Precision oncology based on omics data: The NCT Heidelberg experience

Peter Horak(German Cancer Research Center), Barbara Klink(German Cancer Research Center), Christoph Heining(German Cancer Research Center), Stefan Gröschel(German Cancer Research Center), Barbara Hutter(Heidelberg University), Martina Fröhlich(Heidelberg University), Sebastian Uhrig(Heidelberg University), Daniel Hübschmann(Heidelberg University), Matthias Schlesner(Heidelberg University), Roland Eils(Heidelberg University), Daniela Richter(German Cancer Research Center), Katrin Pfütze(German Cancer Research Center), Christina Geörg(German Cancer Research Center), Bettina Meißburger(German Cancer Research Center), Stephan Wolf(Heidelberg University), Angela Schulz(Heidelberg University), Roland Penzel(Heidelberg University), Esther Herpel(Heidelberg University), Martina Kirchner(Heidelberg University), Amelie Lier(Heidelberg University), Volker Endris(Heidelberg University), Stephan Singer(Heidelberg University), Peter Schirmacher(Heidelberg University), Wilko Weichert(Technical University of Munich), Albrecht Stenzinger(Heidelberg University), Richard F. Schlenk(National Center for Tumor Diseases), Evelin Schröck(German Cancer Research Center), Benedikt Brors(Heidelberg University), Christof von Kalle(German Cancer Research Center), Hanno Glimm(German Cancer Research Center), Stefan Fröhling(German Cancer Research Center)
International Journal of Cancer
June 9, 2017
Cited by 171Open Access
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Abstract

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis toward controlled clinical trials of genomics-guided treatments.


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