PATH-46. COMPUTATIONAL HISTOPATHOLOGY INFORMED RAPID TARGETED NANOPORE SEQUENCING ENABLES AFFORDABLE NEXT DAY REPORTING OF COMPREHENSIVE MOLECULAR MARKERS FOR CNS TUMOUR DIAGNOSTICS


Journal article


A. Patel, H. Dogan, Alexander W. Jung, Z. Seferbekova, A. Payne, M. Ritter, D. Schrimpf, D. Stichel, Stefan Hamelmann, C. Blume, P. Euskirchen, V. Goidts, M. Sill, S. Pfister, M. Loose, W. Wick, A. von Deimling, David C. Jones, M. Schlesner, M. Gerstung, F. Sahm
Neuro-Oncology, 2022

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APA   Click to copy
Patel, A., Dogan, H., Jung, A. W., Seferbekova, Z., Payne, A., Ritter, M., … Sahm, F. (2022). PATH-46. COMPUTATIONAL HISTOPATHOLOGY INFORMED RAPID TARGETED NANOPORE SEQUENCING ENABLES AFFORDABLE NEXT DAY REPORTING OF COMPREHENSIVE MOLECULAR MARKERS FOR CNS TUMOUR DIAGNOSTICS. Neuro-Oncology.


Chicago/Turabian   Click to copy
Patel, A., H. Dogan, Alexander W. Jung, Z. Seferbekova, A. Payne, M. Ritter, D. Schrimpf, et al. “PATH-46. COMPUTATIONAL HISTOPATHOLOGY INFORMED RAPID TARGETED NANOPORE SEQUENCING ENABLES AFFORDABLE NEXT DAY REPORTING OF COMPREHENSIVE MOLECULAR MARKERS FOR CNS TUMOUR DIAGNOSTICS.” Neuro-Oncology (2022).


MLA   Click to copy
Patel, A., et al. “PATH-46. COMPUTATIONAL HISTOPATHOLOGY INFORMED RAPID TARGETED NANOPORE SEQUENCING ENABLES AFFORDABLE NEXT DAY REPORTING OF COMPREHENSIVE MOLECULAR MARKERS FOR CNS TUMOUR DIAGNOSTICS.” Neuro-Oncology, 2022.


BibTeX   Click to copy

@article{a2022a,
  title = {PATH-46. COMPUTATIONAL HISTOPATHOLOGY INFORMED RAPID TARGETED NANOPORE SEQUENCING ENABLES AFFORDABLE NEXT DAY REPORTING OF COMPREHENSIVE MOLECULAR MARKERS FOR CNS TUMOUR DIAGNOSTICS},
  year = {2022},
  journal = {Neuro-Oncology},
  author = {Patel, A. and Dogan, H. and Jung, Alexander W. and Seferbekova, Z. and Payne, A. and Ritter, M. and Schrimpf, D. and Stichel, D. and Hamelmann, Stefan and Blume, C. and Euskirchen, P. and Goidts, V. and Sill, M. and Pfister, S. and Loose, M. and Wick, W. and von Deimling, A. and Jones, David C. and Schlesner, M. and Gerstung, M. and Sahm, F.}
}

Abstract

Integrative brain tumour diagnostics indisputably requires comprehensive reporting of molecular markers. The 2021 WHO classification of central nervous system (CNS) tumours substantially increased the set of markers for routine evaluation, with greater significance to DNA methylation analysis in diagnostics. Limited by investment and batching, smaller labs and clinics might suffer major delays in delivering clinical decisions. To make precision diagnostics accessible, we introduce an integrated computational histopathology and adaptive nanopore sequencing workflow for next day CNS tumour diagnostics.

We used CNS-CHiP- a multitask deep transfer learning model to predict key molecular alterations and methylation classification from H&E stained CNS tumour slides. For further characterisation and subtyping, we used the predictions to formulate a custom panel for each patient. Targeted sequencing and analyses were performed using Rapid-CNS2- a custom neurooncology nanopore sequencing pipeline for parallel copy-number, mutational and methylation analysis that is flexible in target selection with no additional library preparation and can be initiated upon receipt of frozen sections. Sequencing was performed on a portable MinION or GridION.

We demonstrate our workflow on diagnostic samples received by the Department of Neuropathology, University Hospital Heidelberg. CNS-CHiP predicted multiple pathognomonic alterations (eg. IDH mutation, 7 gain/10 loss) with reasonable accuracy. This provided basic information regarding the tumor type instantly. Personalised panels enabled small target sizes, resulting in low sequencing time (up to 24h) and competitive costs. The GPU-accelerated bioinformatics pipeline reduced analysis time from > 24h to < 3h.

Our workflow harnessing histology-based molecular predictions to instruct targeted nanopore sequencing can be set up with low initial investment and has the potential to facilitate reporting of molecular results on the next day of sample collection. CNS-CHiP combined with Rapid-CNS2 thus aims to make CNS tumour diagnostics affordable and accessible to smaller hospitals and labs especially in low- and middle-income countries.



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