Transcriptional profiling of long-intergenic noncoding RNAs in lung squamous cell carcinoma and its value in diagnosis and prognosis

Abstract

Background: Long intergenic noncoding RNAs (lincRNAs) are a series of novel transcribed regions expressed in cancers that may represent candidate biomarkers for lung squamous cell carcinoma (LSqCC) treatment. In this study, we evaluated the lincRNA profile in LSqCC patients and screened valuable lincRNAs for diagnosis and prognosis. Methods: Transcriptome profiling of 549 samples derived from 501 LSqCC patients were identified in TCGA database. 48 patients had paired primary tumor (PT) and solid normal (SN) tissue samples, while 453 patients had only PT samples. 1,771 lincRNA candidates were evaluated. Paired test (Wilcoxon two-sample paired signed rank tests) was performed in paired PT and SN samples. Logistic regression analysis were performed in independent 453 PT samples and 48 SN samples to screen the significant lincRNAs candidates for malignances. Independent 501 PT samples were further used to screen the significant lincRNAs candidates for prognosis. Results: Among 1,771 lincRNAs, 10 lincRNAs were significant highly-expressed risk candidates in PT samples, and 10 protective lincRNAs candidates were significant lowly-expressed in PT samples. Among 10 highly-expressed risk lincRNAs, a small panel of LINC00487, LINC01927, and C10orf143 (LINC00959) could effectively predict malignancies in paired samples (AUC = 0.7274, 95%CI = (0.6264, 0.8285)). When combined with protective lincRNA candidates LINC02315, LINC00491, and LINC01697, the predictive efficiency was greatly improved in both paired samples (AUC = 0.8030, 95%CI = (0.7250, 0.8810)) and independent samples (AUC = 0.7481, 95%CI= (0.6642, 0.8320)). Additionally, three highly-expressed risk lincRNAs, LINC01031, LINC01088, and LINC01931, were significantly associated with poor prognosis in PT samples, suggesting potential targets for anti-LSqCC treatment. Conclusion: Therefore, lincRNAs could be promising biomarkers for predicting malignancies and potential anti-LSqCC targets for drug development.