Weak Cation Exchange Magnetic Beads Research Articles

Combining serum peptide signatures with International Federation of Gynecology and Obstetrics (FIGO) risk score to predict the outcomes of patients with gestational trophoblastic neoplasia (GTN) after first-line chemotherapy.

Gestational trophoblastic neoplasia (GTN) is a group of clinically rare tumors that develop in the uterus from placental tissue. Currently, its satisfactory curability derives from the timely and accurately classification and refined management for patients. This study aimed to discover biomarkers that could predict the outcomes of GTN patients after first-line chemotherapy. A total of 65 GTN patients were included in the study. Patients were divided into the good or poor outcome group and the clinical characteristics of the patients in the two groups were compared. Furthermore, the serum peptide profiles of all patients were uncovered by using weak cation exchange magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Feature peaks were identified by three machine learning algorithms and then models were constructed and compared using five machine learning methods. Additionally, liquid chromatography mass spectrometry was used to identify the feature peptides. Multivariate logistic regression analysis showed that the International Federation of Gynecology and Obstetrics (FIGO) risk score was associated with poor outcomes. Eight feature peaks (m/z =1287, 2042, 2862, 2932, 2950, 3240, 3277 and 6626) were selected for model construction and validation by the three algorithms. Based on the panel combining FIGO risk score and peptide serum signatures, the neural network (nnet) model showed promising performance in both the training (AUC=0.9635) and validation (AUC=0.8788) cohorts. Peaks at m/z 2042, 2862, 2932, 3240 were identified as the partial sequences of transthyretin, fibrinogen alpha chain (FGA), beta-globin and FGA, respectively. We combined FIGO risk score and serum peptide signatures using the nnet method to construct the model which can accurately predict outcome of GTN patients after first-line chemotherapy. With this model, patients can be further classified and managed, and those with poor predicted outcomes can be given more attention for developing treatment failure.

Levels of inter-alpha-trypsin inhibitor heavy chain H4 urinary polypeptide in gestational diabetes mellitus

ABSTRACT Gestational diabetes mellitus (GDM) can cause a variety of adverse maternal and fetal complications. The purpose of this study was to screen and identify the urinary polypeptides related to the severity of GDM and to analyze the correlation between urinary peptide levels and neonatal metabolic indices. A total of 31 normal pregnant women (N group) and 74 patients with GDM (GDM group) were randomly selected between February 2018 and August 2019. Patients with GDM were divided into two groups according to their fasting plasma glucose (FPG) levels. The urine samples were enriched using weak cation-exchange magnetic beads (MB-WCX), and eight different urine polypeptides were screened and analyzed. The peptide spectra were obtained using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). The urinary peptide signatures of the two groups were compared using the BioExplorer software. The difference analysis of the eight urinary polypeptides between the normal pregnant (N) group and GDM group showed that two polypeptides with mass-to- charge ratios (m/z) of 2175.7 and 2318.8, respectively, were significantly different between the two groups (P < 0.01). The m/z 2175.7 polypeptide was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS), and the corresponding name of the molecule was inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4). The changes in ITIH4 levels correlated with those in the neonatal metabolic indices. By establishing the Fisher discriminant function equation for the GDM group, the difference in sample distribution and mean value of the two groups could be observed directly. Abbreviations: GDM: gestational diabetes mellitus; FPG: fasting plasma glucose; MB-WCX: weak cation exchange magnetic beads; MALDI-TOF MS: matrix-assisted laser desorption ionization time-of-flight mass spectrometry; m/z: mass charge ratio; LC-MS: liquid chromatography-tandem mass spectrometry; glycosylated hemoglobin (HbA1c); PPG: postprandial plasma glucose; ITIH4: inter-alpha-trypsin inhibitor heavy chain H4; IR: insulin resistance; NFPG: neonatal fasting plasma glucose; NH: neonatal height; NW: neonatal weight; BMI: body mass index; RPL: recurrent pregnancy loss; OGTT: oral glucose tolerance test; ADA: American Diabetes Association; LIS: Laboratory Information System

