Biomarkers For Clinical Diagnosis Research Articles

Photothermal visual sensing of alkaline phosphatase based on the etching of Au@MnO2 core-shell nanoparticles

Alkaline phosphatase (ALP), as a crucial enzyme involved in many physiological activities, is always used as one of the significant biomarkers in clinical diagnosis. Herein, a novel, simple, and effective photothermal quantitative method based on the etching of MnO2-coated gold nanoparticles (Au@MnO2 NPs) was established for ALP activity assay with a household thermometer-based visual readout. The photothermal effect of Au@MnO2 NPs is much higher than that of MnO2 NPs or Au NPs. The MnO2 shell of Au@MnO2 NPs can be etched by ascorbic acid, a product of ALP-catalyzed hydrolysis of 2-phospho-l-ascorbic acid. With the etching of Au@MnO2 NPs, the photothermal conversion efficiency decreased gradually, causing the decrease of the temperature increment of the solutions by degrees. A household thermometer, instead of large-scale and professional instruments, was used as a signal reader to realize the visual quantitative detection. The photothermal platform was used successfully for the determination of ALP with a wide linear range from 2.0 to 50 U/L and a detection limit as low as 0.75 U/L. Moreover, the inhibition efficiency of sodium vanadate for ALP activity was investigated, proving the photothermal quantitative method will be a potential platform for screening enzyme inhibitors. Such a sensitive, facile, and low-cost sensing assay provides a new prospect to develop platforms for point-of-care testing.

Identification of Differential Metabolites Between Type 2 Diabetes and Postchronic Pancreatitis Diabetes (Type 3c) Based on an Untargeted Metabolomics Approach.

A nontargeted metabolomics approach was established to characterize serum metabolic profile in type 3c diabetes mellitus (T3cDM) secondary to chronic pancreatitis and compare with T2DM. Forty patients were recruited for metabolite analysis based on liquid chromatography-mass spectrometry. Cluster heatmap and KEGG metabolic pathway enrichment analysis were used to analyze the specific and differential metabolites. The receiver operating characteristics (ROCs) were generated and correlation analysis with clinical data was conducted. Metabolites including sphingosine, lipids, carnitine, bile acid, and hippuric acid were found to be different between T2DM and T3cDM, mainly enriched in bile acid biosynthesis, fatty acid biosynthesis, and sphingolipid metabolic pathways. The ROCs were generated with an area under the curve of 0.907 (95% confidence interval, 0.726-1) for the model with 15 metabolites. T3cDM is characterized by increased sphingosine, carnitine, bile acid, and most lipids, providing novel biomarkers for clinical diagnosis and a future direction in research on pathophysiological mechanisms.

A Dual Endogenous Stimuli-Responsive Framework Nucleic Acid Nanodevice for MicroRNA Imaging

Open AccessCCS ChemistryRESEARCH ARTICLES29 Dec 2022A Dual Endogenous Stimuli-Responsive Framework Nucleic Acid Nanodevice for MicroRNA Imaging Lie Li, Haiyan Chen, Xiaohong Wen, Suping Li, Mei Yang, Qiuping Guo and Kemin Wang Lie Li Google Scholar More articles by this author , Haiyan Chen Google Scholar More articles by this author , Xiaohong Wen Google Scholar More articles by this author , Suping Li Google Scholar More articles by this author , Mei Yang Google Scholar More articles by this author , Qiuping Guo Google Scholar More articles by this author and Kemin Wang Google Scholar More articles by this author https://doi.org/10.31635/ccschem.022.202202465 SectionsAboutPDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinked InEmail Framework nucleic acids (FNAs) have emerged as intelligent sensing systems for the detection of tumor-related biomarkers in living cells. However, orthogonally controlled manipulation of FNAs-based nanodevices for on-site imaging of microRNAs (miRNAs) remains an intractable challenge. Herein, we report a dual endogenous stimuli-responsive framework nucleic acid nanodevice that can perform miRNA sensing and imaging in a tumor-specific manner. The sensing function of the nanodevice is silent (OFF) by rationally incorporated ATP aptamer and abasic site, which can be activated (ON) with ATP and human apurinic/apyrimidinic endonuclease 1 (APE1) in tumor cells, enabling the on-site and efficient miRNA imaging with improved tumor specificity. Furthermore, we demonstrate the capability of the nanodevice for specific miRNA imaging both in living cells and in vivo based on the “dual keys” (overexpressed ATP and APE1 in tumors) priming mode. Therefore, this work illustrates a simple biosensing methodology with great potential for precise imaging of tumor biomarkers in clinical diagnosis and therapeutic evaluation. Download figure Download PowerPoint Previous articleNext article FiguresReferencesRelatedDetails Issue AssignmentVolume 0Issue jaPage: 1-19 Copyright & Permissions© 2022 Chinese Chemical Society Downloaded 0 times PDF downloadLoading ...

