Predicting response to neoadjuvant treatment in breast cancer using pre-clinical models
Óscar Rueda
MRC Biostatistics Unit (University of Cambridge)
Triple negative breast cancers (TNBC) exhibit inter- and intra-tumour heterogeneity, which is reflected in diverse drug responses and interplays with tumour evolution. Here, we develop a preclinical experimental and analytical framework using treatment-naive TNBC patient-derived tumour xenografts (PDTX) to test their predictive value in personalised cancer treatment approaches. We observed that patients and their matched PDTX exhibit concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. We exploited this platform further to study non-genetic mechanisms involved in relapse dynamics. We identified that treatment results in permanent phenotypic changes with functional and therapeutic consequences. Using high throughout drug screening methods in ex vivo patient derived xenografted cells (PDTCs), we revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumours previously treated with clinically relevant cycles of standard-of-care chemotherapy.