Time evolution of kallikrein 6 (A) and S100B levels (B), in ng/mL, for patient 2.

<p>Time evolution of kallikrein 6 (A) and S100B levels (B), in ng/mL, for patient 2.</p

Kallikrein 6 as a Serum Prognostic Marker in Patients with Aneurysmal Subarachnoid Hemorrhage

<div><h3>Background</h3><p>Aneurysmal subarachnoid hemorrhage (aSAH) is a devastating condition that frequently causes death or significant disabilities. Blood tests to predict possible early complications could be very useful aids for therapy. The aim of this study was to analyze serum levels of kallikrein 6 (KLK6) in individuals with aSAH to determine the relevance of this protease with the outcome of these patients.</p> <h3>Methodology/Principal Findings</h3><p>A reference interval for KLK6 was established by using serum samples (n = 136) from an adult population. Additionally, serum samples (n = 326) from patients with aSAH (n = 13) were collected for 5 to 14 days, to study the concentration of KLK6 in this disease. The correlation between KLK6 and S100B, an existing brain damage biomarker, was analyzed in 8 of 13 patients. The reference interval for KLK6 was established to be 1.04 to 3.93 ng/mL. The mean levels in patients with aSAH within the first 56 hours ranged from 0.27 to 1.44 ng/mL, with lowest levels found in patients with worse outcome. There were significant differences between patients with good recovery or moderate disability (n = 8) and patients with severe disability or death (n = 5) (mean values of 1.03 ng/mL versus 0.47 ng/mL, respectively) (p<0.01). There was no significant correlation between KLK6 and S100B.</p> <h3>Conclusions/Significance</h3><p>Decreased serum concentrations of KLK6 are found in patients with aSAH, with the lowest levels in patients who died.</p> </div

Time evolution of kallikrein 6 (A) and S100B levels (B), in ng/mL, for patient 12.

<p>The dashed line represents the lower reference limit of kallikrein 6 (1.04 ng/mL).</p

Box and Whisker diagram of serum kallikrein 6 levels (ng/mL) in patients with subarachnoid hemorrhage (n = 13), within the first 56 hours.

<p>The number of samples for each patient varies from 5 to 8.</p

Time evolution of kallikrein 6 (A) and S100B levels (B), in ng/mL, for patient 6.

<p>Time evolution of kallikrein 6 (A) and S100B levels (B), in ng/mL, for patient 6.</p

Integrating Meta-Analysis of Microarray Data and Targeted Proteomics for Biomarker Identification: Application in Breast Cancer

The development of signature biomarkers has gained considerable attention in the past decade. Although the most well-known examples of biomarker panels stem from gene expression studies, proteomic panels are becoming more relevant, with the advent of targeted mass spectrometry-based methodologies. At the same time, the development of multigene prognostic classifiers for early stage breast cancer patients has resulted in a wealth of publicly available gene expression data from thousands of breast cancer specimens. In the present study, we integrated transcriptome and proteome-based platforms to identify genes and proteins related to patient survival. Candidate biomarker proteins have been identified in a previously generated breast cancer tissue extract proteome. A mass-spectrometry-based assay was then developed for the simultaneous quantification of these 20 proteins in breast cancer tissue extracts. We quantified the relative expression levels of the 20 potential biomarkers in a cohort of 96 tissue samples from patients with early stage breast cancer. We identified two proteins, KPNA2 and CDK1, which showed potential to discriminate between estrogen receptor positive patients of high and low risk of disease recurrence. The role of these proteins in breast cancer prognosis warrants further investigation

Development of a Multiplex Selected Reaction Monitoring Assay for Quantification of Biochemical Markers of Down Syndrome in Amniotic Fluid Samples

Down syndrome (DS) is one of the most common chromosomal abnormalities affecting about 1 of every 700 fetuses. Current screening strategies have detection rates of 90–95% at a 5% false positive rate. The aim of this study was to discover new biomarkers of DS in amniotic fluid by using a multiplex selected reaction monitoring assay. Nine proteins were analyzed: CEL, CPA1, MUC13, CLCA1, MUC5AC, PLUNC, and HAPLN1, and CGB as positive control and serotransferrin as negative control. One proteotypic peptide for each protein was selected, and internal heavy isotope-labeled peptide standards were spiked into the samples. Fifty-four samples from pregnant women carrying normal (<i>n</i> = 37) or DS-affected (<i>n</i> = 17) fetuses were analyzed. The median protein concentrations for DS and normal samples, respectively, were as follows: 20 and 49 ng/mL (<i>p</i> < 0.01) for CEL; 3.7 and 14 ng/mL (<i>p</i> < 0.001) for CPA1; 80 and 263 ng/mL (<i>p</i> < 0.001) for MUC13; 46 and 135 ng/mL (<i>p</i> < 0.001) for CLCA1; 0.65 and 0.93 μg/mL (<i>p</i> < 0.05) for MUC5AC; 61 and 73 ng/mL (<i>p</i> > 0.05) for PLUNC; 144 and 86 ng/mL (<i>p</i> < 0.01) for HAPLN1; 0.89 and 0.54 μg/mL (<i>p</i> = 0.05) for CGB; 91 and 87 μg/mL (<i>p</i> > 0.05) for serotransferrin. Statistically significant differences were found in six out of the seven candidate proteins analyzed, reflecting a different regulation in DS

