Standardized approach to proteome profiling of human serum based on magnetic bead separation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Building a rheumatology biobank for reliable basic/translational research and precision medicine

Research biobanks are non-profit structures that collect, manipulate, store, analyze and distribute systematically organized biological samples and data for research and development purposes. Over the recent years, we have established a biobank, the Rheumatology BioBank (RheumaBank) headed by the Medicine and Rheumatology unit of the IRCCS Istituto Ortopedico Rizzoli (IOR) in Bologna, Italy for the purpose of collecting, processing, storing, and distributing biological samples and associated data obtained from patients suffering from inflammatory joint diseases. RheumaBank is a research biobank, and its main objective is to promote large-scale, high-quality basic, translational, and clinical research studies that can help elucidate pathogenetic mechanisms and improve personalization of treatment choice in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and other spondyloarthritides (SpA).

Detection of viral antibodies in camel sera using magnetic particle spectroscopy

Pandemics like SARS-Cov-2 very frequently have their origin in different animals and in particular herds of camels could be a source of zoonotic diseases. This study took advantage on a highly sensitive and adaptable method for the fast and reliable detection of viral antibodies in camels using low-cost equipment. Magnetic nanoparticles (MNP) have high variability in their functionalization with different peptides and proteins. We confirm that 3-aminopropyl triethoxysilane (APTES)-coated MNP could be functionalized with viral proteins. The protein loading could be confirmed by simple loading controls using FACS-analysis (p < 0.05). Complementary combination of antigen and antibody yields in a significant signal increase could be proven by both FACS and COMPASS. However, COMPASS needs only a few seconds for the measurement. In COMPASS, the phase φ_n on selected critical point of the fifth higher harmonic (n = 5th). Here, positive sera display highly significant signal increase over the control or negative sera. Furthermore, a clear distinction could be made in antibody detection as an immune response to closely related viruses (SARS-CoV2 and MERS). Using modified MNPs along with COMPASS offers a fast and reliable method that is less cost intensive than current technologies and offers the possibility to be quickly adapted in case of new occurring viral infections. KEY POINTS: • COMPASS (critical offset magnetic particle spectroscopy) allows the fast detection of antibodies. • Magnetic nanoparticles can be adapted by exchange of the linked bait molecule. • Antibodies could be detected in camel sera without washing steps within seconds.

Novel serum proteomic biomarkers for early diagnosis and aggressive grade identification of prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most common tumors and the second leading cause of cancer-related death in men. The discovery of novel biomarkers for PCa diagnosis in the early stage, as well as discriminating aggressive PCa from non-aggressive PCa continue to pose a challenge. The aim of this study was to identify serum proteins that were sensitive and specific enough to detect early-stage and aggressive PCa.

METHODS

The serum proteomic profiling of patients with PCa and benign prostatic hyperplasia (BPH) was comprehensively analyzed using data-independent acquisition mass spectrometry (DIA-MS), and the bioinformatics analysis was performed. The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA) and immunoturbidimetry assay.

RESULTS

Statistically significant difference in abundance showed 56 DEPs between early-stage PCa and BPH and 47 DEPs between aggressive and non-aggressive PCa patients. In addition, the verification results showed that serum L-selectin concentration was significantly higher (p<0.05) in Gleason 6 PCa when compared with BPH, and the concentration of osteopontin (SPP1) and ceruloplasmin (CP) increased with higher Gleason score.

CONCLUSIONS

DIA-MS has great potential in cancer-related biomarker screening. Our data demonstrated that adding SPP1 and CP to PSA improved the separation of Gleason 7 (4 + 3) or above from Gleason 7 (3 + 4) or below compared with PSA diagnosis alone. Serum SPP1 and CP could be effective biomarkers to differentiate aggressive PCa (especially Gleason 7 (4 + 3) or above) from non-aggressive disease.

Metabolomics of Human Semen: A Review of Different Analytical Methods to Unravel Biomarkers for Male Fertility Disorders

Background: Human life without sperm is not possible. Therefore, it is alarming that the fertilizing ability of human spermatozoa is continuously decreasing. The reasons for that are widely unknown, but there is hope that metabolomics-based investigations may be able to contribute to overcoming this problem. This review summarizes the attempts made so far. Methods: We will discuss liquid chromatography–mass spectrometry (LC-MS), gas chromatography (GC), infrared (IR) and Raman as well as nuclear magnetic resonance (NMR) spectroscopy. Almost all available studies apply one of these methods. Results: Depending on the methodology used, different compounds can be detected, which is (in combination with sophisticated methods of bioinformatics) helpful to estimate the state of the sperm. Often, but not in all cases, there is a correlation with clinical parameters such as the sperm mobility. Conclusions: LC-MS detects the highest number of metabolites and can be considered as the method of choice. Unfortunately, the reproducibility of some studies is poor, and, thus, further improvements of the study designs are needed to overcome this problem. Additionally, a stronger focus on the biochemical consequences of the altered metabolite concentrations is also required.

Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer

BACKGROUND

Therapeutic response predictors like age, nodal status, and tumor grade and markers, like ER/PR, HER2, and Ki67, are not reliable in predicting the response to a specific form of chemotherapy. The current study aims to identify and validate reliable markers that can predict pathological complete response (pCR) in fluorouracil, epirubicin, and cyclophosphamide (FEC)-based neoadjuvant therapy with (NACT/RT) and without concurrent radiation (NACT).

MATERIALS AND METHODS

Tandem mass tag (TMT) quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed proteins from core needle breast biopsy between pCR (n = 4) and no-pCR (n = 4). Immunoblotting of shortlisted proteins with the tissue lysates confirmed the differential expression of the markers. Further, immunohistochemistry (IHC) was performed on formalin-fixed paraffin-embedded sections of treatment-naive core needle biopsies. In the NACT, 29 pCR and 130 no-pCR and in NACT/RT, 32 pCR and 71 no-pCR were used.

RESULTS

733 and 807 proteins were identified in NACT and NACT/RT groups, respectively. Ten proteins were shortlisted for validation as potential pCR-predictive markers. THBS1, TNC, and DCN were significantly overexpressed in no-pCR in both the groups. In NACT, CPA3 was significantly upregulated in the no-pCR. In NACT/RT, HnRNPAB was significantly upregulated and HMGB1 significantly downregulated in the no-pCR. HMGB1 was the only marker to show prognostic significance.

