Abstract

BackgroundClinical studies implying the sunitinib multi-kinase inhibitor have led to disappointing results for breast cancer care but mostly focused on HER2-negative subtypes. Preclinical researches involving this drug mostly concern Triple Negative Breast Cancer (TNBC) murine models. Here, we explored the therapeutic efficacy of sunitinib on a PyMT-derived transplanted model classified as luminal B (HER2-positive) and monitored the response to treatment using both in vivo and ex vivo approaches.MethodsTumour-induced animals were treated for 9 (n = 7) or 14 (n = 8) days with sunitinib at 40 mg/kg or with vehicle only. Response to therapy was assessed in vivo by monitoring glucose tumour metabolism and hypoxia using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) and [18F]fluoromisonidazole ([18F]FMISO) Positron Emission Tomography (PET). After primary tumour excision, ex vivo digital microscopy was performed on treated and control samples to estimate vascular density (CD31), apoptosis (Tunel), proliferation (Ki-67), Tumour-Associated Macrophage (TAM) infiltration (F4/80), metabolism (GLUT1) and cellular response to hypoxia (HIF1 alpha). The drug impact on the metastasis rate was evaluated by monitoring the PyMT gene expression in the lungs of the treated and control groups.ResultsConcomitant with sunitinib-induced tumour size regression, [18F]FDG PET imaging showed a stable glycolysis-related metabolism inside tumours undergoing treatment compared to an increased metabolism in untreated tumours, resulting at treatment end in 1.5 less [18F]FDG uptake in treated (n = 4) vs control (n = 3) tumours (p < 0.05). With this small sample, [18F]FMISO PET showed a non-significant decrease of hypoxia in treated vs control tumours. The drug triggered a 4.9 fold vascular volume regression (p < 0.05), as well as a 17.7 fold induction of tumour cell apoptosis (p < 0.001). The hypoxia induced factor 1 alpha (HIF1 alpha) expression was twice lower in the treated group than in the control group (p < 0.05). Moreover, the occurrence of lung metastases was not reduced by the drug.Conclusions[18F]FDG and [18F]FMISO PET were relevant approaches to study the response to sunitinib in this luminal B (HER2-positive) model. The sunitinib-induced vascular network shrinkage did not significantly increase tumour hypoxia, suggesting that tumour regression was mainly due to the pro-apoptotic properties of the drug. Sunitinib did not inhibit the metastatic process in this PyMT transplanted model.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1540-2) contains supplementary material, which is available to authorized users.

Highlights

  • Clinical studies implying the sunitinib multi-kinase inhibitor have led to disappointing results for breast cancer care but mostly focused on human epidermal growth factor receptor 2 (HER2)-negative subtypes

  • Two recent reports focusing on HER2-positive breast cancers found an improved overall response rate (ORR) in adding sunitinib to regimens based on TZM with or without docetaxel administration [8, 9]

  • Sunitinib-induced mammary tumour regression on the PyMT model In set A of mice, the mean tumour volume measured by calliper was 209 ± 38 mm3 (n = 7) just before treatment

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Summary

Introduction

Clinical studies implying the sunitinib multi-kinase inhibitor have led to disappointing results for breast cancer care but mostly focused on HER2-negative subtypes. Preclinical researches involving this drug mostly concern Triple Negative Breast Cancer (TNBC) murine models. Based on encouraging preclinical data, the sunitinib drug, a multi-kinase inhibitor, has been investigated in several clinical studies in association with various cytotoxic drugs but led to disappointing results in breast cancer patients. A detailed panorama of the relationships between the histological- and the transcriptomicbased classifications has been recently published [12] In this context, the breast cancer patient care is evolving as it is expected that the efficacies of chemotherapeutic regimens should depend on the considered subtype

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