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Expression-driven reverse engineering of targeted imaging and therapeutic agents
Abstract:
Cancer is a particularly daunting disease to treat because, in its most insidious forms, cells are disseminated throughout the body, rendering surgery and local therapies ineffective. Hence, systemic disease must be targeted by its metabolic, physiological or molecular phenotype rather than by its location. Both tumour metabolism and physiology have been exploited to target therapies with some success. There is every reason to expect that these approaches will continue to advance therapies that discriminate tumour metabolism from that of normal tissues. As an alternative, molecular phenotyping (pharmacogenomics) is a relatively new science, and holds great promise for development of novel therapies and approaches. The discipline of pharmacogenomics has, to date, involved segmentation of patients according to their protein expression patterns in order to direct existing therapies to those populations who stand to benefit the most. In this communication, the authors propose a further application of this technology to develop agents that are reverse-engineered to explicitly target a patient's expressed protein patterns.
Insights
Targeting cancer
Area of Science:
- Oncology
- Pharmacogenomics
- Molecular Biology
Background:
- Systemic cancer treatment necessitates targeting cellular phenotypes rather than tumor location.
- Exploiting tumor metabolism and physiology has shown success in developing targeted therapies.
- Molecular phenotyping, or pharmacogenomics, offers a novel approach to cancer treatment.
Discussion:
- Pharmacogenomics currently segments patients based on protein expression to guide existing therapies.
- This communication proposes developing novel agents reverse-engineered to target specific patient protein patterns.
- This approach aims to create highly personalized and effective cancer treatments.
Key Insights:
- Cancer's systemic nature requires targeting molecular phenotypes.
- Pharmacogenomics enables patient stratification based on protein expression.
- Reverse-engineering drugs to match patient protein profiles is a promising strategy.
Outlook:
- Advancements in pharmacogenomics will drive the development of therapies discriminating tumor from normal tissue metabolism.
- Personalized medicine through molecular phenotyping holds significant promise for future cancer treatment.
- Developing targeted agents based on individual protein expression patterns represents a new frontier in oncology.