Sequence-Guided Localization of DNA Hybridization Enables Highly Selective and Robust Genotyping.

Genetic variations are always related to human diseases or susceptibility to therapies. Nucleic acid probes that precisely distinguish closely related sequences become an indispensable requisite both in research and clinical applications. Here, a Sequence-guided DNA LOCalization for leaKless DNA detection (SeqLOCK) is introduced as a technique for DNA hybridization, where the intended targets carrying distinct "guiding sequences" act selectively on the probes. In silicon modeling, experimental results reveal considerable agreement (R2  = 0.9228) that SeqLOCK is capable of preserving high discrimination capacity at an extraordinarily wide range of target concentrations. Furthermore, SeqLOCK reveals high robustness to various solution conditions and can be directly adapted to nucleic acid amplification techniques (e.g., polymerase chain reaction) without the need for laborious pre-treatments. Benefiting from the low hybridization leakage of SeqLOCK, three distinct variations with a clinically relevant mutation frequency under the background of genomic DNA can be discriminated simultaneously. This work establishes a reliable nucleic acid hybridization strategy that offers great potential for constructing robust and programmable systems for molecular sensing and computing.

Comprehensive analysis of fifteen hub genes to identify a promising diagnostic model, regulated networks, and immune cell infiltration in acute kidney injury.

BACKGROUND: Acute kidney injury is a common clinical problem with no sensitive and specific diagnostic biomarkers and definitive treatments. The underlying molecular mechanisms of acute kidney injury are unclear. Therefore, it is pivotal to explore the underlying mechanisms and screen for novel diagnostic biomarkers, and therapeutic targets. METHODS: The present study identified 15 hub genes by WGCNA analysis. LASSO-based logistic regression analysis was used to select key features and construct a diagnostic model of AKI. In addition, GO and KEGG analyses were performed and TF-mRNA and miRNA-mRNA network analysis and immune infiltration analysis of hub genes were performed to reveal the underlying mechanisms of AKI. RESULTS: A diagnostic model was constructed by LASSO-based logistic regression analysis and was validated by RT-qPCR based on 15 hub genes. GO and KEGG analyses revealed DEGs were enriched in oxidation-reduction process, cell adhesion, proliferation, migration, and metabolic process. The enriched TFs were BRD2, EP300, ETS1, MYC, SPI1, and ZNF263. The enriched miRNAs were miR-181c-5p, miR-218-5p, miR-485-5p, miR-532-5p and miR-6884-5p. The immune infiltration analysis showed that Macrophages M2 was decreasing significantly revealing a protective factor for further AKI treatment. CONCLUSIONS: The present study identified 15 hub genes based on WGCNA. Development and validation of a potentially diagnostic model based on 15 hub genes. In addition, exploring the interaction between transcriptional factors and 15 hub genes, and miRNA-mRNA relationship pairs. Furthermore, immune infiltration analysis was performed by analyzing gene expression profiles of AKI. Our study provides some basis for further experimental studies.

A quantitative detection of Cardiotrophin-1 in chronic heart failure by chemiluminescence immunoassay.

BACKGROUND: Cardiotrophin-1 (CT-1) is a cytokine that could induce cardiomyocytes hypertrophy and dysfunction. Plasma CT-1 might serve as a cardiac biomarker both in diagnosis, staging, and prognostic assessment of heart failure. METHODS: In this study, a one-step paramagnetic particles-based chemiluminescence immunoassay (MPs-CILA) for rapid and sensitive detection of plasma CT-1 was established. Plasma samples were directly incubated with biotin-labeled anti-CT-1 antibody (bio-Ab) and acridine ester labeled anti-CT-1 antibody (AE-Ab) to form sandwiched complex. The sandwiched CT-1 was then captured by streptavidin modified paramagnetic particles (MPs-SA) for rapid separation and signal generation. RESULTS: The proposed MPs-CLIA presents a laudable linear relationship ranging from 7.8 pg/mL to 200 ng/mL with a detection limit of 1.0 pg/mL. The recoveries of spiked human plasma samples at low (10pg/mL), medium (100 pg/mL), and high (800 pg/mL) levels of CT-1 were 96%, 104%, and 110% respectively. The intra-analysis coefficient variation (CVs) of the 3 samples was 8.92%, 6.69%, and 3.54%, respectively. And the inter-analysis coefficient variation (CVs) was 9.25%, 10.9%, and 4.3%, respectively. These results strongly indicate high sensitivity, wide linear range, acceptable precision, and applicable reproducibility of the proposed method to detect plasma level of CT-1. Finally, Plasma CT-1 from 140 subjects with or without chronic heart failure was analyzed to assess the clinical application of MPs-CILA. CONCLUSIONS: Noteworthily, the MPs-CLIA method is highly automated such that it is suitable for high-throughput detection of CT-1 in clinical inspection.

