A Radioresponse-Related lncRNA Biomarker Signature for Risk Classification and Prognosis Prediction in Non-Small-Cell Lung Cancer
Author(s) -
Jiahang Song,
Shuming Zhang,
Yuanyuan Sun,
Junjie Gu,
Ziqi Ye,
Xinchen Sun,
Qiyun Tang
Publication year - 2021
Publication title -
journal of oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.228
H-Index - 54
eISSN - 1687-8469
pISSN - 1687-8450
DOI - 10.1155/2021/4338838
Subject(s) - medicine , biomarker , lung cancer , oncology , signature (topology) , cancer , biology , genetics , geometry , mathematics
Purpose Radiotherapy resistance is now recognized as the major obstacle to the effective therapeutic management of non-small-cell lung cancer (NSCLC). As a single biomarker has limited effect in stratifying NSCLC patients, this research aimed to identify long non-coding RNAs (lncRNAs) correlated with radiotherapy response to ameliorate forecast of NSCLC prognosis.Methods In a cohort of NSCLC patients with radiotherapy history ( n = 96) from TCGA, genetic data of lncRNA expression profiling were performed. To identify radioresponse-related lncRNA sets which dysregulated significantly between radiosensitive (RS) and radioresistant (RR) groups, differential expression analysis was carried out. Cox relative regression was implemented to set up a radioresponse-related risk model. Moreover, we adopted survival analysis to measure the predictive potentiality of the prognosis model.Results Four radioresponse-related lncRNAs (CASC19, LINC01977, LINC02471, and MAGI2-AS3) were screened to create a prognostic signature. Then, we described a lncRNA signature-based regulatory network and explored the correlation of the immune microenvironment and the signature. Additionally, in vitro assays uncovered inhibition of LINC01977 weakened radioresistance of NSCLC cells.Conclusion We provided a novel radioresponse-related lncRNAs signature with excellent clinical potency for an effective prognostic forecast of patients.
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