Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma

Abstract Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a mean...

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Autores principales:	Matthew A. Wall, Serdar Turkarslan, Wei-Ju Wu, Samuel A. Danziger, David J. Reiss, Mike J. Mason, Andrew P. Dervan, Matthew W. B. Trotter, Douglas Bassett, Robert M. Hershberg, Adrián López García de Lomana, Alexander V. Ratushny, Nitin S. Baliga
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/8be0e48133514e37800ac2c098080257
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spelling	oai:doaj.org-article:8be0e48133514e37800ac2c0980802572021-12-02T14:33:50ZGenetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma10.1038/s41698-021-00185-02397-768Xhttps://doaj.org/article/8be0e48133514e37800ac2c0980802572021-06-01T00:00:00Zhttps://doi.org/10.1038/s41698-021-00185-0https://doaj.org/toc/2397-768XAbstract Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes. We identified 141 genetic programs whose activity profiles stratify patients into 25 distinct transcriptional states and proved to be more predictive of outcomes than did mutations. The coherence of these programs and accuracy of our network-based risk prediction was validated in two independent datasets. We observed subtype-specific vulnerabilities to interventions with existing drugs and revealed plausible mechanisms for relapse, including the establishment of an immunosuppressive microenvironment. Investigation of the t(4;14) clinical subtype using the TRN revealed that 16% of these patients exhibit an extreme-risk combination of genetic programs (median progression-free survival of 5 months) that create a distinct phenotype with targetable genes and pathways.Matthew A. WallSerdar TurkarslanWei-Ju WuSamuel A. DanzigerDavid J. ReissMike J. MasonAndrew P. DervanMatthew W. B. TrotterDouglas BassettRobert M. HershbergAdrián López García de LomanaAlexander V. RatushnyNitin S. BaligaNature PortfolioarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENnpj Precision Oncology, Vol 5, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Matthew A. Wall Serdar Turkarslan Wei-Ju Wu Samuel A. Danziger David J. Reiss Mike J. Mason Andrew P. Dervan Matthew W. B. Trotter Douglas Bassett Robert M. Hershberg Adrián López García de Lomana Alexander V. Ratushny Nitin S. Baliga Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
description	Abstract Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes. We identified 141 genetic programs whose activity profiles stratify patients into 25 distinct transcriptional states and proved to be more predictive of outcomes than did mutations. The coherence of these programs and accuracy of our network-based risk prediction was validated in two independent datasets. We observed subtype-specific vulnerabilities to interventions with existing drugs and revealed plausible mechanisms for relapse, including the establishment of an immunosuppressive microenvironment. Investigation of the t(4;14) clinical subtype using the TRN revealed that 16% of these patients exhibit an extreme-risk combination of genetic programs (median progression-free survival of 5 months) that create a distinct phenotype with targetable genes and pathways.
format	article
author	Matthew A. Wall Serdar Turkarslan Wei-Ju Wu Samuel A. Danziger David J. Reiss Mike J. Mason Andrew P. Dervan Matthew W. B. Trotter Douglas Bassett Robert M. Hershberg Adrián López García de Lomana Alexander V. Ratushny Nitin S. Baliga
author_facet	Matthew A. Wall Serdar Turkarslan Wei-Ju Wu Samuel A. Danziger David J. Reiss Mike J. Mason Andrew P. Dervan Matthew W. B. Trotter Douglas Bassett Robert M. Hershberg Adrián López García de Lomana Alexander V. Ratushny Nitin S. Baliga
author_sort	Matthew A. Wall
title	Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
title_short	Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
title_full	Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
title_fullStr	Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
title_full_unstemmed	Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
title_sort	genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8be0e48133514e37800ac2c098080257
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Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma

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