Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
DNA Cell Biol. 2020 Apr;39(4):671-682. doi: 10.1089/dna.2019.5223. Epub 2020 Feb 10.
Comprehensive genomic testing will be required to identify appropriate targets for the precision therapy of breast cancer. Although RNA sequencing (RNA-seq) is an unparalleled platform for this purpose, existing molecular-based prognostic signatures are not optimal for RNA-seq data. In this study, we analyzed RNA-seq datasets to generate a novel prognostic gene signature for breast cancer patients. RNA-seq and clinical datasets from breast cancer patients were obtained from The Cancer Genome Atlas and randomly assigned to training ( = 379) and test ( = 378) cohorts. Using the training cohort, sequential univariate Cox analysis, robust likelihood-based survival analysis, and stepwise multivariable Cox analysis identified a five-gene signature composed of one long noncoding RNA gene and four protein-coding genes. The five-gene signature was then used to dichotomize patients into risk groups and validated using Kaplan-Meier and multivariable Cox analyses. In the full test cohort, the high-risk group had worse overall survival (hazard ratio [HR] = 4.74, 95% confidence interval [CI] = 2.33-9.64, < 0.0001) and worse relapse-free survival (HR = 2.26, 95% CI = 1.11-4.61, = 0.024) than the low-risk group. Similarly, overall survival was worse in the high-risk group within nearly all clinically important subsets, including early stage disease (I/II) (HR = 7.87, 95% CI = 3.69-16.77, < 0.0001), and luminal A (HR = 4.23, 95% CI = 1.11-16.12, = 0.034), luminal B (HR = 12.79, 95% CI = 2.74-59.69, = 0.001), and basal (HR = 18.11, 95% CI = 3.21-102.05, = 0.001) subtypes. Notably, the five-gene signature exhibited superior prognostic performance compared with the Oncotype DX 21-gene signature. This novel five-gene signature may therefore be a powerful prognostic tool for personalized treatment of breast cancer patients as part of an integrated RNA-seq clinical sequencing program.
全面的基因组检测对于乳腺癌的精准治疗至关重要。RNA 测序(RNA-seq)是目前该领域的领先平台,但现有的基于分子的预后标志物并不适用于 RNA-seq 数据。本研究旨在通过 RNA-seq 数据构建新的乳腺癌患者预后基因标志物。我们从癌症基因组图谱中获取了乳腺癌患者的 RNA-seq 数据和临床资料,并将其随机分配到训练集(n=379)和测试集(n=378)。采用训练集,通过单因素 Cox 分析、稳健似然比生存分析和逐步多因素 Cox 分析,筛选出由一个长非编码 RNA 基因和四个蛋白编码基因组成的五基因标志物。进一步对该五基因标志物进行Kaplan-Meier 和多因素 Cox 分析,将患者分为高风险组和低风险组。在全测试队列中,高风险组的总生存期(HR=4.74,95%CI=2.33-9.64, <0.0001)和无复发生存期(HR=2.26,95%CI=1.11-4.61, = 0.024)均显著低于低风险组。此外,在几乎所有重要的临床亚组中,高风险组的总生存期均较差,包括早期疾病(I/II 期)(HR=7.87,95%CI=3.69-16.77, <0.0001)和 luminal A 型(HR=4.23,95%CI=1.11-16.12, = 0.034)、luminal B 型(HR=12.79,95%CI=2.74-59.69, = 0.001)和基底样型(HR=18.11,95%CI=3.21-102.05, = 0.001)。此外,与 Oncotype DX 21 基因标志物相比,该五基因标志物具有更好的预后预测能力。因此,该五基因标志物可能成为乳腺癌患者个性化治疗的有效预后工具,作为整合 RNA-seq 临床测序方案的一部分。