Identification of urinary peptides associated with allergic rhinitis

BackgroundWhether in the world or in China, allergic rhinitis (AR) is a disease that seriously affects people's daily life. However, the current diagnostic methods for AR still have certain limitations. Adopt matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for proteomics detection makes it possible to screen for high-throughput biomarkers. This study intends to use this technology to analyze the urine proteomics of AR patients to find potential biomarkers for AR diagnosis. Materials and methodsUrine and clinical data were collected from 60 patients with AR and 60 healthy controls. MALDI-TOF-MS based on weak cation exchange magnetic beads was used to obtain and analyze the urine peptide profiles between AR patients and healthy controls. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic ability of identified peptides and proteins. ResultsThe results revealed significantly different expressions of nine peptide peaks between AR and healthy controls (ROC area under the curve [AUC], 0.660–0.780). We constructed a diagnostic model containing seven proteins identified from the above-mentioned peptide peaks. The AUC of the seven peptides panel for AR diagnosis was 0.882 with 75.0% sensitivity and 90.0% specificity. ConclusionsThe seven peptides diagnostic model established in this study had high specificity and moderate sensitivity in the diagnosis of AR. MALDI-TOF MS is a potential tool for diagnosing AR by the use of urine samples.

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.

Urinary Peptides Associated Closely with Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is a common disease of pregnant women, which has a higher incidence in recent years. The purpose of this study is to explore urinary biomarkers that could predict and monitor gestational diabetes mellitus (GDM). Urine samples from 30 normal pregnant women and 78 GDM patients were collected and purified by weak cationic exchange magnetic beads (MB-WCX), then analyzed by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS). The urinary peptide signatures of the two groups were compared by BioExplorer software. The potential ability of the differently expressed peptides to distinguish GDM patients from normal pregnant women was evaluated by receiver operating characteristic (ROC) analysis. At last, the differently expressed peptides were identified by liquid chromatography tandem mass spectrometry (LC-MS). There were four differently expressed peptides (m/z 1000.5, 1117.5, 1142.9, and 2022.9) between two groups, which were identified as fragments of urinary albumin, α2-macroglobulin, human hemopexin, and α1-microglobulin, respectively. The diagnostic efficacy of m/z 1142.9 was better than the other peptides. The area under the curve (AUC) of the m/z 1142.9 was 0.690 (95% CI: 0.583-0.796). The discovery of urinary polypeptides provides the possibility for the early prediction of GDM and the monitoring of glucose metabolism in GDM patients by a noninvasive method.

Novel serum peptide model revealed by MALDI-TOF-MS and its diagnostic value in early bladder cancer.

Bladder cancer is the ninth most common cancer worldwide and has high morbidity and mortality. We aimed to search for potential serum peptide biomarkers and establish a diagnostic model for early bladder cancer. A total of 67 bladder cancer patients and 64 healthy volunteers were randomly divided into a training set and testing set 1. There were 30 hematuria patients used as testing set 2. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on weak cation exchange magnetic beads was used to obtain and analyze the serum peptide profiles between bladder cancer patients and healthy volunteers in the training set. Serum peptide diagnostic model through a k-nearest neighbor algorithm, was established and validated, and significantly differentially expressed protein biomarkers were ultimately identified. We constructed a diagnostic model containing five peptides (m/z 1954.9, m/z 2081.0, m/z 3938.3, m/z 3946.5, and m/z 4268.8). In the training set, the area under the curve (AUC) value of the five-peptide model was 0.923, and the sensitivity and specificity was 93.75% and 96.77%, respectively. In testing set 1, the sensitivity and specificity was 91.43% and 90.91%, respectively, and the specificity of testing set 2 was 73.33%. For early-stage bladder cancer, the sensitivity and specificity was 92.31% and 93.75%, respectively; the sensitivity of early low-grade bladder cancer was 90.00%; and the AUC value was 0.944. The five-peptide diagnostic model established in this study had high sensitivity and specificity, especially in the diagnosis of early bladder cancer, and could differentiate between healthy volunteers and hematuria patients.

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

BackgroundClinical 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.MethodsUnstimulated 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.ResultsBy 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.ConclusionsStimulated 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.

