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Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas

Isocitrate dehydrogenase-mutant low-grade gliomas (IDHmut-LGG) grow slowly but frequently undergo malignant transformation, which eventually leads to premature death. Chemotherapy and radiotherapy treatments prolong survival, but can also induce genetic (or epigenetic) alterations involved in transf...

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Autores principales: Aoki, Kosuke, Suzuki, Hiromichi, Yamamoto, Takashi, Yamamoto, Kimiyo N., Maeda, Sachi, Okuno, Yusuke, Ranjit, Melissa, Motomura, Kazuya, Ohka, Fumiharu, Tanahashi, Kuniaki, Hirano, Masaki, Nishikawa, Tomohide, Shimizu, Hiroyuki, Kitano, Yotaro, Yamaguchi, Junya, Yamazaki, Shintaro, Nakamura, Hideo, Takahashi, Masamichi, Narita, Yoshitaka, Nakada, Mitsutoshi, Deguchi, Shoichi, Mizoguchi, Masahiro, Momii, Yasutomo, Muragaki, Yoshihiro, Abe, Tatsuya, Akimoto, Jiro, Wakabayashi, Toshihiko, Saito, Ryuta, Ogawa, Seishi, Haeno, Hiroshi, Natsume, Atsushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635454/
https://www.ncbi.nlm.nih.gov/pubmed/34333454
http://dx.doi.org/10.1158/0008-5472.CAN-21-0985
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author Aoki, Kosuke
Suzuki, Hiromichi
Yamamoto, Takashi
Yamamoto, Kimiyo N.
Maeda, Sachi
Okuno, Yusuke
Ranjit, Melissa
Motomura, Kazuya
Ohka, Fumiharu
Tanahashi, Kuniaki
Hirano, Masaki
Nishikawa, Tomohide
Shimizu, Hiroyuki
Kitano, Yotaro
Yamaguchi, Junya
Yamazaki, Shintaro
Nakamura, Hideo
Takahashi, Masamichi
Narita, Yoshitaka
Nakada, Mitsutoshi
Deguchi, Shoichi
Mizoguchi, Masahiro
Momii, Yasutomo
Muragaki, Yoshihiro
Abe, Tatsuya
Akimoto, Jiro
Wakabayashi, Toshihiko
Saito, Ryuta
Ogawa, Seishi
Haeno, Hiroshi
Natsume, Atsushi
author_facet Aoki, Kosuke
Suzuki, Hiromichi
Yamamoto, Takashi
Yamamoto, Kimiyo N.
Maeda, Sachi
Okuno, Yusuke
Ranjit, Melissa
Motomura, Kazuya
Ohka, Fumiharu
Tanahashi, Kuniaki
Hirano, Masaki
Nishikawa, Tomohide
Shimizu, Hiroyuki
Kitano, Yotaro
Yamaguchi, Junya
Yamazaki, Shintaro
Nakamura, Hideo
Takahashi, Masamichi
Narita, Yoshitaka
Nakada, Mitsutoshi
Deguchi, Shoichi
Mizoguchi, Masahiro
Momii, Yasutomo
Muragaki, Yoshihiro
Abe, Tatsuya
Akimoto, Jiro
Wakabayashi, Toshihiko
Saito, Ryuta
Ogawa, Seishi
Haeno, Hiroshi
Natsume, Atsushi
author_sort Aoki, Kosuke
collection PubMed
description Isocitrate dehydrogenase-mutant low-grade gliomas (IDHmut-LGG) grow slowly but frequently undergo malignant transformation, which eventually leads to premature death. Chemotherapy and radiotherapy treatments prolong survival, but can also induce genetic (or epigenetic) alterations involved in transformation. Here, we developed a mathematical model of tumor progression based on serial tumor volume data and treatment history of 276 IDHmut-LGGs classified by chromosome 1p/19q codeletion (IDH(mut)/1p19q(codel) and IDH(mut)/1p19q(noncodel)) and performed genome-wide mutational analyses, including targeted sequencing and longitudinal whole-exome sequencing data. These analyses showed that tumor mutational burden correlated positively with malignant transformation rate, and chemotherapy and radiotherapy significantly suppressed tumor growth but increased malignant transformation rate per cell by 1.8 to 2.8 times compared with before treatment. This model revealed that prompt adjuvant chemoradiotherapy prolonged malignant transformation-free survival in small IDHmut-LGGs (≤ 50 cm(3)). Furthermore, optimal treatment differed according to genetic alterations for large IDHmut-LGGs (> 50 cm(3)); adjuvant therapies delayed malignant transformation in IDH(mut)/1p19q(noncodel) but often accelerated it in IDH(mut)/1p19q(codel). Notably, PI3K mutation was not associated with malignant transformation but increased net postoperative proliferation rate and decreased malignant transformation-free survival, prompting the need for adjuvant therapy in IDH(mut)/1p19q(codel). Overall, this model uncovered therapeutic strategies that could prevent malignant transformation and, consequently, improve overall survival in patients with IDHmut-LGGs. SIGNIFICANCE: A mathematical model successfully estimates malignant transformation-free survival and reveals a link between genetic alterations and progression, identifying precision medicine approaches for optimal treatment of IDH-mutant low-grade gliomas.
