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Circulating Long Noncoding RNAs Act as Diagnostic Biomarkers in Non-Small Cell Lung Cancer

ABSTRACT: Identification of novel effective early diagnostic biomarkers may provide alternative strategies to reduce the mortality for non-small cell lung cancer (NSCLC) patients. Circulating long non-coding RNAs (lncRNAs) have emerged as a new class of promising cancer biomarkers. Our study aimed to identify circulating lncRNAs for diagnosing NSCLC. A total 528 plasma samples were continuously collected and allocated to four progressive phases: discovery, training, verification, and expansion phases. The expression of candidate lung cancer related lncRNAs were detected using quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). We identified a 4-lncRNA panel (RMRP, NEAT1, TUG1, and MALAT1) that provided a high diagnostic value in NSCLC (AUC = 0.86 and 0.89 for training and verification phase, respectively). Subgroup analyses showed that the 4-lncRNA panel had a sensitivity of 78.95% [95% confidence interval (CI) = 62.22%–89.86%] in stage I-II patients and 75.00% (95% CI = 52.95%–89.40%) in patients with small tumor size (?3cm). Notably, the sensitivity of 4-lncRNA panel was significantly higher than that of routine protein panels in adenocarcinoma (CEA, CA125, and CYFRA21-1, 86.30% vs. 73.96%). Adding 4-lncRNA to protein markers significantly improved the diagnostic capacity in both adenocarcinoma (AUC=0.85, 95% CI = 0.78–0.91) and squamous cell carcinoma (AUC=0.93, 95% CI = 0.86–0.97). In conclusion, we identified a plasma 4-lncRNA panel that has considerable clinical value in diagnosing NSCLC. The 4-lncRNA panel could improve the diagnostic values of routine tumor protein markers in diagnosing NSCLC. Circulating lncRNAs could be used as promising candidates for NSCLC diagnosis.

SUBMITTER: Yuan S

PROVIDER: S-EPMC7793881 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Lung cancer is the first leading cause of cancer deaths worldwide. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Increasing evidence shows that long noncoding RNA (lncRNA) are capable of modulating tumor initiation, proliferation and metastasis. In the present study, we aimed to evaluate whether circulating lncRNA could be used as biomarkers for diagnosis and prognosis of NSCLC. Expression profiles of 14 lncRNA selected from other studies were validated in 20 pairs of tissues by quantitative real-time PCR, and the dysregulated lncRNA thus identified were further validated in serum samples from two independent cohorts along with three tumor makers (CEA, CYFRA21-1, and SCCA). Receiver-operating characteristic analysis was utilized to estimate the diagnostic efficiency of the candidate lncRNA and tumor markers. Importantly, we observed an association between lncRNA expression and overall survival (OS) rate of NSCLC. The expressions of SOX2 overlapping transcript (SOX2OT) and ANRIL were obviously upregulated in NSCLC tissues and serum samples compared with normal controls (P < 0.01). Based on the data from the training set, we next used a logistic regression model to construct an NSCLC diagnostic panel consisting of two lncRNA and three tumor markers. The area under the curve of this panel was 0.853 (95% confidence interval = 0.804-0.894, sensitivity = 77.1%, specificity = 79.2%), and this was distinctly superior to any biomarker alone (all at P < 0.05). Similar results were observed in the validation set. Intriguingly, Kaplan-Meier analysis demonstrated that low expressions of SOX2OT and ANRIL were both associated with higher OS rate (P = 0.008 and 0.017, respectively), and SOX2OT could be used as an independent prognostic factor (P = 0.036). Taken together, our study demonstrated that the newly developed diagnostic panel consisting of SOX2OT, ANRIL, CEA, CYFRA21-1, and SCCA could be valuable in NSCLC diagnosis. LncRNA SOX2OT and ANRIL might be ideal biomarkers for NSCLC prognosis.

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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Circulating Long Noncoding RNAs Act as Diagnostic Biomarkers in Non-Small Cell Lung Cancer

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