Tumor microenvironment characterization identifies two lung adenocarcinoma subtypes with specific immune and metabolic state. Issue 6 (17th April 2020) - Huang, Jianbing; Li, Jiagen; Zheng, Sufei; Lu, Zhiliang; Che, Yun; Mao, Shuangshuang; Lei, Yuanyuan; Zang, Ruochuan; Liu, Chengming; Wang, Xinfeng; Fang, Lingling; Sun, Nan; et al.
Abstract: The tumor microenvironment (TME) is a vital component of tumor tissue. Increasing evidence suggests their significance in predicting outcomes and guiding therapies. However, no studies have reported a systematic analysis of the clinicopathologic significance of TME in lung adenocarcinoma (LUAD). Here, we inferred tumor stromal cells in 1184 LUAD patients using computational algorithms based on bulk tumor expression data, and evaluated the clinicopathologic significance of stromal cells. We found LUAD patients showed heterogeneous abundance in stromal cells. Infiltration of stromal cells was influenced by clinicopathologic features, such as age, gender, smoking, and TNM stage. By clustering stromal cells, we identified 2 clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features. The immune active subtype is characterized by repressed metabolism and repressed proliferation of tumor cells, while the immune repressed subtype is characterized by 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 a TME score using principal component analysis based on the immune activation signature. The TME score predicted TME subtypes effectively in 3 independent datasets with areas under the receiver operating characteristic curves of 0.960, 0.812, and 0.819, respectively. In conclusion, we proposed 2 clinically and molecularly distinct LUAD subtypes based on tumor microenvironment that could be valuable in predicting clinical outcome and guiding immunotherapy. Abstract : In the present study, we systematically profiled tumor microenvironment (TME) cell landscape of 1184 lung adenocarcinomas using computational algorithms and analyzed clinical implications of TME cells. Based on the TME cell profile, we identified and characterized 2 clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features that could be valuable in predicting clinical outcome and guiding immunotherapy.