Tumor microenvironment (TME) are vital components of tumor tissue. Increasing evidence suggest their significance in predicting outcomes and guiding therapies. However, no studies have reported a systematic analysis of clinicopathological significance of TME in lung adenocarcinoma (LUAD). Here, we inferred tumor stromal cells in 1,184 LUAD patients using computational algorithms based on bulk tumor expression data, and evaluated clinicopathological significance of stromal cells. We found LUAD patients showed heterogeneous abundance in stromal cells. Infiltration of stromal cells was influenced by clinicopathological features, such as age, gender, smoking and TNM stage. By clustering stromal cells, we identified two clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features. The immune active subtype is characterized with repressed metabolism and repressed proliferation of tumor cells, while the immune repressed subtype is characterized with active metabolism and active proliferation of tumor cells. Differentially expressed gene analysis of the two LUAD subtypes identified an immune-activation signature. To diagnose TME subtypes practically, we constructed TME score using principal component analysis based on the immune-activation signature. The TME score predicted TME subtypes effectively in three independent datasets with areas under the curves (AUCs) of 0.960, 0.812, and 0.819, respectively. In conclusion, we proposed two clinically and molecularly distinct LUAD subtypes based on tumor microenvironment that may be valuable in predicting clinical outcome and guiding immunotherapy.
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