Purpose: Histologic tumor grade is a well-established prognostic factor for breast cancer, and tumor grade^associated genes are the common denominator of many prognostic gene signatures. The objectives of this study are as follows: (a) to develop a simple gene expression index for tumor grade (molecular grade index or MGI), and (b) to determine whether MGI and our previously described HOXB13:IL17BR index together provide improved prognostic information. Experimental Design: From our previously published list of genes whose expression correlates with both tumor grade and tumor stage progression, we selected five cell cycle^related genes to build MGI and evaluated MGI in two publicly available microarray data sets totaling 410 patients. Using two additional cohorts (n = 323), we developed a real-time reverse transcription PCR assay for MGI, validated its prognostic utility, and examined its interaction with HOXB13:IL17BR. Results: MGI performed consistently as a strong prognostic factor and was comparable with a more complex 97-gene genomic grade index in multiple data sets. In patients treated with endocrine therapy, MGI and HOXB13:IL17BR modified each other's prognostic performance. High MGI was associated with significantly worse outcome only in combination with high HOXB13:IL17BR, and likewise, high HOXB13:IL17BR was significantly associated with poor outcome only in combination with high MGI. Conclusions: We developed and validated a five-gene reverse transcription PCR assay for MGI suitable for analyzing routine formalin-fixed paraffin-embedded clinical samples. The combination of MGI and HOXB13:IL17BR outperforms either alone and identifies a subgroup (f30%) of early stage estrogen receptor^positive breast cancer patients with very poor outcome despite endocrine therapy.The most recent (2005) St. Gallen consensus guidelines for treatment selection for early stage breast cancer consider both risk of recurrence and endocrine responsiveness to better balance risk and benefit of systemic adjuvant therapies (1). To better define risk stratification, genome-wide expression profiling studies have created multiple prognostic gene signatures for breast cancer (2, 3). An important issue is whether these signatures overlap in their prognostic information and whether combining several of these signatures would provide more accurate prognosis. In one comparative study, four signatures (the intrinsic subtypes, 70-gene signature, wound response signature, and Recurrence Score) were found to be highly concordant in classifying patients into low and high-risk groups (4). Notably, combining these signatures did not yield significant improvement in predictive accuracy, suggesting that the prognostic information provided by these signatures is largely overlapping (4). Sotiriou et al. (5) showed that a 97-gene tumor grade signature was comparable with the 70-gene signature and the Recurrence Score algorithm (6) in independent cohorts, and they hypothesized that most of the prognostic power of these signatures comes f...