Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease

Background:Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa) biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. <br>Methodology/Principal Findings: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls) were enrolled in 3 centres. Biomarker panels a) for PCa diagnosis (comparison of PCa patients versus benign controls) and b) for advanced disease (comparison of patients with post surgery Gleason score <7 versus Gleason score >>7) were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (<pT3a) or advanced (≥pT3a) disease with 80% sensitivity and 82% specificity in a preliminary validation setting. Seminal profiles showed excellent pre-analytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase​,prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study.</br> <br>Conclusions/Significance: Seminal plasma represents a robust source of potential peptide makers for primary PCa diagnosis. Our findings warrant further prospective validation to confirm the diagnostic potential of identified seminal biomarker candidates.</br&gt

Socio-Emotional Competencies and School Performance in Adolescence: What Role for School Adjustment?

There is growing evidence in the literature of positive relationships between socio-emotional competencies and school performance. Several hypotheses have been used to explain how these variables may be related to school performance. In this paper, we explored the role of various school adjustment variables in the relationship between interpersonal socio-emotional competencies and school grades, using a weighted network approach. This network approach allowed us to analyze the structure of interrelations between each variable, pointing to both central and mediatory school and socio-emotional variables within the network. Self-reported data from around 3,400 French vocational high school students were examined. This data included a set of interpersonal socio-emotional competencies (cognitive and affective empathy, socio-emotional behaviors and collective orientation), school adjustment measures (adaptation to the institution, school anxiety, self-regulation at school, and self-perceived competence at school) as well as grades in mathematics and French language. The results showed that self-regulation at school weighted the most strongly on the whole network, and was the most important mediatory pathway. More specifically, self-regulation mediated the relationships between interpersonal socio-emotional competencies and school grades

Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

<p>Abstract</p> <p>Background</p> <p>There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to non-disease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.</p> <p>Methods</p> <p>Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.</p> <p>Results</p> <p>Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissue-specific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty-six candidate biomarkers for these four cancer types are proposed.</p> <p>Conclusions</p> <p>We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted.</p

Preclinical evaluation of a TEX101 protein ELISA test for the differential diagnosis of male infertility

BACKGROUND: TEX101 is a cell membrane protein exclusively expressed by testicular germ cells and shed into seminal plasma. We previously verified human TEX101 as a biomarker for the differential diagnosis of azoospermia, and developed a first-of-its-kind TEX101 ELISA. To demonstrate the clinical utility of TEX101, in this work we aimed at evaluating ELISA performance in a large population of fertile, subfertile, and infertile men. METHODS: Mass spectrometry, size-exclusion chromatography, ultracentrifugation, and immunohistochemistry were used to characterize TEX101 protein as an analyte in seminal plasma. Using the optimized protocol for seminal plasma pretreatment, TEX101 was measured by ELISA in 805 seminal plasma samples. RESULTS: We demonstrated that TEX101 was present in seminal plasma mostly in a free soluble form and that its small fraction was associated with seminal microvesicles. TEX101 median values were estimated in healthy, fertile pre-vasectomy men (5436 ng/mL, N = 64) and in patients with unexplained infertility (4967 ng/mL, N = 277), oligospermia (450 ng/mL, N = 270), and azoospermia (0.5 ng/mL, N = 137). Fertile post-vasectomy men (N = 57) and patients with Sertoli cell-only syndrome (N = 13) and obstructive azoospermia (N = 36) had undetectable levels of TEX101 (≤0.5 ng/mL). A cut-off value of 0.9 ng/mL provided 100% sensitivity at 100% specificity for distinguishing pre- and post-vasectomy men. The combination of a concentration of TEX101 > 0.9 ng/mL and epididymis-specific protein ECM1 > 2.3 μg/mL provided 81% sensitivity at 100% specificity for differentiating between non-obstructive and obstructive azoospermia, thus eliminating the majority of diagnostic testicular biopsies. In addition, a cut-off value of ≥0.6 ng/mL provided 73% sensitivity at 64% specificity for predicting sperm or spermatid retrieval in patients with non-obstructive azoospermia. CONCLUSIONS: We demonstrated the clinical utility of TEX101 ELISA as a test to evaluate vasectomy success, to stratify azoospermia forms, and to better select patients for sperm retrieval. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-017-0817-5) contains supplementary material, which is available to authorized users

The paradoxical role of meritocratic selection in the perpetuation of social inequalities at school

