Optical Fiber Ball Resonator Sensor Spectral Interrogation through Undersampled KLT: Application to Refractive Index Sensing and Cancer Biomarker Biosensing.

Optical fiber ball resonators based on single-mode fibers in the infrared range are an emerging technology for refractive index sensing and biosensing. These devices are easy and rapid to fabricate using a CO2 laser splicer and yield a very low finesse reflection spectrum with a quasi-random pattern. In addition, they can be functionalized for biosensing by using a thin-film sputtering method. A common problem of this type of device is that the spectral response is substantially unknown, and poorly correlated with the size and shape of the spherical device. In this work, we propose a detection method based on Karhunen-Loeve transform (KLT), applied to the undersampled spectrum measured by an optical backscatter reflectometer. We show that this method correctly detects the response of the ball resonator in any working condition, without prior knowledge of the sensor under interrogation. First, this method for refractive index sensing of a gold-coated resonator is applied, showing 1594 RIU-1 sensitivity; then, this concept is extended to a biofunctionalized ball resonator, detecting CD44 cancer biomarker concentration with a picomolar-level limit of detection (19.7 pM) and high specificity (30-41%).

Ethical principles, opportunities and constraints in clinical proteomics.

Recent advances in MS-based proteomics have vastly increased the quality and scope of biological information that can be derived from human samples. These advances have rendered current workflows increasingly applicable in biomedical and clinical contexts. As proteomics is poised to take an important role in the clinic, associated ethical responsibilities increase in tandem with the impact on the health, privacy, and well-being of individuals. Here we conducted and report a systematic literature review of ethical issues in clinical proteomics. We add our perspectives from a background of bioethics, the results of our accompanying paper extracting individual-sensitive results from patient samples, and the literature addressing similar issues in genomics. The spectrum of potential issues ranges from patient re-identification to incidental findings of clinical significance. The latter can be divided into actionable and unactionable findings. Some of these have the potential to be employed in discriminatory or privacy-infringing ways. However, incidental findings may also have great positive potential. A plasma proteome profile, for instance, could inform on the general health or disease status of an individual regardless of the narrow diagnostic question that prompted it. We suggest that early discussion of ethical issues in clinical proteomics is important to ensure that eventual regulations reflect the considered judgment of the community as well as to anticipate opportunities and problems that may arise as the technology matures further.

Global Proteome and Phosphoproteome Characterization of Sepsis-induced Kidney Injury.

Sepsis-induced acute kidney injury (S-AKI) is the most common complication in hospitalized and critically ill patients, highlighted by a rapid decline of kidney function occurring a few hours or days after sepsis onset. Systemic inflammation elicited by microbial infections is believed to lead to kidney damage under immunocompromised conditions. However, although AKI has been recognized as a disease with long-term sequelae, partly because of the associated higher risk of chronic kidney disease (CKD), the understanding of kidney pathophysiology at the molecular level and the global view of dynamic regulations in situ after S-AKI, including the transition to CKD, remains limited. Existing studies of S-AKI mainly focus on deriving sepsis biomarkers from body fluids. In the present study, we constructed a mid-severity septic murine model using cecal ligation and puncture (CLP), and examined the temporal changes to the kidney proteome and phosphoproteome at day 2 and day 7 after CLP surgery, corresponding to S-AKI and the transition to CKD, respectively, by employing an ultrafast and economical filter-based sample processing method combined with the label-free quantitation approach. Collectively, we identified 2,119 proteins and 2950 phosphosites through multi-proteomics analyses. Among them, we identified an array of highly promising candidate marker proteins indicative of disease onset and progression accompanied by immunoblot validations, and further denoted the pathways that are specifically responsive to S-AKI and its transition to CKD, which include regulation of cell metabolism regulation, oxidative stress, and energy consumption in the diseased kidneys. Our data can serve as an enriched resource for the identification of mechanisms and biomarkers for sepsis-induced kidney diseases.

A Mouse Brain-based Multi-omics Integrative Approach Reveals Potential Blood Biomarkers for Ischemic Stroke.

