanendrarajan, Sharmilan Zangari, Maurizio Janz, Siegfried Barlogie, Bart Van Rhee, Frits Tricot, Guido Shaughnessy, John D. Zhan, Fenghuang |
author_facet | Sun, Fumou Cheng, Yan Ying, Jun Mery, David Al Hadidi, Samer Wanchai, Visanu Siegel, Eric R. Xu, Hongwei Gai, Dongzheng Ashby, Timothy Cody Bailey, Clyde Chen, Jin-Ran Schinke, Carolina Thanendrarajan, Sharmilan Zangari, Maurizio Janz, Siegfried Barlogie, Bart Van Rhee, Frits Tricot, Guido Shaughnessy, John D. Zhan, Fenghuang |
author_sort | Sun, Fumou |
collection | PubMed |
description | Multiple myeloma is preceded by monoclonal gammopathy of undetermined significance (MGUS). Serum markers are currently used to stratify MGUS patients into clinical risk groups. A molecular signature predicting MGUS progression has not been produced. We have explored the use of gene expression profiling to risk-stratify MGUS and developed an optimized signature based on large samples with long-term follow-up. Microarrays of plasma cell mRNA from 334 MGUS with stable disease and 40 MGUS that progressed to MM within 10 years, was used to define a molecular signature of MGUS risk. After a three-fold cross-validation analysis, the top thirty-six genes that appeared in each validation and maximized the concordance between risk score and MGUS progression were included in the gene signature (GS36). The GS36 accurately predicted MGUS progression (C-statistic is 0.928). An optimal cut-point for risk of progression by the GS36 score was found to be 0.7, which identified a subset of 61 patients with a 10-year progression probability of 54.1%. The remainder of the 313 patients had a probability of progression of only 2.2%. The sensitivity and specificity were 82.5% and 91.6%. Furthermore, combination of GS36, free light chain ratio and immunoparesis identified a subset of MGUS patients with 82.4% risk of progression to MM within 10 years. A gene expression signature combined with serum markers created a highly robust model for predicting risk of MGUS progression. These findings strongly support the inclusion of genomic analysis in the management of MGUS to identify patients who may benefit from more frequent monitoring. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-023-01472-y. |
format | Online Article Text |
id | pubmed-10308756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103087562023-06-30 A gene signature can predict risk of MGUS progressing to multiple myeloma Sun, Fumou Cheng, Yan Ying, Jun Mery, David Al Hadidi, Samer Wanchai, Visanu Siegel, Eric R. Xu, Hongwei Gai, Dongzheng Ashby, Timothy Cody Bailey, Clyde Chen, Jin-Ran Schinke, Carolina Thanendrarajan, Sharmilan Zangari, Maurizio Janz, Siegfried Barlogie, Bart Van Rhee, Frits Tricot, Guido Shaughnessy, John D. Zhan, Fenghuang J Hematol Oncol Correspondence Multiple myeloma is preceded by monoclonal gammopathy of undetermined significance (MGUS). Serum markers are currently used to stratify MGUS patients into clinical risk groups. A molecular signature predicting MGUS progression has not been produced. We have explored the use of gene expression profiling to risk-stratify MGUS and developed an optimized signature based on large samples with long-term follow-up. Microarrays of plasma cell mRNA from 334 MGUS with stable disease and 40 MGUS that progressed to MM within 10 years, was used to define a molecular signature of MGUS risk. After a three-fold cross-validation analysis, the top thirty-six genes that appeared in each validation and maximized the concordance between risk score and MGUS progression were included in the gene signature (GS36). The GS36 accurately predicted MGUS progression (C-statistic is 0.928). An optimal cut-point for risk of progression by the GS36 score was found to be 0.7, which identified a subset of 61 patients with a 10-year progression probability of 54.1%. The remainder of the 313 patients had a probability of progression of only 2.2%. The sensitivity and specificity were 82.5% and 91.6%. Furthermore, combination of GS36, free light chain ratio and immunoparesis identified a subset of MGUS patients with 82.4% risk of progression to MM within 10 years. A gene expression signature combined with serum markers created a highly robust model for predicting risk of MGUS progression. These findings strongly support the inclusion of genomic analysis in the management of MGUS to identify patients who may benefit from more frequent monitoring. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13045-023-01472-y. BioMed Central 2023-06-29 /pmc/articles/PMC10308756/ /pubmed/37386588 http://dx.doi.org/10.1186/s13045-023-01472-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Correspondence Sun, Fumou Cheng, Yan Ying, Jun Mery, David Al Hadidi, Samer Wanchai, Visanu Siegel, Eric R. Xu, Hongwei Gai, Dongzheng Ashby, Timothy Cody Bailey, Clyde Chen, Jin-Ran Schinke, Carolina Thanendrarajan, Sharmilan Zangari, Maurizio Janz, Siegfried Barlogie, Bart Van Rhee, Frits Tricot, Guido Shaughnessy, John D. Zhan, Fenghuang A gene signature can predict risk of MGUS progressing to multiple myeloma |
title | A gene signature can predict risk of MGUS progressing to multiple myeloma |
title_full | A gene signature can predict risk of MGUS progressing to multiple myeloma |
title_fullStr | A gene signature can predict risk of MGUS progressing to multiple myeloma |
title_full_unstemmed | A gene signature can predict risk of MGUS progressing to multiple myeloma |
title_short | A gene signature can predict risk of MGUS progressing to multiple myeloma |
title_sort | gene signature can predict risk of mgus progressing to multiple myeloma |
topic | Correspondence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308756/ https://www.ncbi.nlm.nih.gov/pubmed/37386588 http://dx.doi.org/10.1186/s13045-023-01472-y |
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