Increased Phosphorylation of Vimentin in Noninfiltrative Meningiomas

International audienceBACKGROUND: Tissue invasion or tissue infiltration are clinical behaviors of a poor-prognosis subset of meningiomas. We carried out proteomic analyses of tissue extracts to discover new markers to accurately distinguish between infiltrative and noninfiltrative meningiomas. METHODOLOGY/PRINCIPAL FINDINGS: Protein lysates of 64 different tissue samples (including two brain-invasive and 32 infiltrative tumors) were submitted to SELDI-TOF mass spectrometric analysis. Mass profiles were used to build up both unsupervised and supervised hierarchical clustering. One marker was found at high levels in noninvasive and noninfiltrative tumors and appeared to be a discriminative marker for clustering infiltrative and/or invasive meningiomas versus noninvasive meningiomas in two distinct subsets. Sensitivity and specificity were 86.7% and 100%, respectively. This marker was purified and identified as a multiphosphorylated form of vimentin, a cytoskeletal protein expressed in meningiomas. CONCLUSIONS/SIGNIFICANCE: Specific forms of vimentin can be surrogate molecular indicators of the invasive/infiltrative phenotype in tumors

Nanoporous Organosilicates Thin Films for Selective Enrichment of Metabolites

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Accessing to the minor proteome of red blood cells through the influence of the nanoparticle surface properties on the corona composition

Affif Zaccaria,1,* Florence Roux-Dalvai,2,3,* Ali Bouamrani,1 Adrien Mombrun,1 Pascal Mossuz,4 Bernard Monsarrat,2,3 François Berger1 1Clinatec CEA-LETI, Grenoble, 2CNRS, IPBS (Institut de Pharmacologie et de Biologie Structurale), 3Université de Toulouse, UPS, IPBS, Toulouse, 4TIMC-Therex UMR 5525 CNRS, UJF, CHU Grenoble, Grenoble, France *These authors contributed equally to this work Abstract: Nanoparticle (NP)–protein interactions in complex samples have not yet been clearly understood. Nevertheless, several studies demonstrated that NP’s physicochemical features significantly impact on the protein corona composition. Taking advantage of the NP potential to harvest different subsets of proteins, we assessed for the first time the capacity of three kinds of superparamagnetic NPs to highlight the erythrocyte minor proteome. Using both qualitative and quantitative proteomics approaches, nano-liquid chromatography–tandem mass spectrometry allowed the identification of 893 different proteins, confirming the reproducible capacity of NPs to increase the number of identified proteins, through a reduction of the sample concentration range and the capture of specific proteins on the three different surfaces. These NP-specific protein signatures revealed significant differences in their isoelectric point and molecular weight. Moreover, this NP strategy offered a deeper access to the erythrocyte proteome highlighting several signaling pathways implicated in important erythrocyte functions. The automated potentiality, the reproducibility, and the low-consuming sample demonstrate the strong compatibility of our strategy for large-scale clinical studies and may become a standardized sample preparation in future erythrocyte-associated proteomics studies. Keywords: nanoparticles, red blood cells, mass spectrometry, quantitative proteomics, protein corona, minor proteome&nbsp

SiOCH thin films deposited by chemical vapor deposition: From low-κ to chemical and biochemical sensors

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Expression of S100A8 in leukemic cells predicts poor survival in de novo AML patients.

International audienceCytogenetic stratification remains insufficient for almost half of the acute myeloblastic leukemia (AML) cases, with AML patients requiring subsequent molecular investigation. In our study, we used mass spectrometry (MS)-based proteomic approaches to characterize de novo AML. Fifty-four samples (mononuclear cells from bone marrow or peripheral blood mononuclear cells collected and frozen before treatment) from two independent cohorts of newly diagnosed AML patients were analyzed. We showed that the protein signature of leukemic cells defined two clusters that displayed significant variation for overall and disease-free survival (P=0.001 and 0.0004, respectively). This proteomic classification refines the cytogenetic classes. AML patients with intermediate and unfavorable cytogenetic classifications could be subdivided according to their protein profiles into subgroups with significantly different survival rates. Among the proteins expressed by leukemic cells, we isolated a 10,800-Da marker that retained the highest discriminative value between living and deceased patients. The 10,800-Da marker was identified by MS peptide sequencing as S100A8 (also designated MRP8 or calgranulin A). Western blot analysis confirmed its expression mainly in AML patients with the worst prognosis, arguing for a selective deregulation associated with poor prognosis. These results suggest that the expression of S100A8 in leukemic cells is a predictor of low survival

Preparation of the Low Molecular Weight Serum Proteome for Mass Spectrometry Analysis.

The ability to cure or manage many diseases is highly dependent on the ability to correctly diagnose them at the earliest possible stage. Diagnosis relies heavily on biomarkers whether these be visual symptoms or molecules found within samples acquired from the patient. For conditions that lack useful biomarkers, researchers are often faced with the task of sifting through very complex biological samples (i.e., serum, plasma, urine, tissue, cells, etc.) with the hope of discovering a small number of molecules that are exquisitely diagnostic for the condition of interest. One discovery strategy that has been frequently used is to fractionate the biological samples being studied into simpler aliquots that can be more easily characterized using existing technologies. One such fractionation method is to isolate a specific portion based on a specific property (i.e., size, phosphorylation state, charge, etc.) of the proteins within the sample. This method provides a simplified sample that can be characterized at a higher coverage level than the complex sample from which it was derived. This chapter details one of these methods, the extraction and analysis of the low molecular weight proteome of human serum