CONCLUSION

Quantitative proteomics followed by IHC identified and validated potential biomarkers for predicting patient response to therapy. These markers can be used, following larger-scale validation, in combination with routine histological analysis providing vital indications of treatment response.

MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

As antibiotics resistance on superbugs has risen, more and more studies have focused on developing rapid antibiotics susceptibility tests (AST). Meanwhile, identification of multiple antibiotics resistance on Staphylococcus aureus provides instant information which can assist clinicians in administrating the appropriate prescriptions. In recent years, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a powerful tool in clinical microbiology laboratories for the rapid identification of bacterial species. Yet, lack of study devoted on providing efficient methods to deal with the MS shifting problem, not to mention to providing tools incorporating the MALDI-TOF MS for the clinical use which deliver the instant administration of antibiotics to the clinicians. In this study, we developed a web tool, MDRSA, for the rapid identification of oxacillin-, clindamycin-, and erythromycin-resistant Staphylococcus aureus. Specifically, the kernel density estimation (KDE) was adopted to deal with the peak shifting problem, which is critical to analyze mass spectra data, and machine learning methods, including decision trees, random forests, and support vector machines, which were used to construct the classifiers to identify the antibiotic resistance. The areas under the receiver operating the characteristic curve attained 0.8 on the internal (10-fold cross validation) and external (independent testing) validation. The promising results can provide more confidence to apply these prediction models in the real world. Briefly, this study provides a web-based tool to provide rapid predictions for the resistance of antibiotics on Staphylococcus aureus based on the MALDI-TOF MS data. The web tool is available at: http://fdblab.csie.ncu.edu.tw/mdrsa/.

Establishing Classification Tree Models in Rheumatoid Arthritis Using Combination of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Magnetic Beads

Background: There is no simple method for early diagnosis and evaluation of rheumatoid arthritis (RA). This study aimed to determine potential biomarkers and establish diagnostic patterns for RA using proteomic fingerprint technology combined with magnetic beads.

Methods: The serum protein profiles of 97 RA patients and 76 healthy controls (HCs) were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) with weak cationic exchange (WCX) magnetic beads. Samples were randomly divided into training (83 RA patients and 56 HCs) and test sets (14 RA patients and 20 HCs). Patients were classified according to their Disease Activity Score: in remission, n = 28; with low disease activity, n = 17; with moderate disease activity, n = 21; with high disease activity, n = 31. There are 44 RA patients alone, 22 RA patients with interstitial lung disease (RA-ILD), 18 RA patients with secondary Sjögren's syndrome (RA-sSS), 6 RA patients with osteonecrosis of the femoral head (RA-ONFH), and 7 RA patients with other complications. Eleven patients were treated with etanercept only for half a year, after which their serum protein profiles were detected. The proteomic pattern was identified by Biomarker Patterns Software, and the potential biomarkers for RA diagnosis were further identified and quantified by enzyme-linked immunosorbent assay.

Results: The diagnostic pattern with four potential protein biomarkers, mass-to-charge (m/z) 3,448.85, 4,716.71, 8,214.29, and 10,645.10, could accurately recognize RA patients from HCs (specificity, 91.57%; sensitivity, 92.86%). The test set were correctly classified by this model (sensitivity, 95%; specificity, 100%). The components containing the four biomarkers were preliminarily retrieved through the ExPasy database, including the C-C motif chemokine 24 (CCL24), putative metallothionein (MT1DP), sarcolipin (SLN), and C-X-C motif chemokine 11 (CCXL11). Only the CCL24 level was detected to have a significant decrease in the serum of RA patients as compared with HCs (p < 0.05). No significant difference was found in others, but a decreasing trend consistent with the down-regulation of the four biomarkers detected by MALDI-TOF-MS was observed. The diagnostic models could effectively discriminate between RA alone and RA with complications (RA-ILD: m/z 10,645.10 and 12,595.86; RA-sSS: m/z 6,635.62 and 33,897.72; RA-ONFH: m/z 2,071.689). The classification model, including m/z 1,130.776, 1,501.065, 2,091.198, and 11,381.87, could distinguish between RA patients with disease activity and those in remission. RA with low disease activity could be efficiently discriminated from other disease activity patients by specific protein biomarkers (m/z 2,032.31, 2,506.214, and Z9286.495). Two biomarkers (m/z 2,032.31 and 4,716.71) were applied to build the classification model for RA patients with moderate and high disease activities. Biological markers for etanercept (m/z 2,671.604064, 5,801.840579, 8,130.195641, and 9,286.49499) were observed between the responder (n = 7) and non-responder groups (n = 4) (p < 0.05).

Conclusion: We successfully established a series of diagnostic models involving RA and RA with complications as well as assessed disease activity. Furthermore, we found that CCL24 may be a valuable auxiliary diagnostic indicator for RA. These results provide reference values for clinical practice in the future.

Protein Biomarkers in Uveitis

The diseases affecting the retina or uvea (iris, ciliary body, or choroid) generate changes in the biochemical or protein composition of ocular fluids/tissues due to disruption of blood-retinal barrier. Ocular infections and inflammations are sight-threatening diseases associated with various infectious and non-infectious etiologies. Several etiological entities cause uveitis, a complex intraocular inflammatory disease. These causes of uveitis differ in different populations due to geographical, racial, and socioeconomic variations. While clinical appearance is sufficiently diagnostic in many diseases, some of the uveitic entities manifest nonspecific or atypical clinical presentation. Identification of biomarkers in such diseases is an important aid in their diagnostic armamentarium. Different diseases and their different severity states release varying concentrations of proteins, which can serve as biomarkers. Proteomics is a high throughput technology and a powerful screening tool for serum biomarkers in various diseases that identifies proteins by mass spectrometry and helps to improve the understanding of pathogenesis of a disease. Proteins determine the biological state of a cell. Once identified as biomarkers, they serve as future diagnostic and pharmaceutical targets. With a potential to redirect the diagnosis of idiopathic uveitis, ocular proteomics provide a new insight into the pathophysiology and therapeutics of various ocular inflammatory diseases. Tears, aqueous and vitreous humor represent potential repositories for proteomic biomarkers discovery in uveitis. With an extensive proteomics work done on animal models of uveitis, various types of human uveitis are being subjected to proteome analysis for biomarker discovery in different ocular fluids (vitreous, aqueous, or tears).

