Quantitative Detection of Multiple Cardiovascular Biomarkers by an Antibody Microarray-Based Metal-Enhanced Fluorescence Assay.

Accurate detection of multiple cardiovascular biomarkers is crucial for the timely screening of acute coronary syndrome (ACS) and differential diagnosis from acute aortic syndrome (AAS). Herein, an antibody microarray-based metal-enhanced fluorescence assay (AMMEFA) has been developed to quantitatively detect 7 cardiovascular biomarkers through the formation of a sandwich immunoassay on the poly(glycidyl methacrylate-co-2-hydroxyethyl methacrylate)-decorated GNR-modified slide (GNR@P(GMA-HEMA) slide). The AMMEFA exhibits high specificity and sensitivity, the linear ranges span 5 orders of magnitude, and the limits of detection (LODs) of cardiac troponin I (cTnI), heart-type fatty acid binding protein (H-FABP), C-reactive protein (CRP), copeptin, myoglobin, D-Dimer, and N-terminal pro-brain natriuretic peptide (NT-proBNP) reach 0.07, 0.2, 65.7, 0.6, 0.2, 8.3, and 0.3 pg mL-1, respectively. To demonstrate its practicability, the AMMEFA has been applied to quantitatively analyze 7 cardiovascular biomarkers in 140 clinical plasma samples. In addition, the expression levels of cardiovascular biomarkers were analyzed by the least absolute shrinkage and selector operator (LASSO) regression, and the area under receiver operator characteristic curves (AUCs) of healthy donors (HDs), ACS patients, and AAS patients are 0.99, 0.98, and 0.97, respectively.

Changes in serum immunoglobulin G glycosylation patterns for antiphospholipid syndrome patients with lectin microarray.

Antiphospholipid syndrome is a rare autoimmune disease characterized by persistent antiphospholipid antibodies. Immunoglobulin G plays a vital role in disease progression, with its structure and function affected by glycosylation. We aimed to investigate the changes in the serum immunoglobulin G glycosylation pattern in antiphospholipid syndrome patients. We applied lectin microarray on samples from 178 antiphospholipid syndrome patients, 135 disease controls (including Takayasu arteritis, rheumatoid arthritis and cardiovascular disease) and 100 healthy controls. Lectin blots were performed for validation of significant differences. Here, we show an increased immunoglobulin G-binding level of soybean agglutinin (p = 0.047, preferring N-acetylgalactosamine) in antiphospholipid syndrome patients compared with healthy and disease controls. Additionally, the immunoglobulin G from antiphospholipid syndrome patients diagnosed with pregnancy events had lower levels of fucosylation (p = 0.001, recognized by Lotus tetragonolobus) and sialylation (p = 0.030, recognized by Sambucus nigra I) than those with simple thrombotic events. These results suggest the unique serum immunoglobulin G glycosylation profile of antiphospholipid syndrome patients, which may inform future studies to design biomarkers for more accurate diagnosis of antiphospholipid syndrome and even for the prediction of clinical symptoms in patients.

Definition of the binding specificity of the T7 bacteriophage primase by analysis of a protein binding microarray using a thermodynamic model.

Protein binding microarrays (PBM), SELEX, RNAcompete and chromatin-immunoprecipitation have been intensively used to determine the specificity of nucleic acid binding proteins. While the specificity of proteins with pronounced sequence specificity is straightforward, the determination of the sequence specificity of proteins of modest sequence specificity is more difficult. In this work, an explorative data analysis workflow for nucleic acid binding data was developed that can be used by scientists that want to analyse their binding data. The workflow is based on a regressor realized in scikit-learn, the major machine learning module for the scripting language Python. The regressor is built on a thermodynamic model of nucleic acid binding and describes the sequence specificity with base- and position-specific energies. The regressor was used to determine the binding specificity of the T7 primase. For this, we reanalysed the binding data of the T7 primase obtained with a custom PBM. The binding specificity of the T7 primase agrees with the priming specificity (5'-GTC) and the template (5'-GGGTC) for the preferentially synthesized tetraribonucleotide primer (5'-pppACCC) but is more relaxed. The dominant contribution of two positions in the motif can be explained by the involvement of the initiating and elongating nucleotides for template binding.

Disordered clock protein interactions and charge blocks turn an hourglass into a persistent circadian oscillator.

