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.
Animals ; Humans ; Rats ; Multivariate Analysis ; Postmortem Changes ; Protein Array Analysis ; Technology

OBJECTIVE: To study the cytokine patterns in patients with rheumatoid arthritis (RA) and healthy individuals and identify candidate serum biomarkers for clinical diagnosis of RA. METHODS: This study was conducted among 59 patients diagnosed with RA in our hospital from 2015 to 2019 with 46 age- and gender-matched healthy subjects who received regular physical examinations in our hospital as the control group. Serological autoimmune profiles of 5 RA patients and 5 healthy control subjects were obtained from human cytokine microarrays. We selected 4 differentially expressed cytokines (LIMPII, ROBO3, Periostin and IGFBP-4) and 2 soluble cytokine receptors of interest (2B4 and Tie-2) and examined their serum levels using enzyme-linked immunosorbent assay in 54 RA patients and 41 healthy control subjects. Spearman correlation test was performed to assess the correlation of serum cytokine and soluble receptor expression levels with the clinical features including rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), disease activity score (DAS28) and health assessment questionnaire (HAQ). Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic capability of these cytokines. RESULTS: We identified 6 dysregulated cytokines and soluble receptors (2B4, LIMPII, Tie-2, ROBO3, periostin and IGFBP-4) in RA patients (P < 0.01). The serum levels of LIMPII, ROBO3 and periostin were significantly correlated with the disease activity indicators including RF (P < 0.001), CRP (P < 0.001), DAS28 (P < 0.001) and HAQ (P < 0.001) in RA patients. Among the 6 candidate cytokines, 2B4 showed the largest area under the curve (AUC) of 0.861 for RA diagnosis (P < 0.001), followed then by LIMPII, ROBO3, periostin, Tie-2 and IGFBP-4. CONCLUSION Serum levels of LIMPII, ROBO3 and periostin can be indicative of the disease activity of RA, and serum 2B4, LIMPII, periostin, ROBO3, IGFBP-4 and Tie-2 levels may serve as biomarkers for the diagnosis of RA.
Arthritis, Rheumatoid/diagnosis* ; Biomarkers ; C-Reactive Protein ; Cytokines ; Humans ; Insulin-Like Growth Factor Binding Protein 4 ; Protein Array Analysis ; Receptors, Cell Surface

Imported malaria has become a major risk factor for malaria prevention and control in China. How to screen malaria quickly for people entering China is an urgent problem to be solved. Protein microarrays are widely used in high-throughput screening and diagnosis. In this study, surface plasmon resonance (SPR) technique for malaria detection was established by using the specific adsorption surface treated by polyethylene glycol polymer, and the malaria specific antigen HRP2 was used as capture probe. The optimal concentration of antigen, sensitivity and specificity of detection, as well as anti-interference ability of the chip were analyzed. The SPR protein chip was applied to detect specific antibodies of malignant malaria in serum with the advantage of label-free, instant and fast. Compared with fluorescence quantitative PCR, there were no significant difference in sensitivity and specificity between the two methods. This study lays a foundation for further development of protein microarray for malaria typing identification, and it is conducive to the rapid screening of malaria for people entering.
Antibodies ; China ; Humans ; Malaria/diagnosis* ; Protein Array Analysis ; Surface Plasmon Resonance

The rapid screening of tumor markers is a challenging task for early diagnosis of cancer. This study aims to use highly sensitive chemiluminescent protein microarray technology to efficiently screen a variety of low abundance tumor related markers. A new material, termed integrated polydimethylsiloxane modified silica gel (iPDMS), was obtained by adding a surface polymerization initiator with olefin end to the conventional polydimethylsiloxane, and fixing into the three-dimensional structure of polydimethylsiloxane by thermal crosslinking through silicon hydrogen bonding. In order to make the iPDMS material resistant to non-specific protein adsorption, a poly(OEGMA) polymer brush was synthesized by surface-initiated atom transfer radical polymerization at the active initiation site. Finally, 20 tumor-related antigens were printed into the specific areas of the microarray by high-throughput spray printing technology, and assembled into 48-well detection microtiterplates of the iPDMS microarray. It was found the VEGFR and VEGF121 autoantibodies that obtained from 8 common tumors (breast cancer, lung cancer, colon cancer, gastric cancer, liver cancer, leukemia, lymphoma and ovarian cancer) can be used as potential tumor markers. The chemiluminescence labeled iPDMS protein microarray can be used for the screening of tumor autoantibodies at early stage.
Adsorption ; Autoantibodies ; Dimethylpolysiloxanes ; Protein Array Analysis ; Silica Gel ; Surface Properties

