Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy

被引:104
作者
Dressman, HK
Hans, C
Bild, A
Olson, JA
Rosen, E
Marcom, PK
Liotcheva, VB
Jones, EL
Vujaskovic, Z
Marks, J
Dewhirst, MW
West, M
Nevins, JR
Blackwell, K
机构
[1] Duke Univ, Med Ctr, Duke Inst Genome Sci & Policy, Durham, NC 27710 USA
[2] Duke Univ, Med Ctr, Dept Mol Genet & Microbiol, Durham, NC 27710 USA
[3] Duke Univ, Med Ctr, Dept Surg, Durham, NC 27710 USA
[4] Duke Univ, Med Ctr, Dept Radiat Oncol, Durham, NC 27710 USA
[5] Duke Univ, Med Ctr, Dept Med, Durham, NC 27710 USA
[6] Duke Univ, Inst Stat & Decis Sci, Durham, NC 27706 USA
关键词
D O I
10.1158/1078-0432.CCR-05-1447
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: Breast cancer is a heterogeneous disease, and markers for disease subtypes and therapy response remain poorly defined. For that reason, we employed a prospective neoadjuvant study in locally advanced breast cancer to identify molecular signatures of gene expression correlating with known prognostic clinical phenotypes, such as inflammatory breast cancer or the presence of hypoxia. In addition, we defined molecular signatures that correlate with response to neoadjuvant chemotherapy. Experimental Design: Tissue was collected under ultrasound guidance from patients with stage IIB/III breast cancer before four cycles of neoadjuvant liposomal doxorubicin paclitaxel chemotherapy combined with local whole breast hyperthermia. Gene expression analysis was done using Affymetrix U133 Plus 2.0 GeneChip arrays. Results: Gene expression patterns were identified that defined the phenotypes of inflammatory breast cancer as well as tumor hypoxia. In addition, molecular signatures were identified that predicted the persistence of malignancy in the axillary lymph nodes after neoadjuvant chemotherapy, This persistent lymph node signature significantly correlated with disease-free survival in two separate large populations of breast cancer patients. Conclusions: Gene expression signatures have the capacity to identify clinically significant features of breast cancer and can predict which individual patients are likely to be resistant to neoadjuvant therapy, thus providing the opportunity to guide treatment decisions.
引用
收藏
页码:819 / 826
页数:8
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