Stroke remains a leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures in the hyper-acute phase of ischemic stroke is still a primary interest for translational research on stroke diagnosis, prognosis, and treatment. Data integration from high-throughput -omics techniques has become crucial to unraveling key interactions among different molecular elements in complex biological contexts, such as ischemic stroke. Thus, we used advanced data integration methods for a multi-level joint analysis of transcriptomics and proteomics data sets obtained from mouse brains at 2 h after cerebral ischemia. By modeling net-like correlation structures, we identified an integrated network of genes and proteins that are differentially expressed at a very early stage after stroke. We validated 10 of these deregulated elements in acute stroke, and changes in their expression pattern over time after cerebral ischemia were described. Of these, CLDN20, GADD45G, RGS2, BAG5, and CTNND2 were next evaluated as blood biomarkers of cerebral ischemia in mice and human blood samples, which were obtained from stroke patients and patients presenting stroke-mimicking conditions. Our findings indicate that CTNND2 levels in blood might potentially be useful for distinguishing ischemic strokes from stroke-mimicking conditions in the hyper-acute phase of the disease. Furthermore, circulating GADD45G content within the first 6 h after stroke could also play a key role in predicting poor outcomes in stroke patients. For the first time, we have used an integrative biostatistical approach to elucidate key molecules in the initial stages of stroke pathophysiology and highlight new notable molecules that might be further considered as blood biomarkers of ischemic stroke.

Sialylation of Asparagine 612 Inhibits Aconitase Activity during Mouse Sperm Capacitation; a Possible Mechanism for the Switch from Oxidative Phosphorylation to Glycolysis.

After ejaculation, mammalian spermatozoa must undergo a process known as capacitation in order to successfully fertilize the oocyte. Several post-translational modifications occur during capacitation, including sialylation, which despite being limited to a few proteins, seems to be essential for proper sperm-oocyte interaction. Regardless of its importance, to date, no single study has ever identified nor quantified which glycoproteins bearing terminal sialic acid (Sia) are altered during capacitation. Here we characterize sialylation during mouse sperm capacitation. Using tandem MS coupled with liquid chromatography (LC-MS/MS), we found 142 nonreductant peptides, with 9 of them showing potential modifications on their sialylated oligosaccharides during capacitation. As such, N-linked sialoglycopeptides from C4b-binding protein, endothelial lipase (EL), serine proteases 39 and 52, testis-expressed protein 101 and zonadhesin were reduced following capacitation. In contrast, mitochondrial aconitate hydratase (aconitase; ACO2), a TCA cycle enzyme, was the only protein to show an increase in Sia content during capacitation. Interestingly, although the loss of Sia within EL (N62) was accompanied by a reduction in its phospholipase A1 activity, a decrease in the activity of ACO2 (i.e. stereospecific isomerization of citrate to isocitrate) occurred when sialylation increased (N612). The latter was confirmed by N612D recombinant protein tagged with both His and GFP. The replacement of Sia for the negatively charged Aspartic acid in the N612D mutant caused complete loss of aconitase activity compared with the WT. Computer modeling show that N612 sits atop the catalytic site of ACO2. The introduction of Sia causes a large conformational change in the alpha helix, essentially, distorting the active site, leading to complete loss of function. These findings suggest that the switch from oxidative phosphorylation, over to glycolysis that occurs during capacitation may come about through sialylation of ACO2.

Accurate MS-based Rab10 Phosphorylation Stoichiometry Determination as Readout for LRRK2 Activity in Parkinson's Disease.

Pathogenic mutations in the Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson's disease (PD). They increase its activity, resulting in augmented Rab10-Thr73 phosphorylation and conversely, LRRK2 inhibition decreases pRab10 levels. Currently, there is no assay to quantify pRab10 levels for drug target engagement or patient stratification. To meet this challenge, we developed an high accuracy and sensitivity targeted mass spectrometry (MS)-based assay for determining Rab10-Thr73 phosphorylation stoichiometry in human samples. It uses synthetic stable isotope-labeled (SIL) analogues for both phosphorylated and nonphosphorylated tryptic peptides surrounding Rab10-Thr73 to directly derive the percentage of Rab10 phosphorylation from attomole amounts of the endogenous phosphopeptide. The SIL and the endogenous phosphopeptides are separately admitted into an Orbitrap analyzer with the appropriate injection times. We test the reproducibility of our assay by determining Rab10-Thr73 phosphorylation stoichiometry in neutrophils of LRRK2 mutation carriers before and after LRRK2 inhibition. Compared with healthy controls, the PD predisposing mutation carriers LRRK2 G2019S and VPS35 D620N display 1.9-fold and 3.7-fold increased pRab10 levels, respectively. Our generic MS-based assay further establishes the relevance of pRab10 as a prognostic PD marker and is a powerful tool for determining LRRK2 inhibitor efficacy and for stratifying PD patients for LRRK2 inhibitor treatment.

Concentration Determination of >200 Proteins in Dried Blood Spots for Biomarker Discovery and Validation.

The use of protein biomarkers as surrogates for clinical endpoints requires extensive multilevel validation including development of robust and sensitive assays for precise measurement of protein concentration. Multiple reaction monitoring (MRM) is a well-established mass-spectrometric method that can be used for reproducible protein-concentration measurements in biological specimens collected via microsampling. The dried blood spot (DBS) microsampling technique can be performed non-invasively without the expertise of a phlebotomist, and can enhance analyte stability which facilitate the application of this technique in retrospective studies while providing lower storage and shipping costs, because cold-chain logistics can be eliminated. Thus, precise, sensitive, and multiplexed methods for measuring protein concentrations in DBSs can be used for de novo biomarker discovery and for biomarker quantification or verification experiments. To achieve this goal, MRM assays were developed for multiplexed concentration measurement of proteins in DBSs.The lower limit of quantification (LLOQ) was found to have a median total coefficient of variation (CV) of 18% for 245 proteins, whereas the median LLOQ was 5 fmol of peptide injected on column, and the median inter-day CV over 4 days for measuring endogenous protein concentration was 8%. The majority (88%) of the assays displayed parallelism, whereas the peptide standards remained stable throughout the assay workflow and after exposure to multiple freeze-thaw cycles. For 190 proteins, the measured protein concentrations remained stable in DBS stored at ambient laboratory temperature for up to 2 months. Finally, the developed assays were used to measure the concentration ranges for 200 proteins in twenty same sex, same race and age matched individuals.

Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping.

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

Immune Signature Against Plasmodium falciparum Antigens Predicts Clinical Immunity in Distinct Malaria Endemic Communities.

A large body of evidence supports the role of antibodies directed against the Plasmodium spp. parasite in the development of naturally acquired immunity to malaria, however an antigen signature capable of predicting protective immunity against Plasmodium remains to be identified. Key challenges for the identification of a predictive immune signature include the high dimensionality of data produced by high-throughput technologies and the limitation of standard statistical tests in accounting for synergetic interactions between immune responses to multiple targets. In this study, using samples collected from young children in Ghana at multiple time points during a longitudinal study, we adapted a predictive modeling framework which combines feature selection and machine learning techniques to identify an antigen signature of clinical immunity to malaria. Our results show that an individual's immune status can be accurately predicted by measuring antibody responses to a small defined set of 15 target antigens. We further demonstrate that the identified immune signature is highly versatile and capable of providing precise and accurate estimates of clinical protection from malaria in an independent geographic community. Our findings pave the way for the development of a robust point-of-care test to identify individuals at high risk of disease and which could be applied to monitor the impact of vaccinations and other interventions. This approach could be also translated to biomarker discovery for other infectious diseases.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases.

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

Domain-specific Quantification of Prion Protein in Cerebrospinal Fluid by Targeted Mass Spectrometry.

Therapies currently in preclinical development for prion disease seek to lower prion protein (PrP) expression in the brain. Trials of such therapies are likely to rely on quantification of PrP in cerebrospinal fluid (CSF) as a pharmacodynamic biomarker and possibly as a trial endpoint. Studies using PrP ELISA kits have shown that CSF PrP is lowered in the symptomatic phase of disease, a potential confounder for reading out the effect of PrP-lowering drugs in symptomatic patients. Because misfolding or proteolytic cleavage could potentially render PrP invisible to ELISA even if its concentration were constant or increasing in disease, we sought to establish an orthogonal method for CSF PrP quantification. We developed a multi-species targeted mass spectrometry method based on multiple reaction monitoring (MRM) of nine PrP tryptic peptides quantified relative to an isotopically labeled recombinant protein standard for human samples, or isotopically labeled synthetic peptides for nonhuman species. Analytical validation experiments showed process replicate coefficients of variation below 15%, good dilution linearity and recovery, and suitable performance for both CSF and brain homogenate and across humans as well as preclinical species of interest. In n = 55 CSF samples from individuals referred to prion surveillance centers with rapidly progressive dementia, all six human PrP peptides, spanning the N- and C-terminal domains of PrP, were uniformly reduced in prion disease cases compared with individuals with nonprion diagnoses. Thus, lowered CSF PrP concentration in prion disease is a genuine result of the disease process and not an artifact of ELISA-based measurement. As a result, dose-finding studies for PrP lowering drugs may need to be conducted in presymptomatic at-risk individuals rather than in symptomatic patients. We provide a targeted mass spectrometry-based method suitable for preclinical quantification of CSF PrP as a tool for drug development.

Analysis of Endogenous Peptides Released from Osteoarthritic Cartilage Unravels Novel Pathogenic Markers.

Osteoarthritis (OA) is a pathology characterized by the loss of articular cartilage. In this study, we performed a peptidomic strategy to identify endogenous peptides (neopeptides) that are released from human osteoarthritic tissue, which may serve as disease markers. With this aim, secretomes of osteoarthritic and healthy articular cartilages obtained from knee and hip were analyzed by shotgun peptidomics. This discovery step led to the identification of 1175 different peptides, corresponding to 101 proteins, as products of the physiological or pathological turnover of cartilage extracellular matrix. Then, a targeted multiple reaction monitoring-mass spectrometry method was developed to quantify the panel of best marker candidates on a larger set of samples (n = 62). Statistical analyses were performed to evaluate the significance of the observed differences and the ability of the neopeptides to classify the tissue. Eight of them were differentially abundant in the media from wounded zones of OA cartilage compared with the healthy tissue (p < 0.05). Three neopeptides belonging to Clusterin and one from Cartilage Oligomeric Matrix Protein showed a disease-dependent decrease specifically in hip OA, whereas two from Prolargin (PRELP) and one from Cartilage Intermediate Layer Protein 1 were significantly increased in samples from knee OA. The release of one peptide from PRELP showed the best metrics for tissue classification (AUC = 0.834). The present study reveals specific neopeptides that are differentially released from knee or hip human osteoarthritic cartilage compared with healthy tissue. This evidences the intervention of characteristic pathogenic pathways in OA and provides a novel panel of peptidic candidates for biomarker development.

Identification of Serum Biomarkers for Systemic Lupus Erythematosus Using a Library of Phage Displayed Random Peptides and Deep Sequencing.

Systemic lupus erythematosus (SLE) is one of the most serious autoimmune diseases, characterized by highly diverse clinical manifestations. A biomarker is still needed for accurate diagnostics. SLE serum autoantibodies were discovered and validated using serum samples from independent sample cohorts encompassing 306 participants divided into three groups, i.e. healthy, SLE patients, and other autoimmune-related diseases. To discover biomarkers for SLE, a phage displayed random peptide library (Ph.D. 12) and deep sequencing were applied to screen specific autoantibodies in a total of 100 serum samples from 50 SLE patients and 50 healthy controls. A statistical analysis protocol was set up for the identification of peptides as potential biomarkers. For validation, 10 peptides were analyzed using enzyme-linked immunosorbent assays (ELISA). As a result, four peptides (SLE2018Val001, SLE2018Val002, SLE2018Val006, and SLE2018Val008) were discovered with high diagnostic power to differentiate SLE patients from healthy controls. Among them, two peptides, i.e. SLE2018Val001 and SLE2018Val002, were confirmed between SLE with other autoimmune patients. The procedure we established could be easily adopted for the identification of autoantibodies as biomarkers for many other diseases.

Proteomic Profiling of Paired Interstitial Fluids Reveals Dysregulated Pathways and Salivary NID1 as a Biomarker of Oral Cavity Squamous Cell Carcinoma.

