The number of descriptions of emerging viruses has grown at an unprecedented rate since the beginning of the 21 st century. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is the third highly pathogenic coronavirus that has introduced itself into the human population in the current era, after SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Molecular and cellular studies of the pathogenesis of this novel coronavirus are still in the early stages of research; however, based on similarities of SARS-CoV-2 to other coronaviruses, it can be hypothesized that the NF-κB, cytokine regulation, ERK, and TNF-α signaling pathways are the likely causes of inflammation at the onset of COVID-19. Several drugs have been prescribed and used to alleviate the adverse effects of these inflammatory cellular signaling pathways, and these might be beneficial for developing novel therapeutic modalities against COVID-19. In this review, we briefly summarize alterations of cellular signaling pathways that are associated with coronavirus infection, particularly SARS-CoV and MERS-CoV, and tabulate the therapeutic agents that are currently approved for treating other human diseases.

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein–protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

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As a unique population of tumor bulk, cancer stem cells have been implicated in tumor relapse and chemoresistance in triple-negative breast cancer (TNBC). Therefore, understanding the phenotype of cancer stem cells can pave the way for introducing novel molecular targeted therapies for treating TNBC patients. Preclinical studies have identified CD44+CD24-/low as a cancer stem cell phenotype; however, clinical studies have reported seemingly controversial results regarding the prognostic values of CD44 and CD44+CD24-/low phenotype in TNBC patients. To critically review the clinicopathological significance and prognostic values of CD44 and CD44+CD24-/low phenotype in TNBC patients, the Scopus, Embase, PubMed, and Web of Science databases were systematically searched to obtain the relevant records published before 20 October 2020. Based on nine included studies, CD44 and CD44+CD24-/low phenotype are associated with inferior prognosis in TNBC patients. Moreover, these cancer stem cell markers have been associated with advanced tumor stage, tumor size, higher tumor grade, tumor metastasis, and lymphatic involvement in TNBC patients. Our evidence has also indicated that, unlike the treatment-naïve TNBC patients, the tumoral cells of chemoradiotherapy-treated TNBC patients can upregulate the CD44+CD24-/low phenotype and establish an inverse association with androgen receptor (AR), leading to the inferior prognosis of affected patients. In summary, CD44 and CD44+CD24-/low phenotype can be utilized to determine TNBC patients’ prognosis in the pathology department as a routine practice, and targeting these phenotypes can substantially improve the prognosis of TNBC patients.

Preclinical studies have indicated that T-cell immunoglobulin and ITIM domain (TIGIT) can substantially attenuate anti-tumoral immune responses. Although multiple clinical studies have evaluated the significance of TIGIT in patients with solid cancers, their results remain inconclusive. Thus, we conducted the current systematic review and meta-analysis based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) to determine its significance in patients with solid cancers. We systematically searched the Web of Science, Embase, PubMed, and Scopus databases to obtain peer-reviewed studies published before September 20, 2020. Our results have shown that increased TIGIT expression has been significantly associated with inferior overall survival (OS) (HR = 1.42, 95% CI: 1.11–1.82, and p-value = 0.01). Besides, the level of tumor-infiltrating TIGIT+CD8+ T-cells have been remarkably associated inferior OS and relapse-free survival (RFS) of affected patients (HR = 2.17, 95% CI: 1.43–3.29, and p-value < 0.001, and HR = 1.89, 95% CI: 1.36–2.63, and p-value < 0.001, respectively). Also, there is a strong positive association between TIGIT expression with programmed cell death-1 (PD-1) expression in these patients (OR = 1.71, 95% CI: 1.10–2.68, and p-value = 0.02). In summary, increased TIGIT expression and increased infiltration of TIGIT+CD8+ T-cells can substantially worsen the prognosis of patients with solid cancers. Besides, concerning the observed strong association between TIGIT and PD-1, ongoing clinical trials, and promising preclinical results, PD-1/TIGIT dual blockade can potentially help overcome the immune-resistance state seen following monotherapy with a single immune checkpoint inhibitor in patients with solid cancers.

Autoimmune diseases, especially among young people in the US, are one of the leading causes of morbidity and death. The immune responses are the fundamental pathogenicity of autoimmune disorders. The equilibrium between stimulatory and inhibitory signals is critical for the stimulation, migration, survival, and T cell‐related immune responses. The B7 family can substantially regulate T cell‐mediated immune responses. Nevertheless, recent breakthroughs in immune checkpoint blockade in cancer immunotherapy have facilitated autoimmune diseases, especially among the prone populations. In the current study, we tried to concisely review the role of the B7 family in regulating immune reactions and the influence of immune checkpoint inhibitors on autoimmunity development.

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M. (2022). Downregulation of miR-185 is a common pathogenic event in 22q11.2 deletion syndrome-related and idiopathic schizophrenia. Metabolic Brain Disease, 37(4),