4.6 Article

Identification of Tumor Microenvironment-Related Prognostic lncRNAs in Lung Adenocarcinoma

Journal

FRONTIERS IN ONCOLOGY
Volume 11, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.719812

Keywords

lung adenocarcinoma; lncRNAs; LASSO regression; immune microenvironment; prognostic biomarkers

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Funding

  1. Wu Jie Ping Medical Foundation [320.6750.2020-19-31]

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In this study, 16 key lncRNAs were identified as potential biomarkers and therapeutic targets for predicting the survival of LUAD. The LASSO method was used to select these lncRNAs, and their relationship with TP53 mutation and pathological stage was also explored. The lncRNA-based model was effective in predicting patient prognosis in validation cohort, suggesting the importance of immune microenvironment-related lncRNAs in LUAD prognosis.
Background Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is a severe threat to human health. Although many therapies have been applied to LUAD, the long-term survival rate of patients remains unsatisfactory. We aim to find reliable immune microenvironment-related lncRNA biomarkers to improve LUAD prognosis. Methods ESTIMATE analysis was performed to evaluate the degree of immune infiltration of each patient in TAGA LUAD cohort. Correlation analysis was used to identify the immune microenvironment-related lncRNAs. Univariate cox regression analysis, LASSO analysis, and Kaplan Meier analysis were used to construct and validate the prognostic model based on microenvironment-related lncRNAs. Results We obtained 1,178 immune microenvironment-related lncRNAs after correlation analysis. One hundred and eighty of them are independent prognostic lncRNAs. Sixteen key lncRNAs were selected by LASSO method. This lncRNA-based model successfully predicted patients' prognosis in validation cohort, and the risk score was related to pathological stage. Besides, we also found that TP53 had the highest frequency mutation in LUAD, and the mutation of TP53 in the high-risk group, which was identified by our survival model, has a poor prognosis. lncRNA-mRNA co-expression network further suggested that these lncRNAs play a vital role in the prognosis of LUAD. Conclusion Here, we filtered 16 key lncRNAs, which could predict the survival of LUAD and may be potential biomarkers and therapeutic targets.

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