Comparative evaluation of peptidome and microbiota in different types of saliva samples

Background

Clinical and research interest in salivary peptidome and microbiota is ever-growing owing to its great value for diagnosis, risk assessment and prediction of prognosis in oral and systemic diseases. Saliva can be stimulated for the purpose of rapid collection, but currently there are no studies systematically addressing the similarities and differences of salivary peptidome and microbiota in different types of samples. The purpose of this study was to investigate the variations of salivary peptidome and microbial profiles in response to different stimulating conditions.

Methods

Unstimulated saliva and three types of stimulated saliva samples (olfaction, gustation, and mastication stimulated saliva) were collected from 10 systematically and orally healthy donors. The peptidome profiles were detected by weak cation exchange magnetic beads and analyzed through matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF MS), while their microbial profiles were analyzed by 16S rDNA V3-V4 hypervariable region amplicon sequencing utilizing the Illumina MiSeq PE300 platform. The distance matrixes of salivary peptidome and microbial profiles were generated and the intra-individual distances were extracted, then the variations brought by different sampling conditions and repeated collections were compared.

Results

By comparisons of the overall salivary peptidome and microbial profiles, olfactory stimulation led to minimal variations comparing with that of unstimulated saliva, but appreciable variations were observed between saliva samples collected with gustatory/masticatory stimulation and unstimulated saliva. The three types of stimulated saliva exhibited significantly different peptidome and microbial profiles.

Conclusions

Stimulated saliva collected in response to olfactory stimulation is an appropriate alternative to unstimulated saliva, whereas gustatory/masticatory stimulation introduced appreciable variations. It is suggested that only one type of stimulating method should be used throughout one peptidome/microbiome research, which provides comprehensive insight into the optimization of sampling methods for salivaomic studies in the future.

The Influence of Blood Collection Tubes in Biomarkers' Screening by Mass Spectrometry

PURPOSE

Mass spectrometry is one of the rapidly developing bio-analytical techniques in recent years, and it shows that the results of biomarkers' screening can be influenced by pre-analytical process. The selection of the blood collection tubes is one of the most significant steps of pre-analytical process which is often neglected by researchers. So, it is urgent to define the influence of blood collection tubes clearly in biomarkers' screening.

EXPERIMENTAL DESIGN

Two types of blood collection tubes, non-additive tubes and coagulant activator tubes, are used to collect serum samples from patients and healthy controls. All samples are analyzed using matrix-assisted laser desorption ionization-time of flight mass spectrum in this study.

RESULTS

The serum protein profile changes while using coagulant tubes whether for patients or healthy controls. It is found that the effect of coagulant on serum protein of patients is smaller than that of control group. There are 27 significantly different peaks between the control group and the control coagulant group. However, between patient group and patient coagulant group, only one differential peak is obtained. Coagulant changes the expression differences between patients and healthy controls, making the differences expand, shrink or reverse, and most of the polypeptides are small molecule, which will change the results of biomarker's screening.

CONCLUSIONS AND CLINICAL RELEVANCE

This research suggested that different types of blood collection tubes would influence the final laboratory results. So it's important for clinicians to choose the proper tubes to detect biomarkers and make correct diagnoses.

Free cholesterol, cholesterol precursor and plant sterol levels in atherosclerotic plaques are independently associated with symptomatic advanced carotid artery stenosis

BACKGROUND AND AIMS

Circulating sterols result either from cholesterol (CH) synthesis or intestinal uptake. They are mainly esterified and can be oxygenated. Sterols accumulate in atherosclerotic plaques whereby their clinical impact is uncertain. Here, we determined associations between circulating and plaque sterol levels in patients with advanced carotid artery stenosis in respect to a prior ischemic event and statin treatment.

METHODS

Free and esterified CH, CH precursors and plant sterols as well as oxysterols were quantified by liquid chromatography-tandem mass spectrometry in 63 consecutive patients undergoing carotid endarterectomy.

RESULTS

CH, CH precursors, plant sterols and oxysterols accumulated in carotid artery plaques. Absolute circulating sterol levels were not predictive for their corresponding plaque levels. After normalisation to CH, plant sterol but not oxysterol levels correlated between plasma and plaques. Among the circulating sterols, oxysterols occurred proportionally less in plaques. Furthermore, CH and plant sterols were less esterified in plaques than in plasma. Patients who experienced a prior ischemic event (n = 29) and asymptomatic patients had, except for lanosterol, comparable circulating sterol levels. In contrast, the absolute plaque levels of free CH, CH precursors and plant sterols as well as oxysterols were increased in symptomatic compared to asymptomatic patients. These differences remained significant for free CH, precursors and 3 out of 4 analyzed plant sterols after adjustment to the most influencing covariates - statin treatment, type 2 diabetes and age.

CONCLUSIONS

Increased absolute plaque levels of free CH, precursors and plant sterols predict an ischemic event in patients with advanced carotid artery stenosis.

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

PURPOSE

Due to a lack of effective early diagnostic measures, new diagnostic methods for bacterial bloodstream infections (BSIs) are urgently needed. A protein-peptide profiling approach can be used to identify novel diagnostic biomarkers of BSIs.

EXPERIMENTAL DESIGN

In this study, MALDI-TOF MS and nano-LC/ESI-MS/MS are used to analyze serum peptides. In addition, GO and network analyses are conducted as a means of analyzing these potential protein markers. Finally, the potential biomarkers are verified in independent clinical samples via ELISA.

RESULTS

m/z 1533.8, 2794.3, 3597.3, 5007.3, and 7816.7 reveal an identical trend; the intensity of m/z 1533.8, 2794.3, and 3597.3 are higher in the infection group relative to controls, whereas the intensity of m/z 5007.3 and 7816.7 are lower in the infection group. Four peaks are successfully identified including ITIH4, KNG1, SAA2, and C3. GO and network analyses find these proteins to form an interaction network, which may be correlated with BSI. ELISA results indicate that ITIH4, KNG1, and SAA2 are effective in differentiating infected from normal control group and the febrile group.

