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Updated: Oct 9, 2025

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
Published on: May 18, 2020
Establishing pteridine metabolism in a progressive isogenic breast cancer cell model
Lindsey Rasmussen1, Zachary Foulks1, Casey Burton2,3
1Department of Chemistry, Missouri University of Science and Technology, 400 W 11th Street, Rolla, MO, 65409, USA.
Introduction:
Pteridines include folate-derived metabolites that have been putatively associated with certain cancers in clinical studies. However, their biological significance in cancer metabolism and role in cancer development and progression remains poorly understood.
Objectives:
The purpose of this study was to examine the effects of tumorigenicity on pteridine metabolism by studying a panel of 15 pteridine derivatives using a progressive breast cancer cell line model with and without folic acid dosing.
Methods:
The MCF10A progressive breast cancer model, including sequentially derived MCF10A (benign), MCF10AT (premalignant), and MCF10CA1a (malignant) cell lines were dosed with 0, 100, and 250 mg/L folic acid. Pteridines were analyzed in both intracellular and extracellular contexts using an improved high-performance liquid chromatography-tandem mass spectrometry method.
Results:
Pteridines were located predominately in the extracellular media. Folic acid dosing increased extracellular levels of pterin, 6-hydroxylumazine, xanthopterin, 6-hydroxymethylpterin, and 6-carboxypterin in a dose-dependent manner. In particular, pterin and 6-hydroxylumazine levels were positively correlated with tumorigenicity upon folate dosing.
Conclusions:
Folic acid is a primary driver for pteridine metabolism in human breast cell. Higher folate levels contribute to increased formation and excretion of pteridine derivatives to the extracellular media. In breast cancer, this metabolic pathway becomes dysregulated, resulting in the excretion of certain pteridine derivatives and providing in vitro evidence for the observation of elevated pteridines in the urine of breast cancer patients. Finally, this study reports a novel use of the MCF10A progressive breast cancer model for metabolomics applications that may readily be applied to other metabolites of interest.
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