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Treatment Resistant Cancers02:56

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
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Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
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Integrative physical oncology.

Haralampos Hatzikirou1, Arnaud Chauviere, Amy L Bauer

  • 1Department of Pathology, University of New Mexico, Albuquerque, NM, USA.

Wiley Interdisciplinary Reviews. Systems Biology and Medicine
|August 20, 2011
PubMed
Summary
This summary is machine-generated.

Integrative physical oncology uses physics-based mathematical models to understand cancer's complex, multiscale development. This study assesses current models for tumor growth, offering insights into the future of this scientific field.

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Area of Science:

  • Integrative Physical Oncology (IPO)
  • Computational Biology
  • Cancer Research

Background:

  • Solid tumors are complex biological systems evolving across intracellular, intercellular, and tissue scales.
  • Existing biological data extrapolation to clinical decisions lacks physical consistency.
  • Bridging nano- to macro-scales in tumor development remains a significant challenge.

Purpose of the Study:

  • To assess recent multiscale modeling approaches in cancer research.
  • To critically evaluate hybrid-multiscale models for tumor growth.
  • To provide perspectives on the future development and impact of Integrative Physical Oncology.

Main Methods:

  • Review of existing literature on multiscale modeling in cancer.
  • Analysis of modeling approaches at intracellular, intercellular, and tissue scales.
  • Critical evaluation of hybrid-multiscale models for brain and breast cancers.

Main Results:

  • Identification of recent modeling advancements across different biological scales.
  • Assessment of the strengths and limitations of current hybrid-multiscale models.
  • Discussion of the empirical extrapolation of biological data versus physically consistent modeling.

Conclusions:

  • Integrative Physical Oncology offers a framework for physically consistent mathematical modeling of tumor development.
  • Further development of IPO is crucial for advancing our understanding of cancer progression.
  • Hybrid-multiscale models show promise but require critical evaluation and refinement.