Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics

Junmin Wang; Alireza Delfarah; Patrick E Gelbach; Emma Fong; Paul Macklin; Shannon M Mumenthaler; Nicholas A Graham; Stacey D Finley

doi:10.1016/j.ymben.2021.11.006

Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics

Metab Eng. 2022 Jan:69:175-187. doi: 10.1016/j.ymben.2021.11.006. Epub 2021 Nov 25.

Authors

Junmin Wang¹, Alireza Delfarah², Patrick E Gelbach¹, Emma Fong³, Paul Macklin⁴, Shannon M Mumenthaler⁵, Nicholas A Graham², Stacey D Finley⁶

Affiliations

¹ Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
² Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA.
³ Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA, 90064, USA.
⁴ Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 46202, USA.
⁵ Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA, 90064, USA; Division of Medical Oncology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA.
⁶ Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA; Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA. Electronic address: sfinley@usc.edu.

Abstract

Colorectal cancer (CRC) is a major cause of morbidity and mortality in the United States. Tumor-stromal metabolic crosstalk in the tumor microenvironment promotes CRC development and progression, but exactly how stromal cells, in particular cancer-associated fibroblasts (CAFs), affect the metabolism of tumor cells remains unknown. Here we take a data-driven approach to investigate the metabolic interactions between CRC cells and CAFs, integrating constraint-based modeling and metabolomic profiling. Using metabolomics data, we perform unsteady-state parsimonious flux balance analysis to infer flux distributions for central carbon metabolism in CRC cells treated with or without CAF-conditioned media. We find that CAFs reprogram CRC metabolism through stimulation of glycolysis, the oxidative arm of the pentose phosphate pathway (PPP), and glutaminolysis, as well as inhibition of the tricarboxylic acid cycle. To identify potential therapeutic targets, we simulate enzyme knockouts and find that CAF-treated CRC cells are especially sensitive to inhibitions of hexokinase and glucose-6-phosphate, the rate limiting steps of glycolysis and oxidative PPP. Our work gives mechanistic insights into the metabolic interactions between CRC cells and CAFs and provides a framework for testing hypotheses towards CRC-targeted therapies.

Keywords: Flux balance analysis; Mathematical biosciences; Metabolomics; Systems biology; Tumor microenvironment.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Cancer-Associated Fibroblasts* / metabolism
Cancer-Associated Fibroblasts* / pathology
Chromatography, Liquid
Colorectal Neoplasms* / genetics
Colorectal Neoplasms* / metabolism
Colorectal Neoplasms* / pathology
Humans
Metabolomics
Tandem Mass Spectrometry
Tumor Microenvironment

Grants and funding

U01 CA232137/CA/NCI NIH HHS/United States