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Review
. 2024 Feb 13;21(1):14.
doi: 10.1186/s12987-024-00515-x.

Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data

Affiliations
Review

Mass spectrometry-based proteomics of cerebrospinal fluid in pediatric central nervous system malignancies: a systematic review with meta-analysis of individual patient data

Christian Mirian et al. Fluids Barriers CNS. .

Abstract

Background: The cerebrospinal fluid (CSF) proteome could offer important insights into central nervous system (CNS) malignancies. To advance proteomic research in pediatric CNS cancer, the current study aims to (1) evaluate past mass spectrometry-based workflows and (2) synthesize previous CSF proteomic data, focusing on both qualitative summaries and quantitative re-analysis. MAIN: In our analysis of 11 studies investigating the CSF proteome in pediatric patients with acute lymphoblastic leukemia (ALL) or primary brain tumors, we observed significant methodological variability. This variability negatively affects comparative analysis of the included studies, as per GRADE criteria for quality of evidence. The qualitative summaries covered 161 patients and 134 non-tumor controls, while the application of validation cohort varied among the studies. The quantitative re-analysis comprised 15 B-ALL vs 6 "healthy" controls and 15 medulloblastoma patients vs 22 non-tumor controls. Certain CSF proteins were identified as potential indicators of specific malignancies or stages of neurotoxicity during chemotherapy, yet definitive conclusions were impeded by inconsistent data. There were no proteins with statistically significant differences when comparing cases versus controls that were corroborated across studies where quantitative reanalysis was feasible. From a gene ontology enrichment, we observed that age disparities between unmatched case and controls may mislead to protein correlations more indicative of age-related CNS developmental stages rather than neuro-oncological disease. Despite efforts to batch correct (HarmonizR) and impute missing values, merging of dataset proved unfeasible and thereby limited meaningful data integration across different studies.

Conclusion: Infrequent publications on rare pediatric cancer entities, which often involve small sample sizes, are inherently prone to result in heterogeneous studies-particularly when conducted within a rapidly evolving field like proteomics. As a result, obtaining clear evidence, such as CSF proteome biomarkers for CNS dissemination or early-stage neurotoxicity, is currently impractical. Our general recommendations comprise the need for standardized methodologies, collaborative efforts, and improved data sharing in pediatric CNS malignancy research. We specifically emphasize the possible importance of considering natural age-related variations in CSF due to different CNS development stages when matching cases and controls in future studies.

Keywords: Brain tumor; Central nervous system; Cerebrospinal fluid; Leukemia; Mass spectrometry; Meta-analysis; Pediatric; Proteomics.

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Conflict of interest statement

The authors declares that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flow-chart of the search strategy
Fig. 2
Fig. 2
The dynamic range comparing the Yu and Guo cohort
Fig. 3
Fig. 3
A Dynamic ranges for Bruschi and Reichl cohort. B Volcano plot based on t-test for comparing patients with a medulloblastoma to control. *P-value at 0.05 (uncorrected)
Fig. 4
Fig. 4
Gene ontology enrichment analysis of proteins expressed in ALL patients in the Yu cohort (A, no controls), while comparing ALL patients to controls in the Guo cohort (B)
Fig. 5
Fig. 5
Gene ontology enrichment analysis comparing medulloblastoma patients to controls using the Bruschi (A) and Reichl (B) cohort
Fig. 6
Fig. 6
Merging of ALL proteomic data (Yu et al. and Guo et al.) and medulloblastoma proteomic data using the HarmonizR-approach for batch correction without imputation

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