A Sensitive Immunochromatographic Test Strip Based on Hydrophobic Quantum Dots Incorporated into Mg/Fe Nanoflowers for HCG Detection

As the most widely used disposable paper-based diagnostic tool in the world, immunochromatographic test strips (ICTS) have occupied more and more positions in the field of rapid diagnosis due to their ease of operation and affordability. Therefore, the development of an easily prepared, sensitive, and accurate signal reporter is of great significance for the detection of some low-abundance biomarkers in clinical diagnosis. Herein, Mg/Fe layered double hydroxide nanoflowers (MF NFs) were selected as adsorption templates and sulfhydryl-functionalized, followed by one-step loading of hydrophobic CdSe/ZnS quantum dots in the organic phase via a metal-thiol covalent bond. After coating the reporter with branched polyethyleneimine (PEI), a novel ICTS fluorescent reporter was prepared. The modification of PEI not only improved the hydrophilicity of MF@CdSe/ZnS NFs but also introduced amino functional groups on the surface of the reporter for subsequent conjugation with antibodies. X-ray photoelectron spectroscopy, UV-vis absorption, X-ray diffraction, fluorescence spectroscopy, and infrared spectroscopy were used to characterize the composition of MF@CdSe/ZnS NFs. Under the optimal experimental conditions, the detection range of MF@CdSe/ZnS@PEI-ICTS for the model analyte HCG was 0.1–500 mIU/mL, and the limit of detection (LOD) reached was 0.1 mIU/mL. The potential for practical application was validated by the detection of HCG in spiked healthy human serum, showing overall recoveries between 90.48 and 116.1% with coefficients of variation that ranged from 3.66 to 12.91%.

Expression and clinical significance of short-chain fatty acids in pregnancy complications.

To investigate the expression of short-chain fatty acids (SCFAs)-metabolites of intestinal flora-in gestational complications of gestational diabetes mellitus (GDM), preeclampsia (PE), and intrahepatic cholestasis of pregnancy (ICP), and its clinical significance. Targeted metabonomics was used to detect SCFAs in the serum of 28 GDM pregnant women, 28 PE pregnant women, 29 ICP pregnant women, and 27 healthy pregnant women (NP); their expression changes were observed; the correlation between SCFAs and clinical characteristics was studied; and their potential as biomarkers for clinical diagnosis was evaluated. There were significant differences in the SCFA metabolic spectrum between the GDM, PE, ICP, and NP groups. Quantitative analysis showed that the content of isobutyric acid in the three pregnancy complications groups (the GDM, PE, and ICP groups) was significantly higher than that in the NP group (p < 0.05), and other SCFAs also showed significant differences in the three pregnancy complications groups compared with the NP group (p < 0.05). Receiver operating characteristic (ROC) curve analysis of the generalized linear model showed that multiple SCFAs were highly sensitive and specific as diagnostic markers in the pregnancy complications groups, where isobutyric acid was highly predictive in GDM (area under the ROC curve (AUC) = 0.764) and PE (AUC = 1), and caproic acid was highly predictive in ICP (AUC = 0.968), with potential clinical application. The metabolic products of intestinal flora, SCFAs, during pregnancy are closely related to pregnancy complications (GDM, PE, and ICP), and SCFAs can be used as potential markers of pregnancy complications.

Human circulating small non-coding RNA signature as a non-invasive biomarker in clinical diagnosis of acute myeloid leukaemia.

