DNA methylation-based profiling is an effective asset for identification of tumors in suspected, yet immunohistochemically, unspecified neuro-oncological cases
Christian Uhl , Naseem Ayoub , Katharina Faust , Peter Vajkoczy , Leonille Schweizer , Josefine Radke , Felix Ehret , David Capper , Julia Sophie Onken
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Abstract
Introduction
Patients with suspected neuro-oncological disease on radiographic images and no histopathological evidence of a tumor on the surgically retrieved tissue, pose a great challenge for clinicians and neuropathologists. Meanwhile, genome-wide DNA methylation-based molecular profiling has been established to allow robust brain tumor classification.
Research question
Does DNA methylation-based molecular profiling make a relevant contribution to the diagnosis and resolution of these non-specific neuro-oncological cases.
Materials and methods
We screened all neurosurgical cases at our institution between 2009 and 2021 with suspected neuro-oncological diseases on MRI but negative or unspecific histopathological diagnosis. We differentiated two groups: cases with cell-enriched, reactive tissue (with or without suspected single tumor cells), insufficient to classify the lesion according to WHO 2021 diagnostic criteria for CNS tumors (group 1) and cases that were not cell-enriched, without reactive changes and no suspected tumor cells (group 2). The primary endpoint of the study was to assess the feasibility of establishing a molecular diagnosis in accordance with the WHO 2021 diagnostic criteria for CNS tumors.
Results
23 cases with unspecified histopathological diagnosis were identified, 16 cases were assigned to group 1, seven cases to group 2. DNA-methylation-based profiling and copy number variations enabled a tumor diagnosis in nine (56.3 %) cases in group 1 and three (42.9 %) cases in group 2, adding up to 12 tumors (52.2 %). Five cases were identified as physiological cortex.
Discussion and conclusion
Our findings underscore the potential of integrating DNA methylation-based profiling into diagnostic workflows, contributing to an accurate diagnosis in challenging cases.