Cancer Precision Medicine: Why More Is More and DNA Is Not Enough

Abstract

Every tumour is different. They arise in patients with different genomes, from cells with different epigenetic modifications, and by random processes affecting the genome and/or epigenome of a somatic cell, allowing it to escape the usual controls on its growth. Tumours and patients therefore often respond very differently to the drugs they receive. Cancer precision medicine aims to characterise the tumour (and often also the patient) to be able to predict, with high accuracy, its response to different treatments, with options ranging from the selective characterisation of a few genomic variants considered particularly important to predict the response of the tumour to specific drugs, to deep genome analysis of both tumour and patient, combined with deep transcriptome analysis of the tumour. Here, we compare the expected results of carrying out such analyses at different levels, from different size panels to a comprehensive analysis incorporating both patient and tumour at the DNA and RNA levels. In doing so, we illustrate the additional power gained by this unusually deep analysis strategy, a potential basis for a future precision medicine first strategy in cancer drug therapy. However, this is only a step along the way of increasingly detailed molecular characterisation, which in our view will, in the future, introduce additional molecular characterisation techniques, including systematic analysis of proteins and protein modification states and different types of metabolites in the tumour, systematic analysis of circulating tumour cells and nucleic acids, the use of spatially resolved analysis techniques to address the problem of tumour heterogeneity as well as the deep analyses of the immune system of the patient to, e.g., predict the response of the patient to different types of immunotherapy. Such analyses will generate data sets of even greater complexity, requiring mechanistic modelling approaches to capture enough of the complex situation in the real patient to be able to accurately predict his/her responses to all available therapies.

A data- and model-driven approach for cancer treatment

“…Additional omics, such as transcriptome sequencing (RNAseq), offer valuable insights for orienting treatment recommendations, such as the MammaPrint signature that predicts treatment response in breast cancer [9]. RNAseq enables access to a deeper level of knowledge on the tumor biology (oncogenic changes in gene expression, epigenetic effects, splice variants, information on unexpected gene fusions, etc) [10,11], and the tumor microenvironment, which is becoming an increasingly attractive target for clinical intervention, with drugs targeting hypoxia, for instance. The breakthrough of immune checkpoint inhibitors (ICIs) has changed the precision medicine landscape [12] and shows that the focus of targeted therapies goes much beyond mutated forms of cancer genes to the immune environment.…”

Ein daten- und modellgesteuerter Ansatz zur Behandlung maligner Tumoren

“…RNAseq ermöglicht den Zugang zu einem tiefergehenden Wissen über die Tumorbiologie (u. a. onkogene Veränderungen in der Genexpression, epigenetische Effekte, Spleißvarianten, unerwartete Genfusionen etc. ; [10,11]) und die Tumormikroumgebung, ein stetig wichtiger werdendes Gebiet für klinische Interventionen (z. B. mit Medikamenten, die auf Hypoxie abzielen).…”

Three-Dimensional Patient-Derived In Vitro Sarcoma Models: Promising Tools for Improving Clinical Tumor Management

“…Yet, sequencing alone has proven to be “remarkably unhelpful,” and the belief that sequencing your DNA is going to extend your life is “a cruel illusion” as James Watson put it in a recent interview with the New York Times ( 95 ). Today, genome researchers still struggle to be able to sufficiently support clinical decision-making with meaningful sequence data, and to compensate for this deficit, they propose that “more is more” ( 96 ). Yet, these genome centrics are neither feasible in the clinical setting nor payable by the majority of patients and insurance companies.…”