Background: Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; AML is highly heterogeneous and involves abnormalities at multiple omics levels. Small non-coding RNAs (sncRNAs) present in body fluids are important regulatory molecules and considered promising non-invasive clinical diagnostic biomarkers for disease. However, the signature of sncRNA profile alteration in AML patient serum and bone marrow supernatant is still under exploration. Methods: We examined data for blood and bone marrow samples from 80 consecutive, newly-diagnosed patients with AML and 12 healthy controls for high throughput small RNA-sequencing. Differentially expressed sncRNAs were analysed to reveal distinct patterns between AML patients and controls. Machine learning methods were used to evaluate the efficiency of specific sncRNAs in discriminating individuals with AML from controls. The altered expression level of individual sncRNAs was evaluated by RT-PCR, Q-PCR, and northern blot. Correlation analysis was employed to assess sncRNA patterns between serum and bone marrow supernatant. Results: We identified over 20 types of sncRNA categories beyond miRNAs in both serum and bone marrow supernatant, with highly coordinated expression patterns between them. Non-classical sncRNAs, including rsRNA (62.86%), ysRNA (14.97%), and tsRNA (4.22%), dominated among serum sncRNAs and showed sensitive alteration patterns in AML patients. According to machine learning-based algorithms, the tsRNA-based signature robustly discriminated subjects with AML from controls and was more reliable than that comprising miRNAs. Our data also showed that serum tsRNAs to be closely associated with AML prognosis, suggesting the potential application of serum tsRNAs as biomarkers to assist in AML diagnosis. Conclusions: We comprehensively characterized the expression pattern of circulating sncRNAs in blood and bone marrow and their alteration signature between healthy controls and AML patients. This study enriches research of sncRNAs in the regulation of AML, and provides insights into the role of sncRNAs in AML.

Weighted gene co-expression network analysis combined with machine learning validation to identify key hub biomarkers in colorectal cancer.

Colorectal cancer (CRC) is one of the most common malignancies worldwide; however, the potentially possible molecular biological mechanism of CRC is still not completely comprehended. This study aimed to confirm candidate key hub genes involved in the growth and development of CRC and their connection with immune infiltration as well as the related pathways. Gene expression data were selected from the GEO dataset. Hub genes for CRC were identified on the basis of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and LASSO regression. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were applied to reveal possible functions of the differential genes. Single-sample GSEA (ssGSEA) was implemented to identify the relationship between immune cells infiltration and hub genes. Two hundred and sixty-two differentially expressed genes (DEGs) were identified. Three modules were acquired based on WGCNA, and the blue module presented the highest relevance with CRC. Ten hub genes (AQP8, B3GALT5, CDH3, CEMIP, CPM, FOXQ1, PLAC8, SCNN1B, SPINK5, and SST) were acquired with LASSO analysis as underlying biomarkers for CRC. Compared with normal tissues, CRC tissues presented significantly higher numbers of CD4 T cells, CD8 T cells, B cells, natural regulatory T (Treg) cells, and monocytes. The functional enrichment analyses demonstrated that hub genes were primarily enriched in metabolic process, inflammatory-related, and immune-related response. Ten hub genes were identified to be involved in the occurrence and development of CRC and may be deemed as novel biomarkers for clinical diagnosis and treatment.

Enzymatic reaction modulated gold nanoparticle aggregation-induced photothermal and smartphone readable colorimetry dual-mode biosensing platform for trypsin detection in clinical samples

There is an urgent demand to develop a portable and user-friendly biosensing platform for accurately and rapidly detecting biomarkers in clinical diagnosis. In this work, a photothermal and smartphone-based colorimetric dual-mode biosensing platform was proposed for trypsin assay based on the localized surface plasmon resonance (LSPR) effect of gold nanoparticles (Au NPs). Two competing processes were presented between the protection and the destabilization of dispersed Au NPs, respectively. Bovine serum albumin (BSA) can restrain the Au NPs aggregation due to the surface protection of Au NPs in the salt solution. In the presence of trypsin, the Au NPs are aggregated due to the enzymatic digestion of surface BSA ligand and electrostatic interaction, resulting strong photothermal effect and obvious RGB (Red/Green/Blue) value change (color from red to blue). The whole process can be performed within 1 h and the point-of-care testing (POCT) was realized by using a thermometer and smartphone as signal recorders. The limits of detection (LODs) were calculated to be 6 µg mL−1 by photothermal sensing and 1.2 µg mL−1 by RGB recognition. This biosensing platform was successfully used for trypsin assay in clinical acute pancreatitis samples and showed great consistency with clinical diagnostic results, validating the potential POCT application.

