Department of Breast Center, Ningbo Women and Children's Hospital, No. 339 Liuting Street, Ningbo, 315012, Zhejiang, China.
Sci Rep. 2022 Jul 19;12(1):12349. doi: 10.1038/s41598-022-16575-8.
Despite increased early diagnosis and improved treatment in breast cancer (BRCA) patients, prognosis prediction is still a challenging task due to the disease heterogeneity. This study was to identify a novel gene signature that can accurately evaluate BRCA patient survival. The gene expression and clinical data of BRCA patients were collected from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of BRCA International Consortium (METABRIC) databases. Genes associated with prognosis were determined by Kaplan-Meier survival analysis and multivariate Cox regression analysis. A prognostic 16-gene score was established with linear combination of 16 genes. The prognostic value of the signature was validated in the METABRIC and GSE202203 datasets. Gene expression analysis was performed to investigate the diagnostic values of 16 genes. The 16-gene score was associated with shortened overall survival in BRCA patients independently of clinicopathological characteristics. The signalling pathways of cell cycle, oocyte meiosis, RNA degradation, progesterone mediated oocyte maturation and DNA replication were the top five most enriched pathways in the high 16-gene score group. The 16-gene nomogram incorporating the survival-related clinical factors showed improved prediction accuracies for 1-year, 3-year and 5-year survival (area under curve [AUC] = 0.91, 0.79 and 0.77 respectively). MORN3, IGJ, DERL1 exhibited high accuracy in differentiating BRCA tissues from normal breast tissues (AUC > 0.80 for all cases). The 16-gene profile provides novel insights into the identification of BRCA with a high risk of death, which eventually guides treatment decision making.
尽管乳腺癌(BRCA)患者的早期诊断和治疗有所提高,但由于疾病异质性,预后预测仍然是一项具有挑战性的任务。本研究旨在确定一种新的基因特征,能够准确评估 BRCA 患者的生存情况。从癌症基因组图谱(TCGA)和 BRCA 国际联合会(METABRIC)分子分类数据库中收集了 BRCA 患者的基因表达和临床数据。通过 Kaplan-Meier 生存分析和多变量 Cox 回归分析确定与预后相关的基因。通过线性组合 16 个基因建立了一个预后 16 基因评分。该特征的预后价值在 METABRIC 和 GSE202203 数据集进行了验证。进行基因表达分析以研究 16 个基因的诊断价值。该基因评分与 BRCA 患者的总生存期缩短独立相关,与临床病理特征无关。在高 16 基因评分组中,细胞周期、卵母细胞减数分裂、RNA 降解、孕激素介导的卵母细胞成熟和 DNA 复制信号通路是前五个最富集的通路。纳入与生存相关的临床因素的 16 基因列线图显示出对 1 年、3 年和 5 年生存(AUC 分别为 0.91、0.79 和 0.77)的预测准确性有所提高。MORN3、IGJ、DERL1 在区分 BRCA 组织和正常乳腺组织方面具有很高的准确性(所有病例的 AUC 均大于 0.80)。该 16 基因特征为识别高死亡风险的 BRCA 提供了新的见解,最终指导治疗决策。