IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations
Summary: This article aims to develop and validate a pathological prognostic model for predicting prognosis in patients with isocitrate dehydrogenase (IDH)-mutant gliomas and reveal the biological underpinning of the prognostic pathological features. The pathomic model was constructed based on whole...
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| Language: | English |
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Elsevier
2025-01-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004224028323 |
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| author | Xiaotao Wang Zilong Wang Weiwei Wang Zaoqu Liu Zeyu Ma Yang Guo Dingyuan Su Qiuchang Sun Dongling Pei Wenchao Duan Yuning Qiu Minkai Wang Yongqiang Yang Wenyuan Li Haoran Liu Caoyuan Ma Miaomiao Yu Yinhui Yu Te Chen Jing Fu Sen Li Bin Yu Yuchen Ji Wencai Li Dongming Yan Xianzhi Liu Zhi-Cheng Li Zhenyu Zhang |
| author_facet | Xiaotao Wang Zilong Wang Weiwei Wang Zaoqu Liu Zeyu Ma Yang Guo Dingyuan Su Qiuchang Sun Dongling Pei Wenchao Duan Yuning Qiu Minkai Wang Yongqiang Yang Wenyuan Li Haoran Liu Caoyuan Ma Miaomiao Yu Yinhui Yu Te Chen Jing Fu Sen Li Bin Yu Yuchen Ji Wencai Li Dongming Yan Xianzhi Liu Zhi-Cheng Li Zhenyu Zhang |
| author_sort | Xiaotao Wang |
| collection | DOAJ |
| description | Summary: This article aims to develop and validate a pathological prognostic model for predicting prognosis in patients with isocitrate dehydrogenase (IDH)-mutant gliomas and reveal the biological underpinning of the prognostic pathological features. The pathomic model was constructed based on whole slide images (WSIs) from a training set (N = 486) and evaluated on internal validation set (N = 209), HPPH validation set (N = 54), and TCGA validation set (N = 352). Biological implications of PathScore and individual pathomic features were identified by pathogenomics set (N = 100). The WSI-based pathological signature was an independent prognostic factor. Incorporating the pathological features into a clinical model resulted in a pathological-clinical model that predicted survival better than either the pathological model or clinical model alone. Ten categories of pathways (metabolism, proliferation, immunity, DNA damage response, disease, migrate, protein modification, synapse, transcription and translation, and complex cellular functions) were significantly correlated with the WSI-based pathological features. |
| format | Article |
| id | doaj-art-0283cb62f7814bca8c9b480e27281d98 |
| institution | Kabale University |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-0283cb62f7814bca8c9b480e27281d982025-01-02T04:11:46ZengElsevieriScience2589-00422025-01-01281111605IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associationsXiaotao Wang0Zilong Wang1Weiwei Wang2Zaoqu Liu3Zeyu Ma4Yang Guo5Dingyuan Su6Qiuchang Sun7Dongling Pei8Wenchao Duan9Yuning Qiu10Minkai Wang11Yongqiang Yang12Wenyuan Li13Haoran Liu14Caoyuan Ma15Miaomiao Yu16Yinhui Yu17Te Chen18Jing Fu19Sen Li20Bin Yu21Yuchen Ji22Wencai Li23Dongming Yan24Xianzhi Liu25Zhi-Cheng Li26Zhenyu Zhang27Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, Henan Provincial People’s Hospital, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China; Corresponding authorInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; The Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China; Corresponding authorDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China; Corresponding authorSummary: This article aims to develop and validate a pathological prognostic model for predicting prognosis in patients with isocitrate dehydrogenase (IDH)-mutant gliomas and reveal the biological underpinning of the prognostic pathological features. The pathomic model was constructed based on whole slide images (WSIs) from a training set (N = 486) and evaluated on internal validation set (N = 209), HPPH validation set (N = 54), and TCGA validation set (N = 352). Biological implications of PathScore and individual pathomic features were identified by pathogenomics set (N = 100). The WSI-based pathological signature was an independent prognostic factor. Incorporating the pathological features into a clinical model resulted in a pathological-clinical model that predicted survival better than either the pathological model or clinical model alone. Ten categories of pathways (metabolism, proliferation, immunity, DNA damage response, disease, migrate, protein modification, synapse, transcription and translation, and complex cellular functions) were significantly correlated with the WSI-based pathological features.http://www.sciencedirect.com/science/article/pii/S2589004224028323Medical imagingBioinformaticsCancer |
| spellingShingle | Xiaotao Wang Zilong Wang Weiwei Wang Zaoqu Liu Zeyu Ma Yang Guo Dingyuan Su Qiuchang Sun Dongling Pei Wenchao Duan Yuning Qiu Minkai Wang Yongqiang Yang Wenyuan Li Haoran Liu Caoyuan Ma Miaomiao Yu Yinhui Yu Te Chen Jing Fu Sen Li Bin Yu Yuchen Ji Wencai Li Dongming Yan Xianzhi Liu Zhi-Cheng Li Zhenyu Zhang IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations iScience Medical imaging Bioinformatics Cancer |
| title | IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations |
| title_full | IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations |
| title_fullStr | IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations |
| title_full_unstemmed | IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations |
| title_short | IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations |
| title_sort | idh mutant glioma risk stratification via whole slide images identifying pathological feature associations |
| topic | Medical imaging Bioinformatics Cancer |
| url | http://www.sciencedirect.com/science/article/pii/S2589004224028323 |
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