Identification and Validation of a Prognostic Signature Based on Methylation Profiles and Methylation-Driven Gene DAB2 as a Prognostic Biomarker in Differentiated Thyroid Carcinoma.

Recurrence is the major death cause of differentiated thyroid carcinoma (DTC), and a better understanding of recurrence risk at early stage may lead to make the optimal medical decision to improve patients' prognosis. The 2015 American Thyroid Association (ATA) risk stratification system primary based on clinic-pathologic features is the most commonly used to describe the initial risk of persistent/recurrent disease. Besides, multiple prognostics models based on multigenes expression profiles have been developed to predict the recurrence risk of DTC patients. Recent evidences indicated that aberrant DNA methylation is involved in the initiation and progression of DTC and can be useful biomarkers for clinical diagnosis and prognosis prediction of DTC. Therefore, there is a need for integrating gene methylation feature to assess the recurrence risk of DTC. Gene methylation profile from The Cancer Genome Atlas (TCGA) was used to construct a recurrence risk model of DTC by successively performed univariate Cox regression, LASSO regression, and multivariate Cox regression. Two Gene Expression Omnibus (GEO) methylation cohorts of DTC were utilized to validate the predictive value of the methylation profiles model as external cohort by receiver operating characteristic (ROC) curve and survival analysis. Besides, CCK-8, colony-formation assay, transwell, and scratch-wound assay were used to investigate the biological significance of critical gene in the model. In our study, we constructed and validated a prognostic signature based on methylation profiles of SPTA1, APCS, and DAB2 and constructed a nomogram based on the methylation-related model, age, and AJCC_T stage that could provide evidence for the long-term treatment and management of DTC patients. Besides, in vitro experiments showed that DAB2 inhibited proliferation, colony-formation, and migration of BCPAP cells and the gene set enrichment analysis and immune infiltration analysis showed that DAB2 may promote antitumor immunity in DTC. In conclusion, promoter hypermethylation and loss expression of DAB2 in DTC may be a biomarker of unfavorable prognosis and poor response to immune therapy.

Hsa-miR-607, lncRNA TUG1 and hsa_circ_0071106 can be combined as biomarkers in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is a multifactorial disorder that leads to alterations in gene regulation. ncRNAs have the characteristics of tissue specificity, disease specificity, timing specificity, high stability and post transcriptional regulation effect. These preconditions are more conducive to promote ncRNA to become a new biomarker for clinical diagnosis. Our study aims to explore the relationship between circRNA, lncRNA, miRNA and T2DM, and to evaluate their diagnostic value for T2DM. A total of 101 pairs of T2DM and controls were conducted in the study. QRT-PCR was used to study the differential expression of circRNAs, miRNAs and lncRNAs. ROC curve was used to estimate their diagnostic value in T2DM. Compared with healthy controls, the expression levels of hsa_circ_0071106, hsa_circ_0000284, hsa_circ_0071271, hsa-miR-29a-5p, hsa-miR-3690, hsa-miR-607, lncRNA MEG3 and lncRNA TUG1were higher in T2DM (all P < 0.05). The AUCs of hsa_circ_0071106, hsa-miR-607 and lncRNA TUG1 for diagnosis of T2DM were 0.563,0.645 and 0.642, respectively. The combined AUC of hsa-miR-607, lncRNA TUG1 and hsa_circ_0071106 was 0.798 ([0.720~0.875], P < 0.001). Moreover, the sensitivity of combined diagnosis was 75.2% and the specificity was 100.0%. The levels of lncRNA TUG1, hsa-miR-607 and hsa_circ_0071106 in peripheral blood have potential clinical diagnostic value for T2DM.