CONCLUSIONS AND CLINICAL RELEVANCE

These biomarkers have the potential to offer new insights into the signaling networks underlying the development and progression of BSI.

Combined magnetic ligand fishing and high-resolution inhibition profiling for identification of α-glucosidase inhibitory ligands: A new screening approach based on complementary inhibition and affinity profiles

Plants are well-recognized sources of inhibitors for α-glucosidase - a key target enzyme for management of type 2 diabetes. Recently, two advanced bioactivity-profiling techniques, i.e., ligand fishing and high-resolution inhibition profiling, have shown great promises for accelerating identification of α-glucosidase inhibitors from complex plant extracts. Non-specific affinities and non-specific inhibitions are major sources of false positive hits from ligand fishing and high-resolution inhibition profiling, respectively. In an attempt to minimize such false positive hits, we describe a new screening approach based on ligand fishing and high-resolution inhibition profiling for detection of high-affinity ligands and assessment of inhibitory activity, respectively. The complementary nature of ligand fishing and high-resolution inhibition profiling was explored to identify α-glucosidase inhibitory ligands from a complex mixture, and proof-of-concept was demonstrated with crude ethyl acetate extract of Ginkgo biloba. In addition to magnetic beads with a 3-carbon aliphatic linker, α-glucosidase was immobilized on magnetic beads with a 21-carbon aliphatic linker; and the two different types of magnetic beads were compared for their hydrolytic activity and fishing efficiency.

Plasma Peptidome Pattern of Breast Cancer Using Magnetic Beads-Based Plasma Fractionation and MALDI-TOF MS: A Case Control Study in Egypt

Objective: The present study aimed to determine peptidome patterns in breast cancer (BC). Methods: We analyzed the plasma proteomic profiling of 80 BC patients and 50 healthy controls, using hydrophobic interaction chromatography magnetic beads (MB-HIC8) separation followed by Matrix assisted laser desorption ionization/ time of flight mass spectrometry (MALDI-TOF MS). Results: ClinProTools software identified 92 peaks that differed among the analyzed groups, 33 peaks were significantly different (P < 0.05). Of those, 22 peaks were up-regulated while 11 peaks were down-regulated in BC patients compared with the healthy controls. Three peptide ion signatures (m/z 1,570.31, 1,897.4 and 2,568.17) were provided by the Quick Classifier model to discriminate BC patients from healthy control subjects with 96.4% accuracy. External validation was performed by an independent group and this achieved a sensitivity of 100% and a specificity of 76.9%. Conclusion: MALDI-TOF MS has good analytical performance in distinguishing BC patients from healthy controls.

Selected reaction monitoring for colorectal cancer diagnosis using a set of five serum peptides identified by BLOTCHIP®-MS analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most predominant types of cancer, and it is the fourth most common cause of cancer-related death and it is important to diagnose CRC in early stage to decrease the mortality by CRC. In our previous study, we identified a combination of five peptides as a biomarker candidate to diagnose CRC by BLOTCHIP^®-MS analysis using a set of healthy control subjects and CRC patients (stage II-IV). The aim of the present study was to validate the serum biomarker peptides reported in our previous study using a second cohort and to establish their potential usefulness in CRC diagnosis.

METHODS

A total of 56 patients with CRC (n = 14 each of stages I-IV), 60 healthy controls, and 60 patients with colonic adenoma were included in this study. The five peptides were extracted and analyzed by selected reaction monitoring using ProtoKey^® Colorectal Cancer Risk Test Kit (Protosera, Inc., Amagasaki, Japan).

RESULTS

The results clearly showed that the four CRC groups, stages I-IV, could be sufficiently discriminated from the control group and colonic polyp group. This five-peptide set could identify CRC at each stage compared to the control population in this validation cohort, including those with early-stage disease. The AUC values for each stage of CRC compared to the control population were 0.779, 0.946, 0.852, and 0.973 for stages I, II, III, and IV, respectively.

CONCLUSIONS

In this case-control validation study, we confirmed high diagnostic performance for CRC using five peptides that were identified in our previous study as serum biomarker candidates for the detection of CRC.

Stability and reproducibility of proteomic profiles measured with an aptamer-based platform

The feasibility of SOMAscan, a multiplex, high sensitivity proteomics platform, for use in studies using archived plasma samples has not yet been assessed. We quantified 1,305 proteins from plasma samples donated by 16 Nurses’ Health Study (NHS) participants, 40 NHSII participants, and 12 local volunteers. We assessed assay reproducibility using coefficients of variation (CV) from duplicate samples and intra-class correlation coefficients (ICC) and Spearman correlation coefficients (r) of samples processed (i.e., centrifuged and aliquoted into separate components) immediately, 24, and 48 hours after collection, as well as those of samples collected from the same individuals 1 year apart. CVs were <20% for 99% of proteins overall and <10% for 92% of proteins in heparin samples compared to 66% for EDTA samples. We observed ICC or Spearman r (comparing immediate vs. 24-hour delayed processing) ≥0.75 for 61% of proteins, with some variation by anticoagulant (56% for heparin and 70% for EDTA) and protein class (ranging from 49% among kinases to 83% among hormones). Within-person stability over 1 year was good (ICC or Spearman r ≥ 0.4) for 91% of proteins. These results demonstrate the feasibility of SOMAscan for analyses of archived plasma samples.

Assessment by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry of the Effects of Preanalytical Variables on Serum Peptidome Profiles Following Long-Term Sample Storage

PURPOSE

Human serum and plasma are often used as clinical specimens in proteomics analyses, and peptidome profiling of human serum is a promising tool for identifying novel disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used for peptidomic biomarker discovery. Careful sample collection and handling are required as either can have a profound impact on serum peptidome patterns, yet the effects of preanalytical variables on serum peptidome profiles have not been completely elucidated. The present study investigated the effects of preanalytical variables, including storage temperature, duration (up to 12 months), and thawing methods, on MALDI-TOF MS-based serum peptidome patterns.

