Journal Article

DKFZ-2025-00257

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics.

Ritter, M. (First author)DKFZ* ; Blume, C.DKFZ* ; Tang, Y.DKFZ* ; Patel, A. J.DKFZ* ; Patel, B.DKFZ* ; Berghaus, N.DKFZ* ; Kada Benotmane, J. ; Kueckelhaus, J. ; Yabo, Y. ; Zhang, J. ; Grabis, E. ; Villa, G. ; Zimmer, D. N. ; Khriesh, A. ; Sievers, P.DKFZ* ; Seferbekova, Z.DKFZ* ; Hinz, F.DKFZ* ; Ravi, V. M. ; Seiz-Rosenhagen, M. ; Ratliff, M. ; Herold-Mende, C. ; Schnell, O.DKFZ* ; Beck, J. ; Wick, W.DKFZ* ; von Deimling, A.DKFZ* ; Gerstung, M.DKFZ* ; Heiland, D. H.DKFZ* ; Sahm, F. (Last author)DKFZ*

2025
Nature Research London

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Please use a persistent id in citations: doi:10.1038/s43018-024-00904-z

Abstract: 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.

Note: #EA:B320#LA:B320# / 2025 Feb;6(2):292-306

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Contributing Institute(s):

1. KKE Neuroonkologie (B320)
2. DKTK HD zentral (HD01)
3. Künstl. Intelligenz in der Onkologie (B450)
4. B062 Pädiatrische Neuroonkologie (B062)
5. DKTK Koordinierungsstelle Freiburg (FR01)
6. KKE Neuropathologie (B300)

Research Program(s):

1. 312 - Funktionelle und strukturelle Genomforschung (POF4-312) (POF4-312)

Appears in the scientific report 2025

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Nature ; Essential Science Indicators ; IF >= 20 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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