TMT-based quantitative proteomics analysis and potential serum protein biomarkers for systemic lupus erythematosus

Systemic lupus erythematosus (SLE) was not only a typical systemic autoimmune disease, but also one of the most challenging heterogeneous diseases for physicians. Currently, the pathogenesis of SLE was unclear, and there were no accurate, universal or easy-to-use diagnostic criteria for assessing SLE activity and predicting SLE severity. Proteins were direct effectors of biological mechanisms, and were closer to clinical phenotypes than the other discovered biomarkers. Moreover, proteins were widely used as biomarkers for clinical diagnosis and mechanism research of many diseases. Herein, we compared the proteins profiles of healthy individuals (HCs) and SLE patients to reveal the pathogenesis and provide evidence for diagnosis and management of persons with SLE. Serum samples were collected from 28 SLE patients and 30 HCs. Tandem mass tag (TMT)-based quantitative proteomics method was used to identify, screen and detect differentially expressed proteins (DEPs) in the collected serum samples. A total of 744 proteins were identified, and 84 of them were considered as DEPs with 71 upregulated and 13 downregulated. Bioinformatics analysis suggested that these DEPs were mainly involved in many biological processes, including immune response, signal transduction, inflammatory response, proteolysis, innate immune response and apoptosis, which were closely related to the pathogenesis of SLE. After comprehensive analysis, serum amyloid A1 (SAA1) and endothelin (CD248) were identified as specific biomarkers for the diagnosis of SLE, and were confirmed by subsequent enzyme-linked immunosorbent assays (ELISA), indicating a high reliability of TMT-based quantitative proteomics results. Areas under the ROC curve (AUC) results confirmed that SAA1 and CD248 combination as early immune diagnosis biomarkers of SLE presented excellent sensitivity and specificity.

Rapid Quantification of Endogenous Steroids in Human Serum Using Leidenfrost Effect-Assisted Thermal Desorption Atmospheric Pressure Photoionization Orbitrap Mass Spectrometry.

Unconjugated sex steroids in human serum play a crucial role in physiological and pathological studies and are frequently considered as biomarkers in clinical diagnosis. Because of their low polarity, poor volatility, and low concentration, the rapid and highly sensitive analysis of sex steroids in real serum matrix by ambient mass spectrometry is still challenging. Here, Leidenfrost effect-assisted thermal desorption atmospheric pressure photoionization orbitrap mass spectrometry (LETD-APPI-MS) was developed and applied to quantify free sex steroids in human serum without derivatization and chromatography separation within a few minutes. The concentration of target analyte could be increased by approximately two orders during the LETD process. The limit of quantifications and detections of endogenous sex steroids in human serum were measured at the ppt level. In contrast with commonly used immunoassays in clinical laboratories, LETD-APPI-MS enables the accurate measurements of multiple free sex steroids without the interference of cross-reactions. The endogenous sex steroids of 38 female serums at four physiological stages during pregnancy were rapidly tested by LETD-APPI-MS, whose results were highly consistent with that using liquid chromatography-atmospheric pressure chemical ionization mass spectrometry (LC-APCI-MS), indicating LETD-APPI-MS has a strong clinical application potential in steroid analysis.

Targeted protein quantitation in human body fluids by mass spectrometry.

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Serum proteomics unveil characteristic protein diagnostic biomarkers and signaling pathways in patients with esophageal squamous cell carcinoma

BackgroundEsophageal squamous cell carcinoma (ESCC) is a common digestive tract malignant tumor with high incidence and dismal prognosis worldwide. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of ESCC are not unequivocally understood yet. The serum proteome may provide valuable clues for the early diagnosis of ESCC and the discovery of novel molecular insights.MethodsIn the current study, an optimized proteomics approach was employed to discover novel serum-based biomarkers for ESCC, and unveil abnormal signal pathways. Gene ontology (GO) enrichment analysis was done by Gene Set Enrichment Analysis (GSEA) and Metascape database, respectively. Pathway analysis was accomplished by GeneCards database. The correlation coefficient was assessed using Pearson and distance correlation analyses. Prioritized candidates were further verified in two independent validation sets by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) staining.ResultsA total of 633 non-redundant proteins were identified in the serum of patients with ESCC, of which 59 and 10 proteins displayed a more than 1.5-fold increase or decrease compared with healthy controls. Verification was performed for six candidate biomarkers, including S100A8/A9, SAA1, ENO1, TPI1 and PGAM1. Receiver operating characteristics (ROC) curve plotting showed the high diagnostic sensitivity and specificity of these six protein molecules as a biomarker panel: the area under characteristic curve (AUC) is up to 0.945. Differentially expressed proteins were subjected to functional enrichment analysis, which revealed the dysregulation of signaling pathways mainly involved in glycolysis, TLR4, HIF-1α, Cori cycle, TCA cycle, folate metabolism, and platelet degranulation. The latter finding was all the more noteworthy as a strong positive correlation was discovered between activated glycolysis and TLR4 pathways and unfavorable clinicopathological TNM stages in ESCC.ConclusionsOur findings propose a potential serum biomarker panel for the early detection and diagnosis of ESCC, which could potentially broaden insights into the characteristics of ESCC from the proteomic perspective.