OBJECTIVE: To detect the differentially expressed inflammatory proteins in acute gouty arthritis (AGA) with protein chip. METHODS: The Raybiotech cytokine antibody chip was used to screen the proteomic expression in serum samples of 10 AGA patients and 10 healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were applied to determine the biological function annotation of differentially expressed proteins and the enrichment of signal pathways. ELISA method was used to verify the differential protein expression in 60 AGA patients and 60 healthy subjects. The ROC curve was employed to evaluate the diagnostic value of differential proteins in AGA patients. RESULTS: According to|log CONCLUSIONS Proteomics can be applied to identify the biomarkers of AGA, which may be used for risk prediction and diagnosis of AGA patients.
Arthritis, Gouty/diagnosis* ; Cytokines/genetics* ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Inflammation ; Protein Array Analysis ; Proteomics

Objective To obtain the protein expression profile of rat liver tissue after death by the 2100 bioanalyzer combined with protein chip, and infer the relationship between protein expression profile and postmortem interval. Methods Rats were killed by abdominal anesthesia and placed at 16 ℃. Water-soluble proteins in liver tissues were extracted at 14 time points after death. The expression profile data of proteins with relative molecular weight of 14 000-230 000 were obtained using protein chip, and principal component analysis （PCA）, partial least squares-discriminant analysis （PLS-DA） and Fisher discriminant were used to analyze the data. Results According to the changes of protein expression profile, the postmortem interval was divided into group A （0 d）, group B （1-9 d）, group C （12-30 d） according to the result of PLS-DA. The prediction accuracy of the training set and test set of the model were all 100.0%, and the internal cross-validation of the training set was 100.0% according to Fisher discriminant. The Fisher discriminant model at each time point of group B and C was established to narrow the time window of postmortem interval estimation. The prediction accuracy of the training set and test set were all 100.0%, and the internal cross-validation accuracy of the training set was 100.0% in group B. The prediction accuracy of the training set and test set were respectively 95.2% and 78.6% in group C, and the internal cross-validation of the training set was 88.1%. Conclusion Protein chip detection technology can quickly and easily obtain the expression profile of water-soluble proteins of rat liver tissue with a relative molecular weight of 14 000-230 000 at different time points after death. PLS-DA and Fisher discriminant models are established to classify and predict the postmortem interval, in order to provide new ideas and methods for postmortem interval estimation.
Animals ; Autopsy ; Discriminant Analysis ; Least-Squares Analysis ; Postmortem Changes ; Protein Array Analysis ; Rats ; Technology

OBJECTIVETo identify potential serum biomarkers for distinguishing between latent tuberculosis infection (LTBI) and active tuberculosis (TB).

METHODSA proteome microarray containing 4,262 antigens was used for screening serum biomarkers of 40 serum samples from patients with LTBI and active TB at the systems level. The interaction network and functional classification of differentially expressed antigens were analyzed using STRING 10.0 and the TB database, respectively. Enzyme-linked immunosorbent assays (ELISA) were used to validate candidate antigens further using 279 samples. The diagnostic performances of candidate antigens were evaluated by receiver operating characteristic curve (ROC) analysis. Both antigen combination and logistic regression analysis were used to improve diagnostic ability.

RESULTSMicroarray results showed that levels of 152 Mycobacterium tuberculosis (Mtb)-antigen- specific IgG were significantly higher in active TB patients than in LTBI patients (P < 0.05), and these differentially expressed antigens showed stronger associations with each other and were involved in various biological processes. Eleven candidate antigens were further validated using ELISA and showed consistent results in microarray analysis. ROC analysis showed that antigens Rv2031c, Rv1408, and Rv2421c had higher areas under the curve (AUCs) of 0.8520, 0.8152, and 0.7970, respectively. In addition, both antigen combination and logistic regression analysis improved the diagnostic ability.

CONCLUSIONSeveral antigens have the potential to serve as serum biomarkers for discrimination between LTBI and active TB.

