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Neoadjuvant chemotherapy induces expression levels of breast cancer resistance protein that predict disease-free survival in breast cancer.

ABSTRACT: Three main xenobiotic efflux pumps have been implicated in modulating breast cancer chemotherapy responses. These are P-glycoprotein (Pgp), Multidrug Resistance-associated Protein 1 (MRP1), and Breast Cancer Resistance Protein (BCRP). We investigated expression of these proteins in breast cancers before and after neoadjuvant chemotherapy (NAC) to determine whether their levels define response to NAC or subsequent survival. Formalin-fixed paraffin-embedded tissues were collected representing matched pairs of core biopsy (pre-NAC) and surgical specimen (post-NAC) from 45 patients with invasive ductal carcinomas. NAC regimes were anthracyclines +/- taxanes. Immunohistochemistry was performed for Pgp, MRP1 and BCRP and expression was quantified objectively using computer-aided scoring. Pgp and MRP1 were significantly up-regulated after exposure to NAC (Wilcoxon signed-rank p?=?0.0024 and p<0.0001), while BCRP showed more variation in response to NAC, with frequent up- (59% of cases) and down-regulation (41%) contributing to a lack of significant difference overall. Pre-NAC expression of all markers, and post-NAC expression of Pgp and MRP1 did not correlate with NAC response or with disease-free survival (DFS). Post-NAC expression of BCRP did not correlate with NAC response, but correlated significantly with DFS (Log rank p?=?0.007), with longer DFS in patients with low post-NAC BCRP expression. In multivariate Cox regression analyses, post-NAC BCRP expression levels proved to predict DFS independently of standard prognostic factors, with high expression associated with a hazard ratio of 4.04 (95% confidence interval 1.3-12.2; p?=?0.013). We conclude that NAC-induced expression levels of BCRP predict survival after NAC for breast cancer, while Pgp and MRP1 expression have little predictive value.

SUBMITTER: Kim B

PROVIDER: S-EPMC3642197 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Neoadjuvant chemotherapy induces expression levels of breast cancer resistance protein that predict disease-free survival in breast cancer.

Kim Baek B Fatayer Hiba H Hanby Andrew M AM Horgan Kieran K Perry Sarah L SL Valleley Elizabeth M A EM Verghese Eldo T ET Williams Bethany J BJ Thorne James L JL Hughes Thomas A TA

PloS one 20130502 5

Three main xenobiotic efflux pumps have been implicated in modulating breast cancer chemotherapy responses. These are P-glycoprotein (Pgp), Multidrug Resistance-associated Protein 1 (MRP1), and Breast Cancer Resistance Protein (BCRP). We investigated expression of these proteins in breast cancers before and after neoadjuvant chemotherapy (NAC) to determine whether their levels define response to NAC or subsequent survival. Formalin-fixed paraffin-embedded tissues were collected representing matc ...[more]

PMID: 23658771

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Project description:BackgroundNeoadjuvant chemotherapy (NACT) is considered a standard treatment strategy for locally advanced triple negative breast cancer (TNBC). TNBC patients who achieve a pathologic complete response (pCR) are predicted to have a better prognosis while unfavorable chemo-sensitivity is still associated with a higher risk of disease relapse. The objective of this study was to construct a nomogram to predict disease-free survival (DFS) for TNBC patients following NACT.MethodsA total of 165 TNBC patients who underwent standard NACT and surgery were retrospectively reviewed, and data on their clinicopathological factors before and after NACT were collected. Independent prognostic factors for DFS were identified by Cox regression based on lower Akaike information criteria (AIC) and Bayesian information criterion (BIC). A nomogram to predict the 2-year and 5-year DFS following NACT for TNBC was constructed based on training cohort (n = 132) and validated by a validation cohort (n = 33).ResultsEither limited or full pCR (breast-only pCR, node-only pCR, or both-pCR) indicated significantly improved DFS and overall survival (OS) (p < 0.001). Lager residual tumor size (hazard ratio [HR] 1.175, p = 0.011) and the presence of lymphatic vessel invasion (LVI) (HR 3.168, p = 0.001) were identified as independent predictors of disease relapse in the training cohort. Five variables, including age, primary tumor size, histological grade, residual tumor size, and LVI were used to establish the nomogram. The C-index of the nomogram was 0.815, and calibration curves showed an acceptable consistency between the actual and nomogram-predicted 2-year and 5-year DFS. The proposed nomogram demonstrated superior predictive performance compared with Residual Cancer Burden (RCB) classification and the 8th American Joint Committee on Cancer Post Neoadjuvant Therapy Classification (AJCC ypTNM) staging system (area under the curve [AUC] for 2-year DFS: 0.870 vs. 0.758 vs. 0.711, respectively; AUC for 5-year DFS: 0.794 vs. 0.731 vs. 0.702, respectively) in the validation cohort.ConclusionsThe nomogram proposed in our study enabled to quantify the risk of disease relapse and demonstrated superior predictive performance than a survival predict instrument. It was an easy-to-use tool for clinicians to guide individualized surveillance of TNBC patients following standard NACT.

Project description:Background: To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS. Methods: Patients (n = 150) from two hospitals who received NAC from August 2011 to May 2017 were diagnosed with TNBC by pathological biopsy, and follow-up through May 2020 was retrospectively analysed. Patients from one hospital (n = 109) were used as the training group, and patients from the other hospital (n = 41) were used as the validation group. ROIs were drawn on 1.5 T MRI T1W enhancement images of the whole volume of the tumour obtained with a 3D slicer. Radiomics signatures predicting DFS were identified, optimal cut-off value for Rad-score was determined, and the associations between DFS and radiomics signatures, MRI findings, and clinicopathological variables were analysed. A nomogram was developed and validated for individualized DFS estimation. Results: The median follow-up time was 53.5 months, and 45 of 150 (30.0%) patients experienced recurrence and metastasis. The optimum cut-off value of the Rad-score was 0.2528, which stratified patients into high- and low-risk groups for DFS in the training group (p<0.001) and was validated in the external validation group. Multivariate analysis identified three independent indicators: multifocal/centric disease status, pCR status, and Rad-score. A nomogram based on these factors showed discriminatory ability, the C-index of the model was 0.834 (95% CI, 0.761-0.907) and 0.868 (95% CI, 0.787-949) in the training and the validation groups, respectively, which is better than clinicoradiological nomogram(training group: C-index = 0.726, 95% CI = 0.709-0.743; validation group: C-index = 0.774,95% CI = 0.743-0.805). Conclusion: The Rad-score derived from preoperative MRI features is an independent biomarker for DFS prediction in patients with TNBC to NAC, and the combined radiomics nomogram improved individualized DFS estimation.

Dataset Information

Neoadjuvant chemotherapy induces expression levels of breast cancer resistance protein that predict disease-free survival in breast cancer.

Publications

Neoadjuvant chemotherapy induces expression levels of breast cancer resistance protein that predict disease-free survival in breast cancer.

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