A nutrient-responsive cancer-on-chip model for assessing chemotherapy responses under glucose restriction

Area of Science:

• Biomedical Engineering
• Cancer Research
• Metabolic Studies

Background:

• Fasting-mimicking diets (FMDs) show promise as adjuvant cancer therapies.
• Conventional models fail to capture nutrient modulation's effects on chemotherapy.
• Understanding nutrient-drug interactions requires advanced preclinical systems.

Purpose of the Study:

• To develop a nutrient-responsive cancer-on-chip (CoC) platform.
• To investigate glucose modulation's impact on chemotherapy efficacy.
• To compare CoC models with static cultures for predicting treatment response.

Main Methods:

• Developed a 3D human breast cancer CoC platform.
• Administered cisplatin under varying glucose conditions (high, low, none).
• Utilized static and dynamic 3D systems for comparative analysis.

Main Results:

• Complete glucose deprivation reduced tumor cell viability and metabolic activity.
• The CoC platform demonstrated enhanced chemotherapy-induced cell death compared to static cultures.
• Glucose-free pre-conditioning improved chemotherapy sensitivity, creating a transient vulnerability window.

Conclusions:

• Nutrient-responsive CoC systems offer improved mechanistic insights into FMDs.
• Dynamic CoC models better predict clinical responses to fasting-associated therapies.
• This platform aids in investigating context-dependent therapeutic strategies.