Organismal physiology is widely regulated by the molecular circadian clock, a feedback loop composed of protein complexes whose members are enriched in intrinsically disordered regions. These regions can mediate protein-protein interactions via SLiMs, but the contribution of these disordered regions to clock protein interactions had not been elucidated. To determine the functionality of these disordered regions, we applied a synthetic peptide microarray approach to the disordered clock protein FRQ in Neurospora crassa. We identified residues required for FRQ's interaction with its partner protein FRH, the mutation of which demonstrated FRH is necessary for persistent clock oscillations but not repression of transcriptional activity. Additionally, the microarray demonstrated an enrichment of FRH binding to FRQ peptides with a net positive charge. We found that positively charged residues occurred in significant "blocks" within the amino acid sequence of FRQ and that ablation of one of these blocks affected both core clock timing and physiological clock output. Finally, we found positive charge clusters were a commonly shared molecular feature in repressive circadian clock proteins. Overall, our study suggests a mechanistic purpose for positive charge blocks and yielded insights into repressive arm protein roles in clock function.

Revisiting the antigen markers of vector-borne parasitic diseases identified by immunomics: identification and application to disease control.

INTRODUCTION: Protein microarray is a promising immunomic approach for identifying biomarkers. Based on our previous study that reviewed parasite antigens and recent parasitic omics research, this article expands to include information on vector-borne parasitic diseases (VBPDs), namely, malaria, schistosomiasis, leishmaniasis, babesiosis, trypanosomiasis, lymphatic filariasis, and onchocerciasis. AREAS COVERED: We revisit and systematically summarize antigen markers of vector-borne parasites identified by the immunomic approach and discuss the latest advances in identifying antigens for the rational development of diagnostics and vaccines. The applications and challenges of this approach for VBPD control are also discussed. EXPERT OPINION: The immunomic approach has enabled the identification and/or validation of antigen markers for vaccine development, diagnosis, disease surveillance, and treatment. However, this approach presents several challenges, including limited sample size, variability in antigen expression, false-positive results, complexity of omics data, validation and reproducibility, and heterogeneity of diseases. In addition, antigen involvement in host immune evasion and antigen sensitivity/specificity are major issues in its application. Despite these limitations, this approach remains promising for controlling VBPD. Advances in technology and data analysis methods should continue to improve candidate antigen identification, as well as the use of a multiantigen approach in diagnostic and vaccine development for VBPD control.

Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies.

The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

Antibody array-based proteome approach reveals proteins involved in grape seed development.

Grape (Vitis vinifera) is one of the most widely cultivated fruits globally, primarily used for processing and fresh consumption. Seedless grapes are favored by consumers for their convenience, making the study of seedlessness a subject of great interest to scientists. To identify regulators involved in this process in grape, a monoclonal antibody (mAb)-array-based proteomics approach, which contains 21,120 mAbs, was employed for screening proteins/antigens differentially accumulated in grape during development. Differences in antigen signals were detected between seeded and seedless grapes revealing the differential accumulation of 2,587 proteins. After immunoblotting validation, 71 antigens were further immunoprecipitated and identified by mass spectrometry (MS). An in planta protein-protein interaction (PPI) network of those differentially accumulated proteins was established using mAb antibody by immunoprecipitation (IP)-MS, which reveals the alteration of pathways related to carbon metabolism and glycolysis. To validate our result, a seedless-related protein, DUF642 domain-containing protein (VvDUF642), which is functionally uncharacterized in grapes, was ectopically overexpressed in tomato (Solanum lycopersicum "MicroTom") and led to a reduction in seed production. PPI network indicated that VvDUF642 interacts with pectin acetylesterase (VvPAE) in grapes, which was validated by BiFC and Co-IP. As anticipated, overexpression of VvPAE substantially reduced seed production in tomato. Moreover, S. lycopersicum colourless non-ripening expression was altered in VvDUF642- and VvPAE-overexpressing plants. Taken together, we provided a high-throughput method for the identification of proteins involved in the seed formation process. Among those, VvDUF642 and VvPAE are potential targets for breeding seedless grapes and other important fruits in the future.

Functional proteomics based on protein microarray technology for biomedical research.

