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Radiogenomics-based cancer prognosis in colorectal cancer
Radiogenomics aims at investigating the relationship between imaging radiomic features and gene expression alterations. This study addressed the potential prognostic complementary value of contrast enhanced computed tomography (CE-CT) radiomic features and gene expression data in primary colorectal...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611779/ https://www.ncbi.nlm.nih.gov/pubmed/31278324 http://dx.doi.org/10.1038/s41598-019-46286-6 |
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author | Badic, Bogdan Hatt, Mathieu Durand, Stephanie Jossic-Corcos, Catherine Le Simon, Brigitte Visvikis, Dimitris Corcos, Laurent |
author_facet | Badic, Bogdan Hatt, Mathieu Durand, Stephanie Jossic-Corcos, Catherine Le Simon, Brigitte Visvikis, Dimitris Corcos, Laurent |
author_sort | Badic, Bogdan |
collection | PubMed |
description | Radiogenomics aims at investigating the relationship between imaging radiomic features and gene expression alterations. This study addressed the potential prognostic complementary value of contrast enhanced computed tomography (CE-CT) radiomic features and gene expression data in primary colorectal cancers (CRC). Sixty-four patients underwent CT scans and radiomic features were extracted from the delineated tumor volume. Gene expression analysis of a small set of genes, previously identified as relevant for CRC, was conducted on surgical samples from the same tumors. The relationships between radiomic and gene expression data was assessed using the Kruskal–Wallis test. Multiple testing was not performed, as this was a pilot study. Cox regression was used to identify variables related to overall survival (OS) and progression free survival (PFS). ABCC2 gene expression was correlated with N (p = 0.016) and M stages (p = 0.022). Expression changes of ABCC2, CD166, CDKNV1 and INHBB genes exhibited significant correlations with some radiomic features. OS was associated with Ratio 3D Surface/volume (p = 0.022) and ALDH1A1 expression (p = 0.042), whereas clinical stage (p = 0.004), ABCC2 expression (p = 0.035), and Entropy(GLCM_E) (p = 0.0031), were prognostic factors for PFS. Combining CE-CT radiomics with gene expression analysis and histopathological examination of primary CRC could provide higher prognostic stratification power, leading to improved patient management. |
format | Online Article Text |
id | pubmed-6611779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66117792019-07-15 Radiogenomics-based cancer prognosis in colorectal cancer Badic, Bogdan Hatt, Mathieu Durand, Stephanie Jossic-Corcos, Catherine Le Simon, Brigitte Visvikis, Dimitris Corcos, Laurent Sci Rep Article Radiogenomics aims at investigating the relationship between imaging radiomic features and gene expression alterations. This study addressed the potential prognostic complementary value of contrast enhanced computed tomography (CE-CT) radiomic features and gene expression data in primary colorectal cancers (CRC). Sixty-four patients underwent CT scans and radiomic features were extracted from the delineated tumor volume. Gene expression analysis of a small set of genes, previously identified as relevant for CRC, was conducted on surgical samples from the same tumors. The relationships between radiomic and gene expression data was assessed using the Kruskal–Wallis test. Multiple testing was not performed, as this was a pilot study. Cox regression was used to identify variables related to overall survival (OS) and progression free survival (PFS). ABCC2 gene expression was correlated with N (p = 0.016) and M stages (p = 0.022). Expression changes of ABCC2, CD166, CDKNV1 and INHBB genes exhibited significant correlations with some radiomic features. OS was associated with Ratio 3D Surface/volume (p = 0.022) and ALDH1A1 expression (p = 0.042), whereas clinical stage (p = 0.004), ABCC2 expression (p = 0.035), and Entropy(GLCM_E) (p = 0.0031), were prognostic factors for PFS. Combining CE-CT radiomics with gene expression analysis and histopathological examination of primary CRC could provide higher prognostic stratification power, leading to improved patient management. Nature Publishing Group UK 2019-07-05 /pmc/articles/PMC6611779/ /pubmed/31278324 http://dx.doi.org/10.1038/s41598-019-46286-6 Text en © The Author(s) 2019 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 Badic, Bogdan Hatt, Mathieu Durand, Stephanie Jossic-Corcos, Catherine Le Simon, Brigitte Visvikis, Dimitris Corcos, Laurent Radiogenomics-based cancer prognosis in colorectal cancer |
title | Radiogenomics-based cancer prognosis in colorectal cancer |
title_full | Radiogenomics-based cancer prognosis in colorectal cancer |
title_fullStr | Radiogenomics-based cancer prognosis in colorectal cancer |
title_full_unstemmed | Radiogenomics-based cancer prognosis in colorectal cancer |
title_short | Radiogenomics-based cancer prognosis in colorectal cancer |
title_sort | radiogenomics-based cancer prognosis in colorectal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611779/ https://www.ncbi.nlm.nih.gov/pubmed/31278324 http://dx.doi.org/10.1038/s41598-019-46286-6 |
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