Molecular and clinical features of the TP53 signature gene expression profile in early-stage breast cancer.
Molecular and clinical features of the TP53 signature gene expression profile in early-stage breast cancer.
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DOI：
10.18632/oncotarget.24447
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发表时间：
2018-03-06
期刊：
影响因子：
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通讯作者：
Kato S
中科院分区：
文献类型：
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作者：
Yamaguchi S;Takahashi S;Mogushi K;Izumi Y;Nozaki Y;Nomizu T;Kakugawa Y;Ishida T;Ohuchi N;Ishioka C;Kato S
TP53特征对早期乳腺癌的预后具有强大的预测性能，但报道这一点的实验依赖于公共微阵列数据和新鲜冷冻样本。在TP53签名可用于临床环境之前，需要使用福尔马林固定石蜡包埋（FFPE）样品的简单且低成本的诊断系统。基于TP53特征的生物学特性的新治疗方法预计将随之而来。在174个FFPE早期乳腺癌样本中使用数字定量通过nCounter技术（NanoString）评估TP53特征。患者被分类为TP53特征突变型（n = 64）或野生型（n = 110）。通过RNA-seq将TP53标签的预测能力与同一队列的153个新鲜冷冻样本中的其他基因表达标签的预测能力进行比较。利用TCGA组学数据和RNA-seq数据阐明TP53标签的分子特征，以探索TP53标签突变型患者的新治疗策略。TP53特征是一个强有力的预后预测因子，也比其他基因表达特征更准确，不依赖于其他临床病理因素。TCGA数据分析显示，TP53标签的风险评分是染色体和基因组不稳定性的指标，TP53标签突变类型与较高的PD-L1表达、拷贝数变异和体细胞突变数量相关。使用nCounter系统诊断的TP53特征不仅是预后的稳健预测因子，而且是对免疫检查点抑制剂的反应性的潜在预测因子。
TP53 signature has a robust predictive performance for prognosis in early-stage breast cancer, but the experiment that reported this relied on public microarray data and fresh-frozen samples. Before TP53 signature can be used in a clinical setting, a simple and low-cost diagnostic system using formalin-fixed paraffin-embedded (FFPE) samples is needed. New treatments based on the biological characteristics of TP53 signature are expected to follow. TP53 signature was evaluated in 174 FFPE early breast cancer specimens using digital quantification via the nCounter technique (NanoString). Patients were classified as TP53 signature mutant type (n = 64) or wild type (n = 110). Predictive power of TP53 signature was compared with those of other gene expression signatures in 153 fresh-frozen samples of the same cohort by RNA-seq. The molecular features of TP53 signature were elucidated using TCGA omics data and RNA-seq data to explore new therapeutic strategies for patients with TP53 signature mutant type. TP53 signature was a strong predictor of prognosis and was also more accurate than other gene expression signatures and independent of other clinicopathological factors. TCGA data analysis showed that risk score of TP53 signature was an index of chromosomal and genomic instability and that TP53 signature mutant type was associated with higher PD-L1 expression, variation in copy numbers, and numbers of somatic mutations. TP53 signature as diagnosed using the nCounter system is not only a robust predictor of prognosis but also a potential predictor of responsiveness to immune checkpoint inhibitors.