Determination of plasma ß-amyloids by rolling circle amplification chemiluminescent immunoassay for noninvasive diagnosis of Alzheimer's disease.

A rolling circle amplification chemiluminescence immunoassay (RCA-CLIA) was developed for precise quantitation of Aß in plasma. Capture antibodies conjugated with magnetic beads and detection antibodies with collateral single-stranded DNA (ssDNA) were bound to Aß42/Aß40 antigens to form a typical double-antibody sandwich structure. The RCA reaction was triggered by the addition of ssDNA, which generated products with a large number of sites for the binding of acridinium ester (AE)-labeled detection probes, thereby realizing the purpose of the amplification. The RCA-CLIA method had higher sensitivity than conventional CLIA without loss of specificity. Under optimum conditions, the linear range of Aß42 and Aß40 detection was 3.9-140 pg/mL and 3.9-180 pg/mL, respectively, with corresponding low detection limits of 1.99 pg/mL and 3.14 pg/mL, respectively. Plasma Aß42 and Aß40 were detected in the blood of 21 AD patients and 22 healthy people, wherein this ratio could significantly distinguish AD patients from healthy individuals with a sensitivity of 90.48% and specificity of 63.64% for a cutoff value of 154. The Aß42/Aß40 ratio of plasma acts as an accurate indicator for AD diagnosis; therefore, detection of plasma Aß using the RCA-CLIA exhibits great potential in noninvasive diagnosis and progressive assessment of AD.

ARMS TaqMan real-time PCR for genotyping factor V Leiden mutation in Han Chinese.

Factor V Leiden (FVLeiden ) is a missense mutation of 1691 position (G1691A) in exon 10 of FV gene, and being a genetic risk for venous thrombosis. Currently, there are several PCR-based methods for detecting FVLeiden mutation; however, these methods have disadvantages such as time-consuming, cumbersome steps and potentially hazardous gels. The aims of present study were to develop a simple, time-saving, accurate, and gel-free method, called amplification refractory mutation system (ARMS) TaqMan real-time PCR, for detecting FVLeiden mutation. We severally designed two specific reverse primers for mutant and wild-type through intentional introduction of mismatched nucleotide at the penultimate 3' position. Although target amplicon amplification efficiency is reduced, but another corresponding amplicon is almost completely inhibited. Then, specific TaqMan-probe was designed to detect target amplicon. Established method was used to detect 500 unselected samples in Han Chinese, the results showed 499 cases of wild-type and one heterozygote. Afterward, 50 randomly picked wild-type cases and one heterozygote were reexamined by bidirectional DNA sequencing, which is considered as "Gold standard method." Exhilaratingly, the results detected by the two methods were completely consistent. At last, allelic frequency of FVLeiden was calculated the in Han Chinese. Given the above results, A FVLeiden heterozygote has been found in 500 random samples in Han Chinese, and the allelic frequency was 0.1%. In conclusion, the ARMS TaqMan real-time PCR is an ideal detecting system for genotyping FVLeiden mutation in clinical application, and FVLeiden mutation exists in Han Chinese despite extremely low prevalence.

Comparison of the performance in detection of HPV infections between the high-risk HPV genotyping real time PCR and the PCR-reverse dot blot assays.

