Clinical Network Systems Biology: Traversing the Cancer Multiverse

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has reveale...

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Published inJournal of clinical medicine Vol. 12; no. 13; p. 4535
Main Authors Mambetsariev, Isa, Fricke, Jeremy, Gruber, Stephen B, Tan, Tingting, Babikian, Razmig, Kim, Pauline, Vishnubhotla, Priya, Chen, Jianjun, Kulkarni, Prakash, Salgia, Ravi
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 07.07.2023
MDPI
Subjects
Artificial intelligence
Biology
Biomarkers
Cancer
Care and treatment
Clinical medicine
Clinical trials
Collaboration
Design techniques
Drug development
Epigenetics
Hypotheses
Oncology, Experimental
Patients
Precision medicine
Regulatory approval
Review
Systems biology
United States
precision medicine
cancer systems biology
team medicine
clinical network systems biology
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Summary:In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody-drug conjugates, and immunotherapy. This 'Team Medicine' approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.
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These authors contributed equally to this work and should be considered co-first authors.
ISSN:2077-0383
2077-0383
DOI:10.3390/jcm12134535