EXPERIMENTAL DESIGN

Aliquots of serum samples were pretreated with weak cation exchanger magnetic beads using an automated ClinProtRobot system and then analyzed by MALDI-TOF MS.

RESULTS

A number of significant differences in peak intensities were observed depending on sample processing variables.

CONCLUSIONS AND CLINICAL RELEVANCE

These peaks can be used as sample quality markers to assess the effects of long-term storage on serum peptidome profiles using MALDI-TOF MS.

Clinical validation of a blood-based classifier for diagnostic evaluation of asymptomatic individuals with pulmonary nodules

BACKGROUND

The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial.

METHODS

Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial.

RESULTS

A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p < 0.0001). CEA and CYFRA 21-1, two of the markers included in the PNC, also accurately distinguished malignant lesions from benign controls.

CONCLUSIONS

A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.

Chronological Profiling of Plasma Native Peptides after Hepatectomy in Pigs: Toward the Discovery of Human Biomarkers for Liver Regeneration

Liver regeneration after partial hepatectomy (PHx) is a time-dependent process, which is tightly regulated by multiple signaling cascades. Failure of this complex process leads to posthepatectomy liver failure (PHLF), which is associated with a high rate of mortality. Thus, it is extremely important to establish a useful biomarker of liver regeneration to help prevent PHLF. Here, we hypothesized that alterations in the plasma peptide profile may predict liver regeneration following PHx and hence we set up a diagnostic platform for monitoring posthepatectomy outcome. We chronologically analyzed plasma peptidomic profiles of 5 partially hepatectomized microminipigs using the ClinProt^TM system, which consists of magnetic beads and MALDI-TOF/TOF MS. We identified endogenous circulating peptides specific to each phase of the postoperative course after PHx in pigs. Notably, peptide fragments of histones were detected immediately after PHx; the presence of these fragments may trigger liver regeneration in the very acute phase after PHx. An N-terminal fragment of hemoglobin subunit α (3627 m/z) was detected as an acute-phase-specific peptide. In the recovery phase, the short N-terminal fragments of albumin (3028, 3042 m/z) were decreased, whereas the long N-terminal fragment of the protein (8926 m/z) was increased. To further validate and extract phase-specific biomarkers using plasma peptidome after PHx, plasma specimens of 4 patients who underwent PHx were analyzed using the same method as we applied to pigs. It revealed that there was also phase-specificity in peptide profiles, one of which was represented by a fragment of complement C4b (2378 m/z). The strategy described herein is highly efficient for the identification and characterization of peptide biomarkers of liver regeneration in a swine PHx model. This strategy is feasible for application to human biomarker studies and will yield clues for understanding liver regeneration in human clinical trials.

Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry‐based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta‐analyses guidelines. Twenty‐five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice.

Mesoporous silica chip: enabled peptide profiling as an effective platform for controlling bio-sample quality and optimizing handling procedure

Background

High quality clinical samples are critical for meaningful interpretation of data obtained in both basic and translational medicine. More specifically, optimized pre-analysis handling to bio-sample is crucial for avoiding biased analysis in a clinical setting. A universally applicable method for the evaluation of sample quality and pre-analysis handling is therefore in great demand.

Methods

The fingerprint pattern of low molecular weight (LMW) peptides in sera is directly associated with sample quality and handling process. Previous studies for enrichment/isolation of LMW peptides have shown that LMW peptides can be enriched by silica meso-porous material in a sensitive and high-throughput manner. Here, a peptide profile approach utilizing mesoporous silica chip-based sample preparation combined with MALDI MS analysis was used as a new platform for evaluation of bio-sample quality. Rat sera were selected as model sample and analyzed according to their LMW peptide fingerprint spectra.

Results

This novel method can complete the entire sample preparation procedure in a short period of time (<40 min), requires minimum amounts of sample (<10 µL), is of high sensitivity (LOD 10 ng/mL) as well as high reproducibility (CV% < 15%). According to the acquired LMW peptide spectra, we were able to distinguish the serum samples processed under different conditions (including different storage temperature, time, and freezing/thaw cycles) with the help of bioinformatics tools (principle composition analysis and significant difference analysis), and identify the samples that had significantly changed due to the inappropriate processing. Based on the percentage of significantly changed peaks in LMW peptide mass spectrum after handling, a judgment standard was established that can be used to evaluate the status of preservation of a biological sample. In addition, our principle study established recommendations for storage time, storage temperature and freeze/thaw conditions.

Conclusion

Our novel method for analysis of bio-samples allows for effective identification of variations in composition within samples, and provides a cost-effective tool for simple sample manipulation in a clinical setting.

Multicentric study of the effect of pre-analytical variables in the quality of plasma samples stored in biobanks using different complementary proteomic methods

Analytical proteomics has experienced exponential progress in the last decade and can be expected to lead research studies on diagnostic and therapeutic biomarkers in the near future. Because the development of this type of analysis requires the use of a large number of human samples with a minimum of quality requirements, our objective was to identify appropriate indicators for quality control of plasma samples stored in biobanks for research in proteomics. To accomplish this, plasma samples from 100 healthy donors were obtained and processed according to the pre-analytical variables of: a) time delay for the first centrifugation of the original blood sample (4 or 24h) and b) number of freeze/thaw cycles (1, 2 or 3) of the processed plasma samples. The analyses of samples were performed by different and complementary methods such as SPE MALDI-TOF, DIGE, shotgun (iTRAQ, nLC MALDI TOF/TOF) and targeted nLC MS/MS proteomic techniques (SRM). In general, because the distribution of proteins in all samples was found to be very similar, the results shown that delayed processing of blood samples and the number of freeze/thaw cycles has little or no effect on the integrity of proteins in the plasma samples.

SIGNIFICANCE

The results of the present work indicate that blood proteins in plasma are broadly insensitive to such preanalytical variables as delayed processing or freeze/thaw cycles when analyzed at the peptide level. Although there are other studies related to protein stability of clinical samples with similar results, what is remarkable about our work is the large number of plasma samples examined and that our analyses assessed protein integrity by combining a wide set of complementary proteomic approaches performed at different proteomic platform participating laboratories that all yielded similar results. We believe our study is the most comprehensive performed to date to determine the changes in proteins induced by delayed sample processing and plasma freeze/thaw cycles.

