Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial

Khurum Khan(Royal Marsden NHS Foundation Trust), David Cunningham(Royal Marsden NHS Foundation Trust), Benjamin Werner(Institute of Cancer Research), Georgios Vlachogiannis(Institute of Cancer Research), Inmaculada Spiteri(Institute of Cancer Research), Timon Heide(Institute of Cancer Research), Javier Fernández-Mateos(Institute of Cancer Research), Alexandra Vatsiou(Institute of Cancer Research), Andrea Lampis(Institute of Cancer Research), Mahnaz Darvish-Damavandi(Institute of Cancer Research), Hazel Lote(Institute of Cancer Research), Ian Said Huntingford(Institute of Cancer Research), Somaieh Hedayat(Institute of Cancer Research), Ian Chau(Royal Marsden NHS Foundation Trust), Nina Tunariu(Royal Marsden NHS Foundation Trust), Giulia Mentrasti(Institute of Cancer Research), Francesco Trevisani(Institute of Cancer Research), Sheela Rao(Royal Marsden NHS Foundation Trust), Gayathri Anandappa(Royal Marsden NHS Foundation Trust), David Watkins(Royal Marsden NHS Foundation Trust), Naureen Starling(Royal Marsden NHS Foundation Trust), Janet Thomas(Royal Marsden NHS Foundation Trust), Clare Peckitt(Royal Marsden NHS Foundation Trust), Nasir Khan(Royal Marsden NHS Foundation Trust), Massimo Rugge(University of Padua), Ruwaida Begum(Royal Marsden NHS Foundation Trust), Blanka Hezelova(Royal Marsden NHS Foundation Trust), Annette Bryant(Royal Marsden NHS Foundation Trust), Thomas R. Jones(Royal Marsden NHS Foundation Trust), Paula Proszek(Royal Marsden NHS Foundation Trust), Matteo Fassan(University of Padua), Jens C. Hahne(Institute of Cancer Research), Michael Hubank(Royal Marsden NHS Foundation Trust), Chiara Braconi(Royal Marsden NHS Foundation Trust), Andrea Sottoriva(Institute of Cancer Research), Nicola Valeri(Royal Marsden NHS Foundation Trust)
Cancer Discovery
August 30, 2018
Cited by 237Open Access
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Abstract

Abstract Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in RAS wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as RAS wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies. Significance: Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. Cancer Discov; 8(10); 1270–85. ©2018 AACR. See related commentary by Siravegna and Corcoran, p. 1213. This article is highlighted in the In This Issue feature, p. 1195


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