ArticleBMC cancer2017
The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.
Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- Basal-epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer.EMBO molecular medicine · 2024Article
- A generalized non-linear model predicting efficacy of neoadjuvant therapy in HER2+ breast cancer.iScience · 2023Article
- Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network-Based Artificial Intelligence Tool.JCO clinical cancer informatics · 2023Article
- A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction.Scientific reports · 2022Article
- ZMIZ2 promotes the development of triple-receptor negative breast cancer.Cancer cell international · 2022Article
- Knockdown of E2F4 suppresses the growth of ovarian cancer cells through the cell cycle pathway.International journal of clinical and experimental pathology · 2021Article
- Machine Learning Algorithms for Prediction of Survival Curves in Breast Cancer Patients.Applied bionics and biomechanics · 2021Article
- Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy.Cancer medicine · 2020Article
- Are baseline ultrasound and mammographic features associated with rates of pathological completes response in patients receiving neoadjuvant chemotherapy for breast cancer?Cancer imaging : the official publication of the International Cancer Imaging Society · 2019Article
- A Predictor of Pathological Complete Response to Neoadjuvant Chemotherapy Stratifies Triple Negative Breast Cancer Patients with High Risk of Recurrence.Scientific reports · 2019Article
- Metformin prevention of doxorubicin resistance in MCF-7 and MDA-MB-231 involves oxidative stress generation and modulation of cell adaptation genes.Scientific reports · 2019Article
- A two-gene epigenetic signature for the prediction of response to neoadjuvant chemotherapy in triple-negative breast cancer patients.Clinical epigenetics · 2019Article
- ERClinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
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.
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