Screening and analysis of small molecular peptides in urine of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common clinical disease with complicated clinical process and harmful effects on pregnant women and fetus. The purpose of this study is to use the convenient urine samples in combination with glucose levels to detect or predict GDM. In this study, urine samples of non-pregnant women, normal pregnant women and GDM patients were collected. The peptides in urine were enriched by weak cationic exchange magnetic beads (MB-WCX) and analyzed by matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). 46 polypeptide peaks with statistical difference (P < 0.01) were screened out by using Bioexplorer analysis software. The level of molecules with mass-to-charge ratio of 1079.2, 1290.6 and 1500.7 was higher in the GDM group than the other two groups. Through the analysis of differential molecules by liquid chromatography tandem mass spectrometry (LC-MS), the above molecules were identified as coagulation factor IX, TBC1 family member 5 isoform a [Homo sapiens] (TBC1D5a) and immunoglobulin kappa constant. The discovery of polypeptides provides the research basis for further primary screening and assistant diagnosis of GDM through urine samples.

The Urinary Peptidome as a Noninvasive Biomarker Development Strategy for Prenatal Screening of Down's Syndrome.

Prenatal screening for Down's syndrome based on maternal age, ultrasound measures, and maternal serum biomarkers is recommended worldwide, but the false-positive rate and poor diagnostic performance of these screening tests remain problematic. Genetic analysis of cell-free DNA in maternal blood has been developed as a new prenatal screening for Down's syndrome, but it has a number of limitations, including turnaround time and cost. Prenatal screening diagnostic innovation calls for new tests that are noninvasive, accurate, and affordable. We report original observations on potential peptide biomarkers in maternal urine for screening of fetal Down's syndrome. The peptidome of urine samples from 23 pregnant women carrying Down's syndrome fetuses and 30 pregnant women carrying fetuses with normal karyotype was fractionated by weak cation exchange magnetic beads and analyzed by MALDI-TOF mass spectrometry. Levels of six peptides (m/z 1022.1, 1032.1, 1099.5, 1155.9, 1306.6, and 2365.6) were significantly altered between the case and control groups after controlling for maternal and gestational age. A classification model was constructed based on these candidate peptides that could differentiate fetuses with Down's syndrome from controls with a sensitivity of 95.7%, a specificity of 70.0%, and an area under receiver operating characteristic curves of 0.909 (95% confidence interval, 0.835-0.984). Peptide peaks at m/z 1099.5 and 1155.9 were identified as the partial sequences of alpha-1-antitrypsin and heat shock protein beta-1, respectively. These new findings support the new idea that maternal urinary peptidome offers prospects for noninvasive biomarker discovery and development for the prenatal screening of fetal Down's syndrome.

Toward Candidate Proteomic Biomarkers in Clinical Monitoring of Acute Promyelocytic Leukemia Treatment with Arsenic Trioxide

The introduction of arsenic trioxide (ATO) in treatment of acute promyelocytic leukemia (APL) has resulted in high clinical complete remission (CR) rates over 90%. On the contrary, the risk for early death (ED) in APL patients treated with ATO continues to have a negative impact for optimization of APL therapeutics. There is an urgent need for precision medicine and biomarkers in clinical monitoring of ATO toxicity in APL, and ED in particular. This retrospective case series cohort proteomics study was conducted as a hypothesis generation effort and provides here several potential molecular leads on serum peptides expressed at different times after treatment with ATO in patients with APL. In 12 patients with a de novo APL diagnosis, and treated with single-agent ATO as frontline remission induction therapy, serum peptides were fractionated by weak cation exchange magnetic beads and analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Ten peptides (m/z 2075.5, 2084.2, 2203.0, 2265.2, 2872.8, 2916.6, 3145.2, 3153.4, 3953.4, and 3964.8) were significantly downregulated in serum after ATO treatment. Among them, four peptides were identified as (1) Immunoglobulin heavy chain V-III region BUT, (2) RRP15-like protein, (3) filaggrin, and (4) protein SON isoform F. To the best of our knowledge, this is the first clinical oncology proteomic biomarker study with a view to future rational therapeutic monitoring of patients with APL in the course of single-agent ATO treatment and hematological CR.

