Research Article

Bioinformatics of Department, Key laboratory of Cell Biology, Ministry of Public Health, & Key Laboratory of Medical Cell Biology, Ministry of Education, School of Life Sciences, China Medical University, Shenyang 110122, PR China

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Yunhui Li^‡

*Author for correspondence:

E-mail Address: liyunhui2737@163.com

;

E-mail Address: bliang@cmu.edu.cn

https://orcid.org/0000-00013-1466-8776

Clinical Laboratory, PLA North Military Command Region General Hospital, Shenyang 110003, PR China

^‡Authors contributed equally

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Bin Liang^‡

*Author for correspondence:

E-mail Address: liyunhui2737@163.com

;

E-mail Address: bliang@cmu.edu.cn

https://orcid.org/0000-0001-8052-7926

^‡Authors contributed equally

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Published Online:5 Jun 2020

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Abstract

Aim: Understanding the cell types and cell compositions in tumor environment (TME) and the gene changes in lung adenocarcinoma (LUAD) may provide insights on immune profiles and treatment targets for LUAD patients. Materials & methods: The RNA-Seq data from The Cancer Genome Atlas database were used to calculate the stromal scores and immune scores and analyzed the fractions of tumor infiltrating immune cells in LUAD samples with ESTIMATE and CIBERSORT algorithm. Results: We extracted a list of TME-related differentially expressed genes and performed the functional enrichment analysis. We found these genes were mainly enriched in immune response and cancer-related signal pathways. The prognosis analysis indicated that LINC00211, MUC2, LINC00426, LY86-AS1 ZEB2-AS1 and EREG were associated with prognosis in LUAD patients. Conclusion: The current study provides novel insights into immune files and gene changes in TME in LUAD patients.

Keywords:

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Vol. 16, No. 24

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History

Received 16 December 2020

Accepted 20 May 2020

Published online 5 June 2020

Published in print August 2020

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Keywords

Author contributions

L Bin designed the study, including data analysis, supervised the data treatment and wrote the manuscript. T Ye performed the data collection, data analysis and software use. L Yunhui contributed to the revision of manuscript.

Acknowledgments

We thank the TCGA database for providing their platforms and contributors for their valuable datasets.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

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Comprehensive analysis of microenvironment-related genes in lung adenocarcinoma

Abstract

References