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Tasci E, Shah Y, Jagasia S, Zhuge Y, Shephard J, Johnson MO, Elemento O, Joyce T, Chappidi S, Cooley Zgela T, Sproull M, Mackey M, Camphausen K, Krauze AV. MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma. Int J Mol Sci 2024; 25:4082. [PMID: 38612892 PMCID: PMC11012706 DOI: 10.3390/ijms25074082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 04/02/2024] [Accepted: 04/03/2024] [Indexed: 04/14/2024] Open
Abstract
Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.
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Affiliation(s)
- Erdal Tasci
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Yajas Shah
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Sarisha Jagasia
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Ying Zhuge
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Jason Shephard
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Margaret O. Johnson
- Department of Neurosurgery, Duke University, Durham, NC 27710, USA
- National Tele-Oncology, Veterans Health Administration, Durham, NC 27710, USA
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Thomas Joyce
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Shreya Chappidi
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Theresa Cooley Zgela
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Mary Sproull
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Megan Mackey
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Kevin Camphausen
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
| | - Andra Valentina Krauze
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA
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Han X, Pang J, Xu D, Wang R, Xie F, Yang Y, Sun J, Li Y, Li R, Yin X, Xu Y, Fan J, Dong Y, Wu X, Yang X, Yu D, Wang D, Gao Y, Xiang M, Xu F, Sun J, Chen Y, Ning X. Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features. Physiol Meas 2023; 44:125002. [PMID: 37995382 DOI: 10.1088/1361-6579/ad0f70] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 11/23/2023] [Indexed: 11/25/2023]
Abstract
Objective.This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system.Approach.We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations.Main results.For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model.Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.
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Affiliation(s)
- Xiaole Han
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
| | - Jiaojiao Pang
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Dong Xu
- National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou, People's Republic of China
| | - Ruizhe Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
| | - Fei Xie
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Yanfei Yang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
| | - Jiguang Sun
- Hangzhou Nuochi Life Science Co., Ltd, People's Republic of China
| | - Yu Li
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Ruochuan Li
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Xiaofei Yin
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Yansong Xu
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Jiaxin Fan
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Yiming Dong
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Xiaohui Wu
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Xiaoyun Yang
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
- Department of Gastroenterology, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Digestive Disease, People's Republic of China
| | - Dexin Yu
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
- Department of Radiology, Qilu Hospital of Shandong University, People's Republic of China
| | - Dawei Wang
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
- Department of Radiology, Qilu Hospital of Shandong University, People's Republic of China
| | - Yang Gao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
- National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou, People's Republic of China
- Institute of Large-Scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, People's Republic of China
| | - Min Xiang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
- National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou, People's Republic of China
- Institute of Large-Scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, People's Republic of China
- Hefei National Laboratory, People's Republic of China
| | - Feng Xu
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Jinji Sun
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
- National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou, People's Republic of China
- Institute of Large-Scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, People's Republic of China
- Hefei National Laboratory, People's Republic of China
| | - Yuguo Chen
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, People's Republic of China
- Department of Emergency Medicine, Qilu Hospital of Shandong University, Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, People's Republic of China
- National Innovation Platform for Industry-Education Intearation in Medicine-Engineering Interdisciplinary, Shandong University, People's Republic of China
| | - Xiaolin Ning
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, People's Republic of China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, People's Republic of China
- National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou, People's Republic of China
- Institute of Large-Scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, People's Republic of China
- Hefei National Laboratory, People's Republic of China
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