A new multiplex real-time PCR assay, the high-risk HPV genotyping real time PCR assay (HR HPV RT-PCR), has been developed to detect 15 high-risk HPV types with respective viral loads. In this report, a total of 684 cervical specimens from women diagnosed with vaginitis were assessed by the HR HPV RT-PCR and the PCR reaction and reverse dot blot (PCR-RDB) assays, using a PCR-sequencing method as a reference standard. A total coincidence of 97.7% between the HR HPV RT PCR and the PCR-RDB assays was determined with a Kappa value of 0.953. The HR HPV RT PCR assay had sensitivity, specificity, and concordance rates (accuracy) of 99.7%, 99.7%, and 99.7%, respectively, as confirmed by PCR-sequencing, while the PCR-RDB assay had respective rates of 98.8%, 97.1%, and 98.0%. The overall rate of HPV infection, determined by PCR-sequencing, in women diagnosed with vaginitis was 49.85%, including 36.26% of single infection and 13.6% of multiple infections. The most common infections among the 15 high-risk HPV types in women diagnosed with vaginitis were HPV-52, HPV-16, and HPV-58, with a total detection rate of 10.23%, 7.75%, and 5.85%, respectively. We conclude that the HR HPV RT PCR assay exhibits better clinical performance than the PCR-RDB assay, and is an ideal alternative method for HPV genotyping. In addition, the HR HPV RT PCR assay provides HPV DNA viral loads, and could serve as a quantitative marker in the diagnosis and treatment of single and multiple HPV infections.

Toehold integrated molecular beacon system for a versatile non-enzymatic application.

A molecular beacon (MB) is an oligonucleotide hybridization probe with a hairpin-shaped structure that leads to specific and instantaneous nucleic acid hybridization, enabling a variety of applications. However, integration of additional module sequences interferes with the performance of MBs and increases the complexity of sequence design. Herein, we develop and characterize a toehold integrated molecular beacon (ToMB) strategy for nucleic acid hybridization, where the reaction rate can be flexibly regulated by a target-induced MB conformational switch. Using this basic mechanism, the ToMB is capable of identifying nucleic acids with high specificity and a wider linearity range compared with the conventional molecular beacon system. We further applied the ToMB to the construction of a hybridization chain reaction system and a basic OR logic gate VJHto explore its programmability and versatility. Our results strongly suggest that the novel ToMB can act as a powerful nano-module to construct universal and multifunctional biosensors or molecular computations. Graphical abstract Molecular beacon is employed as a flexible and switchable spacer to control the toehold-mediated strand displacement reaction.

SGK1 inhibition induces autophagy-dependent apoptosis via the mTOR-Foxo3a pathway.

BACKGROUND: Although inhibition of SGK1 has been shown to delay cancer progression, the underlying mechanisms have not yet been elucidated. METHODS: We investigated the cellular responses to GSK650394 treatment and SGK1 silencing (or overexpression) in human prostate cancer (PCa) cell lines and PC3 xenografts by flow cytometry, western blotting, immunofluorescence, transmission electron microscopy and immunohistochemistry. RESULTS: In the present study, we demonstrated that SGK1 inhibition, mediated by either GSK650394 or SGK1 shRNA, induced G2/M arrest, apoptosis and autophagy. Furthermore, 3MA-mediated autophagy inhibition attenuated SGK1 inhibition-induced apoptosis, suggesting that induction of autophagy precedes apoptosis. Moreover, ectopic expression of SGK1 significantly attenuated the GSK650394-induced effects. Suppression of mTOR and Foxo3a phosphorylation is critical for blockade of SGK1-induced autophagy and apoptosis, at least partially via pFoxo3a (S253)-LC3 and pFoxo3a (S253)-p27 interactions. Dual inhibition of mTOR and SGK1 enhances autophagy activation and leads to synergistic cytocidal effects in PCa cells. CONCLUSIONS: In summary, our findings show that SGK1 inhibition exhibits significant antitumour effects against PCa in vitro and in vivo. This study uncovered a novel mechanism of SGK1 inhibition in PCa, which is mediated, at least in part, by inducing autophagy-dependent apoptosis via the mTOR-Foxo3a pathway.