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spelling pubmed-96354542023-01-05 Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas Aoki, Kosuke Suzuki, Hiromichi Yamamoto, Takashi Yamamoto, Kimiyo N. Maeda, Sachi Okuno, Yusuke Ranjit, Melissa Motomura, Kazuya Ohka, Fumiharu Tanahashi, Kuniaki Hirano, Masaki Nishikawa, Tomohide Shimizu, Hiroyuki Kitano, Yotaro Yamaguchi, Junya Yamazaki, Shintaro Nakamura, Hideo Takahashi, Masamichi Narita, Yoshitaka Nakada, Mitsutoshi Deguchi, Shoichi Mizoguchi, Masahiro Momii, Yasutomo Muragaki, Yoshihiro Abe, Tatsuya Akimoto, Jiro Wakabayashi, Toshihiko Saito, Ryuta Ogawa, Seishi Haeno, Hiroshi Natsume, Atsushi Cancer Res Convergence and Technologies Isocitrate dehydrogenase-mutant low-grade gliomas (IDHmut-LGG) grow slowly but frequently undergo malignant transformation, which eventually leads to premature death. Chemotherapy and radiotherapy treatments prolong survival, but can also induce genetic (or epigenetic) alterations involved in transformation. Here, we developed a mathematical model of tumor progression based on serial tumor volume data and treatment history of 276 IDHmut-LGGs classified by chromosome 1p/19q codeletion (IDH(mut)/1p19q(codel) and IDH(mut)/1p19q(noncodel)) and performed genome-wide mutational analyses, including targeted sequencing and longitudinal whole-exome sequencing data. These analyses showed that tumor mutational burden correlated positively with malignant transformation rate, and chemotherapy and radiotherapy significantly suppressed tumor growth but increased malignant transformation rate per cell by 1.8 to 2.8 times compared with before treatment. This model revealed that prompt adjuvant chemoradiotherapy prolonged malignant transformation-free survival in small IDHmut-LGGs (≤ 50 cm(3)). Furthermore, optimal treatment differed according to genetic alterations for large IDHmut-LGGs (> 50 cm(3)); adjuvant therapies delayed malignant transformation in IDH(mut)/1p19q(noncodel) but often accelerated it in IDH(mut)/1p19q(codel). Notably, PI3K mutation was not associated with malignant transformation but increased net postoperative proliferation rate and decreased malignant transformation-free survival, prompting the need for adjuvant therapy in IDH(mut)/1p19q(codel). Overall, this model uncovered therapeutic strategies that could prevent malignant transformation and, consequently, improve overall survival in patients with IDHmut-LGGs. SIGNIFICANCE: A mathematical model successfully estimates malignant transformation-free survival and reveals a link between genetic alterations and progression, identifying precision medicine approaches for optimal treatment of IDH-mutant low-grade gliomas. American Association for Cancer Research 2021-09-15 2021-07-31 /pmc/articles/PMC9635454/ /pubmed/34333454 http://dx.doi.org/10.1158/0008-5472.CAN-21-0985 Text en ©2021 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
spellingShingle Convergence and Technologies
Aoki, Kosuke
Suzuki, Hiromichi
Yamamoto, Takashi
Yamamoto, Kimiyo N.
Maeda, Sachi
Okuno, Yusuke
Ranjit, Melissa
Motomura, Kazuya
Ohka, Fumiharu
Tanahashi, Kuniaki
Hirano, Masaki
Nishikawa, Tomohide
Shimizu, Hiroyuki
Kitano, Yotaro
Yamaguchi, Junya
Yamazaki, Shintaro
Nakamura, Hideo
Takahashi, Masamichi
Narita, Yoshitaka
Nakada, Mitsutoshi
Deguchi, Shoichi
Mizoguchi, Masahiro
Momii, Yasutomo
Muragaki, Yoshihiro
Abe, Tatsuya
Akimoto, Jiro
Wakabayashi, Toshihiko
Saito, Ryuta
Ogawa, Seishi
Haeno, Hiroshi
Natsume, Atsushi
Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title_full Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title_fullStr Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title_full_unstemmed Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title_short Mathematical Modeling and Mutational Analysis Reveal Optimal Therapy to Prevent Malignant Transformation in Grade II IDH-Mutant Gliomas
title_sort mathematical modeling and mutational analysis reveal optimal therapy to prevent malignant transformation in grade ii idh-mutant gliomas
topic Convergence and Technologies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635454/
https://www.ncbi.nlm.nih.gov/pubmed/34333454
http://dx.doi.org/10.1158/0008-5472.CAN-21-0985
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