This chapter traces a route through Proteomics from its origins to the present day. The different proteomics applications are discussed with a focus on microarray technology. Analytical microarrays, functional microarrays and reverse phase microarrays and their different applications are discussed. Several studies are mentioned where the great versatility of this approach is shown. Finally, the advantages and future challenges of microarray technology are outlined.

Autoantibody Profiling Using Human Autoantigen Protein Array and AlphaScreen.

Autoantibodies that recognize self-antigens are believed to have a close relationship with diseases such as autoimmune diseases, cancer, and lifestyle diseases. Analysis of autoantibodies is essential for investigating pathology mechanisms, diagnosis, and therapeutics of these diseases. We developed an autoantibody profiling assay using a cell-free synthesized protein array and high-throughput screening technology. Our assay system can sensitively detect interaction between recombinant antigen protein and autoantibody and efficiently analyze autoantibody profiling in patients' sera.

Direct competitive assay for HER2 detection in human plasma using Bloch surface wave-based biosensors.

The overexpression and/or amplification of the HER2/neu oncogene has been proposed as a prognostic marker in breast cancer. The detection of the related peptide HER2 remains a grand challenge in cancer diagnosis and for therapeutic decision-making. Here, we used a biosensing device based on Bloch Surface Waves excited on a one-dimensional photonic crystal (1DPC) as valid alternative to standard techniques. The 1DPC was optimized to operate in the visible spectrum and the biosensor optics has been designed to combine label-free and fluorescence operation modes. This feature enables a real-time monitoring of a direct competitive assay using detection mAbs conjugated with quantum dots for an accurate discrimination in fluorescence mode between HER2-positive/negative human plasma samples. Such a competitive assay was implemented using patterned alternating areas where HER2-Fc chimera and reference molecules were bio-conjugated and monitored in a multiplexed way. By combining Label-Free and fluorescence detection analysis, we were able to tune the parameters of the assay and provide an HER2 detection in human plasma in less than 20 min, allowing for a cost-effective assay and rapid turnaround time. The proposed approach offers a promising technique capable of performing combined label-free and fluorescence detection for both diagnosis and therapeutic monitoring of diseases.

Antibody Profiling of Dengue Severities Using Flavivirus Protein Microarrays.

Dengue is a viral disease transmitted by Aedes aegypti mosquitoes. According to the World Health Organization, about half of the world's population is at risk of dengue. There are four serotypes of the dengue virus. After infection with one serotype, it will be immune to such a serotype. However, subsequent infection with other serotypes will increase the risk of severe outcomes, e.g., dengue hemorrhagic fever, dengue shock syndrome, and even death. Since severe dengue is challenging to predict and lacks molecular markers, we aim to build a multiplexed Flavivirus protein microarray (Flaviarray) that includes all of the common Flaviviruses to profile the humoral immunity and cross-reactivity in the dengue patients with different outcomes. The Flaviarrays we fabricated contained 17 Flavivirus antigens with high reproducibility (R-square = 0.96) and low detection limits (172-214 pg). We collected serums from healthy subjects (n = 36) and dengue patients within 7 days after symptom onset (mild dengue (n = 21), hospitalized nonsevere dengue (n = 29), and severe dengue (n = 36)). After profiling the serum antibodies using Flaviarrays, we found that patients with severe dengue showed higher IgG levels against multiple Flavivirus antigens. With logistic regression, we found groups of markers with high performance in distinguishing dengue patients from healthy controls as well as hospitalized from mild cases (AUC > 0.9). We further reported some single markers that were suitable to separate dengue patients from healthy controls (AUC > 0.9) and hospitalized from mild outcomes (AUC > 0.8). Together, Flaviarray is a valuable tool to profile antibody specificities, uncover novel markers for decision-making, and shed some light on early preventions and treatments.

Two Decades of Arrayed Imaging Reflectometry for Sensitive, High-Throughput Biosensing.

Arrayed imaging reflectometry (AIR), first introduced in 2004, is a thin-film interference sensor technique that optimizes optical properties (angle of incidence, polarization, substrate refractive index, and thickness) to create a condition of total destructive interference at the surface of a silicon substrate. The advantages of AIR are its sensitivity, dynamic range, multiplex capability, and high-throughput compatibility. AIR has been used for the detection of antibodies against coronaviruses, influenza viruses, Staphylococcus aureus, and human autoantigens. It has also shown utility in detection of cytokines, with sensitivity comparable to bead-based and ELISA assays. Not limited to antibodies or antigens, mixed aptamer and protein arrays as well as glycan arrays have been employed in AIR for differentiating influenza strains. Mixed arrays using direct and competitive inhibition assays have enabled simultaneous measurement of cytokines and small molecules. Finally, AIR has also been used to measure affinity constants, kinetic and at equilibrium. In this review, we give an overview of AIR biosensing technologies and present the latest AIR advances.

