Abstract
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 (ERα(-)) 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(+):ERα(-) tumors, a previously reported stroma-derived signature was predictive for HER2(+):ERα(+) BC. Retrospective analyses revealed that patients with HTICS(+) HER2(+):ERα(-) tumors resisted chemotherapy but responded to chemotherapy plus trastuzumab. HTICS is, therefore, a powerful prognostic signature for HER2(+):ERα(-) BC that can be used to identify high risk patients that would benefit from anti-HER2 therapy.