AI Article Synopsis

  • COVID-19 is caused by the SARS-CoV-2 virus, which enters cells through specific proteins (ACE2 and TMPRSS2) and leads to significant cellular changes, particularly in epithelial cells.
  • SARS-CoV-2 infection triggers metabolic shifts and transcriptional alterations that promote epithelial to mesenchymal transition (EMT), increasing EMT scores and reducing tight junction gene expression, which may affect respiratory health.
  • The study suggests that targeting AXL and ZEB1 with specific inhibitors could help reverse the negative effects of EMT caused by SARS-CoV-2, providing insights into the virus’s impact on both general and cancer-affected populations.

Article Abstract

COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of and . We find that expression is restricted to a select population of highly epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium, induces metabolic and transcriptional changes consistent with epithelial to mesenchymal transition (EMT), including upregulation of and , resulting in an increased EMT score. Additionally, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT via TGFbeta, ZEB1 overexpression and onset of EGFR TKI inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect. These observations highlight the utility of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses, and offer important insights into the potential mechanisms underlying the morbidity and mortality of COVID-19 in healthy patients and cancer patients alike.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302206PMC
http://dx.doi.org/10.1101/2020.05.28.122291DOI Listing

Publication Analysis

Top Keywords

lung cancer
8
infection sars-cov-2
8
tight junction
8
sars-cov-2
6
cancer models
4
models reveal
4
reveal sars-cov-2-induced
4
emt
4
sars-cov-2-induced emt
4
emt contributes
4

Similar Publications

Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.

J Med Internet Res

January 2025

Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.

View Article and Find Full Text PDF

Metastasis stands as one of the most prominent prognostic factors in osteosarcoma. Over 70% of metastatic osteosarcoma occurrences affect the lung. Nonetheless, to date, there has been a scarcity of research addressing predictive factors for lung metastasis risk in osteosarcoma.

View Article and Find Full Text PDF

Lung adenocarcinoma (LUAD) is the most common histological subtype of nonsmall-cell lung cancer. Herein, a multiomics method, which combined proteomic and N-glycoproteomic analyses, was developed to analyze the normal and cancerous bronchoalveolar lavage fluids (BALFs) from six LUAD patients to identify potential biomarkers of LUAD. The data-independent acquisition proteomic analysis was first used to analyze BALFs, which identified 59 differentially expressed proteins (DEPs).

View Article and Find Full Text PDF

This study determined the characteristics of patients with early-stage melanoma (IA-IIA) who later had stage IV recurrence. We retrospectively examined 880 melanoma patients and identified those who progressed to stage IV disease from an initial early-stage (n = 50). We observed a median latent period of 4 years between early-stage diagnosis and metastatic disease.

View Article and Find Full Text PDF

Effects of early palliative care intervention on medical resource use among end-of-life patients.

Int J Qual Health Care

January 2025

Department of Medical Laboratory Science and Biotechnology, Central Taiwan University of Science and Technology, No. 666 Buzih Road, Taichung City 40601, Taiwan.

Background: In Taiwan, as the population ages, palliative care services (PCS) have expanded significantly to include comprehensive benefit plans for critically ill individuals, supported by reimbursements from the National Health Insurance program. However, incorporating palliative care into the medical management of these patients presents several challenges. We aim to evaluate the effects of palliative care interventions on medical resources in end-of-life scenarios, to promote earlier palliative care access and provide high-quality healthcare services for patients.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!