State Key Laboratory of Oncology in Southern China and Department of Gynecology, Cancer Center, Sun Yat-sen University, and Department of Obstetrics and Gynecology, Nanfang Hospital, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China.
Med Oncol. 2012 Dec;29(4):2911-8. doi: 10.1007/s12032-012-0166-3. Epub 2012 Jan 25.
There is no gene signature for predicting relapse and survival of cervical cancer with early stage currently. In this study, we investigate whether gene expression profiling of cervical cancer could be used to predict the prognosis of patient. A series of 100 primary cervical cancer patients who underwent radical hysterectomy between January 2001 and October 2006 were analyzed for gene expression profiles by using a custom oligonucleotide microarray containing probes for 1440 human tumor-related gene transcripts. Supervised analysis of gene expression data identified 19 genes that exhibited differential expression between cervical cancer and normal cervix. Then, all 100 patients were divided into the training (n=50) and testing sets (n=50). Using Cox regression and risk-score analysis, we identified a 7-gene (UBL3, FGF3, BMI1, PDGFRA, PTPRF, RFC4, and NOL7) signature for predicting relapse of patient in the training set. The 7-gene signature was validated by the testing set (sensitivity, 84.6%; specificity, 91.9%; positive predictive value, 78.6%; negative predictive value, 94.4%). Patients with high-risk 7-gene signature had poor relapse-free survivals (RFS) than patients with low-risk 7-gene signature in both training set (P=0.026) and testing set (P=0.042). Multivariate analysis showed that the FIGO stage and 7-gene signature are independent prognostic factors associated with RFS of cervical cancer patients. The 7-gene signature can predict cancer recurrence and survival of cervical cancer patients. This may have prognostic or therapeutic implications for the future management of cervical cancer patients.
目前,尚无用于预测早期宫颈癌复发和生存的基因特征。在这项研究中,我们研究了宫颈癌的基因表达谱是否可用于预测患者的预后。分析了 2001 年 1 月至 2006 年 10 月期间接受根治性子宫切除术的 100 例原发性宫颈癌患者的基因表达谱,使用包含 1440 个人类肿瘤相关基因转录本探针的定制寡核苷酸微阵列进行分析。对基因表达数据进行的监督分析确定了 19 个在宫颈癌和正常宫颈之间表达差异的基因。然后,将所有 100 例患者分为训练集(n=50)和测试集(n=50)。使用 Cox 回归和风险评分分析,我们确定了一个用于预测训练集中患者复发的 7 基因(UBL3、FGF3、BMI1、PDGFRA、PTPRF、RFC4 和 NOL7)特征。通过测试集验证了 7 基因特征(敏感性,84.6%;特异性,91.9%;阳性预测值,78.6%;阴性预测值,94.4%)。在训练集(P=0.026)和测试集(P=0.042)中,高风险 7 基因特征的患者比低风险 7 基因特征的患者的无复发生存率(RFS)更差。多变量分析表明,FIGO 分期和 7 基因特征是与宫颈癌患者 RFS 相关的独立预后因素。7 基因特征可预测宫颈癌患者的癌症复发和生存。这可能对未来宫颈癌患者的管理具有预后或治疗意义。