期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2012
卷号：109
期号：15
页码：5832-5837
DOI：10.1073/pnas.1201105109
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Human Epidermal Growth Factor Receptor 2-positive (HER2+) breast cancer (BC) is a highly aggressive disease commonly treated with chemotherapy and anti-HER2 drugs, including trastuzumab. There is currently no way to predict which HER2+ BC patients will benefit from these treatments. Previous prognostic signatures for HER2+ BC were developed irrespective of the subtype or the hierarchical organization of cancer in which only a fraction of cells, tumor-initiating cells (TICs), can sustain tumor growth. Here, we used serial dilution and single-cell transplantation assays to identify MMTV-Her2/Neu mouse mammary TICs as CD24+:JAG1- at a frequency of 2-4.5%. A 17-gene Her2-TIC-enriched signature (HTICS), generated on the basis of differentially expressed genes in TIC versus non-TIC fractions and trained on one HER2+ BC cohort, predicted clinical outcome on multiple independent HER2+ cohorts. HTICS included up-regulated genes involved in S/G2/M transition and down-regulated genes involved in immune response. Its prognostic power was independent of other predictors, stratified lymph node+ HER2+ BC into low and high-risk subgroups, and was specific for HER2+:estrogen receptor alpha-negative (ER-) patients (10-y overall survival of 83.6% for HTICS- and 24.0% for HTICS+ tumors; hazard ratio = 5.57; P = 0.002). Whereas HTICS was specific to HER2+:ER- tumors, a previously reported stroma-derived signature was predictive for HER2+:ER+ BC. Retrospective analyses revealed that patients with HTICS+ HER2+:ER- tumors resisted chemotherapy but responded to chemotherapy plus trastuzumab. HTICS is, therefore, a powerful prognostic signature for HER2+:ER- BC that can be used to identify high risk patients that would benefit from anti-HER2 therapy.
关键词：HER2+ breast cancer ; cancer stem cells ; prognostic signature ; mouse models
