Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine

Abstract

A grand challenge impeding optimal treatment outcomes for patients with cancer arises from the complex nature of the disease: the cellular heterogeneity, the myriad of dysfunctional molecular and genetic networks as results of genetic (somatic) and environmental perturbations. Systems biology, with its holistic approach to understanding fundamental principles in biology, and the empowering technologies in genomics, proteomics, single-cell analysis, microfluidics and computational strategies, enables a comprehensive approach to medicine, which strives to unveil the pathogenic mechanisms of diseases, identify disease biomarkers and begin thinking about new strategies for drug target discovery. The integration of multidimensional high-throughput 'omics' measurements from tumour tissues and corresponding blood specimens, together with new systems strategies for diagnostics, enables the identification of cancer biomarkers that will enable presymptomatic diagnosis, stratification of disease, assessment of disease progression, evaluation of patient response to therapy and the identification of reoccurrences. Whilst some aspects of systems medicine are being adopted in clinical oncology practice through companion molecular diagnostics for personalized therapy, the mounting influx of global quantitative data from both wellness and diseases is shaping up a transformational paradigm in medicine we termed 'predictive', 'preventive', 'personalized', and 'participatory' (P4) medicine, which requires new strategies, both scientific and organizational, to enable bringing this revolution in medicine to patients and to the healthcare system. P4 medicine will have a profound impact on society - transforming the healthcare system, turning around the ever escalating costs of healthcare, digitizing the practice of medicine and creating enormous economic opportunities for those organizations and nations that embrace this revolution.

Figure 1

A schematic diagram of the billions of different types of digital data points that will become a typical part of a patient's record in 10 years. Note the very different types of data ranging from molecular and cellular to typical medical records to the environmental influences captured by social networks.

Figure 2

A schematic of the network perturbations of one neural degenerative network over the 20 weeks of the progression of this disease in a mouse model. The red nodes indicate mRNAs that have become disease perturbed as compared with the brain transcripts of normal mice. The spreading of the disease-perturbed networks at the 3 different times points is striking--indicating the progressive disease-perturbation of this neurodegenerative network.

Figure 3

A schematic drawing indicating brain-specific and liver-specific blood proteins that come to constitute an organ-specific fingerprint in the blood. These organ-specific proteins serve as reporters for their specific cognate networks to differentiate a normal organ from its specific disease counterpart. When a network becomes disease-perturbed--its cognate proteins will change their concentration levels in the blood. Since different diseases perturb different combinations of networks--the organ-specific blood fingerprints can distinguish health from disease--and if a disease which disease--for each organ whose blood fingerprints are measured quantitatively.

Figure 4

Two central conceptual themes of P4 medicine--the quantification of wellness and the demystification of disease.