Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer.
Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer.
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DOI：
10.3389/fcell.2021.701073
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发表时间：
2021
影响因子：
5.5
通讯作者：
Wang SM
中科院分区：
文献类型：
--
作者：
Guo M;Wang SM
三阴性乳腺癌（TNBC）是一种侵袭性疾病。最近的研究已经确定了患者预后的基因组不稳定性衍生基因。然而，大多数研究主要集中在一个或几个基因组不稳定性相关的基因。TNBC中基因组不稳定性相关基因的预后潜力和临床意义尚未得到很好的探索。在这项研究中，我们开发了一种计算方法来识别TNBC预后标志。其包括（1）使用TNBC中的体细胞突变和拷贝数变异（CNV）来构建二元矩阵并鉴定顶部和底部25%突变样品，（2）比较顶部和底部25%样品之间的基因表达以鉴定基因组不稳定性相关基因，和（3）进行单变量考克斯比例风险回归分析以鉴定存活相关基因标记，和Kaplan-Meier、对数秩检验和多变量考克斯回归分析，以获得用于TNBC结果预测的总生存期（OS）信息。从鉴定的111个基因组不稳定性相关基因中，我们提取了11个基因的基因组不稳定性衍生的基因签名（GIGenSig）。通过生存分析，我们能够根据训练数据集中的特征将TNBC病例分为高风险组和低风险组。（对数秩检验p = 2.66e−04），验证了其在检验中的预后性能（对数秩检验p = 2.45e−02）和乳腺癌国际联盟分子分类学（METABRIC）（对数秩检验p = 2.57e−05）数据集，并进一步验证了五个独立数据集中签名的预测能力。所鉴定的新特征提供了对TNBC中基因组不稳定性的更好理解，并且可以用作临床TNBC管理的预后标志物。
Triple-negative breast cancer (TNBC) is an aggressive disease. Recent studies have identified genome instability-derived genes for patient outcomes. However, most of the studies mainly focused on only one or a few genome instability-related genes. Prognostic potential and clinical significance of genome instability-associated genes in TNBC have not been well explored. In this study, we developed a computational approach to identify TNBC prognostic signature. It consisted of (1) using somatic mutations and copy number variations (CNVs) in TNBC to build a binary matrix and identifying the top and bottom 25% mutated samples, (2) comparing the gene expression between the top and bottom 25% samples to identify genome instability-related genes, and (3) performing univariate Cox proportional hazards regression analysis to identify survival-associated gene signature, and Kaplan–Meier, log-rank test, and multivariate Cox regression analyses to obtain overall survival (OS) information for TNBC outcome prediction. From the identified 111 genome instability-related genes, we extracted a genome instability-derived gene signature (GIGenSig) of 11 genes. Through survival analysis, we were able to classify TNBC cases into high- and low-risk groups by the signature in the training dataset (log-rank test p = 2.66e−04), validated its prognostic performance in the testing (log-rank test p = 2.45e−02) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (log-rank test p = 2.57e−05) datasets, and further validated the predictive power of the signature in five independent datasets. The identified novel signature provides a better understanding of genome instability in TNBC and can be applied as prognostic markers for clinical TNBC management.
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DOI：
10.1001/jama.2011.593
发表时间：
2011-05-11
期刊：
JAMA
影响因子：
--
作者：
Hatzis C;Pusztai L;Valero V;Booser DJ;Esserman L;Lluch A;Vidaurre T;Holmes F;Souchon E;Wang H;Martin M;Cotrina J;Gomez H;Hubbard R;Chacón JI;Ferrer-Lozano J;Dyer R;Buxton M;Gong Y;Wu Y;Ibrahim N;Andreopoulou E;Ueno NT;Hunt K;Yang W;Nazario A;DeMichele A;O'Shaughnessy J;Hortobagyi GN;Symmans WF
通讯作者：
Symmans WF
三阴性乳腺癌的基因组和转录组景观：亚型和治疗策略
影响因子：
50.3
作者：
Jiang, Yi-Zhou;Ma, Ding;Shao, Zhi-Ming
通讯作者：
Shao, Zhi-Ming
影响因子：
9
作者：
Chen L;Zhang J;Lyu Z;Chen Y;Ji X;Cao H;Jin M;Zhu J;Yang J;Ling R;Xing J;Ren T;Lyu Y
通讯作者：
Lyu Y
影响因子：
168.9
作者：
Denkert, Carsten;Liedtke, Cornelia;von Minckwitz, Gunter
通讯作者：
von Minckwitz, Gunter
影响因子：
6.4
作者：
Johansson, Anna L. V.;Andersson, Therese M-L.;Lambe, Mats
通讯作者：
Lambe, Mats