TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer.
TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer.
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DOI：
10.1186/bcr1675
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Jeffrey SS
中科院分区：
文献类型：
--
作者：
Langerød A;Zhao H;Borgan Ø;Nesland JM;Bukholm IR;Ikdahl T;Kåresen R;Børresen-Dale AL;Jeffrey SS
乳腺癌的基因表达谱增强了我们对这种疾病的异质生物学的理解，并有望影响临床护理。本研究的目的是评估基于基因表达的分类以及已建立的预后标志物和 TP53 基因（肿瘤蛋白 p53）突变状态在一组长期（12 至 16 年）随访的乳腺癌患者中的预后价值。使用单变量/多变量 Cox 回归研究了 200 名乳腺癌患者的临床和组织病理学参数对临床结果的影响。还评估了使用时间温度梯度凝胶电泳和测序鉴定的 TP53 基因突变的预后影响。使用 42 K cDNA 微阵列对 80 个样本进行基因表达分析，并将患者分配到五个先前定义的分子表达组。通过将此变量添加到用于分析所有样本的 Cox 回归模型中，评估基于基因表达的分类与标准标记的强度。单变量和多变量分析均显示，TP53 突变状态、肿瘤大小和淋巴结状态是全组乳腺癌患者生存的最强预测因素。对患者基因表达数据的分析表明，TP53 突变状态、基于基因表达的分类、肿瘤大小和淋巴结状态是生存的重要预测因素。 “基底样”和“ERBB2+”基因表达亚组中的乳腺癌病例在前两年死亡率非常高，而“高度增殖管腔”病例的疾病发展速度较慢，5至8年后死亡率最高。 TP53突变状态与“basal-like”和“ERBB2+”亚组有很强的相关性，并且突变的肿瘤具有特征性的基因表达模式。 TP53突变状态和基于基因表达的群体是乳腺癌的重要生存标志物，这些分子标志物可以提供补充临床变量的预后信息。该研究为该疾病的持续表征和分类增添了经验和知识。
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 (tumour protein p53) in a group of breast cancer patients with long-term (12 to 16 years) follow-up. 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 temporal temperature gradient gel electrophoresis and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42 K 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. 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. Breast cancer cases in the 'basal-like' and 'ERBB2+' gene expression subgroups had a very high mortality the first two years, while the 'highly proliferating luminal' cases developed the disease more slowly, showing highest mortality after 5 to 8 years. The TP53 mutation status showed strong association with the 'basal-like' and 'ERBB2+' subgroups, and tumors with mutation had a characteristic gene expression pattern. 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.
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DOI：
10.1073/pnas.091062498
发表时间：
2001-04-24
影响因子：
11.1
作者：
Tusher, VG;Tibshirani, R;Chu, G
通讯作者：
Chu, G
影响因子：
158.5
作者：
van de Vijver, MJ;He, YD;Bernards, R
通讯作者：
Bernards, R
DOI：
10.1073/pnas.0932692100
发表时间：
2003-07-08
影响因子：
11.1
作者：
Sorlie, T;Tibshirani, R;Botstein, D
通讯作者：
Botstein, D
影响因子：
5.8
作者：
Ein-Dor, L;Kela, I;Domany, E
通讯作者：
Domany, E
影响因子：
8.8
作者：
Pharoah, PDP;Day, NE;Caldas, C
通讯作者：
Caldas, C