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A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular ge...

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Autores principales: Bellini, Davide, Milan, Marika, Bordin, Antonella, Rizzi, Roberto, Rengo, Marco, Vicini, Simone, Onori, Alessandro, Carbone, Iacopo, De Falco, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138689/
https://www.ncbi.nlm.nih.gov/pubmed/37108377
http://dx.doi.org/10.3390/ijms24087214
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author Bellini, Davide
Milan, Marika
Bordin, Antonella
Rizzi, Roberto
Rengo, Marco
Vicini, Simone
Onori, Alessandro
Carbone, Iacopo
De Falco, Elena
author_facet Bellini, Davide
Milan, Marika
Bordin, Antonella
Rizzi, Roberto
Rengo, Marco
Vicini, Simone
Onori, Alessandro
Carbone, Iacopo
De Falco, Elena
author_sort Bellini, Davide
collection PubMed
description Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the “omics” clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed “radiomics”. Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of “radiology” and “genomics”, is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.
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spelling pubmed-101386892023-04-28 A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer Bellini, Davide Milan, Marika Bordin, Antonella Rizzi, Roberto Rengo, Marco Vicini, Simone Onori, Alessandro Carbone, Iacopo De Falco, Elena Int J Mol Sci Review Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the “omics” clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed “radiomics”. Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of “radiology” and “genomics”, is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach. MDPI 2023-04-13 /pmc/articles/PMC10138689/ /pubmed/37108377 http://dx.doi.org/10.3390/ijms24087214 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Bellini, Davide
Milan, Marika
Bordin, Antonella
Rizzi, Roberto
Rengo, Marco
Vicini, Simone
Onori, Alessandro
Carbone, Iacopo
De Falco, Elena
A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title_full A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title_fullStr A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title_full_unstemmed A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title_short A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer
title_sort focus on the synergy of radiomics and rna sequencing in breast cancer
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138689/
https://www.ncbi.nlm.nih.gov/pubmed/37108377
http://dx.doi.org/10.3390/ijms24087214
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