Ingenuity pathway analysis of human facet joint tissues: Insight into facet joint osteoarthritis

Newt A1 cell-derived extracellular vesicles promote mammalian nerve growth

Newts have the extraordinary ability to fully regenerate lost or damaged cardiac, neural and retinal tissues, and even amputated limbs. In contrast, mammals lack these broad regenerative capabilities. While the molecular basis of newts' regenerative ability is the subject of active study, the underlying paracrine signaling factors involved remain largely uncharacterized. Extracellular vesicles (EVs) play an important role in cell-to-cell communication via EV cargo-mediated regulation of gene expression patterns within the recipient cells. Here, we report that newt myogenic precursor (A1) cells secrete EVs (A1EVs) that contain messenger RNAs associated with early embryonic development, neuronal differentiation, and cell survival. Exposure of rat primary superior cervical ganglion (SCG) neurons to A1EVs increased neurite outgrowth, facilitated by increases in mitochondrial respiration. Canonical pathway analysis pinpointed activation of NGF/ERK5 signaling in SCG neurons exposed to A1EV, which was validated experimentally. Thus, newt EVs drive neurite growth and complexity in mammalian primary neurons.

Illumination on Chemical Compounds from Qufeng Zhitong Capsule and Its Potential Pharmacological Mechanism against Rheumatoid Arthritis Based on UHPLC/Q-Orbitrap-MS Combined with Network Pharmacology Analysis

Qufeng Zhitong capsule (QZC), a Chinese patent medicine officially approved in China for the treatment of rheumatoid arthritis (RA) and other diseases, possesses the primary effects of dispelling wind, relieving pain, and promoting blood circulation, whose clinical applications have been confined owing to the incomplete elucidation of its chemical compositions and the underlying molecular mechanism for the treatment of RA. In this study, 61 compounds including 16 phenylpropanoids, 15 organic acids, 13 alkaloids, seven flavonoids, six iridoids, one saccharide, two aldehydes, and one saponin in QZC were simultaneously identified and traced to their herbal origins by ultra-high performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC/Q-Orbitrap-MS), where 31 of them were unambiguously identified by reference compounds, and the other 30 were tentatively characterized. Besides, all these compounds were proven to have potential pharmacological activity in the treatment of RA based on network pharmacology analysis. In conclusion, this study first investigated the chemical composition and potential pharmacological effects of the main chemical compounds in QZC, which will contribute to the revelation of bioactive compounds in QZC and provide evidence for clinical application.

Integrated Analysis of miRNAs and Gene Expression Profiles Reveals Potential Biomarkers for Osteoarthritis

Purpose: Currently, the early diagnosis and treatment of osteoarthritis (OA) remain a challenge. In the present study, we attempted to explore potential biomarkers for the diagnosis and treatment of OA.

Methods: The differentially expressed genes (DEGs) were identified based on three mRNA datasets of synovial tissues for OA patients and normal controls downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used for evaluating gene function related categories. Then, miRNA sequencing was performed for differentially expressed miRNAs’ identification. Finally, weighted gene co-expression network analysis (WGCNA) was performed for genes detected by the three mRNA datasets and a competing endogenous RNA (ceRNA) network with DEGs and differentially expressed microRNAs (miRNAs) was constructed for central genes identification. In addition, the relationship between central gene expression and immune infiltration was analyzed, and the candidate agents for OA were predicted based on the Connectivity Map database. Quantitative RT-PCR (qRT-PCR), Western blotting analysis, and immunofluorescent staining were performed to validate the expression levels of differentially expressed miRNAs and differentially expressed target genes in normal and OA tissues and chondrocytes. MiRNA–mRNA network was also validated in chondrocytes in vitro.