Identification of newly developed advanced schistosomiasis with MALDI-TOF mass spectrometry and ClinProTools analysis.

Cases of newly developed advanced schistosomiasis (NDAS) have occurred in areas where schistosomiasis transmission has been blocked for more than 25 years. The causes and pathogenesis of NDAS are still unknown. Diagnosis of NDAS relies on historical investigation and clinical symptoms, such as liver fibrosis, hepatic ascites and abnormal biochemical indexes in serum. It is important but difficult at this stage to develop a new tool for early screening and rapid diagnosis. In this study, serum peptides from thirty patients with NDAS and thirty healthy controls were captured with weak cation exchange magnetic beads, and subjected to MALDI-TOF mass spectrometry and ClinProTools analysis. Eleven peaks with m/z 924, 2661, 2953, 2991, 3241, 3884, 5337, 5905, 5943, 7766 and 9289 were decreased and three peaks with m/z 1945, 2082 and 4282 were increased in the NDAS group. The proteomic detection pattern (PDP) was established with 14 different peptide peaks, and its sensitivity and specificity were investigated with a blind test. The peptide mass fingerprints of sera from 50 NDAS patients and 100 healthy controls were double-blind subjected to the PDP method, and 50 patients and 92 healthy controls were classified as NDAS and healthy separately, which showed 100% sensitivity and 92% specificity. Our results showed that the PDP could be a new and useful method to detect NDAS.

Identification of salivary peptidomic biomarkers in chronic kidney disease patients undergoing haemodialysis

BackgroundChronic kidney disease (CKD) is a worldwide public health problem. To detect discriminating salivary peptide profiles between CKD patients undergoing haemodialysis (HD) and healthy controls (HCs) and to screen candidate biomarkers for CKD, we preliminarily explored the diagnostic potentiality of saliva. MethodsSaliva samples from 30 CKD HD patients and 35 HCs were analysed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with weak cation exchange magnetic beads. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was performed to identify the potential biomarkers. ResultsThe HD group showed higher salivary pH. We chose 3 significantly different (p < 0.01) peptides to establish an effective discrimination model which was validated by a decision tree and ROC curve. Statistically significant correlations (p < 0.05) between the candidate salivary peptidomic biomarkers and serum parameters were found. Eight differentially expressed peptides were identified as segments of Histatin-1, Mucin-7, salivary acidic proline-rich phosphoprotein 1/2 (aPRP 1/2), submaxillary gland androgen-regulated protein 3B, and Histatin-3. ConclusionsOur findings substantiate the pivotal role of peptidomic methods in identifying biomarkers for CKD. Histatin-1, Mucin-7 and aPRP 1/2 are expected to be candidate salivary biomarkers of CKD HD patients. Furthermore, saliva might be a promising non-invasive diagnostic biofluid.

Detection and Identification of Serum Peptides Biomarker in Papillary Thyroid Cancer.

BackgroundPapillary thyroid cancer (PTC) is currently the most commonly diagnosed endocrine malignancy. In addition, the sex- and age-adjusted incidence of PTC has exhibited a greater increase over the last 2 decades than in many other malignancies. Thus, discovering noninvasive specific serum biomarker to distinguish PTC from cancer-free controls in its early stages remains an important goal.Material/MethodsSerum samples from 88 PTC patients and 80 cancer-free controls were randomly allocated into training or validation sets. Serum peptide profiling was performed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) after using weak cation exchange magnetic beads (WCX-MB), and the results were evaluated by use of ClinProTools™ Software. To distinguish PTC from cancer-free controls, quick classifier (QC), supervised neural network (SNN), and genetic algorithm (GA) models were established. The models were blindly validated to verify their diagnostic capabilities. The most discriminative peaks were subsequently identified with a nano-liquid chromatography-electrospray ionization-tandem mass spectrometry system.ResultsSix peptide ions were identified as the most discriminative peaks between the PTC and cancer-free control samples. The QC model exhibited satisfactory sensitivity and specificity among the 3 models that were validated. Two peaks, at m/z 2671.17 and m/z 1464.68, were identified as fragments of the alpha chain of fibrinogen, while a peak at m/z 1738.92 was a fragment of complement component 4A/B.ConclusionsMS combined with ClinProTools™ software was able to detect peptide biomarkers in PTC patients. In addition, the constructed classification models provided a serum peptidome pattern for distinguishing PTC from cancer-free controls. Both fibrinogen α and complement C4A/B were identified as potential markers for diagnosis of PTC.

