A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing
Abstract Molecular features are incorporated into the integrated diagnostic system for adult diffuse gliomas. Of these, copy number variation (CNV) markers, including both arm‐level (1p/19q codeletion, +7/−10 signature) and gene‐level (EGFR gene amplification, CDKN2A/B homozygous deletion) changes,...
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Wiley
2024-11-01
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| Series: | The Journal of Pathology: Clinical Research |
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| Online Access: | https://doi.org/10.1002/2056-4538.70005 |
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| author | Shuai Wu Chenyu Ma Jiawei Cai Chenkang Yang Xiaojia Liu Chen Luo Jingyi Yang Zhang Xiong Dandan Cao Hong Chen |
| author_facet | Shuai Wu Chenyu Ma Jiawei Cai Chenkang Yang Xiaojia Liu Chen Luo Jingyi Yang Zhang Xiong Dandan Cao Hong Chen |
| author_sort | Shuai Wu |
| collection | DOAJ |
| description | Abstract Molecular features are incorporated into the integrated diagnostic system for adult diffuse gliomas. Of these, copy number variation (CNV) markers, including both arm‐level (1p/19q codeletion, +7/−10 signature) and gene‐level (EGFR gene amplification, CDKN2A/B homozygous deletion) changes, have revolutionized the diagnostic paradigm by updating the subtyping and grading schemes. Shallow whole genome sequencing (sWGS) has been widely used for CNV detection due to its cost‐effectiveness and versatility. However, the parallel detection of glioma‐associated CNV markers using sWGS has not been optimized in a clinical setting. Herein, we established a model‐based approach to classify the CNV status of glioma‐associated diagnostic markers with a single test. To enhance its clinical utility, we carried out hypothesis testing model‐based analysis through the estimation of copy ratio fluctuation level, which was implemented individually and independently and, thus, avoided the necessity for normal controls. Besides, the customization of required minimal tumor fraction (TF) was evaluated and recommended for each glioma‐associated marker to ensure robust classification. As a result, with 1× sequencing depth and 0.05 TF, arm‐level CNVs could be reliably detected with at least 99.5% sensitivity and specificity. For EGFR gene amplification and CDKN2A/B homozygous deletion, the corresponding TF limits were 0.15 and 0.45 to ensure the evaluation metrics were both higher than 97%. Furthermore, we applied the algorithm to an independent glioma cohort and observed the expected sample distribution and prognostic stratification patterns. In conclusion, we provide a clinically applicable algorithm to classify the CNV status of glioma‐associated markers in parallel. |
| format | Article |
| id | doaj-art-ec46b391fbca40ac8256e93f953ac4fd |
| institution | OA Journals |
| issn | 2056-4538 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Pathology: Clinical Research |
| spelling | doaj-art-ec46b391fbca40ac8256e93f953ac4fd2025-08-20T01:52:45ZengWileyThe Journal of Pathology: Clinical Research2056-45382024-11-01106n/an/a10.1002/2056-4538.70005A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencingShuai Wu0Chenyu Ma1Jiawei Cai2Chenkang Yang3Xiaojia Liu4Chen Luo5Jingyi Yang6Zhang Xiong7Dandan Cao8Hong Chen9Department of Neurosurgery, Huashan Hospital, Shanghai Medical College Fudan University Shanghai PR ChinaGenetron Health (Beijing) Co. Ltd Beijing PR ChinaDepartment of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital Fujian Medical University Fuzhou PR ChinaGenetron Health (Beijing) Co. Ltd Beijing PR ChinaDepartment of Pathology, Huashan Hospital, Shanghai Medical College Fudan University Shanghai PR ChinaDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College Fudan University Shanghai PR ChinaGenetron Health (Beijing) Co. Ltd Beijing PR ChinaDepartment of Neurosurgery, Huashan Hospital, Shanghai Medical College Fudan University Shanghai PR ChinaGenetron Health (Beijing) Co. Ltd Beijing PR ChinaDepartment of Pathology, Huashan Hospital, Shanghai Medical College Fudan University Shanghai PR ChinaAbstract Molecular features are incorporated into the integrated diagnostic system for adult diffuse gliomas. Of these, copy number variation (CNV) markers, including both arm‐level (1p/19q codeletion, +7/−10 signature) and gene‐level (EGFR gene amplification, CDKN2A/B homozygous deletion) changes, have revolutionized the diagnostic paradigm by updating the subtyping and grading schemes. Shallow whole genome sequencing (sWGS) has been widely used for CNV detection due to its cost‐effectiveness and versatility. However, the parallel detection of glioma‐associated CNV markers using sWGS has not been optimized in a clinical setting. Herein, we established a model‐based approach to classify the CNV status of glioma‐associated diagnostic markers with a single test. To enhance its clinical utility, we carried out hypothesis testing model‐based analysis through the estimation of copy ratio fluctuation level, which was implemented individually and independently and, thus, avoided the necessity for normal controls. Besides, the customization of required minimal tumor fraction (TF) was evaluated and recommended for each glioma‐associated marker to ensure robust classification. As a result, with 1× sequencing depth and 0.05 TF, arm‐level CNVs could be reliably detected with at least 99.5% sensitivity and specificity. For EGFR gene amplification and CDKN2A/B homozygous deletion, the corresponding TF limits were 0.15 and 0.45 to ensure the evaluation metrics were both higher than 97%. Furthermore, we applied the algorithm to an independent glioma cohort and observed the expected sample distribution and prognostic stratification patterns. In conclusion, we provide a clinically applicable algorithm to classify the CNV status of glioma‐associated markers in parallel.https://doi.org/10.1002/2056-4538.70005CNV detection algorithmshallow whole genome sequencing (sWGS)glioma diagnosesclinical practice |
| spellingShingle | Shuai Wu Chenyu Ma Jiawei Cai Chenkang Yang Xiaojia Liu Chen Luo Jingyi Yang Zhang Xiong Dandan Cao Hong Chen A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing The Journal of Pathology: Clinical Research CNV detection algorithm shallow whole genome sequencing (sWGS) glioma diagnoses clinical practice |
| title | A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing |
| title_full | A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing |
| title_fullStr | A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing |
| title_full_unstemmed | A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing |
| title_short | A clinically feasible algorithm for the parallel detection of glioma‐associated copy number variation markers based on shallow whole genome sequencing |
| title_sort | clinically feasible algorithm for the parallel detection of glioma associated copy number variation markers based on shallow whole genome sequencing |
| topic | CNV detection algorithm shallow whole genome sequencing (sWGS) glioma diagnoses clinical practice |
| url | https://doi.org/10.1002/2056-4538.70005 |
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