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Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics
Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal cancer (CRC). In addition, the status of TMB in primar...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748253/ https://www.ncbi.nlm.nih.gov/pubmed/34689378 http://dx.doi.org/10.1111/cas.15173 |
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author | Hoshino, Isamu Yokota, Hajime Iwatate, Yosuke Mori, Yasukuni Kuwayama, Naoki Ishige, Fumitaka Itami, Makiko Uno, Takashi Nakamura, Yuki Tatsumi, Yasutoshi Shimozato, Osamu Nagase, Hiroki |
author_facet | Hoshino, Isamu Yokota, Hajime Iwatate, Yosuke Mori, Yasukuni Kuwayama, Naoki Ishige, Fumitaka Itami, Makiko Uno, Takashi Nakamura, Yuki Tatsumi, Yasutoshi Shimozato, Osamu Nagase, Hiroki |
author_sort | Hoshino, Isamu |
collection | PubMed |
description | Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal cancer (CRC). In addition, the status of TMB in primary and liver metastatic lesions was inferred by radiogenomics on the basis of computed tomography (CT) images. The study population included 24 CRC patients with liver metastases. DNA was extracted from primary and liver metastatic lesions obtained from the patients and TMB values were evaluated by next‐generation sequencing. The TMB value was considered high when it equaled to or exceeded 10/100 Mb. Radiogenomic analysis of TMB was performed by machine learning using CT images and the construction of prediction models. In 7 out of 24 patients (29.2%), the TMB status differed between the primary and liver metastatic lesions. Radiogenomic analysis was performed to predict whether TMB status was high or low. The maximum values for the area under the receiver operating characteristic curve were 0.732 and 0.812 for primary CRC and CRC with liver metastasis, respectively. The sensitivity, specificity, and accuracy of the constructed models for TMB status discordance were 0.857, 0.600, and 0.682, respectively. Our results suggested that accurate inference of the TMB status is possible using radiogenomics. Therefore, radiogenomics could facilitate the diagnosis, treatment, and prognosis of patients with CRC in the clinical setting. |
format | Online Article Text |
id | pubmed-8748253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87482532022-01-14 Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics Hoshino, Isamu Yokota, Hajime Iwatate, Yosuke Mori, Yasukuni Kuwayama, Naoki Ishige, Fumitaka Itami, Makiko Uno, Takashi Nakamura, Yuki Tatsumi, Yasutoshi Shimozato, Osamu Nagase, Hiroki Cancer Sci Original Articles Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal cancer (CRC). In addition, the status of TMB in primary and liver metastatic lesions was inferred by radiogenomics on the basis of computed tomography (CT) images. The study population included 24 CRC patients with liver metastases. DNA was extracted from primary and liver metastatic lesions obtained from the patients and TMB values were evaluated by next‐generation sequencing. The TMB value was considered high when it equaled to or exceeded 10/100 Mb. Radiogenomic analysis of TMB was performed by machine learning using CT images and the construction of prediction models. In 7 out of 24 patients (29.2%), the TMB status differed between the primary and liver metastatic lesions. Radiogenomic analysis was performed to predict whether TMB status was high or low. The maximum values for the area under the receiver operating characteristic curve were 0.732 and 0.812 for primary CRC and CRC with liver metastasis, respectively. The sensitivity, specificity, and accuracy of the constructed models for TMB status discordance were 0.857, 0.600, and 0.682, respectively. Our results suggested that accurate inference of the TMB status is possible using radiogenomics. Therefore, radiogenomics could facilitate the diagnosis, treatment, and prognosis of patients with CRC in the clinical setting. John Wiley and Sons Inc. 2021-11-11 2022-01 /pmc/articles/PMC8748253/ /pubmed/34689378 http://dx.doi.org/10.1111/cas.15173 Text en © 2021 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Hoshino, Isamu Yokota, Hajime Iwatate, Yosuke Mori, Yasukuni Kuwayama, Naoki Ishige, Fumitaka Itami, Makiko Uno, Takashi Nakamura, Yuki Tatsumi, Yasutoshi Shimozato, Osamu Nagase, Hiroki Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title | Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title_full | Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title_fullStr | Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title_full_unstemmed | Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title_short | Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
title_sort | prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748253/ https://www.ncbi.nlm.nih.gov/pubmed/34689378 http://dx.doi.org/10.1111/cas.15173 |
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