Dataset Information

The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.

ABSTRACT:

Background

Neoadjuvant 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.

Methods

We 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.

Results

In 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.

Conclusion

Overall, 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.

SUBMITTER: Mark KMK

PROVIDER: S-EPMC5414335 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Publications

The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.

Mark Kenneth M K KMK Varn Frederick S FS Ung Matthew H MH Qian Feng F Cheng Chao C

BMC cancer 20170502 1

<h4>Background</h4>Neoadjuvant 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.<h4>Methods</h4>We applied our previously ...[more]

PMID: 28464832

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Project description:BackgroundBreast cancer with pathological non-complete response (non-pCR) after neoadjuvant chemotherapy (NAC) has a worse prognosis. Despite Neo-Bioscore has been validated as an independent prognostic model for breast cancer submitted to NAC, non-pCR carcinoma was not assessed in this setting.MethodsThis is a retrospective trial that included women with localized breast cancer who underwent NAC and had non-pCR carcinoma in surgical specimen between 01/01/2013 to 12/31/2015 with a three-year follow-up. Survival analysis was performed by Kaplan-Meier estimator and hazard ratio (HR) set by log-rank test for the primary and secondary endpoints, respectively Disease-Free Survival (DFS) and Overall Survival (OS). According to Neo-Bioscore, the proposed prognostic model named Clustered Neo-Bioscore was classified into low (0-3), low-intermediate (4-5), high-intermediate (6) and high (7) risk. The prognostic accuracy for recurrence risk was assessed by time-dependent receiver operating characteristic (time-ROC) methodology. Multivariate Cox regression assessed the menopausal status, histological grade, Ki-67, estrogen receptor, HER2, tumor subtype, pathological and clinical stages. Confidence interval at 95% (CI95%) and statistical significance at set 2-sided p-value less than 0.05 were adopted.ResultsAmong the 310 women enrolled, 267 patients (86.2%) had non-pCR carcinoma presenting size T3/T4 (63.3%), node-positive axilla (74.9%), stage III (62.9%), Ki-67???20% (71.9%) and non-luminal A (78.3%). Non-pCR carcinoma presented worse DFS-3y (HR?=?3.88, CI95%?=?1.18-11.95) but not OS-3y (HR?=?2.73, CI95%?=?0.66-11.40). Clustered Neo-Bioscore discerned the recurrence risk for non-pCR carcinoma: low (DFS-3y?=?0.86; baseline), low-intermediate (DFS-3y?=?0.70; HR?=?2.61), high-intermediate (DFS-3y?=?0.13, HR?=?14.05), and high (DFS-3y?=?not achieved; HR?=?22.19). The prognostic accuracy was similar between Clustered Neo-Bioscore and Neo-Bioscore (0.76 vs 0.78, p?>?0.05). Triple-negative subtype (HR?=?3.6, CI95%?=?1.19-10.92) and pathological stages II (HR?=?5.35, CI95%?=?1.19-24.01) and III (HR?=?6.56, CI95%?=?1.29-33.32) were prognoses for low-intermediate risk, whereas pathological stage III (HR?=?13.0, CI95%?=?1.60-106.10) was prognosis for low risk.ConclusionsClustered Neo-Bioscore represents a novel prognostic model of non-pCR carcinoma undergoing NAC with a more simplified and appropriate score pattern in the assessment of prognostic factors.

Dataset Information

The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.

Background

Methods

Results

Conclusion

Publications

The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.

Similar Datasets

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