Zhong Lei, Lou Ge, Zhou Xinglu, Qin Youyou, Liu Lin, Jiang Wenqian
Department of Breast Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Department of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Oncotarget. 2017 Jul 1;8(40):67861-67870. doi: 10.18632/oncotarget.18919. eCollection 2017 Sep 15.
Dysregulated expression of lncRNAs has been observed in various human complex diseases (including cancers) by recent transcriptional profiling studies, highlighting potentials of lncRNAs as biomarkers for cancer diagnosis and prognosis. Despite some efforts have been made to search for novel lncRNA signature in breast cancer, the prognostic value of lncRNAs for ER-positive breast cancer patients still needs to be systematically investigated. In this study, we analyzed lncRNA expression profiles in a large of more than 600 breast cancer patients with ER-positive status from The Cancer Genome Atlas (TCGA) and identified six lncRNAs that are significantly associated with survival. Then a linear risk score model comprising six prognostic lncRNAs, termed six-lncRNA signature, was developed to identify high-risk patients from low-risk cases. The results of Kaplan-Meier analysis and ROC curves demonstrated the good sensitivity and specificity in survival prediction both in the training and testing datasets. Multivariate Cox regression analysis and stratified analysis showed that the six-lncRNA signature is an independent prognostic marker in survival prediction for ER-positive breast cancer patients. The GO enrichment analysis suggested that the six-lncRNA might involve with known breast cancer-related biological processes. With further experimental validation, these identified prognostic lncRNAs might have clinical implications for more personalized risk assessment for ER-positive breast cancer patients.
近期的转录组分析研究发现，lncRNAs的表达失调在包括癌症在内的多种人类复杂疾病中均有出现，这凸显了lncRNAs作为癌症诊断和预后生物标志物的潜力。尽管已经有人致力于寻找乳腺癌中的新型lncRNA特征，但lncRNAs对雌激素受体阳性（ER阳性）乳腺癌患者的预后价值仍需进行系统研究。在本研究中，我们分析了来自癌症基因组图谱（TCGA）的600多名ER阳性乳腺癌患者的lncRNA表达谱，并鉴定出六种与生存显著相关的lncRNAs。然后，我们构建了一个包含这六种预后lncRNAs的线性风险评分模型，即六lncRNA特征，用于区分高风险患者和低风险患者。Kaplan-Meier分析和ROC曲线结果表明，该模型在训练集和测试集中均具有良好的生存预测敏感性和特异性。多变量Cox回归分析和分层分析显示，六lncRNA特征是ER阳性乳腺癌患者生存预测中的一个独立预后标志物。基因本体（GO）富集分析表明，这六种lncRNA可能参与已知的乳腺癌相关生物学过程。通过进一步的实验验证，这些鉴定出的预后lncRNAs可能对ER阳性乳腺癌患者进行更个性化的风险评估具有临床意义。
