Functional imaging and circulating biomarkers of response to regorafenib in treatment-refractory metastatic colorectal cancer patients in a prospective phase II study.
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<h4>Objective</h4>Regorafenib demonstrated efficacy in patients with metastatic colorectal cancer (mCRC). Lack of predictive biomarkers, potential toxicities and cost-effectiveness concerns highlight the unmet need for better patient selection.<h4>Design</h4>Patients with <i>RAS</i> mutant mCRC with biopsiable metastases were enrolled in this phase II trial. Dynamic contrast-enhanced (DCE) MRI was acquired pretreatment and at day 15 post-treatment. Median values of volume transfer constant (K<sup>trans</sup>), enhancing fraction (EF) and their product KEF (summarised median values of K<sup>trans</sup>× EF) were generated. Circulating tumour (ct) DNA was collected monthly until progressive disease and tested for clonal <i>RAS</i> mutations by digital-droplet PCR. Tumour vasculature (CD-31) was scored by immunohistochemistry on 70 sequential tissue biopsies.<h4>Results</h4>Twenty-seven patients with paired DCE-MRI scans were analysed. Median KEF decrease was 58.2%. Of the 23 patients with outcome data, >70% drop in KEF (6/23) was associated with higher disease control rate (p=0.048) measured by RECIST V. 1.1 at 2 months, improved progression-free survival (PFS) (HR 0.16 (95% CI 0.04 to 0.72), p=0.02), 4-month PFS (66.7% vs 23.5%) and overall survival (OS) (HR 0.08 (95% CI 0.01 to 0.63), p=0.02). KEF drop correlated with CD-31 reduction in sequential tissue biopsies (p=0.04). <i>RAS</i> mutant clones decay in ctDNA after 8 weeks of treatment was associated with better PFS (HR 0.21 (95% CI 0.06 to 0.71), p=0.01) and OS (HR 0.28 (95% CI 0.07-1.04), p=0.06).<h4>Conclusions</h4>Combining DCE-MRI and ctDNA predicts duration of anti-angiogenic response to regorafenib and may improve patient management with potential health/economic implications.
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Magnetic Resonance Imaging
Signal Transduction & Molecular Pharmacology
Gastrointestinal Cancers Clinical Trials
Medicine (RMH Smith Cunningham)
Evolutionary Genomics & Modelling
Gastrointestinal Cancer Biology and Genomics
Systems and Precision Cancer Medicine
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Gut, 2018, 67 (8), pp. 1484 - 1492