Dataset Information

Evaluation of Non-Supervised MALDI Mass Spectrometry Imaging Combined to MicroProteomics for Glioma Grade III Classification

ABSTRACT: An integrated diagnosis using molecular features is recommended in the updated World Health Organization (WHO) classification. Our aim was to explore the role of MALDI-Mass spectrometry imaging (MSI) coupled to microproteomics in order to classify anaplastic glioma by integration of clinical data.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Brain

DISEASE(S): Brain Cancer

SUBMITTER: Maxence Wisztorski

LAB HEAD: Michel Salzet

PROVIDER: PXD004437 | Pride | 2016-12-13

REPOSITORIES: Pride

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Publications

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification.

Le Rhun Emilie E Duhamel Marie M Wisztorski Maxence M Gimeno Jean-Pascal JP Zairi Fahed F Escande Fabienne F Reyns Nicolas N Kobeissy Firas F Maurage Claude-Alain CA Salzet Michel M Fournier Isabelle I

Biochimica et biophysica acta. Proteins and proteomics 20161124 7

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and ...[more]

PMID: 27890679

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Project description:Gliomas represent 80% of all malignant cerebral tumors and are classified within different malignity grade. Glioblastoma, the most aggressive group, represent more than half of all gliomas but remain a heterogeneous group. Indeed, patient survival can reach from several months to a few years after surgery and chemotherapy. To study gliomas, MALDI mass spectrometry imaging is an interesting technique, allowing the analysis of tumor heterogeneity. In this study, MALDI-MSI is coupled with spatially-resolved microproteomic within the objective to identify subgroups of glioblastomas patients in order to help diagnosis and prognostic. Molecular images are generated from thin tissue section in order to determine the spatial localization of digested peptides. Thanks to unsupervised statistical analysis, we then generated hierarchical clustering of homogeneous molecular regions. According to these regions, spatially resolved proteomic gave access to large scale protein identification and relative quantification. Hierarchical clustering reveal three molecular region within all the tumors sample : region red which represent 33% of surface of all sample, region yellow (25.7%) and region blue (40.8%). Consequently, 3 groups of patient can be determined: group A composed mostly of region red (13/50 patients), group B composed mostly of region yellow (9/50 patients) and group C composed mostly of region blue (24/50 patients). Spatially resolved proteomic was performed and the 147 extractions were analyzed by nano-LC MS/MS. Two-way ANOVA test reveal panel of proteins specifically overexpressed in each region. Protein overexpressed in region red are associated with neurogenesis; protein overexpressed in region yellow are associated with an activation of the immune system and protein overexpressed in region blue are involved with viral processes. To conclude, the combination of MALDI-MSI and microproteomic provides new information on these tumors, allowing us to differentiate three group of patient. In the future, these data will permit to build a more precise classification, a better medical care for patients and the identification of potential new therapeutic targets.

Project description:MicroRNAs (miRNAs) are abundant in the circulation and play a central role in diverse biological processes; they may be useful for early diagnosis of hepatocellular carcinoma (HCC). We conducted a two-phase, case-control study (20 pairs for the discovery set and 49 pairs for the validation set) to test the hypothesis that genome-wide dysregulation of circulating miRNAs differentiate HCC cases from controls. Taqman low density arrays were used to examine genome-wide miRNA expression for the discovery set, and quantitative RT-PCR was used to validate candidate miRNAs for both discovery and validation sets. Sixty-six miRNAs were found to be significantly over-expressed in plasma of HCC cases compared to controls after adjusting for false discovery rate (p<0.05). A volcano plot indicated that 7 miRNAs had greater than 2-fold case-control differences with p<0.01. Four significant miRNAs (miR-150, miR-30c, miR-483-5p and miR-520b) detectable in all samples with varied expression levels were further validated in a validation set. MiR-483-5p was statistically significantly over-expressed in HCC cases compared with controls (3.20 vs. 0.82, p<0.0001). HCC risk factors and clinic-pathological characteristics did not influence miR-483-5p expression. The combination of plasma miR-483-5p level and HCV status can significantly differentiate HCC cases from controls with an AUC of 0.908 (p<0.0001). The sensitivity and specificity were, respectively, 75.5% and 89.8%. These preliminary results suggest the importance of dysregulated circulating miR-483-5p as a potential HCC biomarker. Confirmation of aberrant expression of miR-483-5p in a large prospective HCC study will provide support for its application to HCC detection. A hospital-based HCC case-control study including 20 HCC patients and 20 controls is conducted in Columbia University Medical Center (CUMC), which is approved by the Institutional Review Board. Cases were newly diagnosed HCC patients who were treated in the Hepatobiliary Oncology Clinics, CUMC, and examined pathologically. Controls were recruited from volunteers through the Research Recruitment and Minority Outreach (RRMO) core of Herbert Irving Comprehensive Cancer Center (HICCC). Flyers were placed at strategic locations around CUMC where hospital visitors and employees frequent or were handed out at inreach events at the hospital or at outreach events in the community. Interested participants were directed to contact the trained recruitment staff from the RRMO and given further information about participation. Interested participants were excluded from the control group if diagnosed for any kind of cancer or liver disease. Eligible controls were asked to fill out the same demographic and epidemiological questionnaire as HCC cases. In the current study, controls were matched with HCC cases on age (M-BM-15 yrs), gender (male/female) and ethnicities (Caucasian/Hispanic/African-American/Asian).

Dataset Information

Evaluation of Non-Supervised MALDI Mass Spectrometry Imaging Combined to MicroProteomics for Glioma Grade III Classification

Publications

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification.

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