Screening and identification of biomarkers for systemic sclerosis via microarray technology

Identification and Analyses of Crucial Genes Associated with Pathogenesis of Major Depressive Disorder

Background

Major depressive disorder is a debilitating mental condition that causes severe disability leading to a high fatality rate. No valid blood-based biomarkers for major depressive disorder are currently available. The purpose of this research is to investigate gene biomarkers and pathways that may be linked to major depressive disorder pathogenesis.

Methods

Two microarray databases were retrieved from Gene Expression Omnibus for screening of candidate differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed followed by protein-protein interaction network of differentially expressed genes.

Results

About 1181 differentially expressed genes were identified from the microarray databases. Gene Ontology analyses indicated that these differentially expressed genes were significantly enriched in mRNA splicing via spliceosome, neutrophil degranulation, peptide antigen assembly with MHC class II protein complex, and immunoglobulin production-mediated immune response. The most enriched Kyoto Encyclopedia of Genes and Genomes pathway terms of the 10 significant were Hematopoietic cell lineage. About 20 genes were identified as hub genes after pathway analyses, mostly involved in colorectal cancer and the composition of ribosomes and protein processing, including KRAS, CD86, RPL9, RPL3, and RPL18.

Conclusion

New candidate genes have been identified using bioinformatic approaches that suggest their involvement in the pathogenesis of major depressive disorder and serve as potential genetic diagnostic markers as well as new therapeutic targets.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks

OBJECTIVE

This study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA.

METHODS

Microarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA.

RESULTS

The 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions.

CONCLUSION

The findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.

Integrated Experimental Approach, Phytochemistry, and Network Pharmacology to Explore the Potential Mechanisms of Cinnamomi Ramulus for Rheumatoid Arthritis

Cinnamomi Ramulus (CR) has been extensively used as a remedy for inflammatory diseases in China. This study adopted an integrative approach of experimental research, phytochemistry, and network pharmacology to investigate its alleviative effects on rheumatoid arthritis (RA) and the underlying potential mechanisms. CR extract (50, 100, and 200 mg/kg) and methotrexate (MTX) significantly ameliorated RA symptoms in the collagen-induced arthritis (CIA) rat model. They also reduced paw volume, arthritis index, proinflammatory cytokines (TNF-α, IL-17A, IL-6, and IL-1β), and oxidative damage. Sixty-three compounds were systematically identified as the basic components of CR. Fifty-five common genes obtained from compounds and GEO databases were employed to construct the protein-protein interaction (PPI) network. Among them, 20 hub genes were identified via the cytoHubba. Enrichment analysis of the common genes indicated that the TNF signaling pathway and IL-17 signaling pathway might be the potential key pathways. Moreover, molecular docking methods confirmed the high affinity between the top 10 bioactive components of CR and the top 10 targets. In addition, in vitro results showed that CR extract (0.2, 0.4, and 0.8 mg/mL) inhibited inflammation and oxidative damage in MH7A cells stimulated by lipopolysaccharide (LPS). In summary, this study adopted multiple approaches to elucidate the protective effect and potential mechanisms of CR on RA, indicating that CR might be a promising herbal candidate for further investigation of RA treatment.

Transcriptomic and Single-Cell Analysis Reveals Regulatory Networks and Cellular Heterogeneity in Mouse Primary Sjögren's Syndrome Salivary Glands

Sjögren’s Syndrome (SS) is a chronic autoimmune disease of unknown etiology which primarily affects the salivary and lacrimal glands resulting in the loss of secretory function. Treatment options for SS have been hampered due to the lack of a better understanding of the underlying gene regulatory circuitry and the interplay between the myriad pathological cellular states that contribute to salivary gland dysfunction. To better elucidate the molecular nature of SS, we have performed RNA-sequencing analysis of the submandibular glands (SMG) of a well-established primary Sjögren’s Syndrome (pSS) mouse model. Our comprehensive examination of global gene expression and comparative analyses with additional SS mouse models and human datasets, have identified a number of important pathways and regulatory networks that are relevant in SS pathobiology. To complement these studies, we have performed single-cell RNA sequencing to examine and identify the molecular and cellular heterogeneity of the diseased cell populations of the mouse SMG. Interrogation of the single-cell transcriptomes has shed light on the diversity of immune cells that are dysregulated in SS and importantly, revealed an activated state of the salivary gland epithelial cells that contribute to the global immune mediated responses. Overall, our broad studies have not only revealed key pathways, mediators and new biomarkers, but have also uncovered the complex nature of the cellular populations in the SMG that are likely to drive the progression of SS. These newly discovered insights into the underlying molecular mechanisms and cellular states of SS will better inform targeted therapeutic discoveries.

