Objective: To explore the possible biological function of long-chain non-coding RNA (lncRNA) on epithelial ovarian cancer (EOC) drug resistance and the value of new diagnostic markers through bioinformatics analysis, clinical testing and verification methods. Methods: (1) Mining the lncRNA related to EOC and constructing the competing endogenous RNA (ceRNA) regulatory network: comprehensively apply text mining, data prediction and network construction and other bioinformatics methods to establish a potential ceRNA regulatory network related to EOC drug resistance, namely lncRNA-microRNA (miRNA)-mRNA regulatory network. (2) Clinical verification: a total of 95 cancer tissue specimens were collected from EOC patients who underwent cytoreductive surgery at the Affiliated Tumor Hospital of Guangxi Medical University from June 2008 to October 2016, of which 54 were platinum-resistant patients (resistance group), 41 platinum-based drug-sensitive patients (sensitive group). Real-time fluorescent quantitative PCR was used to detect the expression of lncRNA in EOC tissues of the two groups, the effect of lncRNA expression on the prognosis of EOC patients, and the diagnostic efficacy of lncRNA expression on resistance to EOC were also analyzed. Results: (1) Text mining preliminarily screened out 25 differentially expressed lncRNA related to the occurrence and development of EOC, and further subcellular localization analysis found that 8 lncRNA exist in the cytoplasm. Through further data mining, collinear literature analysis and construction of ceRNA, the regulatory network predicts that the two lncRNA molecules, GAS5 and HOTAIR, could serve as key ceRNA molecules. (2) Through real-time fluoressent quantitative PCR verification, it was found that both GAS5 and HOTAIR were highly expressed in drug-resistant EOC tissues, which affects the progression-free survival (PFS) and overall survival (OS) time of patients with drug-resistant EOC independent risk factors (P<0.05). The receiver operating characteristic (ROC) area under the curve (AUC) of GAS5 alone was 0.678, the AUC of HOTAIR alone was 0.863, and the AUC of GAS5 combined with HOTAIR was 0.871, and there were statistically significant differences (all P<0.05). Conclusions: The high expression of GAS5 and HOTAIR is closely related to the drug resistance of EOC, which could be used as a potential predictor of response to chemotherapy. At the same time, the combined detection of GAS5 and HOTAIR has a certain diagnostic efficiency for patients with platinum-resistant EOC. This method of using the ceRNA regulatory network to predict key molecules will provide new ideas for the diagnosis and treatment of EOC.
目的： 通过生物信息学方法挖掘与卵巢上皮性癌（卵巢癌）耐药相关的可作为竞争性内源RNA（ceRNA）的长链非编码RNA（lncRNA），并进行临床验证。 方法： （1）挖掘与卵巢癌相关的lncRNA并构建ceRNA调控网络：综合应用文本挖掘、数据预测和网络构建等生物信息学方法，建立与卵巢癌耐药相关的潜在ceRNA调控网络，即lncRNA-微小RNA（miRNA）-mRNA调控网络。（2）临床验证：收集2008年6月至2016年10月在广西医科大学附属肿瘤医院行肿瘤细胞减灭术的卵巢癌患者共95例，其中铂类药物耐药患者54例（耐药组），铂类药物敏感患者41例（敏感组），采用实时荧光定量PCR技术检测两组卵巢癌组织中lncRNA的表达，分析lncRNA表达对卵巢癌患者预后的影响，并分析lncRNA表达对卵巢癌耐药的诊断效能。 结果： （1）文本挖掘初步筛选出25个与卵巢癌发生、发展相关的差异表达lncRNA；亚细胞定位分析发现，有8个lncRNA存在于细胞质中；通过进一步数据挖掘、共线文献分析，预测其中的两个lncRNA分子［即生长阻滞特异性转录因子5（GAS5）和HOXC基因座转录因子（HOTAIR）］可作为关键ceRNA分子；构建ceRNA调控网络，GAS5与miRNA（即miR139-5p、miR-24-3p）及mRNA［即乳腺癌易感基因1（BRCA1）、肿瘤蛋白p53（TP53）、表皮生长因子受体（EGFR）、B细胞淋巴瘤2基因（BCL-2）、细胞癌基因（FOS）、H-Ras蛋白（HRAS）］组成ceRNA调控网络，HOTAIR与miRNA（即miR-30a-5p）及mRNA［即磷酸肌醇3激酶调控亚基2（PIK3R2）、TP53、丝蛋白（VIM）］组成ceRNA调控网络。（2）实时荧光定量PCR技术检测显示，与敏感组（设为1.0）比较，耐药组卵巢癌组织中GAS5的表达水平为2.1±1.6，HOTAIR的表达水平为3.5±1.9，两组分别比较，差异均有统计学意义（P=0.011，P<0.01）；Cox回归模型多因素分析显示，GAS5、HOTAIR表达为影响卵巢癌患者无病进展生存率和总生存率的独立危险因素（P<0.05）。GAS5与HOTAIR联合检测诊断卵巢癌的受试者工作特征（ROC）曲线下面积（AUC）为0.871，显著高于GAS5单独检测和HOTAIR单独检测（AUC分别为0.678、0.863），分别比较，差异均有统计学意义（P均<0.05）。 结论： GAS5与HOTAIR高表达与卵巢癌耐药密切相关，可作为卵巢癌化疗反应的潜在预测指标；GAS5与HOTAIR联合检测对卵巢癌患者具有一定的诊断效能。这种利用ceRNA调控网络预测关键分子的方法，为卵巢癌的诊断和治疗提供了新的思路。.