Acute Influenza Infection Promotes Lung Tumor Growth by Reprogramming the Tumor Microenvironment.

One billion people worldwide get flu every year, including patients with non-small cell lung cancer (NSCLC). However, the impact of acute influenza A virus (IAV) infection on the composition of the tumor microenvironment (TME) and the clinical outcome of patients with NSCLC is largely unknown. We set out to understand how IAV load impacts cancer growth and modifies cellular and molecular players in the TME. Herein, we report that IAV can infect both tumor and immune cells, resulting in a long-term protumoral effect in tumor-bearing mice. Mechanistically, IAV impaired tumor-specific T-cell responses, led to the exhaustion of memory CD8+ T cells and induced PD-L1 expression on tumor cells. IAV infection modulated the transcriptomic profile of the TME, fine-tuning it toward immunosuppression, carcinogenesis, and lipid and drug metabolism. Consistent with these data, the transcriptional module induced by IAV infection in tumor cells in tumor-bearing mice was also found in human patients with lung adenocarcinoma and correlated with poor overall survival. In conclusion, we found that IAV infection worsened lung tumor progression by reprogramming the TME toward a more aggressive state.

Immune Signature Linked to COVID-19 Severity: A SARS-Score for Personalized Medicine.

SARS-CoV-2 infection leads to a highly variable clinical evolution, ranging from asymptomatic to severe disease with acute respiratory distress syndrome, requiring intensive care units (ICU) admission. The optimal management of hospitalized patients has become a worldwide concern and identification of immune biomarkers predictive of the clinical outcome for hospitalized patients remains a major challenge. Immunophenotyping and transcriptomic analysis of hospitalized COVID-19 patients at admission allow identifying the two categories of patients. Inflammation, high neutrophil activation, dysfunctional monocytic response and a strongly impaired adaptive immune response was observed in patients who will experience the more severe form of the disease. This observation was validated in an independent cohort of patients. Using in silico analysis on drug signature database, we identify differential therapeutics that specifically correspond to each group of patients. From this signature, we propose a score-the SARS-Score-composed of easily quantifiable biomarkers, to classify hospitalized patients upon arrival to adapt treatment according to their immune profile.