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Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma

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Abstract

The tumor microenvironment (TME) plays an essential role in the occurrence and progression of malignancy. The potential prognostic TME-related biomarkers of lung adenocarcinoma (LUAD) remained unclear, which were investigated in this research. The RNA-sequencing profiles and corresponding clinical parameters were extracted from TCGA and GEO databases, based on which the stromal and immune scores were calculated through the ESTIMATE algorithm. Overlapping differentially expressed genes between stromal and immune score group were analyzed by the LASSO and Random Forrest algorithms and validated in cases from our center. And a prognostic 8-gene signature was constructed using Cox regression. The infiltration of 22 hematopoietic cell phenotypes was assessed by the CIBERSORT algorithms. We found that female, elder patients, and solid predominant subtype had obviously higher stromal and immune scores. And patients with early stage LUAD received a prominently higher immune score. A high stromal or immune score meant a good prognosis. Subsequently, eight TME-related prognostic genes (ATAD5, CYP4F3, CYP4F12, ESPNL, FXYD2, GPX2, NLGN4Y, and SERPINC1) were identified by both LASSO regression and Radom Forest algorithms. High 8-gene signature group exhibited worse overall survival. Furthermore, B cell naïve, plasma cells, T cell follicular helper, and macrophages M1 were prominently more in high signature group. Nevertheless, fewer T cells CD4 memory resting, monocytes, and dendritic cell resting were identified in the high signature group. The composition of the tumor microenvironment significantly affected the prognosis of LUAD patients. We provided a new strategy for the exploration of prognostic TME-related biomarkers and immunotherapy.

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Data availability

The RNA-sequencing profiles and corresponding clinical phenotypes were extracted from TCGA and GEO database, which were open-access.

Code availability

R software (version 3.63) was used for analysis and plotting.

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Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 81672268).

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Author notes

  1. Mengnan Zhao, Ming Li, and Zhencong Chen equally contributed to this work.

Authors and Affiliations

  1. Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China

    Mengnan Zhao, Ming Li, Zhencong Chen, Yunyi Bian, Yuansheng Zheng, Zhengyang Hu, Jiaqi Liang, Yiwei Huang, Jiacheng Yin, Cheng Zhan, Mingxiang Feng & Qun Wang

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  1. Mengnan Zhao
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  2. Ming Li
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  3. Zhencong Chen
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Contributions

Mengnan Zhao: study design, analysis, and interpretation of data, drafting the article, final approval; Zhencong Chen: study design, analysis, and interpretation of data, drafting the article, final approval; Ming Li: study design, analysis, and interpretation of data, drafting the article, final approval; Yunyi Bian: acquisition of data, drafting the article, revising the article, final approval; Yuansheng Zheng: analysis and interpretation of data, drafting the article, final approval; Zhengyang Hu: analysis and interpretation of data, drafting the article, final approval; Jiaqi Liang: analysis and interpretation of data, drafting the article, final approval; Yiwei Huang: analysis and interpretation of data, drafting the article, final approval; Jiacheng Yin: analysis and interpretation of data, drafting the article, final approval; Cheng Zhan: study design, analysis and interpretation of data, drafting the article, revising the article critically for important intellectual content, final approval, agreement to be accountable for all aspects of the work; Mingxiang Feng: study design, drafting the article, revising the article critically for important intellectual content, final approval, agreement to be accountable for all aspects of the work; Qun Wang: study design, drafting the article, revising the article critically for important intellectual content, final approval.

Corresponding authors

Correspondence to Cheng Zhan, Mingxiang Feng or Qun Wang.

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Conflict of interests

The authors declare that they have no conflict of interest.

Ethics approval

This study was conducted with approval by the Ethics Committee of Zhongshan Hospital, Fudan University, Shanghai, China (Approval No. B2017-042).

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Written informed consent was obtained from all patients.

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Zhao, M., Li, M., Chen, Z. et al. Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma. Immunogenetics 72, 455–465 (2020). https://doi.org/10.1007/s00251-020-01189-z

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  • DOI: https://doi.org/10.1007/s00251-020-01189-z

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