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Integrative Approaches to Cancer Immunotherapy
Gregory L Szeto1, Stacey D Finley2
1Department of Chemical, Biochemical, and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA; Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland, Baltimore, MD 21201, USA.
Trends in Cancer
|July 18, 2019
Summary
Cancer immunotherapy is promising but needs improvement. Integrative systems approaches using modeling and data generation can enhance treatment efficacy and predict patient response for better cancer care.
Area of Science:
- Oncology
- Immunology
- Systems Biology
Background:
- Cancer immunotherapy has shown significant success with recent drug approvals.
- Despite advances, challenges remain in broadening efficacy and predicting patient response.
Purpose of the Study:
- To advocate for integrative systems approaches to address key challenges in cancer immunotherapy.
- To improve treatment efficacy across diverse cancer types and patient populations.
- To develop predictive models for patient response to immunotherapy.
Main Methods:
- Applying mechanistic and statistical modeling.
- Establishing standardized experimental tools for systems-level data generation.
- Creating sustainable support mechanisms for research.
Main Results:
- Integrative systems approaches offer a path to answer critical questions in cancer immunotherapy.
- These methods can lead to more effective and personalized cancer treatments.
- Improved prediction of treatment response will optimize patient outcomes.
Conclusions:
- A shift towards integrative systems biology is crucial for advancing cancer immunotherapy.
- Standardized data generation and robust modeling are key to overcoming current limitations.
- Implementation of these approaches promises major breakthroughs in cancer treatment.
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