Machine Learning Reveals a Multipredictor Nomogram for Diagnosing the Alzheimer's Disease Based on Chemiluminescence Immunoassay for Total Tau in Plasma.

Background: Predicting amnestic mild cognitive impairment (aMCI) in conversion and Alzheimer's disease (AD) remains a daunting task. Standard diagnostic procedures for AD population are reliant on neuroimaging features (positron emission tomography, PET), cerebrospinal fluid (CSF) biomarkers (Aß1-42, T-tau, P-tau), which are expensive or require invasive sampling. The blood-based biomarkers offer the opportunity to provide an alternative approach for easy diagnosis of AD, which would be a less invasive and cost-effective screening tool than currently approved CSF or amyloid ß positron emission tomography (PET) biomarkers. Methods: We developed and validated a sensitive and selective immunoassay for total Tau in plasma. Robust signatures were obtained based on several clinical features selected by multiple machine learning algorithms between the three participant groups. Subsequently, a well-fitted nomogram was constructed and validated, integrating clinical factors and total Tau concentration. The predictive performance was evaluated according to the receiver operating characteristic (ROC) curves and area under the curve (AUC) statistics. Decision curve analysis and calibration curves are used to evaluate the net benefit of nomograms in clinical decision-making. Results: Under optimum conditions, chemiluminescence analysis (CLIA) displays a desirable dynamic range within Tau concentration from 7.80 to 250 pg/mL with readily achieved higher performances (LOD: 5.16 pg/mL). In the discovery cohort, the discrimination between the three well-defined participant groups according to Tau concentration was in consistent agreement with clinical diagnosis (AD vs. non-MCI: AUC = 0.799; aMCI vs. non-MCI: AUC = 0.691; AD vs. aMCI: AUC = 0.670). Multiple machine learning algorithms identified Age, Gender, EMPG, Tau, ALB, HCY, VB12, and/or Glu as robust signatures. A nomogram integrated total Tau concentration and clinical factors provided better predictive performance (AD vs. non-MCI: AUC = 0.960, AD vs. aMCI: AUC = 0.813 in discovery cohort; AD vs. non-MCI: AUC = 0.938, AD vs. aMCI: AUC = 0.754 in validation cohort). Conclusion: The developed assay and a satisfactory nomogram model hold promising clinical potential for early diagnosis of aMCI and AD participants.

Identification and Validation of Three Hub Genes Involved in Cell Proliferation and Prognosis of Castration-Resistant Prostate Cancer.

Background: The acquisition of castration resistance is lethal and inevitable in most prostate cancer patients under hormone therapy. However, effective biomarkers and therapeutic targets for castration-resistant prostate cancer remain to be defined. Methods: Comprehensive bioinformatics tools were used to screen hub genes in castration-resistant prostate cancer and were verified in androgen-dependent prostate cancer and castration-resistant prostate cancer in TCGA and the SU2C/PCF Dream Team database, respectively. Gene set enrichment analysis and in vitro experiments were performed to determine the potential functions of hub genes involved in castration-resistant prostate cancer progression. Results: Three hub genes were screened out by bioinformatics analysis: MCM4, CENPI, and KNTC1. These hub genes were upregulated in castration-resistant prostate cancer and showed high diagnostic and prognostic value. Moreover, the expression levels of the hub genes were positively correlated with neuroendocrine prostate cancer scores, which represent the degree of castration-resistant prostate cancer aggression. Meanwhile, in vitro experiments confirmed that hub gene expression was increased in castration-resistant prostate cancer cell lines and that inhibition of hub genes hindered cell cycle transition, resulting in suppression of castration-resistant prostate cancer cell proliferation, which confirmed the gene set enrichment analysis results. Conclusions: MCM4, CENPI, and KNTC1 could serve as candidate diagnostic and prognostic biomarkers of castration-resistant prostate cancer and may provide potential preventive and therapeutic targets.

Serum oncostatin M is a potential biomarker of disease activity and infliximab response in inflammatory bowel disease measured by chemiluminescence immunoassay.

