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Evaluation of the Prognostic Value of Long Noncoding RNAs in Lung Squamous Cell Carcinoma.

ABSTRACT: Lung squamous cell carcinoma (LUSC) is the most common type of lung cancer accounting for 40% to 51%. Long noncoding RNAs (lncRNAs) have been reported to play a significant role in the invasion, migration, and proliferation of lung cancer tissue cells. However, systematic identification of lncRNA signatures and evaluation of the prognostic value for LUSC are still an urgent problem. In this work, LUSC RNA-seq data were collected from TCGA database, and the limma R package was used to screen differentially expressed lncRNAs (DElncRNAs). In total, 216 DElncRNAs were identified between the LUSC and normal samples. lncRNAs associated with prognosis were calculated using univariate Cox regression analysis. The overall survival (OS) prognostic model containing 10 lncRNAs and the disease-free survival (DFS) prognostic model consisting of 11 lncRNAs were constructed using a machine learning-based algorithm, systematic LASSO-Cox regression analysis. We found that the survival rate of samples in the high-risk group was lower than that in the low-risk group. Results of ROC curves showed that both the OS and DFS risk score had better prognostic effects than the clinical characteristics, including age, stage, gender, and TNM. Two lncRNAs (LINC00519 and FAM83A-AS1) that were commonly identified as prognostic factors in both models could be further investigated for their clinical significance and therapeutic value. In conclusion, we constructed lncRNA prognostic models with considerable prognostic effect for both OS and DFS of LUSC.

SUBMITTER: Zhang X

PROVIDER: S-EPMC8776467 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLong 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.MethodsTranscriptome 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.ResultsAmong 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.ConclusionTherefore, lincRNAs could be promising biomarkers for predicting malignancies and potential anti-LSqCC targets for drug development.

Project description:Many long noncoding RNAs (lncRNAs) are deregulated in cancer and contribute to oncogenesis. In urothelial carcinoma (UC), several lncRNAs have been reported to be overexpressed and proposed as biomarkers. As most reports have not been confirmed independently in large tissue sets, we aimed to validate the diagnostic and prognostic value of lncRNA upregulation in independent cohorts of UC patients. Thus, expression of seven lncRNA candidates (GAS5, H19, linc-UBC1, MALAT1, ncRAN, TUG1, UCA1) was measured by RT-qPCR in cell lines and tissues and correlated to clinicopathological parameters including follow-up data (set 1: N n = 10; T n = 106). Additionally, publicly available TCGA data was investigated for differential expression in UC tissues (set 2: N n = 19; T n = 252,) and correlation to overall survival (OS). All proposed candidates tended to be upregulated in tumour tissues, with the exception of MALAT1, which was rather diminished in cancer tissues of both data sets. However, strong overexpression was generally limited to individual tumour tissues and statistically significant overexpression was only observed for UCA1, TUG1, ncRAN and linc-UBC1 in tissue set 2, but for no candidate in set 1. Altered expression of individual lncRNAs was associated with overall survival, but not consistently between both patient cohorts. Interestingly, lower expression of TUG1 in a subset of UC patients with muscle-invasive tumours was significantly correlated with worse OS in both cohorts. Further analysis revealed that tumours with low TUG1 expression are characterized by a basal-squamous-like subtype signature accounting for the association with poor outcome. In conclusion, our study demonstrates that overexpression of the candidate lncRNAs is found in many UC cases, but does not occur consistently and strongly enough to provide reliable diagnostic or prognostic value as an individual biomarker. Subtype-dependent expression patterns of lncRNAs like TUG1 could become useful to stratify patients by molecular subtype, thus aiding personalized treatments.

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Evaluation of the Prognostic Value of Long Noncoding RNAs in Lung Squamous Cell Carcinoma.

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