Nanopore-based random genomic sampling for intraoperative molecular diagnosis
Abstract Background Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosi...
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BMC
2025-01-01
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| Series: | Genome Medicine |
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| Online Access: | https://doi.org/10.1186/s13073-025-01427-7 |
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| author | Francesco E. Emiliani Abdol Aziz Ould Ismail Edward G. Hughes Gregory J. Tsongalis George J. Zanazzi Chun-Chieh Lin |
| author_facet | Francesco E. Emiliani Abdol Aziz Ould Ismail Edward G. Hughes Gregory J. Tsongalis George J. Zanazzi Chun-Chieh Lin |
| author_sort | Francesco E. Emiliani |
| collection | DOAJ |
| description | Abstract Background Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging. Despite recent advances in intraoperative methylation classifications of brain tumors, accuracy may be compromised by low tumor purity. Copy number variations (CNVs), which are almost ubiquitous in cancer, offer highly sensitive molecular biomarkers for diagnosis. These quantitative genomic alterations provide insight into dysregulated oncogenic pathways and can reveal potential targets for molecular therapies. Methods We develop iSCORED, a one-step random genomic DNA reconstruction method that enables efficient, unbiased quantification of genome-wide CNVs. By concatenating multiple genomic fragments into long reads, the method leverages low-pass sequencing to generate approximately 1–2 million genomic fragments within 1 h. This approach allows for ultrafast high-resolution CNV analysis at a genomic resolution of 50 kb. In addition, concurrent methylation profiling enables brain tumor methylation classification and identifies promoter methylation in amplified oncogenes, providing an integrated diagnostic approach. Results In our retrospective cohort of 26 malignant brain tumors, iSCORED demonstrated 100% concordance in CNV detection, including chromosomal alterations and oncogene amplifications, when compared to clinically validated assays such as Next-Generation Sequencing and Chromosomal Microarray. Furthermore, we validated iSCORED’s real-time applicability in 15 diagnostically challenging primary brain tumors, achieving 100% concordance in detecting aberrant CNV detection, including diagnostic chromosomal gains/losses and oncogene amplifications (10/10). Of these, 14 out of 15 brain tumor methylation classifications aligned with final pathological diagnoses. This streamlined workflow—from tissue arrival to automatic generation of CNV and methylation reports—can be completed within 105 min. Conclusions The iSCORED pipeline represents the first method capable of high-resolution CNV detection within the intraoperative timeframe. By combining CNV detection and methylation classification, iSCORED provides a rapid and comprehensive molecular diagnostic tool that can inform rapid clinical decision. The integrated approach not only enhances the accuracy of tumor diagnosis but also optimizes surgical planning and identifies potential molecular therapies, all within the critical intraoperative timeframe. |
| format | Article |
| id | doaj-art-4562731106114e2f866cb57b88790309 |
| institution | Kabale University |
| issn | 1756-994X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj-art-4562731106114e2f866cb57b887903092025-01-26T12:46:04ZengBMCGenome Medicine1756-994X2025-01-0117111810.1186/s13073-025-01427-7Nanopore-based random genomic sampling for intraoperative molecular diagnosisFrancesco E. Emiliani0Abdol Aziz Ould Ismail1Edward G. Hughes2Gregory J. Tsongalis3George J. Zanazzi4Chun-Chieh Lin5Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical CenterAbstract Background Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging. Despite recent advances in intraoperative methylation classifications of brain tumors, accuracy may be compromised by low tumor purity. Copy number variations (CNVs), which are almost ubiquitous in cancer, offer highly sensitive molecular biomarkers for diagnosis. These quantitative genomic alterations provide insight into dysregulated oncogenic pathways and can reveal potential targets for molecular therapies. Methods We develop iSCORED, a one-step random genomic DNA reconstruction method that enables efficient, unbiased quantification of genome-wide CNVs. By concatenating multiple genomic fragments into long reads, the method leverages low-pass sequencing to generate approximately 1–2 million genomic fragments within 1 h. This approach allows for ultrafast high-resolution CNV analysis at a genomic resolution of 50 kb. In addition, concurrent methylation profiling enables brain tumor methylation classification and identifies promoter methylation in amplified oncogenes, providing an integrated diagnostic approach. Results In our retrospective cohort of 26 malignant brain tumors, iSCORED demonstrated 100% concordance in CNV detection, including chromosomal alterations and oncogene amplifications, when compared to clinically validated assays such as Next-Generation Sequencing and Chromosomal Microarray. Furthermore, we validated iSCORED’s real-time applicability in 15 diagnostically challenging primary brain tumors, achieving 100% concordance in detecting aberrant CNV detection, including diagnostic chromosomal gains/losses and oncogene amplifications (10/10). Of these, 14 out of 15 brain tumor methylation classifications aligned with final pathological diagnoses. This streamlined workflow—from tissue arrival to automatic generation of CNV and methylation reports—can be completed within 105 min. Conclusions The iSCORED pipeline represents the first method capable of high-resolution CNV detection within the intraoperative timeframe. By combining CNV detection and methylation classification, iSCORED provides a rapid and comprehensive molecular diagnostic tool that can inform rapid clinical decision. The integrated approach not only enhances the accuracy of tumor diagnosis but also optimizes surgical planning and identifies potential molecular therapies, all within the critical intraoperative timeframe.https://doi.org/10.1186/s13073-025-01427-7Nanopore sequencingCopy number variationMethylation classificationIntraoperative diagnosis |
| spellingShingle | Francesco E. Emiliani Abdol Aziz Ould Ismail Edward G. Hughes Gregory J. Tsongalis George J. Zanazzi Chun-Chieh Lin Nanopore-based random genomic sampling for intraoperative molecular diagnosis Genome Medicine Nanopore sequencing Copy number variation Methylation classification Intraoperative diagnosis |
| title | Nanopore-based random genomic sampling for intraoperative molecular diagnosis |
| title_full | Nanopore-based random genomic sampling for intraoperative molecular diagnosis |
| title_fullStr | Nanopore-based random genomic sampling for intraoperative molecular diagnosis |
| title_full_unstemmed | Nanopore-based random genomic sampling for intraoperative molecular diagnosis |
| title_short | Nanopore-based random genomic sampling for intraoperative molecular diagnosis |
| title_sort | nanopore based random genomic sampling for intraoperative molecular diagnosis |
| topic | Nanopore sequencing Copy number variation Methylation classification Intraoperative diagnosis |
| url | https://doi.org/10.1186/s13073-025-01427-7 |
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