BACKGROUND: Although endoscopy is the gold standard to assess disease activity and infliximab efficacy in inflammatory bowel disease (IBD), the invasive, costly, and time-consuming procedure limits its routine applications. We aimed to investigate the clinical value of serum oncostatin M (OSM) as a surrogate biomarker. METHODS: Fifty healthy controls, 34 non-IBD patients, and 189 IBD patients who were pre-infliximab treatment (n = 122) or in infliximab maintenance (n = 67) were enrolled. A chemiluminescence immunoassay (CLIA) was constructed to quantify serum OSM concentrations. Receiver operator characteristic (ROC) curve analysis was used to evaluate the performance of blood biomarkers for IBD management. RESULTS: The methodology of CLIA exhibited great analytical performance with a wide linear range of 31.25-25000 pg/mL, a low detection limit of 23.2 pg/mL, acceptable precision, and applicable accuracy. Patients with IBD (121.5 [43.3-249.4] pg/mL, p < 0.001) and non-IBD (72.4 [51.4-129.6] pg/mL, p = 0.005) had higher serum OSM levels than healthy controls (35.8 [23.2-56.4] pg/mL). In the analysis of clinical and endoscopic activity, serum OSM levels were elevated in moderate and severe patients compared to those in remission. IBD patients without mucosal healing had higher serum OSM levels than those with mucosal healing (AUC = 0.843). Besides, serum OSM levels were increased in clinical non-responders (287.3 [127.9-438] pg/mL) compared to responders (24.1 [23.2-53.4] pg/mL, p < 0.001), and showed great recognition ability with an AUC of 0.898. CONCLUSIONS: The newly developed methodology of CLIA had great potential for use in the clinic. Elevated serum OSM expression was a promising biomarker of severe disease and infliximab non-response in IBD patients.

Emerging roles and mechanisms of microRNA­222­3p in human cancer (Review).

MicroRNAs (miRNAs/miRs) are a class of small non­coding RNAs that maintain the precise balance of various physiological processes through regulating the function of target mRNAs. Dysregulation of miRNAs is closely associated with various types of human cancer. miR­222­3p is considered a canonical factor affecting the expression and signal transduction of multiple genes involved in tumor occurrence and progression. miR­222­3p in human biofluids, such as urine and plasma, may be a potential biomarker for the early diagnosis of tumors. In addition, miR­222­3p acts as a prognostic factor for the survival of patients with cancer. The present review first summarizes and discusses the role of miR­222­3p as a biomarker for diverse types of cancers, and then focuses on its essential roles in tumorigenesis, progression, metastasis and chemoresistance. Finally, the current understanding of the regulatory mechanisms of miR­222­3p at the molecular level are summarized. Overall, the current evidence highlights the crucial role of miR­222­3p in cancer diagnosis, prognosis and treatment.

Glycolysis-related gene expression profiling serves as a novel prognosis risk predictor for human hepatocellular carcinoma.

Metabolic pattern reconstruction is an important factor in tumor progression. Metabolism of tumor cells is characterized by abnormal increase in anaerobic glycolysis, regardless of high oxygen concentration, resulting in a significant accumulation of energy from glucose sources. These changes promotes rapid cell proliferation and tumor growth, which is further referenced a process known as the Warburg effect. The current study reconstructed the metabolic pattern in progression of cancer to identify genetic changes specific in cancer cells. A total of 12 common types of solid tumors were included in the current study. Gene set enrichment analysis (GSEA) was performed to analyze 9 glycolysis-related gene sets, which are implicated in the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes showed high area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). The findings of the current study showed that 8 genes (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were correlated with overall survival (OS) and recurrence-free survival (RFS). Further analysis showed that the prediction model accurately distinguished between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics showed good discrimination based on internal and external cohorts. These findings indicate that changes in expression level of metabolic genes implicated in glycolysis can contribute to reconstruction of tumor-related microenvironment.

Five-gene signature associating with Gleason score serve as novel biomarkers for identifying early recurring events and contributing to early diagnosis for Prostate Adenocarcinoma.

