Integrative analyses of genes associated with idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF), characterized by irreversible scarring and progressive destruction of the lung tissue, is one of the most common types of idiopathic interstitial pneumonia worldwide. However, there are no reliable candidates for curative therapies. Hence, elucidation of the mechanisms of IPF genesis and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis and treatment of IPF. Recently, efficient microarray and bioinformatics analyses have promoted an understanding of the molecular mechanisms of disease occurrence and development, which is necessary to explore genetic alternations and identify potential diagnostic biomarkers. However, high false-positive rates results have been observed based on single microarray datasets. In the current study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of IPF-related genes. Three publicly available microarray datasets including 54 IPF samples and 34 normal samples were integrated by performing gene set enrichment analysis and analyzing differentially expressed genes (DEGs). Our results identified 350 DEGs genetically associated with IPF. Gene ontology analyses revealed that the changes in the modules were mostly enriched in the positive regulation of smooth muscle cell proliferation, positive regulation of inflammatory responses, and the extracellular space. Kyoto encyclopedia of genes and genomes enrichment analysis of DEGs revealed that IPF involves the TNF signaling pathway, NOD-like receptor signaling pathway, and PPAR signaling pathway. To identify key genes related to IPF in the protein-protein interaction network, 20 hub genes were screened out with highest scores. Our results provided a framework for developing new pathological molecular networks related to specific diseases in silico.     

STAT1 and its related molecules as potential biomarkers in Mycobacterium tuberculosis infection

Tuberculosis (TB) is a severe infectious disease that seriously endangers human health. The immune defence mechanism of the body against TB is still unclear. The purpose of this study was to find the key molecules involved in the immune defence response during TB infection, and provide reference for the treatment of TB and further understanding of the immune defence mechanism of the body. Data from GSE83456 were downloaded from GEO data sets for analysis, and a total of 192 differentially expressed genes were screened out. Most of these genes are enriched in the interferon signalling pathway and are defence response–related. We also found that STAT1 plays an important role in the immune defence of TB infection and it is one of the key genes related to interferon signalling pathway. STAT1-related molecules including hsa-miR-448, hsa-miR-223-3p, SAMD8_hsa_circRNA 994 and TWF1_hsa_circRNA 9897 were therefore screened out. Furthermore, expression levels of hsa-miR-448 and hsa-miR-223-3p were then verified by qRT-PCR. Results showed that both hsa-miR-448 and hsa-miR-223-3p were down-regulated in plasma from patients with pulmonary TB. Taken together, our data indicate that an mRNA-miRNA-circRNA interaction chain may play an important role in the infection of MTB, and STAT1 and related molecules including hsa-miR-223-3p, has-miR-448, SAMD8_hsa_circRNA994 and TWF1_hsa_circRNA9897 were identified as potential biomarkers in the development of active TB.     

Electrochemical-based biosensors for detection of Mycobacterium tuberculosis and tuberculosis biomarkers

Abstract

Early detection of tuberculosis (TB) reduces the interval between infection and the beginning of treatment. However, commercially available tests cannot discriminate between BCG-vaccinated healthy persons and patients. Also, they are not suitable to be used for immunocompromised persons. In recent years, biosensors have attracted great attention due to their simple utility, accessibility, and real-time outputs. These sensors are increasingly being considered as pioneering tools for point-of-care diagnostics in communities with a high burden of TB and limited accessibility to reference laboratories. Among other types of biosensors, the electrochemical sensors have the advantages of low-cost operation, fast processing, simultaneous multi-analyte analyzing, operating with turbid samples, comparable sensitivity and readily available miniaturization. Electrochemical biosensors are sub-divided into several categories including: amperometric, impedimetric, potentiometric, and conductometric biosensors. The biorecognition element in electrochemical biosensors is usually based on antibodies (immunosensors), DNAs or PNAs (genosensors), and aptamers (aptasensors). In either case, whether an interaction of the antigen–antibody/aptamer or the hybridization of probe with target mycobacterial DNA is detected, a change in the electrical current occurs that is recorded and displayed as a plot. Therefore, impedimetric-based methods evaluate resistance to electron transfer toward an electrode by a Nyquist plot and amperometric/voltammetric-based methods weigh the electrical current by means of cyclic voltammetry, square wave voltammetry, and differential pulse voltammetry. Electrochemical biosensors provide a promising scope for the new era of diagnostics. As a consequence, they can improve detection of Mycobacterium tuberculosis traces even in attomolar scales.     

