Next-generation personalised medicine for high-risk paediatric cancer patients - The INFORM pilot study

The 'Individualized Therapy for Relapsed Malignancies in Childhood' (INFORM) precision medicine study is a nationwide German program for children with high-risk relapsed/refractory malignancies, which aims to identify therapeutic targets on an individualised basis. In a pilot phase, reported here, we developed the logistical and analytical pipelines necessary for rapid and comprehensive molecular profiling in a clinical setting. Fifty-seven patients from 20 centers were prospectively recruited. Malignancies investigated included sarcomas (n = 25), brain tumours (n = 23), and others (n = 9). Whole-exome, low-coverage whole-genome, and RNA sequencing were complemented with methylation and expression microarray analyses. Alterations were assessed for potential targetability according to a customised prioritisation algorithm and subsequently discussed in an interdisciplinary molecular tumour board. Next-generation sequencing data were generated for 52 patients, with the full analysis possible in 46 of 52. Turnaround time from sample receipt until first report averaged 28 d. Twenty-six patients (50%) harbored a potentially druggable alteration with a prioritisation score of 'intermediate' or higher (level 4 of 7). Common targets included receptor tyrosine kinases, phosphoinositide 3-kinase-mammalian target of rapamycin pathway, mitogen-activated protein kinase pathway, and cell cycle control. Ten patients received a targeted therapy based on these findings, with responses observed in some previously treatment-refractory tumours. Comparative primary relapse analysis revealed substantial tumour evolution as well as one case of unsuspected secondary malignancy, highlighting the importance of re-biopsy at relapse. This study demonstrates the feasibility of comprehensive, real-time molecular profiling for high-risk paediatric cancer patients. This extended proof-of-concept, with examples of treatment consequences, expands upon previous personalised oncology endeavors, and presents a model with considerable interest and practical relevance in the burgeoning era of personalised medicine. (C) 2016 Elsevier Ltd. All rights reserved.