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Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer
Molecular analysis techniques such as gene expression analysis and proteomics have contributed greatly to our understanding of cancer heterogeneity. In prior studies, gene expression analysis was shown to stratify patient outcome on the basis of tumor-microenvironment associated genes. A specific ge...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096505/ https://www.ncbi.nlm.nih.gov/pubmed/32214177 http://dx.doi.org/10.1038/s41598-020-62403-2 |
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author | Tiwari, Saumya Triulzi, Tiziana Holton, Sarah Regondi, Viola Paolini, Biagio Tagliabue, Elda Bhargava, Rohit |
author_facet | Tiwari, Saumya Triulzi, Tiziana Holton, Sarah Regondi, Viola Paolini, Biagio Tagliabue, Elda Bhargava, Rohit |
author_sort | Tiwari, Saumya |
collection | PubMed |
description | Molecular analysis techniques such as gene expression analysis and proteomics have contributed greatly to our understanding of cancer heterogeneity. In prior studies, gene expression analysis was shown to stratify patient outcome on the basis of tumor-microenvironment associated genes. A specific gene expression profile, referred to as ECM3 (Extracellular Matrix Cluster 3), indicated poorer survival in patients with grade III tumors. In this work, we aimed to visualize the downstream effects of this gene expression profile onto the tissue, thus providing a spatial context to altered gene expression profiles. Using infrared spectroscopic imaging, we identified spectral patterns specific to the ECM3 gene expression profile, achieving a high spectral classification performance of 0.87 as measured by the area under the curve of the receiver operating characteristic curve. On a patient level, we correctly identified 20 out of 22 ECM3 group patients and 19 out of 20 non-ECM3 group patients by using this spectroscopic imaging-based classifier. By comparing pixels that were identified as ECM3 or non-ECM3 with H&E and IHC images, we were also able to observe an association between tissue morphology and the gene expression clusters, showing the ability of our method to capture broad outcome associated features from infrared images. |
format | Online Article Text |
id | pubmed-7096505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70965052020-03-30 Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer Tiwari, Saumya Triulzi, Tiziana Holton, Sarah Regondi, Viola Paolini, Biagio Tagliabue, Elda Bhargava, Rohit Sci Rep Article Molecular analysis techniques such as gene expression analysis and proteomics have contributed greatly to our understanding of cancer heterogeneity. In prior studies, gene expression analysis was shown to stratify patient outcome on the basis of tumor-microenvironment associated genes. A specific gene expression profile, referred to as ECM3 (Extracellular Matrix Cluster 3), indicated poorer survival in patients with grade III tumors. In this work, we aimed to visualize the downstream effects of this gene expression profile onto the tissue, thus providing a spatial context to altered gene expression profiles. Using infrared spectroscopic imaging, we identified spectral patterns specific to the ECM3 gene expression profile, achieving a high spectral classification performance of 0.87 as measured by the area under the curve of the receiver operating characteristic curve. On a patient level, we correctly identified 20 out of 22 ECM3 group patients and 19 out of 20 non-ECM3 group patients by using this spectroscopic imaging-based classifier. By comparing pixels that were identified as ECM3 or non-ECM3 with H&E and IHC images, we were also able to observe an association between tissue morphology and the gene expression clusters, showing the ability of our method to capture broad outcome associated features from infrared images. Nature Publishing Group UK 2020-03-25 /pmc/articles/PMC7096505/ /pubmed/32214177 http://dx.doi.org/10.1038/s41598-020-62403-2 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Tiwari, Saumya Triulzi, Tiziana Holton, Sarah Regondi, Viola Paolini, Biagio Tagliabue, Elda Bhargava, Rohit Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title | Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title_full | Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title_fullStr | Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title_full_unstemmed | Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title_short | Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer |
title_sort | infrared spectroscopic imaging visualizes a prognostic extracellular matrix-related signature in breast cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096505/ https://www.ncbi.nlm.nih.gov/pubmed/32214177 http://dx.doi.org/10.1038/s41598-020-62403-2 |
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