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
ConclusionOur research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor’s local immune condition, and supports clinical decision-making in tumor therapies.
Source: Frontiers in Immunology - Category: Allergy & Immunology Source Type: research
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