A novel polymer-based nitrocellulose platform for implementing a multiplexed microfluidic paper-based enzyme-linked immunosorbent assay

Nitrocellulose (NC) membranes, as porous paper-like substrates with high protein-binding capabilities, are very popular in the field of point-of-care immunoassays. However, generating robust hydrophobic structures in NC membranes to fabricate microfluidic paper-based analytical devices (μPADs) remains a great challenge. At present, the main method relies on an expensive wax printer. In addition, NC membranes very easy to adhere during the printing process due to electrostatic adsorption. Herein, we developed a facile, fast and low-cost strategy to fabricate μPADs in NC membranes by screen-printing polyurethane acrylate (PUA) as a barrier material for defining flow channels and reaction zones. Moreover, hydrophobic barriers based on UV-curable PUA can resist various surfactant solutions and organic solvents that are generally used in immunoassays and biochemical reactions. To validate the feasibility of this PUA-based NC membrane for immunoassays in point-of-care testing (POCT), we further designed and assembled a rotational paper-based analytical device for implementing a multiplexed enzyme-linked immunosorbent assay (ELISA) in a simple manner. Using the proposed device under the optimal conditions, alpha fetoprotein (AFP) and carcinoembryonic antigen (CEA) could be identified, with limits of detection of 136 pg/mL and 174 pg/mL, respectively, which are below the threshold values of these two cancer biomarkers for clinical diagnosis. We believe that this reliable device provides a promising platform for the diagnosis of disease based on ELISA or other related bioassays in limited settings or remote regions.

Pyroptosis-Related Gene Signature and Expression Patterns in the Deterioration of Atherosclerosis.

Background Pyroptosis has been shown to be involved in the overall process of atherosclerosis. This study was aimed at investigating pyroptosis-related gene expression patterns in atherosclerosis and their diagnostic significance. Methods and Results In GSE100927, fifty-four pyroptosis-related genes were identified. Between atherosclerotic plaques and normal samples, the expression patterns of pyroptosis-related genes were significantly different. In order to construct a pyroptosis-related risk score signature (PRSS), the least absolute shrinkage and selection operator (LASSO) was combined with multivariate logistic regression to screen twelve genes. The diagnostic efficiency of the PRSS performed well in GSE43292, as shown by the results of receiver-operating characteristics (ROCs). Consensus clustering identified two expression patterns of pyroptosis-related genes in different statuses of atherosclerotic plaque in GSE163154. The biological behavior of the different clusters was examined by the gene set variation analysis (GSVA). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses revealed that the differentially expressed genes (DEGs) in the two clusters were enriched in the immune response. The Cytoscape software was used to construct protein-protein interaction (PPI) networks for hub gene screening. Following that, the Drug Gene Interaction Database (DGIdb) was utilized to find 47 possible medicines and chemical compounds that interact with hub genes in atherosclerotic plaques. Conclusion The results of this study showed that pyroptosis-related genes contribute to the progression of atherosclerosis and may serve as biomarkers in clinical diagnosis as well as novel therapeutic targets for the treatment of AS.

Ultra-trace enriching biosensing in nanoliter sample

Rapid detection and accurate analysis of trace samples is an important prerequisite for precision medicine. Here we integrated capillary with ultrasound to induce biomarkers enrichment in nanoliter samples, and developed a nanoliter sample enrichment analysis method for ultra-trace miRNA biosensing. The interaction between ultrasonic field and capillary provides a gradient ultrasound field, which is essential for the aggregation of functionalized microspheres along with the enrichment of specific biomarkers. The results indicated that the enrichment of the biomarkers effectively enhanced the fluorescence intensity, and the limit of detection reaches 7.8✕10−12 M in 100 nL. Such integrated device can realize ultrasonic enrichment and visual analysis of target samples, and provides a new idea for rapid and highly sensitive detection of ultra-trace biomarkers in clinical diagnosis.

