Abstract
BackgroundNeoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease.MethodsWe applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures.ResultsIn all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel.ConclusionOverall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options.
Highlights
Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients
E2F4 regulatory activity level predicts neoadjuvant response To examine the differences in E2F4 activity between pathologic complete response (pCR) and residual disease (RD) patients, we calculated an E2F4 Individual regulatory activity score (iRAS) for each tumor in the Hatzis et al dataset, which contains gene expression and clinical information for patients who underwent neoadjuvant chemotherapy [25]
Subsetting these scores by estrogen receptor (ER) status revealed that each group roughly followed a bimodal distribution as well; though ER-negative patients tended to be enriched for high E2F4 iRASs, a likely reflection of their higher proliferation rates
Summary
Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. With the recent advent of high-throughput sequencing technology, several molecular assays have been developed to predict response to neoadjuvant chemotherapy [9,10,11] One such assay, Oncotype DX [9] generates a predicted recurrence score based on the expression profile of 21 genes, and has shown promise in predicting neoadjuvant chemotherapy response in ERpositive patients. [12, 13] Another assay, Agendia’s MammaPrint [10, 11, 14] utilizes a 70-gene expression panel to determine a recurrence risk for early stage breast cancer This assay must be combined with an additional 80-gene molecular subtyping assay, BluePrint [15], to predict neoadjuvant response [16]
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