Background: Liquid biopsy represents a major development in cancer research, with significant translational potential. Similarly, it is increasingly recognized that multi-omic molecular approaches are a powerful avenue through which to understand complex and heterogeneous disease biology. We hypothesize that merging these two promising frontiers of cancer research will improve the discriminatory capacity of current models and allow for improved clinical utility.
Methods: We have compiled a cohort of patients with glioblastoma, brain metastasis, and primary central nervous system lymphoma. Cell-free methylated DNA immunoprecipitation (cfMeDIP) and shotgun proteomic profiling was obtained from the cerebrospinal fluid (CSF) of each patient and used to build tumour-specific classifiers.
Results: We show that the DNA methylation and protein profiles of cerebrospinal fluid can be integrated to fully discriminate lymphoma from its diagnostic counterparts with perfect AUC of 1 (95% confidence interval 1-1) and 100% specificity, significantly outperforming single-platform classifiers.
Conclusions: We present the most specific and accurate CNS lymphoma classifier to date and demonstrates the synergistic capability of multi-platform liquid biopsies. This has far-reaching translational utility for patients with newly diagnosed intra-axial brain tumours.
Keywords: Brain metastases; Classifier; Glioblastoma; Liquid biopsy; Lymphoma; Methylation; Multi-platform; Proteomics.
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.