Screening of Serum Peptidome-Based Biomarker for Multiple Myeloma Renal Impairment

To screen serum peptide associated with renal impairment in patients with multiple myeloma(MM) and search early biomarker of MM renal impairment. The weak cation exchange magnetic bead combined with matrix assisted laser desorption/ionization time of flight mass spectrometry was used to compare and analyze serum peptidome of MM with or without renal impairment. There were 18 peptide peaks with statistical significance in the molecular weight range from 700 to 10 000 Da(P<0.05), among them 7 peptides were upregulated and 11 were downregulated. The Quick Classifier diagnostic model composed of 3 peptides, which can strongly distinguish MM patients with or without renal impairment by means of Embedded Software. Its sensitivity and specificity were 97.14% and 94.12%, respectively. Peptides with molecular weight of 3908.85 Da and 3216.06 Da were significantly upregulated in MM patients with renal impairment, while the peptide with molecular weight of 2990.08 Da was significantly downregulated in MM patients with renal impairment. Peptides associated with MM renal impairment obtained by serum peptidome technology can provide a new clue for early assessment and diagnosis of clinical MM renal impairment.

Serum peptidome profiling for the diagnosis of colorectal cancer: discovery and validation in two independent cohorts.

Colorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Except for the existing fecal occult blood test, colonoscopy and sigmoidoscopy, no widely accepted in vitro diagnostic methods have been available. To identify potential peptide biomarkers for CRC, serum samples from a discovery cohort (100 CRC patients and 100 healthy controls) and an independent validation cohort (91 CRC patients and 91 healthy controls) were collected. Peptides were fractionated by weak cation exchange magnetic beads (MB-WCX) and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Five peptides (peaks at m/z 1895.3, 2020.9, 2080.7, 2656.8 and 3238.5) were identified as candidate biomarkers for CRC. A diagnostic panel based on the five peptides can discriminate CRC patients from healthy controls, with an accuracy of 91.8%, sensitivity of 95.6%, and specificity of 87.9% in the validation cohort. Peptide peaks at m/z 1895.3, 2020.9 and 3238.5 were identified as the partial sequences of complement component 4 (C4), complement component 3 (C3) and fibrinogen α chain (FGA), respectively. This study potentiated peptidomic analysis as a promising in vitro diagnostic tool for diagnosis of CRC. The identified peptides suggest the involvement of the C3, C4 and FGA in CRC pathogenesis.

Longitudinal investigation of salivary proteomic profiles in the development of early childhood caries

ObjectivesTo investigate differentially expressed salivary peptides in the development of early childhood caries (ECC) in 3–4 year-old children. Materials and methodsEighty-two caries-free children at baseline were followed-up for 1year, during which period 15 of them had developed ECC (Group C), whilst another 15 cases out of the 31 individuals who remained healthy were marked as Group H. Stimulated whole saliva samples were collected at 0, 6 and 12 months, and analyzed using weak cation exchange magnetic beads combined with matrix assisted laser desorption/ionization time-of-flight mass spectrometry. Corresponding peptide mass fingerprints were obtained to develop a discriminating model for ECC development. Q-Exactive mass spectrometry was then performed to identify the possible proteins where these peptides might derive from. ResultsNine peptide peaks were found to be significantly different in Group C among the three sampling time points and might correlate with development of caries. Levels of three of them increased over time, whilst that of the other six decreased gradually. We chose three peptides (1346.6, 2603.5 and 3192.8Da) which exhibited the best capability of classification, to establish a model for children at high risk of caries. One peptide (1346.6Da) was identified to be salivary histatin-rich peptide. ConclusionsOur results indicate that peptidomic methods can be applied to help identify new candidate biomarkers for the occurrence and development of ECC. Clinical significanceThe change of salivary peptides may be an indicator of ECC, facilitating more effective measures to be taken in prevention of this disease.

