4.7 Article

Circulating long noncoding RNA act as potential novel biomarkers for diagnosis and prognosis of non-small cell lung cancer

期刊

MOLECULAR ONCOLOGY
卷 12, 期 5, 页码 648-658

出版社

WILEY
DOI: 10.1002/1878-0261.12188

关键词

diagnosis; long noncoding RNA; non-small cell lung cancer; prognosis; serum; tumor biomarker

类别

资金

  1. National Natural Science Foundation of China [81472025, 81400029, 81502164]
  2. Scientific Research Award Foundation for Outstanding Young and Middle-Aged Scientists of Shandong Province [BS2014YY011, BS2015YY004]
  3. Shandong Medical and Health Science and Technology Development Programs [2014WS0143]
  4. Shandong Technological Development Project [2016CYJS01A02, 2015GSF118052, 2016GSF201055, 2016GSF201165]
  5. Taishan Scholar Program of Shandong Province

向作者/读者索取更多资源

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.

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