z-logo
open-access-imgOpen Access
Tumor microenvironment characterization identifies two lung adenocarcinoma subtypes with specific immune and metabolic state
Author(s) -
Huang Jianbing,
Li Jiagen,
Zheng Sufei,
Lu Zhiliang,
Che Yun,
Mao Shuangshuang,
Lei Yuanyuan,
Zang Ruochuan,
Liu Chengming,
Wang Xinfeng,
Fang Lingling,
Sun Nan,
He Jie
Publication year - 2020
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/cas.14390
Subject(s) - stromal cell , immune system , tumor microenvironment , adenocarcinoma , immunotherapy , cancer research , biology , stroma , immunology , immunohistochemistry , cancer , genetics
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here