TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer

Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.

研究背景：乳腺癌的基因表达谱分析加深了我们对该疾病异质性生物学特征的理解，并有望对临床诊疗产生影响。本研究旨在针对一组拥有12至16年长期随访数据的乳腺癌患者群体，评估基于基因表达的分类方法与既定预后标志物、TP53基因（TP53）突变状态的预后价值。
研究方法：本研究采用单变量/多变量Cox回归分析，探究200例乳腺癌患者的临床及组织病理学参数对临床结局的影响。同时对通过温度梯度凝胶电泳（TTGE）和测序技术鉴定的TP53基因突变的预后影响进行评估。其中80份样本采用42K cDNA微阵列进行基因表达分析，并将患者划分为5个此前已明确界定的分子表达亚型。通过将该分类变量纳入针对全部患者的Cox回归模型，对比评估基于基因表达的分类方法与标准预后标志物的预后效能。
研究结果：单变量及多变量分析均显示，在全部患者群体中，TP53突变状态、肿瘤大小与淋巴结状态是乳腺癌生存预后最强的预测因子。针对拥有基因表达数据的患者亚群分析显示，TP53突变状态、基于基因表达的分类、肿瘤大小及淋巴结状态均为生存预后的显著预测因子。TP53突变状态与“基底样型（basal-like）”和“ERBB2阳性型（ERBB2+）”基因表达亚型存在强相关性，携带突变的肿瘤具有特征性的基因表达谱。
研究结论：TP53突变状态与基于基因表达的亚型分类是乳腺癌重要的生存预后标志物，这类分子标志物可提供补充于临床变量的预后信息。本研究为该疾病持续进行的特征鉴定与分类工作提供了经验与认知。本实验数据集包含1990年至1994年间于挪威奥斯陆乌勒瓦尔大学医院（ULL-samples）采集的80例原发性乳腺癌样本，以及1份来自乳房缩小整形术的正常乳腺样本。