Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients

Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19

As a disease causing a global pandemic, the progression of symptoms to severe disease in patients with COVID-19 often has adverse outcomes, but research on the immunopathology of COVID-19 severe disease remains limited. In this study, we used mRNA-seq data from the peripheral blood of COVID-19 patients to identify six COVID-19 severe immune characteristic genes (FPR1, FCGR2A, TLR4, S100A12, CXCL1, and L TF), and found neutrophils to be the critical immune cells in COVID-19 severe disease. Subsequently, using scRNA-seq data from bronchoalveolar lavage fluid from COVID-19 patients, neutrophil subtypes highly expressing the S100A family were found to be located at the end of cellular differentiation and tended to release neutrophil extracellular traps. Finally, it was also found that alveolar macrophages, macrophages, and monocytes with a high expression of COVID-19 severe disease immune characteristic genes may influence neutrophils through intercellular ligand-receptor pairs to promote neutrophil extracellular trap release. This study provides immune characteristic genes, critical immune pathways, and immune cells in COVID-19 severe disease, explores intracellular immune transitions of critical immune cells and pit-induced intercellular communication of immune transitions, and provides new biomarkers and potential drug targets for the treatment of patients with COVID-19 severe disease.

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood.

Methods

To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs.

Results

A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol.

Conclusion

This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Long noncoding RNA NONHSAT160169.1 promotes resistance via hsa-let-7c-3p/SOX2 axis in gastric cancer

In clinical trials involving patients with HER2 (ERBB2 receptor tyrosine kinase 2) positive gastric cancer, the efficacy of the HER2-targeted drug lapatinib has proven to be disappointingly poor. Under the persistent pressure exerted by targeted drug therapy, a subset of tumor cells exhibit acquired drug resistance through the activation of novel survival signaling cascades, alongside the proliferation of tumor cells that previously harbored mutations conferring resistance to the drug. This study was undertaken with the aim of elucidating in comprehensive detail the intricate mechanisms behind adaptive resistance and identifying novel therapeutic targets that hold promise in the development of effective lapatinib-based therapies for the specific subset of patients afflicted with gastric cancer. We have successfully established a gastric cancer cell line with acquired lapatinib resistance, designated as HGC-27-LR cells. Utilizing comprehensive coding and noncoding transcriptome sequencing analysis, we have identified key factors that regulate lapatinib resistance in HGC-27 cells. We have compellingly validated that among all the lncRNAs identified in HGC-27-LR cells, a novel lncRNA (long noncoding RNA) named NONHSAT160169.1 was found to be most notably upregulated following exposure to lapatinib treatment. The upregulation of NONHSAT160169.1 significantly augmented the migratory, invasive, and stemness capabilities of HGC-27-LR cells. Furthermore, we have delved into the mechanism by which NONHSAT160169.1 regulates lapatinib resistance. The findings have revealed that NONHSAT160169.1, which is induced by the p-STAT3 (signal transducer and activator of transcription 3) nuclear transport pathway, functions as a decoy that competitively interacts with hsa-let-7c-3p and thereby abrogates the inhibitory effect of hsa-let-7c-3p on SOX2 (SRY-box transcription factor 2) expression. Hence, our study has unveiled the NONHSAT160169.1/hsa-let-7c-3p/SOX2 signaling pathway as a novel and pivotal axis for comprehending and surmounting lapatinib resistance in the treatment of HER2-positive gastric cancer.

CXCL10 May Be Responsible for Susceptibility to Pulmonary Embolism in COVID-19 Patients

Background

Although the potential of coronavirus disease 2019 (COVID-19) patients to develop pulmonary embolism (PE) is widely recognized, the underlying mechanism has not been completely elucidated. This study aimed to identify genes common to COVID-19 and PE to reveal the underlying pathogenesis of susceptibility to PE in COVID-19 patients.

Methods

COVID-19 genes were obtained from the GEO database and the OMIM, CTD, GeneCards, and DisGeNET databases; PE genes were obtained from the OMIM, CTD, GeneCards, and DisGeNET databases. We overlapped the genes of COVID-19 and PE to obtain common genes for additional analysis, including functional enrichment, protein-protein interaction, and immune infiltration analysis. Hub genes were identified using cytoHubba, a plugin of Cytoscape, and validated using the independent datasets GSE167000 and GSE13535. The genes validated by the above datasets were further validated in clinical samples.

Results

We obtained 36 genes shared by PE and COVID-19. Functional enrichment and immune infiltration analyses revealed the involvement of cytokines and immune activation. Five genes (CCL2, CXCL10, ALB, EGF, and MKI67) were identified as hub genes common to COVID-19 and PE. CXCL10 was validated in both independent datasets (GSE167000 and GSE13535). Serum levels of CXCL10 in the COVID-19 group and the COVID-19 combined with PE group were significantly higher than those in the healthy control group (P<0.001). In addition, there were significant differences between the COVID-19 group and the COVID-19 combined with PE group (P<0.01).

Conclusion

Our study reveals common genes shared by PE and COVID-19 and identifies CXCL10 as a possible cause of susceptibility to PE in COVID-19 patients.

Whole Blood Expression Levels of Long Noncoding RNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 as Biomarkers in Adolescents with Obesity-Related Asthma

Asthma is a heterogeneous entity encompassing distinct endotypes and varying phenotypes, characterized by common clinical manifestations, such as shortness of breath, wheezing, and variable airflow obstruction. Two major asthma endotypes based on molecular patterns are described: type 2 endotype (allergic-asthma) and T2 low endotype (obesity-related asthma). Long noncoding RNAs (lncRNAs) are transcripts of more than 200 nucleotides in length, currently involved in many diverse biological functions, such as chromatin remodeling, gene transcription, protein transport, and microRNA processing. Despite the efforts to accurately classify and discriminate all the asthma endotypes and phenotypes, if long noncoding RNAs could play a role as biomarkers in allergic asthmatic and adolescent obesity-related asthma, adolescents remain unknown. To compare expression levels of lncRNAs: HOTAIRM1, OIP5-AS1, MZF1-AS1, and GAS5 from whole blood of Healthy Adolescents (HA), Obese adolescents (O), allergic asthmatic adolescents (AA) and Obesity-related asthma adolescents (OA). We measured and compared expression levels from the whole blood of the groups mentioned above through RT-q-PCR. We found differentially expressed levels of these lncRNAs between the groups of interest. In addition, we found a discriminative value of previously mentioned lncRNAs between studied groups. Finally, we generated an interaction network through bioinformatics. Expression levels of OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 in whole blood from the healthy adolescent population, obese adolescents, allergic asthma adolescents, and obesity-related asthma adolescents are differently expressed. Moreover, these lncRNAs could act as molecular biomarkers that help to discriminate between all studied groups, probably through molecular mechanisms with several genes and miRNAs implicated.