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Background: Malignant pleural mesothelioma (MPM) a rare neoplasm linked to asbestos exposure is characterized by a poor prognosis. Soluble mesothelin is currently considered the most specific diagnostic biomarker. The aim of the study was to identify novel biomarkers by proteomic analysis of two MPM cell lines secretome., Materials and Methods: The protein patterns of MPM cells secretome were examined and compared to a non-malignant mesothelial cell line using two-dimensional gel electrophoresis coupled to mass spectrometry. Serum levels of candidate biomarkers were determined in MPM patients and control subjects., Results: Two up-regulated proteins involved in cancer biology, prosaposin and quiescin Q6 sulfhydryl oxidase 1, were considered candidate biomarkers. Serum levels of both proteins were significantly higher in MPM patients than control subjects. Combining the data of each receiver-operating characteristic analysis predicted a good diagnostic accuracy., Conclusion: A panel of the putative biomarkers represents a promising tool for MPM diagnosis., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Mitochondria are undeniably the cell powerhouse, directly affecting cell survival and fate. Growing evidence suggest that mitochondrial protein repertoire affects metabolic activity and plays an important role in determining cell proliferation/differentiation or quiescence shift. Consequently, the bioenergetic status of a cell is associated with the quality and abundance of the mitochondrial populations and proteomes. Mitochondrial morphology changes in the development of different cellular functions associated with metabolic switches. It is therefore reasonable to speculate that different cell lines do contain different mitochondrial-associated proteins, and the investigation of these pools may well represent a source for mining missing proteins (MPs). A very effective approach to increase the number of IDs through mass spectrometry consists of reducing the complexity of the biological samples by fractionation. The present study aims at investigating the mitochondrial proteome of five phenotypically different cell lines, possibly expressing some of the MPs, through an enrichment-fractionation approach at the organelle and protein level. We demonstrate a substantial increase in the proteome coverage, which, in turn, increases the likelihood of detecting low abundant proteins, often falling in the category of MPs, and resulting, for the present study, in the identification of METTL12, FAM163A, and RGS13. All MS data have been deposited to the MassIVE data repository ( https://massive.ucsd.edu ) with the data set identifier MSV000082409 and PXD010446.

E. coli is one of the most frequently involved bacteria in uterine diseases. Lipopolysaccharide (LPS) is a component of the outer membrane of Gram-negative bacteria involved in pathogenic processes leading to post-partum metritis and endometritis in cattle. It also causes inflammation of the endometrium. The increase of cell proliferation by LPS is part of the inflammatory process. The aim of this study was to investigate possible changes in protein expression in relation to the proliferative response of bEECs after challenge with E. coli-LPS. In vitro culture of bEECs was performed from cow genital tracts collected at a slaughterhouse. In passage 5, bEECs from each of 9 cows (3 series of 3 cows) were exposed to 0, 8, and 16 μg ml -1 LPS for 72 h. At time 0 and 72 h later, attached cells/living cells were counted and for each time and LPS dosage, cells were frozen for proteomic analyses. All samples from the 3 series were analyzed by 2-D gel electrophoresis coupled to MALDI-TOF/TOF mass spectrometry. The samples from the first series were subjected to shotgun nLC-MS/MS analysis. From the whole differential proteomics analysis, 38 proteins were differentially expressed (p < 0.05 to p < 0.001) following exposure to LPS. Among them, twenty-eight were found to be up-regulated in the LPS groups in comparison to control groups and ten were down-regulated. Differentially expressed proteins were associated with cell proliferation and apoptosis, transcription, destabilization of cell structure, oxidative stress, regulation of histones, allergy and general cell metabolism pathways. The de-regulations induced by LPS were consistent with the proliferative phenotype and indicated strong alterations of several cell functions. In addition, some of the differentially expressed proteins relates to pathways activated at the time of implantation. The specific changes induced through those signals may have negative consequences for the establishment of pregnancy.

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.