Background: Breast cancer (BC) is the most commonly diagnosed cancer in women. Tumor recurrence and metastasis are the key causes of death in BC patients. Long noncoding RNA (lncRNA) is closely associated with BC progression. lncRNA nuclear-enriched abundant transcript (NEAT)1 has been reported to regulate the proliferation and mobility of several types of cancer cells. However, how lncRNA NEAT1 affects the proliferation and invasion of BC cells is not known. Methods: Quantitative real time-polymerase chain reaction (qRT-PCR) was used to measure expression of lncRNA NEAT1 and microRNA (miR)-146b-5p in BC tissues and cell lines. Cell Counting Kit (CCK)-8, cell colony-formation, wound-healing, and Transwell™ assays were undertaken to determine the effects of lncRNA NEAT1 and miR-146b-5p on progression of BC cells. The interaction between lncRNA NEAT1 and miR-146b-5p was examined by luciferase reporter, RNA-binding protein immunoprecipitation (RIP), and RNA-pulldown assays. Results: Expression of lncRNA NEAT1 was upregulated in BC tissues and cell lines. High expression of lncRNA NEAT1 predicted poor overall survival in BC patients. Silencing of expression of lncRNA NEAT1 inhibited epithelial-mesenchymal transition (EMT) and suppressed the proliferation, migration and invasion of BC cells. Ectopic expression of lncRNA NEAT1 induced EMT and promoted BC progression. Mechanistic investigations revealed that miR-146b-5p was a direct target of lncRNA NEAT1, and its expression was correlated negatively with expression of lncRNA NEAT1 in BC tissues. Conclusion: lncRNA NEAT1 could (i) serve as a novel prognostic marker for BC and (ii) be a potential therapeutic target for BC.

Background The coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has become an ongoing pandemic. Understanding the respiratory immune microenvironment which is composed of multiple cell types, together with cell communication based on ligand–receptor interactions is important for developing vaccines, probing COVID-19 pathogenesis, and improving pandemic control measures. Methods A total of 102 consecutive hospitalized patients with confirmed COVID-19 were enrolled in this study. Clinical information, routine laboratory tests, and flow cytometry analysis data with different conditions were collected and assessed for predictive value in COVID-19 patients. Next, we analyzed public single-cell RNA-sequencing (scRNA-seq) data from bronchoalveolar lavage fluid, which offers the closest available view of immune cell heterogeneity as encountered in patients with varying severity of COVID-19. A weighting algorithm was used to calculate ligand–receptor interactions, revealing the communication potentially associated with outcomes across cell types. Finally, serum cytokines including IL6, IL1β, IL10, CXCL10, TNFα, GALECTIN-1, and IGF1 derived from patients were measured. Results Of the 102 COVID-19 patients, 42 cases (41.2%) were categorized as severe. Multivariate logistic regression analysis demonstrated that AST, D-dimer, BUN, and WBC were considered as independent risk factors for the severity of COVID-19. T cell numbers including total T cells, CD4+ and CD8+ T cells in the severe disease group were significantly lower than those in the moderate disease group. The risk model containing the above mentioned inflammatory damage parameters, and the counts of T cells, with AUROCs ranged from 0.78 to 0.87. To investigate the molecular mechanism at the cellular level, we analyzed the published scRNA-seq data and found that macrophages displayed specific functional diversity after SARS-Cov-2 infection, and the metabolic pathway activities in the identified macrophage subtypes were influenced by hypoxia status. Importantly, we described ligand–receptor interactions that are related to COVID-19 serverity involving macrophages and T cell subsets by communication analysis. Conclusions Our study showed that macrophages driving ligand–receptor crosstalk contributed to the reduction and exhaustion of CD8+ T cells. The identified crucial cytokine panel, including IL6, IL1β, IL10, CXCL10, IGF1, and GALECTIN-1, may offer the selective targets to improve the efficacy of COVID-19 therapy. Trial registration: This is a retrospective observational study without a trial registration number.

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