Opportunities and challenges for patient-derived models of brain tumors in functional precision medicine

Area of Science:

• Oncology
• Translational Medicine
• Genomics

Background:

• Precision medicine traditionally relies on genomic data for treatment selection.
• Genomic approaches have limitations in predicting individual patient responses to therapies.
• A paradigm shift towards functional precision medicine is emerging.

Purpose of the Study:

• To review the shift from genomics-based to functional precision medicine.
• To discuss patient-derived models for central nervous system tumors.
• To highlight the potential of these models in predicting treatment efficacy.

Main Methods:

• Review of current literature on precision medicine and patient-derived models.
• Discussion of various classes of patient-derived models for central nervous system tumors.
• Analysis of the unique features and applications of each model class.

Main Results:

• Functional precision medicine evaluates therapeutic efficacy by directly treating ex vivo patient tumors.
• Patient-derived models offer a platform for predicting patient-specific treatment responses.
• Different classes of patient-derived models possess distinct advantages for CNS tumor research.

Conclusions:

• Functional precision medicine offers a promising approach to personalize cancer treatment.
• Patient-derived models are crucial tools for advancing functional precision medicine.
• This approach has the potential to improve treatment selection, prolong survival, and enhance patient outcomes in CNS tumors.