A practical prognostic lncRNA signature for lung squamous cell carcinoma


Background: This study aimed to develop and assess a practical prognostic lncRNA signature for squamous cell carcinoma of the lung (LUSC). Methods: RNA expression profile and clinical data from 388 LUSC patients were accessed and download from the Cancer Genome Atlas (TCGA) database. Differential lncRNA expression was compared and analyzed between normal tissue and tumor samples. By univariate and multivariate Cox regression analyses, a seven-lncRNA signature was developed and used for the purpose of survival prediction in LUSC patients. We applied receiver operating characteristic analysis to assess the performance of our model. The gene ontology enrichment analysis of seven lncRNA-related protein-coding genes was used to predict the potential biological functions of these lncRNAs. Results: Sixteen out of 1414 differentially expressed lncRNAs in the TCGA dataset were associated with the overall survival of LUSC patients. Risk score analysis was used to select seven lncRNAs to be included in our model development and validation. The ROC analysis indicated that the specificity and sensitivity of this profile are high. Further functional enrichment analyses suggest that these lncRNAs may regulate genes that affect the function of the major histocompatibility complex and the cell membrane. Conclusions: The current study identified a seven-lncRNA signature that predicts the outcome of LUSC, offering potentially novel therapeutic targets for the treatment of squamous cell carcinoma of the lung.

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@inproceedings{Shi2017APP, title={A practical prognostic lncRNA signature for lung squamous cell carcinoma}, author={Xiaoshun Shi and Fuxi Huang and Xiaobing Le and Xiaoxiang Li and Kailing Huang and Baoxin Liu and Viola Yingjun Luo and Yan-Hui Liu and Zhuolin Wu and Allen M Chen and Ying Liang and Jiexia Zhang}, year={2017} }