Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics
The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tumor classification. A limiting requirement for NGS...
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
February 2025
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| In: |
Nature cancer
Year: 2025, Jahrgang: 6, Heft: 2, Pages: 292-306 |
| ISSN: | 2662-1347 |
| DOI: | 10.1038/s43018-024-00904-z |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s43018-024-00904-z Verlag, kostenfrei, Volltext: http://www.nature.com/articles/s43018-024-00904-z 
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| Verfasserangaben: | Michael Ritter, Christina Blume, Yiheng Tang, Areeba Patel, Bhuvic Patel, Natalie Berghaus, Jasim Kada Benotmane, Jan Kueckelhaus, Yahaya Yabo, Junyi Zhang, Elena Grabis, Giulia Villa, David Niklas Zimmer, Amir Khriesh, Philipp Sievers, Zaira Seferbekova, Felix Hinz, Vidhya M. Ravi, Marcel Seiz-Rosenhagen, Miriam Ratliff, Christel Herold-Mende, Oliver Schnell, Juergen Beck, Wolfgang Wick, Andreas von Deimling, Moritz Gerstung, Dieter Henrik Heiland &Felix Sahm |
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| 245 | 1 | 0 | |a Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics |c Michael Ritter, Christina Blume, Yiheng Tang, Areeba Patel, Bhuvic Patel, Natalie Berghaus, Jasim Kada Benotmane, Jan Kueckelhaus, Yahaya Yabo, Junyi Zhang, Elena Grabis, Giulia Villa, David Niklas Zimmer, Amir Khriesh, Philipp Sievers, Zaira Seferbekova, Felix Hinz, Vidhya M. Ravi, Marcel Seiz-Rosenhagen, Miriam Ratliff, Christel Herold-Mende, Oliver Schnell, Juergen Beck, Wolfgang Wick, Andreas von Deimling, Moritz Gerstung, Dieter Henrik Heiland &Felix Sahm |
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| 520 | |a The diagnostic landscape of brain tumors integrates comprehensive molecular markers alongside traditional histopathological evaluation. DNA methylation and next-generation sequencing (NGS) have become a cornerstone in central nervous system (CNS) tumor classification. A limiting requirement for NGS and methylation profiling is sufficient DNA quality and quantity, which restrict its feasibility. Here we demonstrate NePSTA (neuropathology spatial transcriptomic analysis) for comprehensive morphological and molecular neuropathological diagnostics from single 5-µm tissue sections. NePSTA uses spatial transcriptomics with graph neural networks for automated histological and molecular evaluations. Trained and evaluated across 130 participants with CNS malignancies and healthy donors across four medical centers, NePSTA predicts tissue histology and methylation-based subclasses with high accuracy. We demonstrate the ability to reconstruct immunohistochemistry and genotype profiling on tissue with minimal requirements, inadequate for conventional molecular diagnostics, demonstrating the potential to enhance tumor subtype identification with implications for fast and precise diagnostic workup. | ||
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