2024
DOI: 10.3389/fimmu.2024.1366928
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Computational identification and experimental verification of a novel signature based on SARS-CoV-2–related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients

Yuzhi Wang,
Yunfei Xu,
Yuqin Deng
et al.

Abstract: BackgroundEarly research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined.MethodsWe acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-… Show more

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