Department of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; Department of Anesthesiology, Institute of Anesthesiology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; Hubei Key Laboratory of Embryonic Stem Cell Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China.
Department of Oncology, Xinchang Hospital Affiliated to Wenzhou Medical University, 117 Gushan Middle Road, Xinchang County 312500, Zhejiang Province, China.
Biochem Pharmacol. 2021 Jul;189:114285. doi: 10.1016/j.bcp.2020.114285. Epub 2020 Oct 15.
Multi-gene prognostic signatures of long non-coding RNAs (lncRNAs) provide new insights into mechanisms of HER2-negative breast cancer development and progression, and predict distant relapse-free survival (DRFS) of patients receiving taxane and anthracycline-based neoadjuvant chemotherapy. The aim of this study was to develop such a multi-lncRNAs signature. Optimal multiple candidate signature lncRNAs associated with DRFS were firstly identified by a univariate Cox proportional hazard regression survival analysis and a robust likelihood-based survival analysis of the GEO dataset GSE25055. A nine-lncRNA prognostic risk score model Risk Score = 0.0289 × EXP - 0.0814 × EXP - 0.2422 × EXP - 0.2433 × EXP + 0.4690 × EXP - 0.2483 × EXP - 0.2464 × EXP + 0.3349 × EXP - 0.0216 × EXP was built according to the coefficients of multivariate survival analysis of the association between the candidate lncRNAs and survival. EXP was the standardized log2-transformed expression level of the gene. According to this model, higher scores predicted lower survival probability. The area under Receiver operating characteristic (ROC) curve (AUC) was 0.777 to 0.823 from 1- to 7- year survival rate. The model and its individual lncRNAs differentiated survival probability between the higher scores (expression) and the lower scores (expression). The nine-lncRNA signature had the robust prognostic power compared with ER, PR, tumor size (T), lymph node invasion (N), TNM stage, pathologic response, chemosensitivity prediction and PAM50 signature. These results were consistent with those based on the GEO dataset GSE25065. The predictive nomograms integrating both the nine-lncRNA signature classifier and clinical-pathological risk factors were robust in predicting 1-, 3- and 5- year survival probabilities. These results supported that the nine-lncRNA signature was a robust and effective model in predicting DRFS of patients with HER2-negative breast cancer following taxane and anthracycline-based neoadjuvant chemotherapy.
多基因长非编码 RNA（lncRNA）预后标志物为了解 HER2 阴性乳腺癌的发展和进展机制提供了新的见解，并预测了接受紫杉烷和蒽环类药物新辅助化疗的患者的远处无复发生存（DRFS）。本研究旨在开发此类多 lncRNA 标志物。首先通过单变量 Cox 比例风险回归生存分析和 GEO 数据集 GSE25055 的稳健似然生存分析确定与 DRFS 相关的最佳候选多基因 lncRNA。根据候选 lncRNA 与生存之间关联的多变量生存分析的系数构建了一个 9 个 lncRNA 预后风险评分模型 Risk Score = 0.0289×EXP - 0.0814×EXP - 0.2422×EXP - 0.2433×EXP + 0.4690×EXP - 0.2483×EXP - 0.2464×EXP + 0.3349×EXP - 0.0216×EXP。EXP 是基因标准化对数 2 转换后的表达水平。根据该模型，较高的分数预示着较低的生存概率。1 年至 7 年生存率的接收者操作特征（ROC）曲线（AUC）面积为 0.777 至 0.823。该模型及其单个 lncRNA 在较高分数（表达）和较低分数（表达）之间区分了生存概率。与 ER、PR、肿瘤大小（T）、淋巴结浸润（N）、TNM 分期、病理反应、化疗敏感性预测和 PAM50 标志物相比，9 个 lncRNA 标志物具有更强的预后能力。GEO 数据集 GSE25065 上的结果一致。整合了 9 个 lncRNA 特征分类器和临床病理危险因素的预测列线图在预测 1、3 和 5 年生存率方面具有稳健性。这些结果支持 9 个 lncRNA 标志物是预测接受紫杉烷和蒽环类药物新辅助化疗的 HER2 阴性乳腺癌患者 DRFS 的一种稳健有效的模型。