Results: A total of 259 DEGs and 26 differentially expressed miRNAs were identified, among which 94 miRNA–mRNA interactions were predicted. The brown module in WGCNA was most closely correlated with the clinical traits of OA. After overlapping the brown module genes with miRNA–mRNA pairs, 27 miRNA–mRNA pairs were obtained. A ceRNA network was constructed with 5505 lncRNA–miRNA–mRNA interactions. B-cell translocation gene 2(BTG2), Abelson-related gene (ABL2), and vascular endothelial growth factor A (VEGFA) were identified to be the central genes with good predictive performance, which were significantly correlated with immune cell infiltration in OA, reflected by declined activated dendritic cells (aDCs), and elevated contents of B cells, macrophages, neutrophils, and T helper cells. Anisomycin, MG-132, thapsigargin, and lycorine were predicted to be the potential candidate agents for OA intervention. In vitro, the expression levels of differentially expressed miRNAs and biomarkers identified in the present study were consistent with the results obtained in normal or OA knee cartilage tissues and chondrocytes. Furthermore, BTG2 was identified to be negatively regulated by miR-125a-5p.

Conclusion: BTG2, ABL2, and VEGFA can be regarded as potential predictive and treatment biomarkers for OA, which might guide the clinical therapy of OA.

CD5L as an Extracellular Vesicle-Derived Biomarker for Liquid Biopsy of Lung Cancer

Cancer screening and diagnosis can be achieved by analyzing specific molecules within serum-derived extracellular vesicles (EVs). This study sought to profile EV-derived proteins to identify potential lung cancer biomarkers. EVs were isolated from 80 serum samples from healthy individuals and cancer patients via polyethylene glycol (PEG)-based precipitation and immunoaffinity separation using antibodies against CD9, CD63, CD81, and EpCAM. Proteomic analysis was performed using 2-D gel electrophoresis and matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI–TOF MS). The expression of proteins that were differentially upregulated in the EVs or tissue of lung cancer samples was validated by Western blotting. The area under the curve (AUC) was calculated to assess the predictability of each differentially expressed protein (DEP) for lung cancer. A total of 55 upregulated protein spots were selected, seven of which (CD5L, CLEC3B, ITIH4, SERFINF1, SAA4, SERFINC1, and C20ORF3) were found to be expressed at high levels in patient-derived EVs by Western blotting. Meanwhile, only the expression of EV CD5L correlated with that in cancer tissues. CD5L also demonstrated the highest AUC value (0.943) and was found to be the core regulator in a pathway related to cell dysfunction. Cumulatively, these results show that EV-derived CD5L may represent a potential biomarker—detected via a liquid biopsy—for the noninvasive diagnosis of lung cancer.

A global and physical mechanism of gastric cancer formation and progression

Gastric cancer is regarded as a major health issue for human being nowadays. The Helicobacter pylori (H. pylori) infection has been found to accelerate the development of gastritis and gastric cancer. Significant efforts have been made towards the understanding of the biology of gastric cancer on both genetic and epigenetic levels. However the physical mechanism behind the gastric cancer formation is still elusive. In this study, we constructed a model for investigating gastric cancer formation by explored the gastric cancer landscape and the flow flux. We uncovered three stable state attractors on the landscape: normal, gastritis and gastric cancer. The definition of each attractor is based on the biological function and gene expression levels. The global stabilities and the switching processes were quantified through the barrier heights and dominant kinetic paths. To investigate the underlying mechanism of the process from normal through the gastritis to the gastric cancer caused by genetic or epigenetic factors, we simulate the oncogenesis of gastric cancer through changes of several gene regulation strengths and H. pylori infection. The simulated results can illustrate the developmental and metastasis process of gastric cancer. Different H. pylori infection degrees accelerating the process from gastritis to gastric cancer can be quantified. Then we applied global sensitivity analysis, one key gene and four key regulations were found. These results are consist with the experimental results and can be used to design the polygenic anti-cancer agents through multiple key genes or regulations. The landscape approach provides a physical and simple strategy for analyzing gastric cancer in a systematic and quantitative way. It also offers new insight into treatment strategy for gastric cancer by adjusting relevant polygenic genes and regulations.