Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay.
Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay.
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DOI：
10.1186/bcr1399
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Bernard PS
中科院分区：
文献类型：
--
作者：
Perreard L;Fan C;Quackenbush JF;Mullins M;Gauthier NP;Nelson E;Mone M;Hansen H;Buys SS;Rasmussen K;Orrico AR;Dreher D;Walters R;Parker J;Hu Z;He X;Palazzo JP;Olopade OI;Szabo A;Perou CM;Bernard PS
预测乳腺癌的临床过程通常很困难，因为它是一种由许多生物亚型组成的多样化疾病。通过微阵列分析的基因表达谱已经确定了对预后和治疗重要的乳腺癌特征。在目前的文章中，我们使用微阵列分析和实时定量逆转录（qRT）-PCR分析，以生物学的“内在”亚型和增殖的基础上，乳腺癌的风险分层。从微阵列数据中选择基因集以评估增殖并将乳腺癌分类为四种不同的分子亚型，命名为管腔型、正常样型、HER 2 +/ER-型和基底样型。使用微阵列（Agilent）和由53个基因组成的qRT-PCR测定法前瞻性地分析了123个乳腺样品（117个浸润性癌、1个纤维腺瘤和5个正常组织）和3个乳腺癌细胞系。通过层次聚类从微阵列和qRT-PCR数据分配生物亚型。使用增殖标记作为单个元基因（14个基因的log 2平均值）来预测雌激素受体状态和生物学“内在”亚型背景下的结果。我们发现qRT-PCR检测可以确定内在亚型（与基于微阵列的分配一致率为93%），并且内在亚型可预测结果。增殖元基因为Luminal亚型患者（P = 0.0012）和雌激素受体阳性肿瘤患者（P = 3.4 × 10-6）提供了额外的预后信息。与低增殖的管腔肿瘤相比，管腔亚型的高增殖赋予了19倍的复发相对风险（置信区间= 95%）。实时qRT-PCR测定可以概括乳腺癌的微阵列分类，并且可以使用内在亚型和增殖对患者进行风险分层。增殖元基因提供了一个客观和定量的测量等级，并增加了重要的预后信息的生物亚型。
Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation. Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive carcinomas, one fibroadenoma and five normal tissues) and three breast cancer cell lines were prospectively analyzed using a microarray (Agilent) and a qRT-PCR assay comprised of 53 genes. Biological subtypes were assigned from the microarray and qRT-PCR data by hierarchical clustering. A proliferation signature was used as a single meta-gene (log2 average of 14 genes) to predict outcome within the context of estrogen receptor status and biological 'intrinsic' subtype. We found that the qRT-PCR assay could determine the intrinsic subtype (93% concordance with microarray-based assignments) and that the intrinsic subtypes were predictive of outcome. The proliferation meta-gene provided additional prognostic information for patients with the Luminal subtype (P = 0.0012), and for patients with estrogen receptor-positive tumors (P = 3.4 × 10-6). High proliferation in the Luminal subtype conferred a 19-fold relative risk of relapse (confidence interval = 95%) compared with Luminal tumors with low proliferation. A real-time qRT-PCR assay can recapitulate microarray classifications of breast cancer and can risk-stratify patients using the intrinsic subtype and proliferation. The proliferation meta-gene offers an objective and quantitative measurement for grade and adds significant prognostic information to the biological subtypes.
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影响因子：
5.3
作者：
Ishida, S;Huang, E;Nevins, JR
通讯作者：
Nevins, JR
DOI：
10.1073/pnas.96.16.9212
发表时间：
1999-08-03
影响因子：
11.1
作者：
Perou, CM;Jeffrey, SS;Botstein, D
通讯作者：
Botstein, D
影响因子：
5.8
作者：
Benito, M;Parker, J;Marron, JS
通讯作者：
Marron, JS
影响因子：
11.2
作者：
Dai, HY;van't Veer, L;Friend, S
通讯作者：
Friend, S
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