Analysis of Seminal Plasma from Patients with Non-obstructive Azoospermia and Identification of Candidate Biomarkers of Male Infertility

Infertility affects approximately 15% of couples with equivalent male and female contribution. Absence of sperm in semen, referred to as azoospermia, accounts for 5–20% of male infertility cases and can result from pretesticular azoospermia, non-obstructive azoospermia (NOA), and obstructive azoospermia (OA). The current clinical methods of differentiating NOA cases from OA ones are indeterminate and often require surgical intervention for a conclusive diagnosis. We catalogued 2048 proteins in seminal plasma from men presented with NOA. Using spectral-counting, we compared the NOA proteome to our previously published proteomes of fertile control men and postvasectomy (PV) men and identified proteins at differential abundance levels among these clinical groups. To verify spectral counting ratios for candidate proteins, extracted ion current (XIC) intensities were also used to calculate abundance ratios. The Pearson correlation coefficient between spectral counting and XIC ratios for the Control–NOA and NOA–PV data sets is 0.83 and 0.80, respectively. Proteins that showed inconsistent spectral counting and XIC ratios were removed from analysis. There are 34 proteins elevated in Control relative to NOA, 18 decreased in Control relative to NOA, 59 elevated in NOA relative to PV, and 16 decreased in NOA relative to PV. Many of these proteins have expression in the testis and the epididymis and are linked to fertility. Some of these proteins may be useful as noninvasive biomarkers in discriminating NOA cases from OA

Analysis of Seminal Plasma from Patients with Non-obstructive Azoospermia and Identification of Candidate Biomarkers of Male Infertility

Infertility affects approximately 15% of couples with equivalent male and female contribution. Absence of sperm in semen, referred to as azoospermia, accounts for 5–20% of male infertility cases and can result from pretesticular azoospermia, non-obstructive azoospermia (NOA), and obstructive azoospermia (OA). The current clinical methods of differentiating NOA cases from OA ones are indeterminate and often require surgical intervention for a conclusive diagnosis. We catalogued 2048 proteins in seminal plasma from men presented with NOA. Using spectral-counting, we compared the NOA proteome to our previously published proteomes of fertile control men and postvasectomy (PV) men and identified proteins at differential abundance levels among these clinical groups. To verify spectral counting ratios for candidate proteins, extracted ion current (XIC) intensities were also used to calculate abundance ratios. The Pearson correlation coefficient between spectral counting and XIC ratios for the Control–NOA and NOA–PV data sets is 0.83 and 0.80, respectively. Proteins that showed inconsistent spectral counting and XIC ratios were removed from analysis. There are 34 proteins elevated in Control relative to NOA, 18 decreased in Control relative to NOA, 59 elevated in NOA relative to PV, and 16 decreased in NOA relative to PV. Many of these proteins have expression in the testis and the epididymis and are linked to fertility. Some of these proteins may be useful as noninvasive biomarkers in discriminating NOA cases from OA

Analysis of Seminal Plasma from Patients with Non-obstructive Azoospermia and Identification of Candidate Biomarkers of Male Infertility

Infertility affects approximately 15% of couples with equivalent male and female contribution. Absence of sperm in semen, referred to as azoospermia, accounts for 5–20% of male infertility cases and can result from pretesticular azoospermia, non-obstructive azoospermia (NOA), and obstructive azoospermia (OA). The current clinical methods of differentiating NOA cases from OA ones are indeterminate and often require surgical intervention for a conclusive diagnosis. We catalogued 2048 proteins in seminal plasma from men presented with NOA. Using spectral-counting, we compared the NOA proteome to our previously published proteomes of fertile control men and postvasectomy (PV) men and identified proteins at differential abundance levels among these clinical groups. To verify spectral counting ratios for candidate proteins, extracted ion current (XIC) intensities were also used to calculate abundance ratios. The Pearson correlation coefficient between spectral counting and XIC ratios for the Control–NOA and NOA–PV data sets is 0.83 and 0.80, respectively. Proteins that showed inconsistent spectral counting and XIC ratios were removed from analysis. There are 34 proteins elevated in Control relative to NOA, 18 decreased in Control relative to NOA, 59 elevated in NOA relative to PV, and 16 decreased in NOA relative to PV. Many of these proteins have expression in the testis and the epididymis and are linked to fertility. Some of these proteins may be useful as noninvasive biomarkers in discriminating NOA cases from OA