Detection of exosomal tyrosine receptor kinase B as a potential biomarker in ovarian cancer

Ovarian cancer (OC) is a lethal disease diagnosed at advanced stages due to the lack of specific biomarkers. Tyrosine receptor kinase B (TrkB), which has recently been found to be related to OC progression, represents a promising potential biomarker for OC diagnosis and prognosis. The discovery of circulating exosomes as biomarkers for various diseases led us to explore exosomal TrkB in OC. Our previous study proved that the expression of TrkB was elevated in OC tissues. In this study, we focused on the detection of exosomal TrkB in OC. Exosomes were first gathered from three different OC cell lines’ conditioned medium, serum samples of patients with OC as well as xenograft mice serum by serial centrifugation method. Then, we identified exosomes by transmission electron microscopy, NanoSight analysis, and expression of typical exosomal protein markers. The existence of TrkB in exosomes was measured by Western blot analysis, and the expression was detected by enzyme-linked immunosorbent assay. In this study, we demonstrated that exosomes could derive from OC cell lines, serum from OC xenograft nude mice, and clinical patients. Our study shows that serum exosomal TrkB may be considered a minimally invasive biomarker for OC.     

Integrated bioinformatic analysis reveals YWHAB as a novel diagnostic biomarker for idiopathic pulmonary arterial hypertension

Idiopathic pulmonary arterial hypertension (IPAH) is a severe cardiovascular disease that is a serious threat to human life. However, the specific diagnostic biomarkers have not been fully clarified and candidate regulatory targets for IPAH have not been identified. The aim of this study was to explore the potential diagnostic biomarkers and possible regulatory targets of IPAH. We performed a weighted gene coexpression network analysis and calculated module-trait correlations based on a public microarray data set (GSE703) and six modules were found to be related to IPAH. Two modules which have the strongest correlation with IPAH were further analyzed and the top 10 hub genes in the two modules were identified. Furthermore, we validated the data by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent sample set originated from our study center. Overall, the qRT-PCR results were consistent with most of the results of the microarray analysis. Intriguingly, the highest change was found for YWHAB, a gene encodes a protein belonging to the 14-3-3 family of proteins, members of which mediate signal transduction by binding to phosphoserine-containing proteins. Thus, YWHAB was subsequently selected for validation. In congruent with the gene expression analysis, plasma 14-3-3β concentrations were significantly increased in patients with IPAH compared with healthy controls, and 14-3-3β expression was also positively correlated with mean pulmonary artery pressure ( R ² = 0.8783; p < 0.001). Taken together, using weighted gene coexpression analysis, YWHAB was identified and validated in association with IPAH progression, which might serve as a biomarker and/or therapeutic target for IPAH.     

Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC-related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC-associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC-associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC-associated genes for their potentiality in diagnosis, prognosis, and targeted therapy.     

Identification of potential key genes associated with osteosarcoma based on integrated bioinformatics analyses

Due to high rates of metastasis and poor clinical outcomes for patients, it is important to study the pathomechanisms of osteosarcoma. However, due to the fact that osteosarcoma shows significant interindividual variation and high heterogeneity, the identification of differentially expressed genes (DEGs) at the population level cannot answer many important questions related to osteosarcoma tumorigenesis. Therefore, a new strategy to identify dysregulated genes in osteosarcoma samples is required. The aim of this study was to improve our understanding of osteosarcoma pathogenesis by identifying genes with universal aberrant expression in osteosarcoma samples. Because the relative expression ordering of genes is stable in normal bone tissues but is disrupted in osteosarcoma tissues, we used the RankComp algorithm to identify DEGs in normal and osteosarcoma tissue samples. We then calculated the dysregulation frequency for each gene. Genes with deregulation frequencies above 80% were deemed to be universal DEGs. Next, coexpression, pathway enrichment, and protein-protein interaction network analyses were performed to characterize the functions of these genes. From 188 samples of osteosarcoma obtained from four datasets measured on different platforms, 51 universal DEGs were identified, including 4 universally upregulated genes and 47 universally downregulated genes. Genes that were differentially coexpressed with these universal DEGs were found to be enriched in 46 cancer-related pathways. In addition, functional and network analyses showed that genes with high dysregulation frequencies were involved in cancer-related functions. Thus, the commonly aberrant genes identified in osteosarcoma tissues may be important targets for osteosarcoma diagnosis and therapy.     

Mycobacterium kansasii infection in squirrel monkeys (Saimiri sciureus sciureus)

Abstract: This report documents asymptomatic infections of Mycobacterium kansasii in four of five tuberculin positive squirrel monkeys (Saimiri sciureus sciureus). The mycobacterial DNA amplified by polymerase chain reaction (PCR) from a bronchial lymph node had no affinity for the species specific probes of M. tuberculosis, M. avium, and M. intracellular, thus allowing the presumptive diagnosis of an atypical mycobacterial infection. Infection by Mycobacterium kansasii was confirmed by culture of bronchial lymph nodes from three monkeys. The source of the infection was never identified.     