Patients with oral cavity squamous cell carcinoma (OSCC) are frequently first diagnosed at an advanced stage, leading to poor prognosis and high mortality rates. Early detection of OSCC using body fluid-accessible biomarkers may improve the prognosis and survival rate of OSCC patients. As tumor interstitial fluid is a proximal fluid enriched with cancer-related proteins, it is a useful reservoir suitable for the discovery of cancer biomarkers and dysregulated biological pathways in tumor microenvironments. Thus, paired interstitial fluids of tumor (TIF) and adjacent noncancerous (NIF) tissues from 10 OSCC patients were harvested and analyzed using one-dimensional gel electrophoresis coupled with liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Using label-free spectral counting-based quantification, 113 proteins were found to be up-regulated in the TIFs compared with the NIFs. The gene set enrichment analysis (GSEA) revealed that the differentially expressed TIF proteins were highly associated with aminoacyl tRNA biosynthesis pathway. The elevated levels of 4 proteins (IARS, KARS, WARS, and YARS) involved in the aminoacyl tRNA biosynthesis were verified in the OSCC tissues with immunohistochemistry (IHC). In addition, nidogen-1 (NID1) was selected for verification as an OSCC biomarker. Salivary level of NID1 in OSCC patients (n = 48) was significantly higher than that in the healthy individuals (n = 51) and subjects with oral potentially malignant disorder (OPMD; n = 53). IHC analysis showed that NID1 level in OSCC tissues was increased compared with adjacent noncancerous epithelium (n = 222). Importantly, the elevated NID1 level was correlated with the advanced stages of OSCC, as well as the poor survival of OSCC patients. Collectively, the results suggested that TIF analysis facilitates understanding of the OSCC microenvironment and that salivary NID1 may be a useful biomarker for OSCC.

Identification of Salivary Biomarkers for Oral Cancer Detection with Untargeted and Targeted Quantitative Proteomics Approaches.

Oral cavity squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. In Taiwan, OSCC is the fifth leading cause of cancer-related mortality and leads to 2800 deaths per year. The poor outcome of OSCC patients is principally ascribed to the fact that this disease is often advanced at the time of diagnosis, suggesting that early detection of OSCC is urgently needed. Analysis of cancer-related body fluids is one promising approach to identify biomarker candidates of cancers. To identify OSCC biomarkers, salivary proteomes of OSCC patients, individuals with oral potentially malignant disorders (OPMDs), and healthy volunteers were comparatively profiled with isobaric tags for relative and absolute quantitation (iTRAQ)-based mass spectrometry (MS). The salivary levels of 67 and 18 proteins in the OSCC group are elevated and decreased compared with that in the noncancerous group (OPMD and healthy groups), respectively. The candidate biomarkers were further selected using the multiple reaction monitoring (MRM)-MS and validated with the immunoassays. More importantly, the higher salivary level of three proteins, complement factor H (CFH), fibrinogen alpha chain (FGA), and alpha-1-antitrypsin (SERPINA1) was correlated with advanced stages of OSCC. Our results indicate that analysis of salivary proteome is a feasible strategy for biomarker discovery, and the three proteins are potential salivary markers for OSCC diagnosis.

Microvesicle Proteomic Profiling of Uterine Liquid Biopsy for Ovarian Cancer Early Detection.

High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.

High-density Peptide Arrays Help to Identify Linear Immunogenic B-cell Epitopes in Individuals Naturally Exposed to Malaria Infection.

High-density peptide arrays are an excellent means to profile anti-plasmodial antibody responses. Different protein intrinsic epitopes can be distinguished, and additional insights are gained, when compared with assays involving the full-length protein. Distinct reactivities to specific epitopes within one protein may explain differences in published results, regarding immunity or susceptibility to malaria. We pursued three approaches to find specific epitopes within important plasmodial proteins, (1) twelve leading vaccine candidates were mapped as overlapping 15-mer peptides, (2) a bioinformatical approach served to predict immunogenic malaria epitopes which were subsequently validated in the assay, and (3) randomly selected peptides from the malaria proteome were screened as a control. Several peptide array replicas were prepared, employing particle-based laser printing, and were used to screen 27 serum samples from a malaria-endemic area in Burkina Faso, West Africa. The immunological status of the individuals was classified as "protected" or "unprotected" based on clinical symptoms, parasite density, and age. The vaccine candidate screening approach resulted in significant hits in all twelve proteins and allowed us (1) to verify many known immunogenic structures, (2) to map B-cell epitopes across the entire sequence of each antigen and (3) to uncover novel immunogenic epitopes. Predicting immunogenic regions in the proteome of the human malaria parasite Plasmodium falciparum, via the bioinformatics approach and subsequent array screening, confirmed known immunogenic sequences, such as in the leading malaria vaccine candidate CSP and discovered immunogenic epitopes derived from hypothetical or unknown proteins.