Identification of urine biomarkers associated with lung adenocarcinoma.

Lung adenocarcinoma (LAC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as urine. Urine collected from LAC patients (n=34) and healthy controls (n=36) was analyzed via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. The results revealed 76 urinary polypeptides significantly different between LAC patients and normal controls (P<0.05). Twenty-two of these peptides were up-regulated and 54 were down-regulated. Thirteen peptides had average peak intensities >600. Twelve of these 13 peptides were successfully identified using nano-liquid chromatography-tandem MS. Receiver operating characteristic analyses identified seven peptides with superior LAC diagnostic performances. Immunohistochemical staining in 20 paired LAC and adjacent normal tissues showed that IGKC, AAT, SH3BGRL3, osteopontin and gelsolin levels were higher in LAC tissues than in adjacent tissuesand were closely associated with LAC. Urinary peptides assessments may thus provide a novel, noninvasive, repeatable method for detecting and monitoring LAC. New, low-cost detection methods and bioinformatics tools are therefore urgently needed for the analysis of low abundance proteins and peptides in body fluids.

The Exploration of Peptide Biomarkers in Malignant Pleural Effusion of Lung Cancer Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Background. Diagnoses of malignant pleural effusion (MPE) are a crucial problem in clinics. In our study, we compared the peptide profiles of MPE and tuberculosis pleural effusion (TPE) to investigate the value of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of MPE. Material and Methods. The 46 MPE and 32 TPE were randomly assigned to training set and validation set. Peptides were isolated by weak cation exchange magnetic beads and peaks in the m/z range of 800–10000 Da were analyzed. Comparing the peptide profile between 30 MPE and 22 TPE samples in training set by ClinProTools software, we screened the specific biomarkers and established a MALDI-TOF-MS classification of MPE. Finally, the other 16 MPE and 10 TPE were included to verify the model. We additionally determined carcinoembryonic antigen (CEA) in MPE and TPE samples using electrochemiluminescent immunoassay method. Results. Five peptide peaks (917.37 Da, 4469.39 Da, 1466.5 Da, 4585.21 Da, and 3216.87 Da) were selected to separate MPE and TPE by MALDI-TOF-MS. The sensitivity, specificity, and accuracy of the classification were 93.75%, 100%, and 96.15%, respectively, after blinded test. The sensitivity of CEA was significantly lower than MALDI-TOF-MS classification (P = 0.035). Conclusions. The results indicate MALDI-TOF-MS is a potential method for diagnosing MPE.

Serum Peptidome Based Biomarkers Searching for Monitoring Minimal Residual Disease in Adult Acute Monocytic Leukemia

