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Research

MALDI-TOF Mass Spectrometry Analysis of Cerebrospinal Fluid Tryptic Peptide Profiles to Diagnose Leptomeningeal Metastases in Patients with Breast Cancer^*

Lennard J. Dekker, Willem Boogerd, Guenther Stockhammer^¶, Johannes C. Dalebout, Ivar Siccama^||, Pingpin Zheng, Johannes M. Bonfrer^**, Jan J. Verschuuren, Guido Jenster, Marcel M. Verbeek^¶¶, Theo M. Luider and Peter A. Sillevis Smitt^,||||

From the Laboratory of Neuro-oncology, Department of Neurology, Dr Molewaterplein 40, 3015 GD, and Department of Urology, P.O. Box 1738, 3000 DR, Erasmus MC, Rotterdam, The Netherlands, Departments of Neurology and ^** Clinical Chemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands, ^¶ Department of Neurology, University of Innsbruck, Anichstrasse 35, 6020, Innsbruck, Austria, ^|| Chordiant, De Lairessestraat 150, 1075 HL, Amsterdam, The Netherlands, Department of Neurology, Leiden University Medical Centre, P.O. Box 9600, 2300 RC, Leiden, The Netherlands, and ^¶¶ Department of Neurology, University Medical Center Nijmegen, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands

Leptomeningeal metastasis (LM) is a devastating complication that occurs in 5% of patients with breast cancer. Early diagnosis and initiation of treatment are essential to prevent neurological deterioration. However, early diagnosis of LM remains challenging because 25% of cerebrospinal fluid (CSF) samples produce false-negative results at first cytological examination. We developed a new, MS-based method to investigate the protein expression patterns present in the CSF from patients with breast cancer with and without LM. CSF samples from 106 patients with active breast cancer (54 with LM and 52 without LM) and 45 control subjects were digested with trypsin. The resulting peptides were measured by MALDI-TOF MS. Then, the mass spectra were analyzed and compared between patient groups using newly developed bioinformatics tools. A total of 895 possible peak positions was detected, and 164 of these peaks discriminated between the patient groups (Kruskal-Wallis, p < 0.01). The discriminatory masses were clustered, and a classifier was built to distinguish patients with breast cancer with and without LM. After bootstrap validation, the classifier had a maximum accuracy of 77% with a sensitivity of 79% and a specificity of 76%. Direct MALDI-TOF analysis of tryptic digests of CSF gives reproducible peptide profiles that can assist in diagnosing LM in patients with breast cancer. The same method can be used to develop diagnostic assays for other neurological disorders.

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