Fan K-J, Liu Y, Yang B, Tian X-D, Li C-R, Wang B
Department of Thoracic Surgery, Chinese PLA General Hospital, Beijing, China.
Eur Rev Med Pharmacol Sci. 2017 May;21(10):2392-2396.
The purpose of this study was to explore whether long non-coding RNA AGAP2-AS1 (AGAP2-AS1) could serve as a novel biomarker for non-small-cell lung cancer (NSCLC).
Cancer and matched normal lung tissues were collected from 198 patients. AGAP2-AS1 levels were examined by RT-PCR, and the associations of AGAP2-AS1 levels with clinicopathological characteristics evaluated. Overall survival was evaluated using the Kaplan-Meier method. Cox proportional hazard modeling was performed for univariate and multivariate analysis to determine the effects of variables on survival. Receiver-operating characteristic. Besides, the receiver operating characteristic (ROC) curve analysis were applied to analyze its diagnostic value.
Expression of AGAP2-AS1 was up-regulated in the NSCLC tissues compared with the adjacent normal tissues (p < 0.01). Furthermore, The level of AGAP2-AS19 in NSCLC was strongly correlated with tumor stage (p = 0.001) and lymph nodes metastasis (p = 0.005). Kaplan-Meier analysis demonstrated patients with higher AGAP2-AS1 expression had a shorter overall survival time than those with lower AGAP2-AS1 expression (p < 0.0001). The multivariate analysis showed that AGAP2-AS1 expression is an independent prognostic factor of overall survival in patients with NSCLC. The results of ROC curve analysis showed that AGAP2-AS1 might be a promising diagnostic marker of NSCLC with an AUC of 0.846.
Our findings revealed that AGAP2-AS1 might be a potential biomarker for the diagnosis and prognosis of NSCLC. However, to completely elucidate its role as a biomarker, further studies are required.
本研究旨在探讨长链非编码RNA AGAP2-AS1是否可作为非小细胞肺癌（NSCLC）的新型生物标志物。
收集198例患者的癌组织及配对的正常肺组织。采用RT-PCR检测AGAP2-AS1水平，并评估AGAP2-AS1水平与临床病理特征的相关性。采用Kaplan-Meier法评估总生存期。进行Cox比例风险建模以进行单因素和多因素分析，以确定变量对生存的影响。此外，应用受试者工作特征（ROC）曲线分析来分析其诊断价值。
与相邻正常组织相比，NSCLC组织中AGAP2-AS1的表达上调（p<0.01）。此外，NSCLC中AGAP2-AS1水平与肿瘤分期（p = 0.001）和淋巴结转移（p = 0.005）密切相关。Kaplan-Meier分析表明，AGAP2-AS1表达较高的患者总生存时间短于AGAP2-AS1表达较低的患者（p<0.0001）。多因素分析显示，AGAP2-AS1表达是NSCLC患者总生存的独立预后因素。ROC曲线分析结果显示，AGAP2-AS1可能是一种有前景的NSCLC诊断标志物，AUC为0.846。
我们的研究结果表明，AGAP2-AS1可能是NSCLC诊断和预后的潜在生物标志物。然而，要完全阐明其作为生物标志物的作用，还需要进一步研究。