Downregulation of AC061961.2, LING01-AS1, and RP11–13E1.5 is associated with dilated cardiomyopathy progression

This study aimed to explore long noncoding RNAs (lncRNAs) implicated in dilated cardiomyopathy (DCM). Ten samples of failing hearts collected from the left ventricles of patients with DCM undergoing heart transplants, and ten control samples obtained from normal heart donors were included in this study. After sequencing, differentially expressed genes (DEGs) and lncRNAs between DCM and controls were screened, followed with functional enrichment analysis and weighted gene coexpression network analysis (WGCNA). Five key lncNRAs were validated through real-time polymerase chain reaction (PCR). Total 1,398 DEGs were identified, including 267 lncRNAs. WGCNA identified seven modules that were significantly correlated with DCM. The top 50 genes in the three modules (black, dark-green, and green–yellow) were significantly correlated with DCM disease state. Four core enrichment lncRNAs, such as AC061961.2, LING01-AS1, and RP11–557H15.4, in the green–yellow module were associated with neurotransmitter secretion. Five core enrichment lncRNAs, such as KB-1299A7.2 and RP11–13E1.5, in the black module were associated with the functions of blood circulation and heart contraction. AC061961.2, LING01-AS1, and RP11–13E1.5 were confirmed to be downregulated in DCM tissues by real-time PCR. The current study suggests that downregulation of AC061961.2, LING01-AS1, and RP11–13E1.5 may be associated with DCM progression, which may serve as key diagnostic biomarkers and therapeutic targets for DCM.     

Differential expression of CD64 in patients with Mycobacterium tuberculosis infection: A potential biomarker for clinical diagnosis and prognosis

To evaluate the clinical utility of neutrophil (n)CD64 index to diagnose pulmonary tuberculosis (PTB) and extrapulmonary TB (ePTB) and to predict the outcome of Mycobacterium tuberculosis infection. We recruited 189 patients with active TB and 140 controls and measured the differential expression of nCD64 index using flow cytometry. The receiver operating characteristics (ROC) curve analysis was performed to estimate the diagnostic performance of the nCD64 index and T‐SPOT.TB assay for the diagnosis of TB. Furthermore, we analysed whether the nCD64 index in patients with TB was correlated with inflammatory indicators. Finally, we assessed the prognosis of patients by following the dynamic changes of the nCD64 index once a week. The nCD64 index was significantly higher in active TB group (PTB and ePTB), than in the anti‐TB and healthy controls (HC) groups. The sensitivity and specificity of nCD64 index for the differential diagnosis of PTB and pneumonia (PN) patients were 68.33% and 77.55%, respectively. The sensitivity and specificity of nCD64 index for the diagnosis of tuberculous meningitis (TBM) were 53.85% and 100%, respectively. Furthermore, there was a weak correlation between the nCD64 index and inflammatory indicators. More importantly, with the improvement in patient condition, the nCD64 index started to decline in the first week of anti‐TB therapy and significantly decreased at 4 weeks after treatment. Our study demonstrated that the CD64 assay is a rapid, non‐invasive and stable method for clinical application, and the nCD64 index can serve as a potential biomarker for the diagnosis and prognosis of TB.     

Checkpoint Kinase 1 (CHK1) Functions as Both a Diagnostic Marker and a Regulator of Epithelial-to-Mesenchymal Transition (EMT) in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is more difficult to treat and has a higher mortality rate than other subtypes. Although hormone receptor-targeted therapy is an effective treatment to increase survival rate in breast cancer patients, it is not suitable for TNBC patients. To address the issues, differentially expressed genes (DEGs) in TNBC patients from the Gene Expression Omnibus (GEO) database were analyzed. A total of 170 genes were obtained from three Genomic Spatial Events (GSEs) using the intersection of each GSE dataset and 61 DEGs were identified after validation with the gene enrichment analysis. We combined this with the degree scores from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network, of which 7 genes were correlated with survival rate. Finally, a proteomics database revealed that only the CHK1 protein level was differently expressed in basal-like compared with other subtypes. We demonstrated that CHK1 expression was higher in TNBC cell lines compared with non-TNBC cell lines, and CHK1 promotes epithelial to mesenchymal transition (EMT) as well as migration and invasion ability. Our study provides new insight into the TNBC subnetwork that may be useful in the prognosis and treatment of TNBC patients.     

Improved understanding of pathogenesis from protein interactions in Mycobacterium tuberculosis

Comprehensive mapping and analysis of protein–protein interactions provide not only systematic approaches for dissecting the infection and survival mechanisms of pathogens but also clues for discovering new antibacterial drug targets. Protein interaction data on Mycobacterium tuberculosis have rapidly accumulated over the past several years. This review summarizes the current progress of protein interaction studies on M. tuberculosis, the causative agent of tuberculosis. These efforts improve our knowledge on the stress response, signaling regulation, protein secretion and drug resistance of the bacteria. M. tuberculosis–host protein interaction studies, although still limited, have recently opened a new door for investigating the pathogenesis of the bacteria. Finally, this review discusses the importance of protein interaction data on identifying and screening new anti-tuberculosis targets and drugs, respectively.