Salivary peptidome profiling for diagnosis of severe early childhood caries

BACKGROUND

Severe early childhood caries (s-ECC), which has quite high prevalence among children, is a widespread problem with significant impacts among both developing and developed countries. At present, it is widely known that no early detective techniques and diagnostic tests could have high sensitivity and specificity when using for clinical screening of s-ECC. In this study, we had applied magnetic bead (MB)-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to screen distinctive candidate biomarkers of this disease, so as to establish protein profiles and diagnostic models of s-ECC.

METHODS

Firstly, we used the technique mentioned above to detect specifically expressed peptides in saliva samples from ten children with s-ECC, separately at the time point of before, 1 and 4 weeks after dental treatment. Then a diagnostic model for s-ECC was established with the K nearest-neighbour method, which was validated in another six children in the next stage of study. After that, linear ion trap-orbitrap-mass spectrometry (LTQ-Orbitrap-MS) was performed to identify which of the proteins in saliva might be the origination of these peptides.

RESULTS

We found that seven peptide peaks were significantly different when comparing the three time points, among them two were higher, while other five were lower in the pre-treatment s-ECC group compared with post-treatment. The sensitivity and specificity of the diagnostic model we built were both 83.3 %. Two of these peptides were identified to be segments of histatin-1, which was one important secretory protein in saliva.

CONCLUSIONS

Hereby we confirmed that MB-based MALDI-TOF MS is an effective method for screening distinctive peptides from the saliva of junior patients with s-ECC, and histatin-1 may probably be one important candidate biomarker of this common dental disease. These findings might have bright prospect in future in establishing new diagnostic methods for s-ECC.

Identification of candidate biomarker mass (m/z) ranges in serous ovarian adenocarcinoma using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

OBJECTIVE

To differentiate plasma from ovarian cancer and healthy individuals using MALDI-TOF mass spectroscopy.

MATERIALS AND METHODS

MALDI-TOF was used to generate profiles of immuno-depleted plasma samples (89 cancers and 199 healthy individuals) that were fractionated using three types of magnetic beads (HIC8, WCX and IMAC-Cu).

RESULTS

Differentially expressed mass ranges showing >1.5-2-fold change in expression from HIC8 (30), WCX (12) and IMAC-Cu (6) fractions were identified. Cross validation and recognition capability scores for the models indicated discrimination between the classes.

CONCLUSIONS

Spectral profiles can differentiate plasma samples of ovarian cancer patients from healthy individuals.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Rapid Detection of Ricin in Serum Based on Cu-Chelated Magnetic Beads Using Mass Spectrometry

The protein toxin ricin obtained from castor bean plant (Ricinus communis) seeds is a potent biological warfare agent due to its ease of availability and acute toxicity. In this study, we demonstrated a rapid and simple method to detect ricin in serum in vitro. The ricin was mixed with serum and digested by trypsin, then all the peptides were efficiently extracted using Cu-chelated magnetic beads and were detected with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The specific ricin peptides were identified by Nanoscale Ultra Performance liquid chromatography coupled to tandem mass spectrometry according to their sequences. The assay required 2.5 hours, and a characteristic peptide could be detected down to 4 ng/μl and used as a biomarker to detect ricin in serum. The high sensitivity and simplicity of the procedure makes it valuable in clinical practice. Graphical Abstract ᅟ.

The application of fuzzy statistics and linear discriminant analysis as criteria for optimizing the preparation of plasma for matrix-assisted laser desorption/ionization mass spectrometry peptide profiling

An alternative bioinformatics approach based on fuzzy theory statistics and linear discriminant analysis is proposed for the interpretation of MALDI MS spectra in peptide profiling. When applied, the methodology enables the establishment of a reproducible plasma preparation protocol appropriate for the evaluation of small data sets. The samples were collected from pregnant women affected by gestational diabetes mellitus (GDM), n=18 and control group, n=13. The following pre-treatment sets were tested: pipette tips with C18 stationary phase (ZipTip, Millipore and Omix, Agilent) and magnetic bead-based weak cation exchange chromatography kit (MB WCX, Bruker Daltonics). The spectra were recorded using a MALDI TOF mass spectrometer (UltrafleXtreme, Bruker Daltonics) for a mass range of m/z from 1000 to 10,000. The significant features were selected using the wrapper selection method, and two classification systems were tested: discriminant analysis (DA) and fuzzy inference system (FIS). ClinProTools software was employed to compare the usefulness of the proposed methodology. The study showed that the optimum results for MS spectra were obtained after the use of the ZipTip as pre-treatment method in plasma preparation. Chemometric analysis allowed the differentiation of the GDM group from the control with a high degree of accuracy: 0.7333 (DA) and 0.8065 (FIS).

Biobanking for Personalized Medicine

A biobank is an entity that collects, processes, stores, and distributes biospecimens and relevant data for use in basic, translational, and clinical research. Biobanking of high-quality human biospecimens such as tissue, blood and other bodily fluids along with associated patient clinical information provides a fundamental scientific infrastructure for personalized medicine. Identification of biomarkers that are specifically associated with particular medical conditions such as cancer, cardiovascular disease and neurological disorders are useful for early detection, prevention, and treatment of the diseases. The ability to determine individual tumor biomarkers and to use those biomarkers for disease diagnosis, prognosis and prediction of response to therapy is having a very significant impact on personalized medicine and is rapidly changing the way clinical care is conducted. As a critical requirement for personalized medicine is the availability of a large collection of patient samples with well annotated patient clinical and pathological data, biobanks thus play an important role in personalized medicine advancement. The goal of this chapter is to explore the role of biobanks in personalized medicine and discuss specific needs regarding biobank development for translational and clinical research, especially for personalized medicine advancement.

Discovery of serum biomarkers of ovarian cancer using complementary proteomic profiling strategies

Purpose

Ovarian cancer is a devastating disease and biomarkers for its early diagnosis are urgently required. Serum may be a valuable source of biomarkers that may be revealed by proteomic profiling. Herein, complementary serum protein profiling strategies were employed for discovery of biomarkers that could discriminate cases of malignant and benign ovarian cancer.

