Integrated analysis of two-lncRNA signature as a potential prognostic biomarker in cervical cancer: a study based on public database

BACKGROUND: Cervical cancer (CC) is a common gynecological malignancy in women worldwide. Evidence suggests that long non-coding RNAs (lncRNAs) can be used as biomarkers in patients with CC. However, prognostic biomarkers for CC are still lacking. The aim of our study was to find lncRNA biomarkers which are able to predict prognosis in CC based on the data from The Cancer Genome Atlas (TCGA). METHODS: The patients were divided into three groups according to FIGO stage. Differentially expressed lncRNAs were identified in CC tissue compared to adjacent normal tissues based on a fold change >2 and <0.5 at P < 0.05 for up- and downregulated lncRNA, respectively. The relationship between survival outcome and lncRNA expression was assessed with univariate and multivariate Cox proportional hazards regression analysis. We constructed a risk score as a method to evaluate prognosis. We used receiver operating characteristic (ROC) curve and the area under curve (AUC) analyses to assess the diagnostic value of a two-lncRNA signature. We detected the expression levels of the two lncRNAs in 31 pairs of newly diagnosed CC specimens and paired adjacent non-cancerous tissue specimens, and also in CC cell lines. Finally, the results were statistically compared using t-tests. RESULTS: In total, 289 RNA sequencing profiles and accompanying clinical data were obtained. We identified 49 differentially expressed lncRNAs, of which two related to overall survival (OS) in CC patients. These two lncRNAs (ILF3-AS1 and RASA4CP) were found together as a single prognostic signature. Meanwhile, the prognosis of patients with low-risk CC was better and positively correlated with OS (P < 0.001). Further analysis showed that the combined two-lncRNA expression signature could be used as an independent biomarker to evaluate the prognosis in CC. qRT-PCR results were consistent with TCGA, confirming downregulated expression of both lncRNAs. Furthermore, upon ROC curve analysis, the AUC of the combined lncRNAs was greater than that of the single lncRNAs alone (0.723 vs 0.704 and 0.685), respectively; P < 0.05. CONCLUSIONS: Our study showed that the two-lncRNA signature of ILF3-AS1 and RASA4CP can be used as an independent biomarker for the prognosis of CC, based on bioinformatic analysis.