Background: Compared to non-recurrent type, recurrent prostate adenocarcinoma (PCa) is highly fatal, and significantly shortens the survival time of affected patients. Early and accurate laboratory diagnosis is particularly important in identifying patients at high risk of recurrence, necessary for additional systemic intervention. We aimed to develop efficient and accurate diagnostic and prognostic biomarkers for new PCa following radical therapy. Methods: We identified differentially expressed genes (DEGs) and clinicopathological data of PCa patients from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) repositories. We then uncovered the most relevant clinical traits and genes modules associated with PCa prognosis using the Weighted gene correlation network analysis (WGCNA). Univariate Cox regression analysis and multivariate Cox proportional hazards (Cox-PH) models were performed to identify candidate gene signatures related to Disease-Free Interval (DFI). Data for internal and external cohorts were utilized to test and validate the accuracy and clinical utility of the prognostic models. Results: We constructed and validated an accurate and reliable model for predicting the prognosis of PCa using 5 Gleason score-associated gene signatures (ZNF695, CENPA, TROAP, BIRC5 and KIF20A). The ROC and Kaplan-Meier analysis revealed the model was highly accurate in diagnosing and predicting the recurrence and metastases of PCa. The accuracy of the model was validated using the calibration curves based on internal TCGA cohort and external GEO cohort. Using the model, patients could be prognostically stratified in to various groups including TNM classification and Gleason score. Multivariate analysis revealed the model could independently predict the prognosis of PCa patients and its utility was superior to that of clinicopathological characteristics. In addition, we fund the expression of the 5 gene signatures strongly and positively correlated with tumor purity but negatively correlated with infiltration CD8+ T cells to the tumor microenvironment. Conclusions: A 5 gene signatures can accurately be used in the diagnosis and prediction of PCa prognosis. Thus this can guide the treatment and management prostate adenocarcinoma.

Prostatic aspirated cellular RNA analysis enables fast diagnosis and staging of prostate cancer.

OBJECTIVE: The aim of this study is to investigate the potential application of prostatic aspirated cellular RNA analysis technique for fast diagnosing and staging prostate cancer. METHODS: Prostatic aspirated cells were obtained immediately after transrectal ultrasound (TRUS)-guided needle biopsy. Cellular RNA such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA, prostate specific antigen (PSA) mRNA and prostate-specific RNA (PCA3) mRNA were analyzed by using Reverse Transcription-Polymerase Chain Reaction (RT-PCR). PCA3 score was calculated as the ratio of PCA3 mRNA to PSA mRNA expression. Diagnostic performance of the fast-aspirated cellular RNA analysis technique for determining prostate cancer and metastatic status were evaluated by developing receiver operating characteristic curves (ROC), and the correlation between aspirated cellular RNA mRNA expressions and risk grouping was calculated, to investigate the underlying potential for PCa staging. RESULTS: PCA3 score was significantly higher in prostatic aspirated cells obtained from cancerous tissues than noncancerous tissues. The median aspirated cellular PCA3 score was higher in patients with PCa compared to BPH, and presenting an area under the ROC curve (AUC) of 0.87 (95%CI: 0.79-0.94) for PCa diagnosis. Multivariate regression analysis revealed that baseline median aspirated cellular PCA3 score (OR=9.316, 95%CI: 1.045-83.033, P<0.05) was an independent predictive factor for metastatic status in PCa patients. CONCLUSION: The ease of use and minimal complexity of fast prostatic aspirated cellular RNA analysis may be a valuable diagnostic technique, providing urgent diagnostic information for accurate PCa diagnosing and staging.

S100A1 is a sensitive and specific cardiac biomarker for early diagnosis and prognostic assessment of acute myocardial infarction measured by chemiluminescent immunoassay.

