A Platform of Patient-Derived Microtumors Identifies Individual Treatment Responses and Therapeutic Vulnerabilities...

Area of Science:

• Oncology
• Translational Medicine
• Biotechnology

Background:

• Therapeutic resistance is a significant challenge in cancer treatment.
• There is a critical need for personalized preclinical models that capture tumor heterogeneity.
• Such models are essential for predicting individual patient responses to various therapies.

Purpose of the Study:

• To develop a 3D preclinical model using patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs).
• To validate the efficacy of chemotherapy, immunotherapy, and targeted therapies in an individual patient context.
• To identify patient-specific treatment vulnerabilities and predict therapeutic responses.

Main Methods:

• Enzymatic digestion of primary ovarian cancer tissue for PDM recovery.
• Cultivation of PDM in defined serum-free media to preserve histopathology.
• Reverse-phase protein array (RPPA) analysis for protein profiling.
• Co-culture of PDM with autologous TILs for drug efficacy testing.

Main Results:

• Rapid and efficient recovery of PDM preserving histopathological features.
• RPPA analysis identified patient-specific sensitivities to platinum-based therapy.
• Co-cultures demonstrated patient-specific enhancement of cytotoxic TIL activity by immune checkpoint inhibitors.
• Combined protein pathway analysis and drug testing predicted therapeutic sensitivities within a clinically relevant timeframe.

Conclusions:

• The developed 3D preclinical model effectively represents patient tumor heterogeneity.
• This platform enables personalized drug testing and prediction of treatment responders.
• The model shows promise for supporting clinical decision-making in ovarian cancer treatment.