Stable-protein Pair Analysis as A Novel Strategy to Identify Proteomic Signatures: Application To Seminal Plasma From Infertile Patients.

Our aim was to define seminal plasma proteome signatures of infertile patients categorized according to their seminal parameters using TMT-LC-MS/MS. To that extent, quantitative proteomic data was analyzed following two complementary strategies: (1) the conventional approach based on standard statistical analyses of relative protein quantification values; and (2) a novel strategy focused on establishing stable-protein pairs. By conventional analyses, the abundance of some seminal plasma proteins was found to be positively correlated with sperm concentration. However, this correlation was not found for all the peptides within a specific protein, bringing to light the high heterogeneity existing in the seminal plasma proteome because of both the proteolytic fragments and/or the post-translational modifications. This issue was overcome by conducting the novel stable-protein pairs analysis proposed herein. A total of 182 correlations comprising 24 different proteins were identified in the normozoospermic-control population, whereas this proportion was drastically reduced in infertile patients with altered seminal parameters (18 in patients with reduced sperm motility, 0 in patients with low sperm concentration and 3 in patients with no sperm in the ejaculate). These results suggest the existence of multiple etiologies causing the same alteration in seminal parameters. Additionally, the repetition of the stable-protein pair analysis in the control group by adding the data from a single patient at a time enabled to identify alterations in the stable-protein pairs profile of individual patients with altered seminal parameters. These results suggest potential underlying pathogenic mechanisms in individual infertile patients, and might open up a window to its application in the personalized diagnostic of male infertility.

Evaluation of Serum Glycoprotein Biomarker Candidates for Detection of Esophageal Adenocarcinoma and Surveillance of Barrett's Esophagus.

Esophageal adenocarcinoma (EAC) is thought to develop from asymptomatic Barrett's esophagus (BE) with a low annual rate of conversion. Current endoscopy surveillance of BE patients is probably not cost-effective. Previously, we discovered serum glycoprotein biomarker candidates which could discriminate BE patients from EAC. Here, we aimed to validate candidate serum glycoprotein biomarkers in independent cohorts, and to develop a biomarker candidate panel for BE surveillance. Serum glycoprotein biomarker candidates were measured in 301 serum samples collected from Australia (4 states) and the United States (1 clinic) using previously established lectin magnetic bead array (LeMBA) coupled multiple reaction monitoring mass spectrometry (MRM-MS) tier 3 assay. The area under receiver operating characteristic curve (AUROC) was calculated as a measure of discrimination, and multivariate recursive partitioning was used to formulate a multi-marker panel for BE surveillance. Complement C9 (C9), gelsolin (GSN), serum paraoxonase/arylesterase 1 (PON1) and serum paraoxonase/lactonase 3 (PON3) were validated as diagnostic glycoprotein biomarkers in lectin pull-down samples for EAC across both cohorts. A panel of 10 serum glycoprotein biomarker candidates discriminated BE patients not requiring intervention (BE± low grade dysplasia) from those requiring intervention (BE with high grade dysplasia (BE-HGD) or EAC) with an AUROC value of 0.93. Tissue expression of C9 was found to be induced in BE, dysplastic BE and EAC. In longitudinal samples from subjects that have progressed toward EAC, levels of serum C9 were significantly (p < 0.05) increased with disease progression in EPHA (erythroagglutinin from Phaseolus vulgaris) and NPL (Narcissus pseudonarcissus lectin) pull-down samples. The results confirm alteration of complement pathway glycoproteins during BE-EAC pathogenesis. Further prospective clinical validation of the confirmed biomarker candidates in a large cohort is warranted, prior to development of a first-line BE surveillance blood test.

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants.

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses.