Investigation of a genomic signature for transcription factor MAF gene amplification and lack of bisphosphonate benefit in early breast cancer.

559 Background: MAF amplification has been associated with increased bone metastases in breast cancer (BC). On the contrary, patients without MAF amplification in the primary tumor are more likely to benefit from adjuvant bisphosphonates as shown in a retrospective analysis of the AZURE trial and confirmed with a subset of NSABP-B34 specimens. A genomic signature could identify patients that lack MAF amplification as candidates for adjuvant bisphosphonates. Here we investigated the genes that could predict MAF amplification status. As MAF amplification is associated with high risk of bone metastases, 70-gene risk of distant recurrence signature (MammaPrint/MP) and 80-gene molecular subtyping signature (BluePrint/BP) were used to stratify the patient groups. Methods: A total of 166 BC patients from the UPMC were included in this pilot cohort. Fluorescence in situ hybridization was performed to detect MAF copy number. Signal-to-nucleus ratio (SNR) of ≥2.5 was used as the MAF-amplified (MAF+) cut-off. Differential gene expression analysis was performed with R limma using whole genome microarray data. MAF+ and MAF- (SNR<2.5) were compared within all patients and within patients matched by MP/BP to balance high risk groups. Differentially expressed genes (DEGs) were defined as absolute fold change ≥2 and adjusted p-value <0.05. Prediction of MAF amplification based on gene expression was performed using a correlation-based metric with training set, as well as with 1179 stage I-III BC patients from the FLEX Study (NCT03053193), which includes MP/BP testing and whole transcriptome data collection. Results: Of the 166 patients, 12% were MAF+ and 88% were MAF-. Among the MAF+ patients, 95% were MP High Risk, as expected from the association of MAF amplification and bone metastasis, as opposed to 29% of MAF- patients. Notably, there was no significant correlation between amplification and gene expression of MAF, which emphasizes the importance of utilizing other genes to predict MAF amplification. Comparing whole transcriptome of MAF+ and MAF- patients, 48 DEGs were found. From the MP/BP matched comparisons, genes ≥2-fold change were included in the final set of 57 genes, where C-X-C motif chemokine ligand and S100 calcium binding protein encoding genes were enriched. The 57-gene classifier of MAF status yielded 92% accuracy, 94% specificity, and 75% sensitivity on the training set. Interestingly, when the classifier was applied on the FLEX cohort, 12% MAF+ cases were identified, similar to the training set. Conclusions: Whole transcriptome analysis showed that BC tumors with MAF amplification are transcriptionally different than those without. Here we provide a set of 57 genes that could potentially predict MAF amplification status. Future work will expand the dataset and further explore the predictive value of such genomic signature in response to bisphosphonates. Clinical trial information: NCT03053193.