Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histologic subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was done on 26 glioblastomas, 22 oligodendrogliomas, and 6 control brain samples. Our results show that Human Exon arrays can identify subgroups of gliomas based on their histologic appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas, a subset of which (47% and 33%) were confirmed by reverse transcription-PCR (RT-PCR). In addition, exon level expression profiling also identified >700 novel exons. Expression of f67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants, and can identify novel exons. The splice variants identified by exon level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets.

Gastric carcinogenesis is driven by an accumulation of genetic changes that to a large extent occur at the chromosomal level. We analysed the patterns of chromosomal instability in 35 gastric carcinomas and their clinical correlations. With microarray competitive genomic hybridization, genomewide chromosomal copy number changes can be studied with high resolution and sensitivity. A genomewide scanning array with 2275 BAC and P1 clones spotted in triplicate was used. This array provided an average resolution of 1.4 Mb across the genome. Patterns of chromosomal aberrations were analysed by hierarchical cluster analysis of the normalized log 2 tumour to normal fluorescence ratios of all clones, and cluster membership was correlated to clinicopathological data including survival. Hierarchical cluster analysis revealed three groups with different genomic profiles that correlated significantly with lymph node status (P ¼ 0.02). Moreover, gastric cancer cases from cluster 3 showed a significantly better prognosis than those from clusters 1 and 2 (P ¼ 0.02). Genomic profiling of gastric adenocarcinomas based on microarray analysis of chromosomal copy number changes predicted lymph node status and survival. The possibility to discriminate between patients with a high risk of lymph node metastasis could clinically be helpful for selecting patients for extended lymph node resection.

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. One of the tumors most frequently associated with LM is breast cancer. During the course of the disease, ϳ5% of patients with metastatic breast cancer will develop symptoms caused by LM. This debilitating complication's response to therapy depends upon early treatment. However, diagnosis of LM remains challenging because 25% of samples tested are false negative at the first cytological examination of the CSF, probably because of sampling error (1).Protein expression profiling of body fluids from patients with cancer has recently become a valuable tool for obtaining information on the state of protein circuits inside tumor cells and outside the cells at the host-tumor interface (2, 3). In serum and CSF, low molecular weight proteins and peptides that are related to this altered microenvironmental "cancerous" state can be detected.We studied the differential tryptic peptide profiles in the CSF from patients with breast cancer with and without LM and in CSF from control subjects. Studying CSF has several advantages over studying serum. First, tumor cells in LM patients are located in the CSF and in the leptomeninges that are surrounded by CSF. Before their transport into serum, tumor-related proteins will therefore first be shed into the CSF. Second, the normal protein concentration of CSF is 100-to 400-fold lower than in serum (4). This results in a significant over-representation of LM-related proteins in CSF compared From the ‡Laboratory of Neuro-oncology, Department of Neurology, Dr Molewaterplein 40, 3015 GD, and § §Department

Breast carcinomas can be classified with a high level of certainty as sporadic or related to BRCA1 germline mutations by using a decision tree with age, Ki67 and EGFR. This can be clinically useful in mutation analysis in families with a borderline risk of hereditary disease.

In protein and peptide mass spectrometry in which profiling of peaks is involved, their masses and intensities are important characteristics. Because of the relative low reproducibility of peak intensities associated with complex samples in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), it is difficult to accurately assess the number of peaks and their intensities. In this study we evaluate these two characteristics for tryptic digests of cerebrospinal fluid. We observed that the reproducibility of peak intensities was relatively poor (CV ¼ 42%) and that additional normalization or spiking did not lead to a large improvement (CV ¼ 30%). Moreover, at least seven mass spectra per sample were required to obtain a reliable peak list. An improvement of the sensitivity (i.e., eventually more peaks are detected) is observed if more replicates per sample are measured. We conclude that the reproducibility and sensitivity of peptide profiling can be significantly improved by a combination of measuring at least seven spectra per sample with a dichotomous scoring of the intensities. This approach will aid the analysis of large numbers of mass spectra of patient samples in a reproducible way for the detection and validation of candidate biomarkers. Copyright # 2005 John Wiley & Sons, Ltd.Mass spectrometry is extensively used in biomarker research. This has resulted in the development of methods for the analysis and comparison of large numbers of mass spectra. We describe here a new method for the analysis of tryptic peptide measurements for cerebro-spinal fluid (CSF) using matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) that addresses the problem of the low reproducibility of intensities. The standard method of using peak intensities was compared with a new approach that uses peak frequencies. To this end, the reproducibilities of peak intensities and of peak frequencies were determined.The MALDI-TOFMS technique is characterized by a relatively high mass accuracy and precision. In contrast, the reproducibility of measured intensities is relatively low in MALDI-TOF and SELDI-TOFMS (surface-enhanced laser desorption/ionization time-of-flight), compared to MS with electrospray ionization. For SELDI-TOFMS, the coefficient of variance (CV) for the peak intensities has been reported to be in the range 10-30%.1-4 The relatively low reproducibility of peak intensities is caused by ion suppression, variation in the amount of matrix, and variation in the crystallization of the matrix as a function of the analyte concentration or ratio. Crystallization depends on a number of factors including contamination of the analyte and the ratio of matrix and analyte. 5,6 If the intensities of peaks in the MALDI-TOF mass spectra of complex samples of peptides or proteins are to be used for analysis, it is essential that the reproducibility of these intensities be determined and used in the analysis. Indeed, more and more publications appear that describe peptid...