Precision Oncology Based on Omics Data: The NCT Heidelberg Experience.

Horak P1,2, Klink B3,4,5,6, Heining C1,2, Gröschel S1,2,7,8,9, Hutter B10, Fröhlich M10, Uhrig S10, Hübschmann D11,12,13, Schlesner M11, Eils R11,12, Richter D1, Pfütze K1,14, Geörg C1,14, Meißburger B1,14, Wolf S15, Schulz A15, Penzel R16, Herpel E16, Kirchner M16, Lier A16, Endris V16, Singer S16, Schirmacher P9,16, Weichert W17,18, Stenzinger A9,16, Schlenk RF19, Schröck E3,4,5,6, Brors B9,10, von Kalle C1,2,9,14, Glimm H1,2,9, Fröhling S1,2,9.

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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 towards controlled clinical trials of genomics-guided treatments. This article is protected by copyright. All rights reserved.