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Merging Metabolic Modeling and Imaging for Screening Therapeutic Targets in Colorectal Cancer.

Niki TavakoliEmma J FongAbigail ColemanYu-Kai HuangMathias BiggerMichael E DocheSeungil KimHeinz-Josef LenzNicholas Alexander GrahamPaul MacklinStacey D FinleyShannon M Mumenthaler
Published in: bioRxiv : the preprint server for biology (2024)
Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved high-throughput computational screening to investigate the effects of enzyme perturbations predicted by a computational model of CRC metabolism to understand system-wide effects efficiently. Our results highlighted hexokinase (HK) as one of the crucial targets, which subsequently became our focus for experimental validation using patient-derived tumor organoids (PDTOs). Through metabolic imaging and viability assays, we found that PDTOs cultured in CAF conditioned media exhibited increased sensitivity to HK inhibition. Our approach emphasizes the critical role of integrating computational and experimental techniques in exploring and exploiting CRC-CAF crosstalk.
Keyphrases
  • high throughput
  • high resolution
  • endothelial cells
  • single cell