BACKGROUND: A member of the S100 family of Ca2+-binding proteins, S100A1 is highly expressed in cardiac muscle tissue. Although this protein is considered an indicator of acute myocardial infarction (AMI), high-throughput and sensitive detection methods are still urgently needed. We constructed a rapid and sensitive method for detecting S100A1 and to investigate the clinical utility of S100A1 as a biomarker for the early diagnosis of AMI and subsequent prognostic assessments. We developed an automated chemiluminescent immunoassay to detect S100A1. We then analyzed the performance of the newly developed assay including evaluation of the analytical sensitivity, analytical selectivity, linear range, accuracy and repeatability. METHODS: We recruited 87 patients with AMI or angina pectoris to explore the value of this marker for the early diagnosis and prognostic assessment. RESULTS: The chemiluminescent-immune-based S100A1 assay had functional analytical sensitivity with a detection limit of 0.13 ng/ml, and a wide linear range of 0.13-31.66 ng/ml. It also exhibited good repeatability with intra-assay and inter-assay findings of <5% and <15%, respectively. Plasma S100A1 was found to have a higher diagnostic sensitivity than conventional cardiac biomarkers (creatine kinase-MB and cardiac troponin T). The survival analysis showed that a higher concentration of plasma S100A1 (>1.02 ng/ml) was notably associated with the poor prognosis of AMI patients after first PCI. CONCLUSIONS: Measurement of circulating S100A1 concentrations with our newly developed chemiluminescent-immune-based assay shows potential for use in the clinic. This assay could enable early identification and prognostic assessment of AMI.

A Multivariate Diagnostic Model Based on Urinary EpCAM-CD9-Positive Extracellular Vesicles for Prostate Cancer Diagnosis.

INTRODUCTION: Prostate cancer (PCa) is one of the most frequently diagnosed cancers and the leading cause of cancer death in males worldwide. Although prostate-specific antigen (PSA) screening has considerably improved the detection of PCa, it has also led to a dramatic increase in overdiagnosing indolent disease due to its low specificity. This study aimed to develop and validate a multivariate diagnostic model based on the urinary epithelial cell adhesion molecule (EpCAM)-CD9-positive extracellular vesicles (EVs) (uEVEpCAM-CD9) to improve the diagnosis of PCa. METHODS: We investigated the performance of uEVEpCAM-CD9 from urine samples of 193 participants (112 PCa patients, 55 benign prostatic hyperplasia patients, and 26 healthy donors) to diagnose PCa using our laboratory-developed chemiluminescent immunoassay. We applied machine learning to training sets and subsequently evaluated the multivariate diagnostic model based on uEVEpCAM-CD9 in validation sets. RESULTS: Results showed that uEVEpCAM-CD9 was able to distinguish PCa from controls, and a significant decrease of uEVEpCAM-CD9 was observed after prostatectomy. We further used a training set (N = 116) and constructed an exclusive multivariate diagnostic model based on uEVEpCAM-CD9, PSA, and other clinical parameters, which showed an enhanced diagnostic sensitivity and specificity and performed excellently to diagnose PCa [area under the curve (AUC) = 0.952, P < 0.0001]. When applied to a validation test (N = 77), the model achieved an AUC of 0.947 (P < 0.0001). Moreover, this diagnostic model also exhibited a superior diagnostic performance (AUC = 0.917, P < 0.0001) over PSA (AUC = 0.712, P = 0.0018) at the PSA gray zone. CONCLUSIONS: The multivariate model based on uEVEpCAM-CD9 achieved a notable diagnostic performance to diagnose PCa. In the future, this model may potentially be used to better select patients for prostate transrectal ultrasound (TRUS) biopsy.

Combined Use of Fecal Biomarkers in Inflammatory Bowel Diseases: Oncostatin M and Calprotectin.