Experimental design

Identically collected and processed serum samples from 22 cases of invasive epithelial ovarian cancer, 45 benign ovarian neoplasms, and 64 healthy volunteers were subjected to immunodepletion and protein equalization coupled to 2D‐DIGE/MS and multidimensional fractionation coupled to SELDI‐TOF profiling with MS/MS for protein identification. Selected candidates were verified by ELISA in samples from malignant (n = 70) and benign (n = 89) cases and combined marker panels tested against serum CA125.

Results

Both profiling platforms were complementary in identifying biomarker candidates, four of which (A1AT, SLPI, APOA4, VDBP) significantly discriminated malignant from benign cases. However, no combination of markers was as good as CA125 for diagnostic accuracy. SLPI was further tested as an early marker using prediagnosis serum samples. While it rose in cases toward diagnosis, it did not discriminate prediagnosis cases from controls.

Conclusions and clinical relevance

The candidate biomarkers warrant further validation in independent sample sets.

Shotgun proteome analysis of honeybee venom using targeted enrichment strategies

The aim of this study was to explore the honeybee venom proteome applying a shotgun proteomics approach using different enrichment strategies (combinatorial peptide ligand libraries and solid phase extraction). The studies were conducted using nano-LC/MALDI-TOF/TOF-MS system. The MS analysis of peptide profiles (in the range of 900-4500 Da) and virtual gel-image of proteins from Lab-on-Chip assay (in the range of 10-250 kDa) confirm that use of targeted enrichment strategies increase detection of honeybee venom components. The gel-free shotgun strategy and sophisticated instrumentation led to a significant increase of the sensitivity and higher number of identified peptides in honeybee venom samples, comparing with the current literature. Moreover, 11 of 12 known honeybee venom allergens were acknowledged and 4 new, so far uncharacterized proteins were identified. In addition, similarity searches were performed in order to investigate biological relations and homology between newly identified proteins sequences from Apis mellifera and other Hymenoptera.

Comparative serum proteomic analysis of serum diagnosis proteins of colorectal cancer based on magnetic bead separation and maldi-tof mass spectrometry

BACKGROUND

At present, the diagnosis of colorectal cancer (CRC) requires a colorectal biopsy which is an invasive procedure. We undertook this pilot study to develop an alternative method and potential new biomarkers for diagnosis, and validated a set of well-integrated tools called ClinProt to investigate the serum peptidome in CRC patients.

METHODS

Fasting blood samples from 67 patients diagnosed with CRC by histological diagnosis, 55 patients diagnosed with colorectal adenoma by biopsy, and 65 healthy volunteers were collected. Division was into a model construction group and an external validation group randomly. The present work focused on serum proteomic analysis of model construction group by ClinProt Kit combined with mass spectrometry. This approach allowed construction of a peptide pattern able to differentiate the studied populations. An external validation group was used to verify the diagnostic capability of the peptidome pattern blindly. An immunoassay method was used to determine serum CEA of CRC and controls.

RESULTS

The results showed 59 differential peptide peaks in CRC, colorectal adenoma and health volunteers. A genetic algorithm was used to set up the classification models. Four of the identified peaks at m/z 797, 810, 4078 and 5343 were used to construct peptidome patterns, achieving an accuracy of 100% (> CEA, P < 0. 05). Furthermore, the peptidome patterns could differentiate the validation group with high accuracy close to 100%.

CONCLUSIONS

Our results showed that proteomic analysis of serum with MALDI-TOF MS is a fast and reproducible approach, which may provide a novel approach to screening for CRC.

A proteomics approach to the identification of plasma biomarkers for latent tuberculosis infection

A proteomic analysis was performed to screen the potential latent tuberculosis infection (LTBI) biomarkers. A training set of spectra was used to generate diagnostic models, and a blind testing set was used to determine the accuracy of the models. Candidate peptides were identified using nano-liquid chromatography-electrospray ionization–tandem mass spectrometry. Based on the training set results, 3 diagnostic models recognized LTBI subjects with good cross-validation accuracy. In the blind testing set, LTBI subjects could be identified with sensitivities and specificities of 85.20% to 88.90% and 85.7% to 100%, respectively. Additionally, 14 potential LTBI biomarkers were identified, and all proteins were identified for the first time through proteomics in the plasma of healthy, latently infected individuals. In all, proteomic pattern analyses can increase the accuracy of LTBI diagnosis, and the data presented here provide novel insights into potential mechanisms involved in LTBI.

Identification alpha-2-HS-glycoprotein precursor and tubulin beta chain as serology diagnosis biomarker of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient. Hence, the need for simple blood tests that could be used for the early detection is crucial for its ultimate control and prevention.

METHODS

The present work is a case-control study focused on proteomic analysis of serum of healthy volunteers and CRC patients by the ClinProt profiling technology based on mass spectrometry. This approach allowed to identifying a pattern of proteins/peptides able to differentiate the studied populations. Moreover, some of peptides differentially expressed in the serum of patients as compared to healthy volunteers were identified by LTQ Orbitrap XL.

RESULTS

A Quick Classifier Algorithm was used to construct the peptidome patterns (m/z 1208, 1467, 1505, 1618, 1656 and 4215) for the identification of CRC from healthy volunteers with accuracy close to 100% (>CEA, P < 0.05). Peaks at m/z 1505 and 1618 were identified as alpha-2-HS-glycoprotein precursor and tubulin beta chain, respectively.

CONCLUSIONS

Alpha-2-HS-glycoprotein precursor and tubulin beta chain could be involved in the pathogenesis of CRC and perform as potential serology diagnosis biomarker.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4796578761089186.

The value of total protein in guiding management of infectious parapneumonic effusion by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND/PURPOSE

Infectious parapneumonic effusion (PE) contains proteins originating from circulation as well as proteins locally released by inflammatory pulmonary cells. The purpose of this study was to investigate the value of total protein analysis in guiding management of infectious PE by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

METHODS

Fifty-seven children with pneumonia followed by PE were consecutively enrolled into our study. Protein profiles generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry after fractionating samples with functionalized magnetic beads (C8) were used for differentiating complicated PE (CPE) from non-CPE. A training set was used to generate classification models and the clinical efficacy of these models in detecting CPE and the need for intervention was then evaluated in an independent set.

