Journal
CANCER IMMUNOLOGY IMMUNOTHERAPY
Volume 70, Issue 10, Pages 2835-2850Publisher
SPRINGER
DOI: 10.1007/s00262-021-02896-6
Keywords
Lung adenocarcinoma; Metabolism; Immune infiltration; Immunotherapy; PD-1
Categories
Funding
- Anhui Provincial Natural Science Foundation [1808085QH270, 2008085QH428]
- Fundamental Research Funds for the Central Universities [WK9110000121]
- National Natural Science Foundation of China, China [82073893, 81703622]
- Postdoctoral Science Foundation [2018M633002]
- Hunan Provincial Natural Science Foundation of China [2018JJ3838]
- Hunan Provincial Health Committee Foundation of China [C2019186]
- Xiangya Hospital Central South University postdoctoral foundation
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This study revealed the significant connection between the metabolic pattern of tumor and tumor immune infiltration, regulating LUAD patients' response to immunotherapy. The scoring system based on metabolism-related gene expression can not only predict LUAD patient prognosis, but also be applied to pan-cancer to predict response to checkpoint immunotherapy.
Background Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), causes high mortality around the world. Previous studies have suggested that the metabolic pattern of tumor is associated with tumor response to immunotherapy and patient's survival outcome. Yet, this relationship in LUAD is still unknown. Methods Therefore, in this study, we identified the immune landscape in different tumor subtypes classified by metabolism-related genes expression with a large-scale dataset (tumor samples, n = 2181; normal samples, n = 419). We comprehensively correlated metabolism-related phenotypes with diverse clinicopathologic characteristics, genomic features, and immunotherapeutic efficacy in LUAD patients. Results And we confirmed tumors with activated lipid metabolism tend to have higher immunocytes infiltration and better response to checkpoint immunotherapy. This work highlights the connection between the metabolic pattern of tumor and tumor immune infiltration in LUAD. A scoring system based on metabolism-related gene expression is not only able to predict prognosis of patient with LUAD but also applied to pan-cancer. LUAD response to checkpoint immunotherapy can also be predicted by this scoring system. Conclusions This work revealed the significant connection between metabolic pattern of tumor and tumor immune infiltration, regulating LUAD patients' response to immunotherapy.
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