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Robust inflammatory breast cancer gene signature using nonparametric random forest analysis
Inflammatory breast cancer (IBC) is a rare, aggressive cancer found in all the molecular breast cancer subtypes. Despite extensive previous efforts to screen for transcriptional differences between IBC and non-IBC patients, a robust IBC-specific molecular signature has been elusive. We report a nove...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477487/ https://www.ncbi.nlm.nih.gov/pubmed/34579745 http://dx.doi.org/10.1186/s13058-021-01467-y |
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author | Zare, Alaa Postovit, Lynne-Marie Githaka, John Maringa |
author_facet | Zare, Alaa Postovit, Lynne-Marie Githaka, John Maringa |
author_sort | Zare, Alaa |
collection | PubMed |
description | Inflammatory breast cancer (IBC) is a rare, aggressive cancer found in all the molecular breast cancer subtypes. Despite extensive previous efforts to screen for transcriptional differences between IBC and non-IBC patients, a robust IBC-specific molecular signature has been elusive. We report a novel IBC-specific gene signature (59 genes; G59) that achieves 100% accuracy in discovery and validation samples (45/45 correct classification) and remarkably only misclassified one sample (60/61 correct classification) in an independent dataset. G59 is independent of ER/HER2 status, molecular subtypes and is specific to untreated IBC samples, with most of the genes being enriched for plasma membrane cellular component proteins, interleukin (IL), and chemokine signaling pathways. Our finding suggests the existence of an IBC-specific molecular signature, paving the way for the identification and validation of targetable genomic drivers of IBC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-021-01467-y. |
format | Online Article Text |
id | pubmed-8477487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84774872021-09-28 Robust inflammatory breast cancer gene signature using nonparametric random forest analysis Zare, Alaa Postovit, Lynne-Marie Githaka, John Maringa Breast Cancer Res Short Report Inflammatory breast cancer (IBC) is a rare, aggressive cancer found in all the molecular breast cancer subtypes. Despite extensive previous efforts to screen for transcriptional differences between IBC and non-IBC patients, a robust IBC-specific molecular signature has been elusive. We report a novel IBC-specific gene signature (59 genes; G59) that achieves 100% accuracy in discovery and validation samples (45/45 correct classification) and remarkably only misclassified one sample (60/61 correct classification) in an independent dataset. G59 is independent of ER/HER2 status, molecular subtypes and is specific to untreated IBC samples, with most of the genes being enriched for plasma membrane cellular component proteins, interleukin (IL), and chemokine signaling pathways. Our finding suggests the existence of an IBC-specific molecular signature, paving the way for the identification and validation of targetable genomic drivers of IBC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-021-01467-y. BioMed Central 2021-09-27 2021 /pmc/articles/PMC8477487/ /pubmed/34579745 http://dx.doi.org/10.1186/s13058-021-01467-y Text en © The Author(s) 2021 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 | Short Report Zare, Alaa Postovit, Lynne-Marie Githaka, John Maringa Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title | Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title_full | Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title_fullStr | Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title_full_unstemmed | Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title_short | Robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
title_sort | robust inflammatory breast cancer gene signature using nonparametric random forest analysis |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8477487/ https://www.ncbi.nlm.nih.gov/pubmed/34579745 http://dx.doi.org/10.1186/s13058-021-01467-y |
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