Role of Serum Inflammatory Cytokines in Sepsis Rats Following BMSCs Transplantation: Protein Microarray Analysis.

Bone marrow stromal cells (BMSCs) have emerged as a potential therapy for sepsis, yet the underlying mechanisms remain unclear. In this study, we investigated the effects of BMSCs on serum inflammatory cytokines in a rat model of lipopolysaccharide (LPS)-induced sepsis. Sepsis was induced by intravenous injection of LPS, followed by transplantation of BMSCs. We monitored survival rates for 72 h and evaluated organ functions, histopathological changes, and cytokines expression. Sepsis rats showed decreased levels of white blood cells, platelets, lymphocyte ratio, and oxygen partial pressure, along with increased levels of neutrophil ratio, carbon dioxide partial pressure, lactic acid, alanine aminotransferase, and aspartate aminotransferase. Histologically, lung, intestine, and liver tissues exhibited congestion, edema, and infiltration of inflammatory cells. However, after BMSCs treatment, there was improvement in organ functions, histopathological injuries, and survival rates. Protein microarray analysis revealed significant changes in the expression of 12 out of 34 inflammatory cytokines. These findings were confirmed by enzyme-linked immunosorbent assay. Pro-inflammatory factors, such as interleukin-1ß (IL-1ß), IL-1α, tumor necrosis factor-α (TNF-α), tissue inhibitor of metal protease 1 (TIMP-1), matrix metalloproteinase 8 (MMP-8), Leptin, and L-selectin were upregulated in sepsis, whereas anti-inflammatory and growth factors, including IL-4, ß-nerve growth factor (ß-NGF), ciliary neurotrophic factor (CNTF), interferon γ (IFN-γ), and Activin A were downregulated. BMSCs transplantation led to a decrease in pro-inflammatory cytokines and an increase in anti-inflammatory and growth factors. We summarized relevant molecular signaling pathways that resulted from cytokines in BMSCs for treating sepsis. Our results illustrated that BMSCs could promote tissue repair and improve organ functions and survival rates in sepsis through modulating cytokine networks.

Comprehensive autoantibody profiling in systemic autoimmunity by a highly-sensitive multiplex protein array.

Comprehensive autoantibody evaluation is essential for the management of autoimmune disorders. However, conventional methods suffer from poor sensitivity, low throughput, or limited availability. Here, using a proteome-wide human cDNA library, we developed a novel multiplex protein assay (autoantibody array assay; A-Cube) covering 65 antigens of 43 autoantibodies that are associated with systemic sclerosis (SSc) and polymyositis/dermatomyositis (PM/DM). The performance of A-Cube was validated against immunoprecipitation and established enzyme-linked immunosorbent assay. Further, through an evaluation of serum samples from 357 SSc and 172 PM/DM patients, A-Cube meticulously illustrated a diverse autoantibody landscape in these diseases. The wide coverage and high sensitivity of A-Cube also allowed the overlap and correlation analysis between multiple autoantibodies. Lastly, reviewing the cases with distinct autoantibody profiles by A-Cube underscored the importance of thorough autoantibody detection. Together, these data highlighted the utility of A-Cube as well as the clinical relevance of autoantibody profiles in SSc and PM/DM.

Profiling humoral responses to COVID-19 immunization in Kawasaki disease using SARS-CoV-2 variant protein microarrays.