Identification of Genes Potentially Associated with Melanoma Tumorigenesis Through Co-Expression Network Analysis

Background

Melanoma is one of the most malignant and aggressive skin tumors, and its incidence is increasing worldwide. However, few studies have investigated the process of tumorigenesis from normal skin to melanoma.

Methods

Several bioinformatics analyses, including GEO databases, Oncomine database, TCGA database, STRING, MCODE and cytoHubba plug-ins, GEPIA, TIMER and TRRUST and DGIdb, were performed to disclose the hub genes and immunology implicated in primary melanoma tumorigenesis. Finally, immunohistochemistry (IHC) and quantitative real-time PCR (qPCR) were used to validate the results of bioinformatics analysis in vitro.

Results

A total of 295 overlapping DEGs (ODEGs) (157 upregulated and 138 downregulated) and 9 hub genes were identified between primary melanoma and normal skin tissues. Functional analysis of these 9 hub genes indicated that the genes were primarily enriched in cell chemotaxis, the chemokine-mediated signaling pathway, the extracellular region, the extracellular space, chemokine activity and CXCR3 chemokine receptor binding. KEGG pathway enrichment showed that these genes were primarily involved in the chemokine signaling pathway, cytokine–cytokine receptor interaction, the toll-like receptor signaling pathway, the cytosolic DNA-sensing pathway and the TNF signaling pathway. Upregulated CCL5, CCL4, CXCL9 and CXCL10 demonstrated good overall survival (OS), and most of them have a higher expression in stage 0 and 1 of melanoma. Moreover, immune infiltration analysis showed that the above hub genes showed a strong positive correlation between their expression and infiltration of the six immune cell subsets. Transcription factor regulation network suggested that RELA and NFKB1 are the transcription factors of CCL4, CCL5, CXCL10 and CXCL2, while IRF7, IRF3 and IRF1 are the transcription factors of CCL5 and CXCL10. Drug–gene interaction analysis identified 46 drug–gene interactions. In vitro data demonstrated that the level of CCL4, CCL5, CXCL9 and CXCL10 is higher in melanoma than that in normal skin tissues, either at tissue or cell lines level.

Conclusion

In summary, we identified 4 key chemokine members related to tumorigenesis and progression in primary melanoma, and these results may help to elucidate melanoma tumorigenesis and facilitate its treatment.

CLCA4 and MS4A12 as the significant gene biomarkers of primary colorectal cancer

Background: Primary colorectal cancer (PCRC) is a common digestive tract cancer in the elderly. However, the treatment effect of PCRC is still limited, and the long-term survival rate is low. Therefore, further exploring the pathogenesis of PCRC, and searching for specific molecular targets for diagnosis are the development trends of precise medical treatment, which have important clinical significance.

Methods: The public data were downloaded from Gene Expression Omnibus (GEO) database. Verification for repeatability of intra-group data was performed by Pearson’s correlation test and principal component analysis. Differentially expressed genes (DEGs) between normal and PCRC were identified, and the protein–protein interaction (PPI) network was constructed. Significant module and hub genes were found in the PPI network. A total of 192 PCRC patients were recruited between 2010 and 2019 from the Fourth Hospital of Hebei Medical University. RT-PCR was used to measure the relative expression of CLCA4 and MS4A12. Furthermore, the study explored the effect of expression of CLCA4 and MS4A12 for overall survival.

Results: A total of 53 DEGs were identified between PCRC and normal colorectal tissues. Ten hub genes concerned to PCRC were screened, namely CLCA4, GUCA2A, GCG, SST, MS4A12, PLP1, CHGA, PYY, VIP, and GUCA2B. The PCRC patients with low expression of CLCA4 and MS4A12 has a worse overall survival than high expression of CLCA4 and MS4A12 (P<0.05).

Conclusion: The research of DEGs in PCRC (53 DEGs, 10 hub genes, especially CLCA4 and MS4A12) and related signaling pathways is conducive to the differential analysis of the molecular mechanism of PCRC.