RESULTS

The MS spectra derived from PE were analyzed, and classification models were constructed in the training set. A total of 123 mass/charge (m/z) values were identified and 23 m/z values which were significant with p < 0.05 were used as classifiers. An optimized genetic algorithm model containing enforced selection of three significant downregulated m/z values (2127, 2232, and 2427) was able to classify CPE with 100% positive predictive value and predict the need of aggressive therapeutic intervention with 77% positive predictive value.

CONCLUSION

A diagnostic model construction comprising three potential biomarkers can predict CPE and need for surgical intervention rapidly and precisely. Pleural fluid proteins downregulated during the progression of pneumonia could potentially guide the management of infectious PE.

Urinary peptide profiling to differentiate between minimal change disease and focal segmental glomerulosclerosis

BACKGROUND

Minimal change disease (MCD) and primary focal segmental glomerulosclerosis (FSGS) are the main causes of primary idiopathic nephrotic syndrome in children and adults, with diagnosis being essential for the appropriate choice of therapy and requiring renal biopsy. However, the presence of only normal glomeruli on renal biopsy of FSGS patients may lead to the misclassification of these patients as having MCD. The aim of this study was to (i) compare the peptide profile of MCD and FSGS patients with that of a group of healthy subjects, (ii) generate and validate a class prediction model to classify MCD and FSGS patients and (ii) identify candidate biomarkers of these glomerular entities by analysis of the urinary peptidome.

METHODS

The urinary peptide profile was analyzed by magnetic bead-based technology combined with MALDI-TOF mass spectrometry in 44 patients diagnosed of MCD (n = 22) and FSGS (n = 22). The resulting spectra were compiled and analyzed using ClinProTools software.

RESULTS

A class prediction model was developed to differentiate MCD and FSGS patients. The validation of this model correctly classified 81.8% (9/11) of MCD patients and 72.7% (8/11) of FSGS patients. Moreover, the signal with m/z 1913.60, identified as a fragment of uromodulin, and the signal with m/z 2392.54, identified as a fragment of alpha-1-antitrypsin, showed higher and lower peak areas, respectively, in FSGS patients compared with MCD patients.

CONCLUSIONS

The simple, non-invasive technique described in the present study may be a useful tool to help clinicians by confirming diagnoses achieved by renal biopsy, thereby reducing misdiagnoses and avoiding the implementation of inappropriate therapies.

Optimization and evaluation of magnetic bead separation combined with matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy (MALDI-TOF MS) for proteins profiling of peritoneal dialysis effluent

Peritoneal dialysis effluent (PDE) potentially carries an archive of peptides relevant to pathological processes in abdominal and surrounding tissues. Magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is one such approach that offers a unique tool for profiling of peptides, but this approach has not been used in the PDE analysis. In this study, we developed a strategy for screening PDE proteins <15 kDa and applied this technique to identify potential biomarkers for peritonitis. We examined four kinds of magnetic beads, including a carbon series (C3, C8), weak cation exchange (WCX) and immobilized metal-affinity chromatography (IMAC-Cu) beads. Samples processed with IMAC-Cu magnetic beads consistently showed more MS signals across all beads within the measured mass range. Moreover, there was no difference in the number and morphology of MS signals between concentrated and unconcentrated samples. The PDE peptidome pattern, based on a panel of 15 peaks, accurately recognized peritonitis PD patients from peritonitis-free patients with sensitivity of 90.5% and specificity of 94.7% respectively. Therefore, IMAC-Cu magnetic beads and unconcentrated samples can be used as a fast and cost-effective approach for sample preparation prior to more in-depth discovery of predictive biomarkers of disease in patients on dialysis.

The procurement, storage, and quality assurance of frozen blood and tissue biospecimens in pathology, biorepository, and biobank settings

Well preserved frozen biospecimens are ideal for evaluating the genome, transcriptome, and proteome. While papers reviewing individual aspects of frozen biospecimens are available, we present a current overview of experimental data regarding procurement, storage, and quality assurance that can inform the handling of frozen biospecimens. Frozen biospecimen degradation can be influenced by factors independent of the collection methodology including tissue type, premortem agonal changes, and warm ischemia time during surgery. Rapid stabilization of tissues by snap freezing immediately can mitigate artifactually altered gene expression and, less appreciated, protein phosphorylation profiles. Collection protocols may be adjusted for specific tissue types as cellular ischemia tolerance varies widely. If data is not available for a particular tissue type, a practical goal is snap freezing within 20min. Tolerance for freeze-thaw events is also tissue type dependent. Tissue storage at -80°C can preserve DNA and protein for years but RNA can show degradation at 5years. For -80°C freezers, aliquots frozen in RNAlater or similar RNA stabilizing solutions are a consideration. It remains unresolved as to whether storage at -150°C provides significant advantages relative to that at -80°C. Histologic quality assurance of tissue biospecimens is typically performed at the time of surgery but should also be conducted on the aliquot to be distributed because of tissue heterogeneity. Biobanking protocols for blood and its components are highly dependent on intended use and multiple collection tube types may be needed. Additional quality assurance testing should be dictated by the anticipated downstream applications.

A practical approach to clinical and research biobanking

Powerful technologies critical to personalized medicine and targeted therapeutics require the analysis of carefully validated, procured, stored, and managed biospecimens. Reflecting advancements in biospecimen science, the National Cancer Institute and the International Society for Biological and Environmental Repositories are periodically publishing best practices that can guide the biobanker. The modern biobank will operate more like a clinical laboratory with formal accreditation, standard operating procedures, and quality assurance protocols. This chapter highlights practical issues of consent, procurement, storage, quality assurance, disbursement, funding, and space. Common topics of concern are discussed including the differences between clinical and research biospecimens, stabilization of biospecimens during procurement, optimal storage temperatures, and technical validation of biospecimen content and quality. With quickly expanding biospecimen needs and limited healthcare budgets, biobanks may need to be selective as to what is stored. Furthermore, a shift to room-temperature storage modalities where possible can reduce long-term space and fiscal requirements.