Expression of Genes for Methylxanthine Pathway-Associated Enzymes Accompanied by Sex Steroid Receptor Status Impacts Breast Carcinoma Progression

Abstract

Consumption of methylxanthine alkaloids appears to induce activities by antagonizing adenosine receptors, implicated in breast cancer behavior in vitro. Our goal was to evaluate expression of genes for methylxanthine receptors and metabolizing enzymes to assess risk of breast carcinoma recurrence. Clinical outcomes, estrogen/progestin receptor results, and gene expression assays guided selection. RNA was isolated from laser capture microdissection-procured carcinoma cells for microarray using established protocols. Gene expression levels of eight methylxanthine receptors, eight metabolizing enzymes, and various phosphodiesterases were retrieved from microarray results. Univariable Cox regressions and Kaplan-Meier plots were determined for each gene with R software. Individually, lower expressions of PDE4A, CYP2A6, or CYP2E were related to decreased progression-free survival (PFS) and overall survival (OS). PDE1A over-expression predicted decreased PFS and OS. ADORA2B and RYR1 over-expressions predicted diminished OS. ER+ cancers exhibited lower ADORA1, ADORA2B, and RYR1 and elevated PDE4A, CYP2A6, and CYP2E expressions. Of PR+ carcinomas, diminished ADORA2B and RYR1 and elevated expressions of ADORA3, PDE4A, CYP2C8, and CYP2E were noted. Least absolute shrinkage and selection operator (LASSO) revealed that CYP2E, PDE1A, and PDE4A expressions collectively predicted PFS whereas ADORA1, CYP2E, PDE1A, PDE1B, and PDE4A expressions jointly predicted OS. Models were clinically significant when validated externally. LASSO also derived a six-gene model and five-gene model that predicted PFS of ER− or PR− carcinomas, respectively. Similarly, five-gene and four-gene models predicted OS in ER− or PR− carcinomas, respectively. Collectively, expression of genes involved in methylxanthine action and metabolism in single-cell types predicted clinical outcomes of breast carcinoma indicating promise for developing diagnostics and design of new therapeutics.

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