The Landscape of lncRNAs in Multiple Myeloma: Implications in the "Hallmarks of Cancer", Clinical Perspectives and Therapeutic Opportunities.

Simple SummaryMultiple myeloma (MM) is an aggressive hematological neoplasia caused by the uncontrolled proliferation of aberrant plasmacells. Neoplastic transformation and progression are driven by a number of biological processes, called ‘hallmarks of cancer’, which are regulated by different molecules, including long non-coding RNAs. A deeper understanding of the mechanisms that regulate MM development and progression will help to improve patients stratification and management, and promote the identification of new therapeutic targets.Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nucleotides that are not translated into proteins. Nowadays, lncRNAs are gaining importance as key regulators of gene expression and, consequently, of several biological functions in physiological and pathological conditions, including cancer. Here, we point out the role of lncRNAs in the pathogenesis of multiple myeloma (MM). We focus on their ability to regulate the biological processes identified as “hallmarks of cancer” that enable malignant cell transformation, early tumor onset and progression. The aberrant expression of lncRNAs in MM suggests their potential use as clinical biomarkers for diagnosis, patient stratification, and clinical management. Moreover, they represent ideal candidates for therapeutic targeting.

A new finding in the key prognosis-related proto-oncogene FYN in hepatocellular carcinoma based on the WGCNA hub-gene screening trategy

BackgroundHepatocellular carcinoma (HCC) is the third-most deadly cancer worldwide. More breakthroughs are needed in the clinical practice for liver cancer are needed, and new treatment strategies are required. This study aims to determine the significant differences in genes associated with LIHC and further analyze its prognostic value further.MethodsHere, we used the TCGA-LIHC database and the profiles of GSE25097 from GEO to explore the differentially co-expressed genes in HCC tissues compared with paratumor (or healthy) tissues. Then, we utilized WGCNA to screen differentially co-expressed genes. Finally, we explored the function of FYN in HCC cells and xenograft tumor models.ResultsWe identified ten hub genes in the protein–protein interaction (PPI) network, but only three (COLEC10, TGFBR3, and FYN) appeared closely related to the prognosis. The expression of FYN was positively correlated with the prognosis of HCC patients. The xenograft model showed that overexpression of FYN could significantly inhibit malignant tumor behaviors and promote tumor cell apoptosis.ConclusionThus, FYN may be central to the development of LIHC and maybe a novel biomarker for clinical diagnosis and treatment.

Exploring the Change of Host and Microorganism in Chronic Obstructive Pulmonary Disease Patients Based on Metagenomic and Metatranscriptomic Sequencing.

BackgroundChronic obstructive pulmonary disease (COPD) is a universal respiratory disease resulting from the complex interactions between genes and environmental conditions. The process of COPD is deteriorated by repeated episodes of exacerbations, which are the primary reason for COPD-related morbidity and mortality. Bacterial pathogens are commonly identified in patients’ respiratory tracts both in the stable state and during acute exacerbations, with significant changes in the prevalence of airway bacteria occurring during acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Therefore, the changes in microbial composition and host inflammatory responses will be necessary to investigate the mechanistic link between the airway microbiome and chronic pulmonary inflammation in COPD patients.MethodsWe performed metatranscriptomic and metagenomic sequencing on sputum samples for twelve AECOPD patients before treatment and for four of them stable COPD (stabilization of AECOPD patients after treatment). Sequencing reads were classified by Kraken2, and the host gene expression was analyzed by Hisat2 and HTseq. The correlation between genes was obtained by the Spearman correlation coefficient. Mann–Whitney U-test was applied to identify microbes that exhibit significantly different distribution in two groups.ResultsAt the phyla level, the top 5 dominant phyla were Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes, and Fusobacteria. The proportion of dominant gates in metagenomic data was similar in metatranscriptomic data. There were significant differences in the abundance of specific microorganisms at the class level between the two methods. No significant difference between AECOPD and stable COPD was found. However, the different expression levels of 5 host genes were significantly increased in stable COPD and were involved in immune response and inflammatory pathways, which were associated with macrophages.ConclusionOur study may provide a clue to investigate the mechanism of COPD and potential biomarkers in clinical diagnosis and treatment.