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Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles

BACKGROUND: Multiple myeloma (MM) is a cancer of terminally differentiated plasma that is part of a spectrum of blood diseases. The role of the micro-environment is crucial for MM clonal evolution. METHODS: This paper describes the analysis carried out on a limited number of genes automatically extr...

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Autores principales: Boccarelli, Angelina, Esposito, Flavia, Coluccia, Mauro, Frassanito, Maria Antonia, Vacca, Angelo, Del Buono, Nicoletta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6076394/
https://www.ncbi.nlm.nih.gov/pubmed/30075788
http://dx.doi.org/10.1186/s12967-018-1589-1
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author Boccarelli, Angelina
Esposito, Flavia
Coluccia, Mauro
Frassanito, Maria Antonia
Vacca, Angelo
Del Buono, Nicoletta
author_facet Boccarelli, Angelina
Esposito, Flavia
Coluccia, Mauro
Frassanito, Maria Antonia
Vacca, Angelo
Del Buono, Nicoletta
author_sort Boccarelli, Angelina
collection PubMed
description BACKGROUND: Multiple myeloma (MM) is a cancer of terminally differentiated plasma that is part of a spectrum of blood diseases. The role of the micro-environment is crucial for MM clonal evolution. METHODS: This paper describes the analysis carried out on a limited number of genes automatically extracted by a nonnegative matrix factorization (NMF) based approach from gene expression profiles of bone marrow fibroblasts of patients with monoclonal gammopathy of undetermined significance (MGUS) and MM. RESULTS: Automatic exploration through NMF, combined with a motivated post-processing procedure and a pathways analysis of extracted genes, allowed to infer that a functional switch is required to lead fibroblasts to acquire pro-tumorigenic activity in the progression of the disease from MGUS to MM. CONCLUSION: The extracted biologically relevant genes may be representative of the considered clinical conditions and may contribute to a deeper understanding of tumor behavior. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1589-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-60763942018-08-07 Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles Boccarelli, Angelina Esposito, Flavia Coluccia, Mauro Frassanito, Maria Antonia Vacca, Angelo Del Buono, Nicoletta J Transl Med Research BACKGROUND: Multiple myeloma (MM) is a cancer of terminally differentiated plasma that is part of a spectrum of blood diseases. The role of the micro-environment is crucial for MM clonal evolution. METHODS: This paper describes the analysis carried out on a limited number of genes automatically extracted by a nonnegative matrix factorization (NMF) based approach from gene expression profiles of bone marrow fibroblasts of patients with monoclonal gammopathy of undetermined significance (MGUS) and MM. RESULTS: Automatic exploration through NMF, combined with a motivated post-processing procedure and a pathways analysis of extracted genes, allowed to infer that a functional switch is required to lead fibroblasts to acquire pro-tumorigenic activity in the progression of the disease from MGUS to MM. CONCLUSION: The extracted biologically relevant genes may be representative of the considered clinical conditions and may contribute to a deeper understanding of tumor behavior. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1589-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-03 /pmc/articles/PMC6076394/ /pubmed/30075788 http://dx.doi.org/10.1186/s12967-018-1589-1 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Boccarelli, Angelina
Esposito, Flavia
Coluccia, Mauro
Frassanito, Maria Antonia
Vacca, Angelo
Del Buono, Nicoletta
Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title_full Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title_fullStr Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title_full_unstemmed Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title_short Improving knowledge on the activation of bone marrow fibroblasts in MGUS and MM disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
title_sort improving knowledge on the activation of bone marrow fibroblasts in mgus and mm disease through the automatic extraction of genes via a nonnegative matrix factorization approach on gene expression profiles
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6076394/
https://www.ncbi.nlm.nih.gov/pubmed/30075788
http://dx.doi.org/10.1186/s12967-018-1589-1
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