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Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using...

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Autores principales: Su, Guan-Hua, Xiao, Yi, You, Chao, Zheng, Ren-Cheng, Zhao, Shen, Sun, Shi-Yun, Zhou, Jia-Yin, Lin, Lu-Yi, Wang, He, Shao, Zhi-Ming, Gu, Ya-Jia, Jiang, Yi-Zhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558123/
https://www.ncbi.nlm.nih.gov/pubmed/37801493
http://dx.doi.org/10.1126/sciadv.adf0837
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author Su, Guan-Hua
Xiao, Yi
You, Chao
Zheng, Ren-Cheng
Zhao, Shen
Sun, Shi-Yun
Zhou, Jia-Yin
Lin, Lu-Yi
Wang, He
Shao, Zhi-Ming
Gu, Ya-Jia
Jiang, Yi-Zhou
author_facet Su, Guan-Hua
Xiao, Yi
You, Chao
Zheng, Ren-Cheng
Zhao, Shen
Sun, Shi-Yun
Zhou, Jia-Yin
Lin, Lu-Yi
Wang, He
Shao, Zhi-Ming
Gu, Ya-Jia
Jiang, Yi-Zhou
author_sort Su, Guan-Hua
collection PubMed
description Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast–enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.
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spelling pubmed-105581232023-10-07 Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets Su, Guan-Hua Xiao, Yi You, Chao Zheng, Ren-Cheng Zhao, Shen Sun, Shi-Yun Zhou, Jia-Yin Lin, Lu-Yi Wang, He Shao, Zhi-Ming Gu, Ya-Jia Jiang, Yi-Zhou Sci Adv Biomedicine and Life Sciences Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast–enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH. American Association for the Advancement of Science 2023-10-06 /pmc/articles/PMC10558123/ /pubmed/37801493 http://dx.doi.org/10.1126/sciadv.adf0837 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Biomedicine and Life Sciences
Su, Guan-Hua
Xiao, Yi
You, Chao
Zheng, Ren-Cheng
Zhao, Shen
Sun, Shi-Yun
Zhou, Jia-Yin
Lin, Lu-Yi
Wang, He
Shao, Zhi-Ming
Gu, Ya-Jia
Jiang, Yi-Zhou
Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title_full Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title_fullStr Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title_full_unstemmed Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title_short Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
title_sort radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets
topic Biomedicine and Life Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558123/
https://www.ncbi.nlm.nih.gov/pubmed/37801493
http://dx.doi.org/10.1126/sciadv.adf0837
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