Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level

Frontiers in Network Physiology

Network Physiology

Sayantan Bhattacharyya¹  Loukia G. Karacosta¹  Shafqat F. Ehsan² 

[1] Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, United States;Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, United States;Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States;

关键词: personalized medicine;    phenotypic maps;    therapy resistance;    tumor heterogeneity;    multi-omics;    systems biology;    computational biology;   

DOI  :  10.3389/fnetp.2023.1256104

 received in 2023-07-10, accepted in 2023-09-28,  发布年份 2023

来源: Frontiers

【 摘 要 】

In this perspective we discuss how tumor heterogeneity and therapy resistance necessitate a focus on more personalized approaches, prompting a shift toward precision medicine. At the heart of the shift towards personalized medicine, omics-driven systems biology becomes a driving force as it leverages high-throughput technologies and novel bioinformatics tools. These enable the creation of systems-based maps, providing a comprehensive view of individual tumor’s functional plasticity. We highlight the innovative PHENOSTAMP program, which leverages high-dimensional data to construct a visually intuitive and user-friendly map. This map was created to encapsulate complex transitional states in cancer cells, such as Epithelial-Mesenchymal Transition (EMT) and Mesenchymal-Epithelial Transition (MET), offering a visually intuitive way to understand disease progression and therapeutic responses at single-cell resolution in relation to EMT-related single-cell phenotypes. Most importantly, PHENOSTAMP functions as a reference map, which allows researchers and clinicians to assess one clinical specimen at a time in relation to their phenotypic heterogeneity, setting the foundation on constructing phenotypic maps for personalized medicine. This perspective argues that such dynamic predictive maps could also catalyze the development of personalized cancer treatment. They hold the potential to transform our understanding of cancer biology, providing a foundation for a future where therapy is tailored to each patient’s unique molecular and cellular tumor profile. As our knowledge of cancer expands, these maps can be continually refined, ensuring they remain a valuable tool in precision oncology.

【 授权许可】

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Copyright © 2023 Bhattacharyya, Ehsan and Karacosta.