The role of circulating tumor DNA from cerebrospinal fluid as a minimal-invasive biomarker for comprehensive genetic profiling and improved outcome prediction in patients with CNS lymphoma

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Primary central nervous system lymphoma (PCNSL) represents a heterogeneous brain cancer type. Genetic factors underlying PCNSL clinical outcomes are poorly understood. Genotyping from tumor material achieved from invasive stereotactic biopsies or brain surgery is often insufficient due to small sample size or inaccurate tissue targeting. Moreover, these procedures cause intra- and postsurgical complications in a subset of patients, including intracranial hemorrhage and severe infections. Circulating tumor DNA (ctDNA) is an emerging biomarker across oncology, including lymphomas. We have successfully transferred a targeted capture next-generation sequencing (NGS) approach (CAPP-Seq, Cancer Personalized Profiling by Deep Sequencing) to our institution that allows ultrasensitive and comprehensive profiling of ctDNA in lymphoma patients. We optimized CAPP-Seq for its use in PCNSL and demonstrated that ctDNA is readily detectable in blood plasma and cerebrospinal fluid (CSF). Moreover, ctDNA from CSF accurately seems to mirror the mutational landscape and genetic composition of PCNSL tumors (n=4). In the proposed study, we aim to utilize available diagnostic CSF from a prospective multi-center trial (n=84, DRKS00005503) to establish CSF ctDNA as a biopsy-free biomarker for comprehensive tumor genotyping, assessment of tumor burden, characterization of PCNSL mutation landscapes, and prediction of PCNSL outcomes. We will further utilize information from CSF ctDNA genotyping together with conventional clinical and radiographic risk factors to develop a novel integrative risk models that allows accurate and improved outcome prediction over single-factor traditional models. If successfull, we envision a role of CSF sequencing as a minimal-invasive way to comprehensively assess PCNSL genotypes without the need for invasive surgical procedures or sufficient amounts of tumor DNA. Moreover, an improved and personalized integrative algorithm for outcome prediction might significantly enhance clinical management of patients with PCNSL with and help guide therapies in the future.