The school system is intended to offer all students the same opportunities, but most international surveys reveal an overall lower achievement for students from disadvantaged groups compared with more advantaged students. Recent experimental research in social psychology has demonstrated that schools as institutions contribute with their implicit cultural norms and structure to the production of inequalities. This chapter examines the role that a structural feature of school, namely meritocratic selection, plays in this reproduction of inequalities at school. First, we describe how meritocracy in the educational system can hold paradoxical effects by masking the virtuous/vicious cycles of opportunities created by educational institutions. Second, we present recent research suggesting that selection practices relying on a meritocratic principle—more than other practices—can lead to biased academic decisions hindering disadvantaged students. We propose that inequalities in school might not just result from isolated failures in an otherwise functional meritocratic system, but rather that merit-based selection itself contributes to the perpetuation of inequalities at school

Correction: A proteome-wide immuno-mass spectrometric identification of serum autoantibodies (Clinical Proteomics (2019) 16 (25) DOI: 10.1186/s12014-019-9246-0)

In the original version of the article [1], an error was noticed under the heading "Immunoprecipitation on protein G magnetic beads" in "Methods" section. The unit symbol in the text that reads as "> 27 μl human" should read as "> 27 μg human". © 2019 The Author(s)

A proteome-wide immuno-mass spectrometric identification of serum autoantibodies

Background: Autoantibodies are produced when tolerance to self-antigens is broken and they can be mediators of tissue injury and systemic inflammation. They are excellent biomarkers because they are minimally invasive to screen and are highly abundant in serum due to limited proteolysis and slow clearance. Conventionally used methods of identifying autoantibodies in patient sera include indirect immunofluorescence, enzyme-linked immunoabsorbent assays (ELISAs) and protein microarrays. Here we present a novel proteome-wide immuno-mass spectrometric method to identify serum autoantibody targets. Methods: Serum samples from patients with inflammatory bowel disease (IBD) were analyzed by ELISA for the presence of autoantibodies to CUB and zona pellucida-like domain-containing protein 1 (CUZD1). Protein was extracted from the human pancreas as well as 16 other human tissues to make a complex tissue lysate protein mixture. Antibodies in patient sera were immobilized and purified on protein G magnetic beads and subsequently incubated with pancreatic lysate containing CUZD1 or the aforementioned complex tissue lysate. After extensive washing, antibody-bound protein antigens were trypsin-digested and identified using shotgun mass spectrometry. Results: The protocol was optimized for the immunoaffinity purification of autoantibody targets from tissue lysate, using CUZD1 from pancreatic lysate and anti-CUZD1 autoantibodies present in IBD patient serum as a proof-of-concept. Pancreatic secretory granule membrane major glycoprotein 2, whose autoantibodies are a known biomarker of Crohn's disease, was also immunoprecipitated from IBD patient serum, as an additional internal positive control. Conclusions: This study demonstrates the effectiveness of a proteomic approach to identify serum autoantibody targets, using immunoaffinity purification followed by tandem mass spectrometry. Our methodology is applicable for proteome-wide analysis of autoantibody targets in a wide variety of clinical settings. © 2019 The Author(s)

Proteomic Profiling of the Human Tissue and Biological Fluid Proteome

In-depth analysis of the human genome sequence has led to the annotation of approximately 20,000 human protein-coding genes. Although mass spectrometry (MS)-based workflows have made a great headway in achieving near genome-wide coverage, an equivalent complete map of the human proteome remains elusive. Delineating the spatial distribution of all human proteins at the organ, tissue, and cellular level can offer insight into health and disease and represents an excellent reference for the discovery of biomarkers and therapeutic targets. Here, we performed label-free liquid chromatography coupled to tandem MS (LC-MS/MS) to profile the normal human proteome. In total, we analyzed 117 samples from 46 normal tissues and organs at autopsy. Our high-resolution MS approach allowed for the quantification of 10,438 unique proteins. In order to expand our coverage of the human proteome, we combined our previously published biological fluid proteomic data from healthy individuals. We considered data from seven biological fluids, including urine, cerebrospinal fluid, synovial fluid, seminal plasma, sweat, cervical vaginal fluid, and nipple aspirate fluid. Overall, we generated tandem mass spectra corresponding to 13,028 unique human protein-coding genes. Although our analysis did not accomplish complete proteome coverage, it should be an important complementary resource for future biomarker discovery. © 2020 American Chemical Society