Kawasaki disease (KD) is a form of acute systemic vasculitis syndrome that predominantly occurs in children under the age of 5 years. Its etiology has been postulated due to not only genetic factors but also the presence of foreign antigens or infectious agents. To evaluate possible associations between Kawasaki disease (KD) and COVID-19, we investigated humoral responses of KD patients against S-protein variants with SARS-CoV-2 variant protein microarrays. In this study, plasma from a cohort of KD (N = 90) and non-KD control (non-KD) (N = 69) subjects in categories of unvaccinated-uninfected (pre-pandemic), SARS-CoV-2 infected (10-100 days after infection), and 1-dose, 2-dose, and 3-dose BNT162b2 vaccinated (10-100 days after vaccination) was collected. The principal outcomes were non-KD-KD differences for each category in terms of anti-human/anti-His for binding antibodies and neutralizing percentage for surrogate neutralizing antibodies. Binding antibodies against spikes were lower in the KD subjects with 1-dose of BNT162b2, and mean differences were significant for the P.1 S-protein (non-KD-KD, 3401; 95% CI, 289.0 to 6512; P = 0.0252), B.1.617.2 S-protein (non-KD-KD, 4652; 95% CI, 215.8 to 9087; P = 0.0351) and B.1.617.3 S-protein (non-KD-KD, 4874; 95% CI, 31.41 to 9716; P = 0.0477). Neutralizing antibodies against spikes were higher in the KD subjects with 1-dose of BNT162b2, and mean percentage differences were significant for the 1-dose BNT162b2 B.1.617.3 S-protein (non-KD-KD, -22.89%; 95% CI, -45.08 to -0.6965; P = 0.0399), B.1.1.529 S-protein (non-KD-KD, -25.96%; 95% CI, -50.53 to -1.376; P = 0.0333), BA.2.12.1 S-protein (non-KD-KD, -27.83%; 95% CI, -52.55 to -3.115; P = 0.0195), BA.4 S-protein (non-KD-KD, -28.47%; 95% CI, -53.59 to -3.342; P = 0.0184), and BA.5 S-protein (non-KD-KD, -30.42%; 95% CI, -54.98 to -5.869; P = 0.0077). In conclusion, we have found that KD patients have a comparable immunization response to healthy individuals to SARS-CoV-2 infection and COVID-19 immunization.

Utility of Protein Microarrays for Detection of Classified and Novel Antibodies in Autoimmune Neurologic Disease.

BACKGROUND AND OBJECTIVES: Neural antibodies are detected by tissue-based indirect immunofluorescence assay (IFA) in Mayo Clinic's Neuroimmunology Laboratory practice, but the process of characterizing and validating novel antibodies is lengthy. We report our assessment of human protein arrays. METHODS: Assessment of arrays (81% human proteome coverage) was undertaken using diverse known positive samples (17 serum and 14 CSF). Samples from patients with novel neural antibodies were reflexed from IFA to arrays. Confirmatory assays were cell-based (CBA) or line blot. Epitope mapping was undertaken using phage display immunoprecipitation sequencing (PhiPSeq). RESULTS: Control positive samples known to be reactive with linear epitopes of intracellular antigens (e.g., ANNA-1 [anti-Hu]) were readily identified by arrays in 20 of 21 samples. By contrast, 10 positive controls known to be enriched with antibodies against cell surface protein conformational epitopes (e.g., GluN1 subunit of NMDA-R) were indistinguishable from background signal. Three antibodies, previously characterized by other investigators (but unclassified in our laboratory), were unmasked in 4 patients using arrays (July-December 2022): Neurexin-3α, 1 patient; regulator of gene protein signaling (RGS)8, 1 patient; and seizure-related homolog like 2 (SEZ6L2), 2 patients. All were accompanied by previously reported phenotypes (encephalitis, 1; cerebellar ataxia, 3). Patient 1 had subacute onset of seizures and encephalopathy. Neurexin-3α ranked high in CSF (second ranked neural protein) but low in serum (660th overall). Neurexin-3α CBA was positive in both samples. Patient 2 presented with rapidly progressive cerebellar ataxia. RGS8 ranked the highest neural protein in available CSF sample by array (third overall). RGS8-specific line blot was positive. Patients 3 and 4 had rapidly progressive cerebellar ataxia. SEZ6L2 was the highest ranked neural antigen by arrays in all samples (CSF, 1, serum, 2; Patient 3, ranked 9th overall in CSF, 11th in serum; Patient 4, 6th overall in serum]). By PhIPSeq, diverse neurexin-3α epitopes (including cell surface) were detected in CSF from patient 1, but no SEZ6L2 peptides were detected for serum or CSF samples from Patient 3. DISCUSSION: Individualized autoimmune neurologic diagnoses may be accelerated using protein arrays. They are optimal for detection of intracellular antigen-reactive antibodies, though certain cell surface-directed antibodies (neurexin-3α and SEZ6L2) may also be detected.

