Kosuke Aoki1,2, Hideo Nakamura3, Hiromichi Suzuki1,2, Keitaro Matsuo4, Keisuke Kataoka2, Teppei Shimamura5, Kazuya Motomura1, Fumiharu Ohka1, Satoshi Shiina1, Takashi Yamamoto1, Yasunobu Nagata2, Tetsuichi Yoshizato1,2, Masahiro Mizoguchi6, Tatsuya Abe7, Yasutomo Momii8, Yoshihiro Muragaki9, Reiko Watanabe10, Ichiro Ito11, Masashi Sanada2, Hironori Yajima12, Naoya Morita12, Ichiro Takeuchi13,14,15, Satoru Miyano16, Toshihiko Wakabayashi1, Seishi Ogawa2, Atsushi Natsume1. 1. Department of Neurosurgery, Nagoya University School of Medicine, Nagoya, Japan. 2. Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto, Japan. 3. Department of Neurosurgery, School of Medicine, Kumamoto University, Kumamoto, Japan. 4. Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan. 5. Division of Systems Biology, Nagoya University School of Medicine, Nagoya, Japan. 6. Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. 7. Department of Neurosurgery, Faculty of Medicine, Saga University, Saga, Japan. 8. Department of Neurosurgery, School of Medicine, Oita University, Oita, Japan. 9. Department of Neurosurgery, Tokyo Women's Medical University, Tokyo, Japan. 10. Division of Pathology and Clinical Laboratories, National Cancer Center Hospital, Tokyo, Japan. 11. Division of Diagnostic Pathology, Shizuoka Cancer Center, Shizuoka, Japan. 12. Department of Scientific and Engineering Simulation, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan. 13. Department of Computer Science/Research Institute for Information Science, Nagoya Institute of Technology, Nagoya, Japan. 14. RIKEN Center for Advanced Intelligence Project, Tokyo, Japan. 15. Center for Materials Research by Information Integration, National Institute for Materials Science, Tsukuba, Japan. 16. Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Abstract
Background: Diffuse lower-grade gliomas (LGGs) are genetically classified into 3 distinct subtypes based on isocitrate dehydrogenase (IDH) mutation status and codeletion of chromosome 1p and 19q (1p/19q). However, the subtype-specific effects of additional genetic lesions on survival are largely unknown. Methods: Using Cox proportional hazards regression modeling, we investigated the subtype-specific effects of genetic alterations and clinicopathological factors on survival in each LGG subtype, in a Japanese cohort of LGG cases fully genotyped for driver mutations and copy number variations associated with LGGs (n = 308). The results were validated using a dataset from 414 LGG cases available from The Cancer Genome Atlas (TCGA). Results: In Oligodendroglioma, IDH-mutant and 1p/19q codeleted, NOTCH1 mutations (P = 0.0041) and incomplete resection (P = 0.0019) were significantly associated with shorter survival. In Astrocytoma, IDH-mutant, PIK3R1 mutations (P = 0.0014) and altered retinoblastoma pathway genes (RB1, CDKN2A, and CDK4) (P = 0.013) were independent predictors of poor survival. In IDH-wildtype LGGs, co-occurrence of 7p gain, 10q loss, mutation in the TERT promoter (P = 0.024), and grade III histology (P < 0.0001) independently predicted poor survival. IDH-wildtype LGGs without any of these factors were diagnosed at a younger age (P = 0.042), and were less likely to have genetic lesions characteristic of glioblastoma, in comparison with other IDH-wildtype LGGs, suggesting that they likely represented biologically different subtypes. These results were largely confirmed in the cohort of TCGA. Conclusions: Subtype-specific genetic lesions can be used to stratify patients within each LGG subtype. enabling better prognostication and management.
Background: Diffuse lower-grade gliomas (LGGs) are genetically classified into 3 distinct subtypes based on isocitrate dehydrogenase (IDH) mutation status and codeletion of chromosome 1p and 19q (1p/19q). However, the subtype-specific effects of additional genetic lesions on survival are largely unknown. Methods: Using Cox proportional hazards regression modeling, we investigated the subtype-specific effects of genetic alterations and clinicopathological factors on survival in each LGG subtype, in a Japanese cohort of LGG cases fully genotyped for driver mutations and copy number variations associated with LGGs (n = 308). The results were validated using a dataset from 414 LGG cases available from The Cancer Genome Atlas (TCGA). Results: In Oligodendroglioma, IDH-mutant and 1p/19q codeleted, NOTCH1 mutations (P = 0.0041) and incomplete resection (P = 0.0019) were significantly associated with shorter survival. In Astrocytoma, IDH-mutant, PIK3R1 mutations (P = 0.0014) and altered retinoblastoma pathway genes (RB1, CDKN2A, and CDK4) (P = 0.013) were independent predictors of poor survival. In IDH-wildtype LGGs, co-occurrence of 7p gain, 10q loss, mutation in the TERT promoter (P = 0.024), and grade III histology (P < 0.0001) independently predicted poor survival. IDH-wildtype LGGs without any of these factors were diagnosed at a younger age (P = 0.042), and were less likely to have genetic lesions characteristic of glioblastoma, in comparison with other IDH-wildtype LGGs, suggesting that they likely represented biologically different subtypes. These results were largely confirmed in the cohort of TCGA. Conclusions: Subtype-specific genetic lesions can be used to stratify patients within each LGG subtype. enabling better prognostication and management.
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