Abstract
Background: Central nervous system lymphoma (CNSL), is a rare subtype of non-Hodgkin lymphoma, primarily affecting the brain and spinal cord. Most therapeutic systemic agents have limited penetration of the blood-brain and blood-cerebrospinal fluid (CSF) barrier, with the latter potentially promoting a treatment "sanctuary"for cancer cells. Evaluation of occult disease, particularly in the CSF, is challenging. In limited clinical experience, the addition of multiagent intraventricular chemotherapy (MAIVC), delivered through intracranially implanted CSF reservoirs, to systemic therapy has demonstrated encouraging outcomes, enhancing both progression-free survival and overall survival. However, given the potential morbidity associated with MAIVC, identification of minimally invasive biomarkers for guiding patient selection and management is necessary. Leveraging the longitudinal, large volume of CSF, the objective of this study was to identify CSF-based proteomic biomarkers that can serve as reliable indicators of CSF clearance in response to MAIVC and CNSL treatment outcome. Methods: One hundred fifteen CSF samples from 59 CNSL patients receiving MAIVC were profiled using a high-throughput protocol coupled with mass-spectrometry that only requires 30 μL of CSF. Results: More than 2000 unique proteins were detected using shotgun proteomics. Cerebrospinal fluid proteomics revealed key proteins (SGCE, LCP1, AGRN, OLFML3, and HRSP12) distinguishing early from never responders to MAIVC, with area under the receiver operating characteristic (AUROC) 0.86 (95% CI: 0.696-1). By integrating tumor volume from brain MRI scans with proteomic data, we identified potential intraventricular tumor burden markers for CNSL management, in particular LCP1. Conclusions: The study identified CSF-based proteomic biomarkers, particularly LCP1, that can classify MAIVC response and indicate tumor burden in CNSL patients.
| Original language | English (US) |
|---|---|
| Article number | vdaf046 |
| Journal | Neuro-Oncology Advances |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Surgery
- Oncology
- Clinical Neurology
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