Clonal architecture and evolutionary history of Waldenström's macroglobulinemia at the single-cell level.

To provide insight into the subclonal architecture and co-dependency patterns of the alterations in Waldenström's macroglobulinemia (WM), we performed single-cell mutational and protein profiling of eight patients. A custom panel was designed to screen for mutations and copy number alterations at the single-cell level in samples taken from patients at diagnosis (n=5) or at disease progression (n=3). Results showed that in asymptomatic WM at diagnosis, MYD88L265P was the predominant clonal alteration; other events, if present, were secondary and subclonal to MYD88L265P. In symptomatic WM, clonal diversity was more evident, uncovering combinations of alterations that synergized to promote clonal expansion and dominance. At disease progression, a dominant clone was observed, sometimes accompanied by other less complex minor clones, which could be consistent with a clonal selection process. Clonal diversity was also reduced, probably due to the effect of treatment. Finally, we combined protein expression with mutational analysis to map somatic genotype with the immunophenotype. Our findings provide a comprehensive view of the clonality of tumor populations in WM and how clonal complexity can evolve and impact disease progression.

[Conditional optimization and methodological evaluation of liquid protein microarray in detecting cystatin C].

OBJECTIVE: To optimize the detection conditions and evaluate of cystatin C(CysC) by liquid protein microarray. METHODS: CysC was detected by double antibody sandwich method using liquid protein microarray. On the basis of determining the optimal concentration combination of captured antibody and detected antibody, the detection conditions were optimized by determining the biological detection limit and lower detection limit, drawing the S-shaped curve and judging the linear range, and establishing the standard curve and regression equation. Methodsologically evaluate the accuracy, precision, reportable range and analytical specificity of the detection method. RESULTS: The optimal concentration combinations of CycC trapping-detection antibodies were 26.6 µg/mL-1∶800. The lower limits of detection and biologic limits of detection of the CysC were 0.037 and 0.237 ng/mL, respectively. Regression equation were as followes: y=-3.315x~2+283.04x+160.89, R~2=0.9921. The relative bias of CysC which was detected on the liquid protein microarry was 5.81%. The dilution recovery and recovery were 70.35%-84.91%(n=3)and 79.94%-122.41%(n=3)respectively. The correlation coefficient of method ology comparison experiment was r=0.616, P<0.05, and there was no significant difference between the two method(t=0.948, P=0.358); The within-run precision range from 3.54% to 4.03%(n=10); The between-run precision range from 12.07% to 15.05%(D=5, n=3); The reportable range was 0.26-3784.04 ng/mL. The analysis of interference test result showed that the both concentrations of hemoglobin(160.00, 71.11 g/L) had interference to the result of CysC detected on the chip. CONCLUSION: This study completed the optimization of conditions and methodological evaluation of liquid protein microarray in detecting CysC.

Screening of novel serum biomarkers for gastric cancer in coastal populations using a protein microarray.

Gastric cancer (GC) has high rates of morbidity and mortality, and this phenomenon is particularly evident in coastal regions where local dietary habits favor the consumption of pickled foods such as salted fish and vegetables. In addition, the diagnosis rate of GC remains low due to the lack of diagnostic serum biomarkers. Therefore, in this study, we aimed to identify potential serum GC biomarkers for use in clinical practice. To identify candidate biomarkers of GC, 88 serum samples were first screened using a high-throughput protein microarray to measure the levels of 640 proteins. Then, 333 samples were used to validate the potential biomarkers using a custom antibody chip. ELISA, western blot, and immunohistochemistry were then used to verify the expression of the target proteins. Finally, logistic regression was performed to select serum proteins for the diagnostic model. As a result, five specific differentially expressed proteins, TGFß RIII, LAG-3, carboxypeptidase A2, Decorin and ANGPTL3, were found to have the ability to distinguish GC. Logistic regression analysis showed that the combination of carboxypeptidase A2 and TGFß RIII had superior potential for diagnosing GC (area under the ROC curve [AUC] = 0.801). The results suggested that these five proteins alone and the combination of carboxypeptidase A2 and TGFß RIII may be used as serum markers for the diagnosis of GC.

Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods.

OBJECTIVES: To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods. METHODS: Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis. RESULTS: The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples. CONCLUSIONS: The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.