Adolescent ; Adult ; Aged ; Antibodies, Bacterial ; Antibody Specificity ; Antigens, Bacterial ; Biomarkers ; blood ; Female ; Humans ; Latent Tuberculosis ; blood ; diagnosis ; Logistic Models ; Male ; Middle Aged ; Mycobacterium tuberculosis ; Protein Array Analysis ; methods ; Proteome ; genetics ; Proteomics ; methods ; ROC Curve ; Young Adult

Triple-negative breast cancer (TNBC) has a higher risk of death within 5 years of being diagnosed than the other forms of breast cancer. It is the second leading cause of death due to cancer among women. Currently, however, no diagnostic blood-based biomarker exists to identify the early stages of TNBC. To address this point, we utilized a human protein microarray system to identify serum autoantibodies that showed different expression patterns between TNBC and normal serum samples, and identified five autoantibodies showing TNBC-specific expression. Among them, we selected the thioredoxin-like 2 (TXNL2) autoantibody and evaluated its diagnostic relevance by dot blot analysis with the recombinant TXNL2 protein. We demonstrated that the TXNL2 autoantibody showed 2- to 6-fold higher expression in TNBC samples than in normal samples suggesting that serum TXNL2 autoantibodies are potential biomarkers for TNBC.
Autoantibodies ; Biomarkers ; Breast Neoplasms ; Cause of Death ; Female ; Humans ; Protein Array Analysis ; Triple Negative Breast Neoplasms*

Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 "CRC genes." These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology.
Adult ; Aged ; Aged, 80 and over ; Biomarkers, Tumor ; genetics ; immunology ; metabolism ; Case-Control Studies ; Colonic Neoplasms ; immunology ; metabolism ; Computational Biology ; methods ; Computer Simulation ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Immunoglobulin G ; immunology ; Male ; Middle Aged ; Protein Array Analysis ; methods

OBJECTIVE: This paper applied a transcriptomic approach to investigate the mechanisms of adriamycin (ADR) in treating proliferative vitreoretinopathy (PVR) using ARPE-19 cells. METHODS: The growth inhibitory effects of ADR on ARPE-19 cells were assessed by sulforhodamine B (SRB) assay and propidium iodide (PI) staining using flow cytometry. The differentially expressed genes between ADR-treated ARPE-19 cells and normal ARPE-19 cells and the signaling pathways involved were investigated by microarray analysis. Mitochondrial function was detected by JC-1 staining using flow cytometry and the Bcl-2/Bax protein family. The phosphorylated histone H2AX (γ-H2AX), phosphorylated checkpoint kinase 1 (p-CHK1), and phosphorylated checkpoint kinase 2 (p-CHK2) were assessed to detect DNA damage and repair. RESULTS: ADR could significantly inhibit ARPE-19 cell proliferation and induce caspase-dependent apoptosis in vitro. In total, 4479 differentially expressed genes were found, and gene ontology items and the p53 signaling pathway were enriched. A protein-protein interaction analysis indicated that the TP53 protein molecules regulated by ADR were related to DNA damage and oxidative stress. ADR reduced mitochondrial membrane potential and the Bcl-2/Bax ratio. p53-knockdown restored the activation of c-caspase-3 activity induced by ADR by regulating Bax expression, and it inhibited ADR-induced ARPE-19 cell apoptosis. Finally, the levels of the γ-H2AX, p-CHK1, and p-CHK2 proteins were up-regulated after ADR exposure. CONCLUSIONS The mechanism of ARPE-19 cell death induced by ADR may be caspase-dependent apoptosis, and it may be regulated by the p53-dependent mitochondrial dysfunction, activating the p53 signaling pathway through DNA damage.
Apoptosis ; Caspases/metabolism* ; Cell Proliferation ; Cell Survival/drug effects* ; Doxorubicin/pharmacology* ; Flow Cytometry ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Membrane Potential, Mitochondrial ; Oligonucleotide Array Sequence Analysis ; Oxidative Stress/drug effects* ; Phosphorylation ; Propidium/chemistry* ; RNA, Small Interfering/metabolism* ; Retinal Pigment Epithelium/metabolism* ; Rhodamines/chemistry* ; Signal Transduction/drug effects* ; Transcriptome ; Tumor Suppressor Protein p53/metabolism* ; Vitreoretinopathy, Proliferative/drug therapy*