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Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine
Open accessAbstract
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.
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“This strategy integrates genomic sequencing, blood-based omics (e.g., metabolomics and proteomics), microbiome analysis, and wearable device data to capture each patient’s unique biological state over time.”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [97]
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Metadata
- Authors
- Tian, Q., Price, N. D., & Hood, L.
- Affiliations
- Institute for Systems Biology (US)
- Corresponding author
- Tian, Q.
- Hood, L.
- Venue
- Journal of Internal Medicine
- Publisher
- Wiley
- Published
- 2012-01-17
- Volume
- 271
- Issue
- 2
- Pages
- 111-121
- ISSN
- 0954-6820 (ISSN-L)
- 1365-2796
- PMC
- PMC3978383
- OpenAlex
- W2118104220
- Cited by
- 224
- References
- 48
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 8 · 2023: 15 · 2022: 10 · 2021: 12 · 2020: 15 · 2019: 10 · 2018: 19 · 2017: 14 · 2016: 17 · 2015: 21 · 2014: 25 · 2013: 21 · 2012: 29
- FWCI
- 1.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (U54 CA151819A)
- National Cancer Institute (U54 CA151819A, U54CA151819, R00CA126184)
- National Institute of General Medical Sciences (GM 076547, P50GM076547)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Science, Research, and Medicine
- Keywords
- P4 medicine, predictive medicine, preventive medicine, personalized medicine, participatory medicine, tumor markers, systems biology, cancer genomics, single-cell analysis, microfluidics, companion diagnostics, precision oncology, tumor recurrence, health care costs, digital health
- MeSH terms
- Humans, Medical Oncology, Mutation, Neoplasms, Biomarkers, Tumor, Genome, Human, Gene Expression Profiling, Genomics, Proteomics, Systems Biology, Precision Medicine, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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