Background: Acute monocytic leukemia (M5) is one common type in acute myeloid leukemia (AML). The present study found that a few M5 had special reproducible chromosomal abnormalities and molecular abnormalities. The heterogeneity and complexity of M5 lead to lack of specific tumor-associated markers for molecular diagnosis and targeted therapy. CLINPROT system, with unique advantages, is a firenew and distinctive proteomics technology and has been widely used in the researches of solid tumor and hemopathic malignancies. This study was to screen a panel of serum peptides associated with M5 different disease states for molecular diagnosis and monitoring minimal residual disease.Methods: 92 M5 were enrolled for the study from those who were newly diagnosed (ND) in the Second Affiliated Hospital of Xi’an Jiao Tong University from January 2009 to July 2014. The median age was 45 years old (range 18-73) and 57.6% were male. Diagnosis was made according to bone marrow cell morphology, cytochemical staining and cellular immune phenotype. 90 healthy cases (HC) (age range 19-70, median age 43 years old, male/female 51/39) were recruited from those who came to our hospital to undergo healthy physical examination and had no any abnormal symptoms and results. Sera of 92 M5 were gained pre- and post-treatment of chemotherapy. Weak cation exchange magnetic bead combined with matrix assisted laser desorption/ ionization time of flight mass spectrometry were used to compare and analyze serum peptidome of M5 with different disease states. Spearman method was used to do correlation analysis of two variables. Statistical significance was defined as p<0.05.Results: A total of 42 peptides in the molecular weight range of 700-10000 Da were detected using ClinProt system and statistically different between adult M5 and healthy controls. Among them, 9 peptides were elevated and 33 were decreased in M5. Genetic algorithm (GA) was used to obtain a diagnostic model consisting of 6 peptides that could discriminate M5 from controls with a high sensitivity (100%) and specificity (96.67%). Mass charge ratios (m/z) were 6041.91, 4662.15, 7823.02, 9210.97, 1108.91 and 3263.37 respectively. Blind test verified that this model correctly identified 60 cases out of total 62 M5 and 57 cases from 60 healthy controls. The relative intensities of peptides with m/z of 6041.91 and 4662.15 were increased in the ND group and non-complete remission (CR) group, when comparing with the CR group and HC group(p=0.002; p<0.001), but there was no significant difference between the two groups for any of the peptides (p=0.27, p=0.31). No significant difference was found between the CR group and HC group (p=0.22, p=0.41). The relative intensities of peptides with m/z of 7823.02, 9210.97, 1108.91 and 3263.37 were reduced in the ND group and non-CR group when comparing with the CR group and HC group (p<0.001, p=0.0023, p=0.004, p<0.001), and the two groups had no significant difference (p=0.26, p=0.09, p=0.32, p=0.61). No significant difference was observed between the HC group and CR group (p=0.52, p=0.35, p=0.17, p=0.73). Spearman correlation analysis showed that relative intensities of peptides with m/z of 4662.15, 7823.02 and 9210.97 were correlated with high white blood cells (r=0.88, p<0.001; r=-0.89, p<0.001; p=-0.87, p<0.001), FLT3 mutation (r=0.90, p<0.001; r=-0.87, p<0.001; r=-0.88, p<0.001) , extramedullary disease (r=0.80, p<0.001; r=-0.86, p<0.001; r=- 0.82, p<0.001). The relative intensities of the other three peptides had weak correlation with the unfavorable clinical features of M5 at diagnosis.Conclusion: This panel of peptides has encouraging efficiency in discriminating M5 from HCs and potential value in monitoring M5 minimal residual disease. DisclosuresNo relevant conflicts of interest to declare.

Weak cation exchange magnetic beads coupled with matrix-assisted laser desorption ionization-time of flight-mass spectrometry in screening serum protein markers in osteopenia.

The present study aimed at investigating the weak cation magnetic separation technology and matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) in screening serum protein markers of osteopenia from ten postmenopausal women and ten postmenopausal women without osteopenia as control group, to find a new method for screening biomarkers and establishing a diagnostic model for primary type I osteoporosis. Serum samples were collected from postmenopausal women with osteopenia and postmenopausal women with normal bone mass. Proteins were extracted from serum samples by weak cation exchange magnetic beads technology, and mass spectra acquisition was done by MALDI-TOF-MS. The visualization and comparison of data sets, statistical peak evaluation, model recognition, and discovery of biomarker candidates were handled by the proteinchip data analysis system software(ZJU-PDAS). The diagnostic models were established using genetic arithmetic based support vector machine (SVM). The SVM result with the highest Youden Index was selected as the model. Combinatorial Peaks having the highest accuracy in distinguishing different samples were selected as potential biomarker. From the two group serum samples, a total of 133 differential features were selected. Ten features with significant intensity differences were screened. In the pair-wise comparisons, processing of MALDI-TOF spectra resulted in the identification of ten differential features between postmenopausal women with osteopenia and postmenopausal women with normal bone mass. The difference of features by Youden index showed that the highest features had a mass to charge ratio of 1699 and 3038 Da. A diagnosis model was established with these two peaks as the candidate marker, and the specificity of the model is 100 %, the sensitivity was 90 % by leave-one-out cross validation test. The two groups of specimens in SVM results on the scatter plot could be clearly distinguished. The peak with m/z 3038 in the SVM model was suggested as Secretin by TagIdent tool. To provide further validation, the secretin levels in serum were analyzed using enzyme-linked immunosorbent assays that is a competitive inhibition enzyme immunoassay technique for the in vitro quantitative measurement of secretin in human serum.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-2276-4) contains supplementary material, which is available to authorized users.