ReviewNature reviews. Clinical oncology2020
A systems approach to clinical oncology uses deep phenotyping to deliver personalized care.
Review in Nature reviews. Clinical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed.
- Towards a Compositional Framework for Describing Human Phenotypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Dynamic cellular programs of human cardiac allograft rejection revealed by spatial transcriptomics.Nature cardiovascular research · 2026Article
- Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026Observational
- Dissecting PANoptosis in the Nervous System: A Unified Cell-Death Mechanism Driving Neuroimmune Activation and Chronic Neuroinflammation.Molecular neurobiology · 2026Review
- Manifold-based learning for high-throughput single-peanut phenotyping.NPJ systems biology and applications · 2026Article
- Clinical subphenotypes and molecular endotypes in sepsis: toward an integrated and dynamic framework.Annals of intensive care · 2026Review
- Systems approach to integrative oncology in breast cancer care: service design, delivery and patient experiences from a UK center.Frontiers in oncology · 2026Article
- Genetic and chromosomal dysregulations of progenitor cells in the etiology and pathogenesis of pediatric cancers.American journal of stem cells · 2026Review
- Refining treatment strategies for non-small cell lung cancer lacking actionable mutations: insights from multi-omics studies.British journal of cancer · 2025Review
- Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery.Current oncology (Toronto, Ont.) · 2025Review
- Multiscale networks in Alzheimer's disease identify brain hypometabolism as central across biological scales.PLoS computational biology · 2025Article
- Longitudinal big biological data in the AI era.Molecular systems biology · 2025Review
- Sepsis subphenotypes, theragnostics and personalized sepsis care.Intensive care medicine · 2025Review
- Human Gut Microbiome Researches Over the Last Decade: Current Challenges and Future Directions.Phenomics (Cham, Switzerland) · 2025Article
- Immune snapshots along the inflammation-to-cancer road in bladder urothelium.Frontiers in immunology · 2025Review
- From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine.Health information science and systems · 2024Review
- Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning.bioRxiv : the preprint server for biology · 2024Article
- Digital twins in dermatology, current status, and the road ahead.NPJ digital medicine · 2024Review
- The genomic and immunogenomic landscape of mechanics pathway informs clinical prognosis and response to mechanotherapy.Science China. Life sciences · 2024Article
- Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials.Nature biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Cancer encompasses a complex, heterogeneous and dynamic group of diseases that arise from perturbations to multiple biological networks within the body. A systems biology-based approach would help to decipher this complexity, to deeply characterize the pathophysiology of the disease and to stratify cancers into appropriate molecular subtypes to facilitate the development of personalized therapies. Technological advances made over the past decade have enabled multiscale, longitudinal measurements ('snapshots') of human biology, from single-cell analyses to whole-body monitoring. In this Perspective, we discuss some of these technologies and how they have (and will) contributed to our understanding of cancer biology as well as to the development of early diagnostics and personalized therapies. We argue that the integration of molecular profiling of cancerous tissues with deep, longitudinal profiling of the physiological state of an individual ('deep phenotyping') is key to understanding the prevention, initiation, progression and response to treatment of cancers. Systems biology-based approaches can provide an unprecedented trove of data for early detection of disease transitions, prediction of therapeutic responses and clinical outcomes, and for the design of personalized treatments.
Indexed as
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.