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ABSTRACT: Background
Although the relationship between inflammatory response and tumor has been gradually recognized, the potential implications of of inflammatory response genes in lung adenocarcinoma (LUAD) remains poorly investigated.Methods
RNA sequencing and clinical data were obtained from multiple independent datasets (GSE29013, GSE30219, GSE31210, GSE37745, GSE42127, GSE50081, GSE68465, GSE72094, TCGA and GTEx). Unsupervised clustering analysis was used to identify different tumor subtypes, and LASSO and Cox regression analysis were applied to construct a novel scoring tool. We employed multiple algorithms (ssGSEA, CIBERSORT, MCP counter, and ESTIMATE) to better characterize the LUAD tumor microenvironment (TME) and immune landscapes. GSVA and Metascape analysis were performe
SUBMITTER: Song C
PROVIDER: S-EPMC9484176 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature