Role of Cigarette Smoke on Angiotensin-Converting Enzyme-2 Protein Membrane Expression in Bronchial Epithelial Cells Using an Air-Liquid Interface Model.

Prevalence studies of current smoking, among hospitalized COVID-19 patients, demonstrated an unexpectedly low prevalence among patients with COVID-19. The aim of the present study was to evaluate the effect of smoke from cigarettes on ACE-2 in bronchial epithelial cells. Normal bronchial epithelial cells (H292) were exposed to smoke by an air-liquid-interface (ALI) system and ACE-2 membrane protein expression was evaluated after 24 h from exposure. Our transcriptomics data analysis showed a significant selective reduction of membrane ACE-2 expression (about 25%) following smoking exposure. Interestingly, we observed a positive direct correlation between ACE-2 reduction and nicotine delivery. Furthermore, by stratifying GSE52237 as a function of ACE-2 gene expression levels, we highlighted 1,012 genes related to ACE-2 in smokers and 855 in non-smokers. Furthermore, we showed that 161 genes involved in the endocytosis process were highlighted using the online pathway tool KEGG. Finally, 11 genes were in common between the ACE-2 pathway in smokers and the genes regulated during endocytosis, while 12 genes with non-smokers. Interestingly, six in non-smokers and four genes in smokers were closely involved during the viral internalization process. Our data may offer a pharmaceutical role of nicotine as potential treatment option in COVID-19.

Immune-checkpoint inhibitors from cancer to COVID­19: A promising avenue for the treatment of patients with COVID­19 (Review).

The severe acute respiratory syndrome associated coronavirus­2 (SARS­CoV­2) poses a threat to human life worldwide. Since early March, 2020, coronavirus disease 2019 (COVID­19), characterized by an acute and often severe form of pneumonia, has been declared a pandemic. This has led to a boom in biomedical research studies at all stages of the pipeline, from the in vitro to the clinical phase. In line with this global effort, known drugs, currently used for the treatment of other pathologies, including antivirals, immunomodulating compounds and antibodies, are currently used off­label for the treatment of COVID­19, in association with the supportive standard care. Yet, no effective treatments have been identified. A new hope stems from medical oncology and relies on the use of immune­checkpoint inhibitors (ICIs). In particular, amongst the ICIs, antibodies able to block the programmed death­1 (PD­1)/PD ligand-1 (PD­L1) pathway have revealed a hidden potential. In fact, patients with severe and critical COVID­19, even prior to the appearance of acute respiratory distress syndrome, exhibit lymphocytopenia and suffer from T­cell exhaustion, which may lead to viral sepsis and an increased mortality rate. It has been observed that cancer patients, who usually are immunocompromised, may restore their anti­tumoral immune response when treated with ICIs. Moreover, viral-infected mice and humans, exhibit a T­cell exhaustion, which is also observed following SARS­CoV­2 infection. Importantly, when treated with anti­PD­1 and anti­PD­L1 antibodies, they restore their T­cell competence and efficiently counteract the viral infection. Based on these observations, four clinical trials are currently open, to examine the efficacy of anti­PD­1 antibody administration to both cancer and non­cancer individuals affected by COVID­19. The results may prove the hypothesis that restoring exhausted T­cells may be a winning strategy to beat SARS­CoV­2 infection.

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform.

BACKGROUND: SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this outbreak, specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. RESULTS: We present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS-CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. Universal Immune System Simulator (UISS) in silico platform is potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2. CONCLUSIONS: In silico trials are showing to be powerful weapons in predicting immune responses of potential candidate vaccines. Here, UISS has been extended to be used as an in silico trial platform to speed-up and drive the discovery pipeline of vaccine against SARS-CoV-2.