BACKGROUND: Fecal biomarkers have emerged as one of the most useful tools for clinical management of inflammatory bowel disease (IBD). Oncostatin M (OSM), like fecal calprotectin (FC), is highly expressed in the inflamed intestinal mucosa which may have potential usefulness. We aimed to evaluate the additional utility of these two fecal biomarkers for IBD diagnosis, activity, and prediction of infliximab response over FC alone. METHODS: In group 1, 236 IBD patients (145 Crohn's disease, 91 ulcerative colitis), 50 disease controls, and 32 healthy controls were recruited for IBD diagnosis and activity. In group 2, baseline stool samples were collected from 62 patients to predict infliximab response at week 28 and 52. The performance of fecal biomarkers for IBD management was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: Fecal OSM and FC levels were increased in IBD patients and were positively correlated with clinical and endoscopic activity. Their combination showed a better ability for disease diagnosis (AUC = 0.93) and slightly improved the capability to identify mucosal healing (AUC = 0.923). Baseline OSM and FC levels were elevated in non-responders at week 28 and 52. The AUCs of OSM, FC, and their combination to predict therapeutic response were 0.763, 0.834, and 0.859 at week 28, 0.638, 0.661, and 0.704 at week 52, respectively. Combined use of fecal and blood biomarkers improved predictive accuracy with an AUC of 0.919 at week 28 and 0.887 at week 52. CONCLUSION: In addition to FC, OSM is a novel fecal biomarker, and their combination is more beneficial for disease diagnosis and prediction of infliximab response but not for disease activity in IBD patients. Further larger-scale studies are required to confirm our findings.

Integrated profiling identifies SLC5A6 and MFAP2 as novel diagnostic and prognostic biomarkers in gastric cancer patients.

Gastric cancer (GC) is one of the leading causes of malignancy­associated mortality worldwide. However, the underlying molecular mechanisms of GC are unclear and the prognosis of GC is poor. Therefore, it is important and urgent to explore the underlying mechanisms and screen for novel diagnostic and prognostic biomarkers, as well as therapeutic targets. In the current study, scale­free gene co­expression networks were constructed using weighted gene co­expression network analysis, the potential associations between gene sets and clinical features were investigated, and the hub genes were identified. The gene expression profiles of GSE38749 were downloaded from the Gene Expression Omnibus database. RNA­seq and clinical data for GC from The Cancer Genome Atlas were utilized for verification. Furthermore, the expression of candidate biomarkers in gastric tissues was investigated. Survival analysis was performed using Kaplan­Meier and log­rank test. The predictive role of candidate biomarkers in GC was evaluated using a receiver operator characteristic (ROC) curve. Gene Ontology, gene set enrichment analysis and gene set variation analysis methods were used to interpret the function of candidate biomarkers in GC. A total of 29 modules were identified via the average linkage hierarchical clustering. A significant module consisting of 48 genes associated with clinical traits was found; three genes with high connectivity in the clinical significant module were identified as hub genes. Among them, SLC5A6 and microfibril­associated protein 2 (MFAP2) were negatively associated with the overall survival, and their expression was elevated in GC compared with non­tumor tissues. Additionally, ROC curves indicated that SLC5A6 and MFAP2 showed a good diagnostic power in discriminating cancerous from normal tissues. SLC5A6 and MFAP2 were identified as novel diagnostic and prognostic biomarkers in GC patients; both of these genes were first reported here in connection with GC and deserved further research.

Rapid and Quantitative Analysis of Exosomes by a Chemiluminescence Immunoassay Using Superparamagnetic Iron Oxide Particles.

Since the discovery of exosomes, their potential diagnostic value has been the focus of considerable research. However, the lack of a rapid and simple technique for the quantitative analysis of exosomes greatly limits the application of exosomes in clinical research. In this study, we describe a newly developed one-step chemiluminescence immunoassay for the rapid quantitative analysis of exosomes from biofluids. Our new technique, named ExoNANO, adopts a double-antibody sandwich strategy using anti-CD63 antibody-conjugated superparamagnetic iron oxide particles (SIOPs) and acridinium ester (ACE)-labeled anti-CD9 antibodies. SIOPs have narrow size distribution and high magnetic susceptibility, and ACE has excellent chemiluminescent properties such as low background signal and no need for a catalyst. We demonstrated that ExoNANO allows the quantitative analysis of exosomes in the range of 2.92 ×105 to 2.80×108 particles/µL, with a limit of detection of 2.63×105 particles/µL. Using ExoNANO, we quantified exosomes in cell culture medium and clinical biofluids such as serum, saliva, ascitic fluid, and cerebrospinal fluid. We believe that ExoNANO might pave the way for the rapid isolation and quantitative analysis of exosomes for routine clinical applications.