Summary
Purpose Improved prognostic accuracy for treatment response and a wider understanding of drug effects in humans are crucial for enhancing the utility of sorafenib and other promising targeted therapies. We developed a strategy of global genomic investigation of sequential tumor biopsy samples at baseline and 21 days post treatment, and applied this approach in a phase I study of sorafenib plus dacarbazine in patients with solid tumors. The objective of this study was also to validate functional parameters of DCE-US as surrogate markers to predict earlier response. Experimental design Patients received 21-day cycles of oral sorafenib, 400 mg twice daily and dacarbazine, 1,000 mg/m2 in a 1-h intravenous infusion on day 1. Efficacy was assessed using response evaluation criteria in solid tumors. Sequential biopsy samples (baseline and day 21) were obtained from the same tumor. Changes from baseline in global gene expression (GE) measured by genomic microarrays and in tumor vascularity at baseline, D8, D21, D 42 and every 2 cycles using dynamic contrast-enhanced ultrasonography (DCE-US) were analyzed for patients with and without a clinical response to treatment at 3 months. Results Among 23 patients evaluable for treatment efficacy, 17 were eligible for gene expression and DCE-US analyses. One patient achieved a partial response; 14 exhibited stable disease. Ten patients were defined as exhibiting stable disease (SD) and 7, progressive disease (PD) at 3 months. Genomic analyses identified a 237-gene signature that distinguished SD from PD at 3 months. Of note, CDK4 overexpression and PDGFR downregulation were associated with PD. Functional parameters of DCE-US representing the blood volume at baseline, day 8, and day 21 were correlated with disease progression at 3 months. Conclusions This novel approach of sequential investigations in a phase I trial was feasible, detecting early changes in gene expression and tumor vascularity evaluated using DCE-US that may be predictive of clinical outcome.
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Acknowledgments
We would like to acknowledge Serge Koscielny for his contributions to the conception of the study. We also acknowledge Meenakshi Subramanian, PhD, and Ann Garvey, PhD, Evidence Scientific Solutions, and Robert Marlowe, BA, for assistance with manuscript writing, which was supported by Bayer HealthCare Pharmaceuticals and Onyx Pharmaceuticals, Inc. We thank Lorna Saint Ange for editing.
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Bayer HealthCare Pharmaceuticals; Programme Hospitalier de Recherche Clinique
Data availability
The microarray data related to this paper were submitted to the Array Express Data Repository at the European Bioinformatics Institute (http://www.ebi.ac.uk/arrayexpress/) under the accession number E-TABM-760.
Conflict of interest
JCS, JPA, VL and NL received grant support from Bayer HealthCare Pharmaceuticals.
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This work was presented in part at the Annual Meeting of the American Society for Clinical Oncology, June 2007, Chicago, IL.
Vladimir Lazar, Nathalie Lassau and Guillaume Meurice contributed equally to the work.
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Supplementary Figure 1
DCE-US contrast uptake curves displaying variables linked to the blood volume, blood flow, and resistance in the vascular network Panel A, generalized representation; Panel B, DCE-US contrast uptake curves in a representative (top graph) patient with SD and a representative patient with PD (bottom graph). Abbreviations: AU, arbitrary units; AUC, area under the curve; TL, time between T0 and the time corresponding to the onset of the lowest peak intensity; Tmax, time between T0 and the time corresponding to the maximum peak intensity; V0, lowest peak intensity; Vmax, maximum peak intensity; Vmax/2, half the maximum peak intensity; RECIST, Response Evaluation Criteria in Solid Tumors. (PPT 409 kb)
Supplementary Figure 2
Gene Network constructed from genes significantly differentially expressed between patients with PD and SD. (PPT 336 kb)
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Lazar, V., Lassau, N., Meurice, G. et al. Sorafenib plus dacarbazine in solid tumors: a phase I study with dynamic contrast-enhanced ultrasonography and genomic analysis of sequential tumor biopsy samples. Invest New Drugs 32, 312–322 (2014). https://doi.org/10.1007/s10637-013-9993-0
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DOI: https://doi.org/10.1007/s10637-013-9993-0