University of Louisville
Deciphering the Molecular Basis of Breast Cancer Behavior using Proteomics and Genomics: STUDY 2 (Sereff): Novel Relationships of Methylxanthine Alkaloid Receptor Genes and Risk of Breast Carcinoma Recurrence
Institution
University of Louisville
Faculty Advisor/ Mentor
James L. Wittliff; Michael W. Daniels
Abstract
Consumption of methylxanthine alkaloids such as caffeine, theophylline and theobromine may induce breast pain. Caffeine may have induced its biological activities by antagonizing adenosine receptors, which have been implicated in breast cancer cell behavior in vitro. Our goal was to evaluate relationships between genes for methylxanthine receptors and metabolizing enzymes in relationship to risk of recurrence. Expression of 8 xanthine receptors, 8 metabolizing enzymes and various phosphodiesterases were measured by microarray analyses of RNA isolated from LCM-procured carcinoma cells from 247 breast biopsies. Using statistical software R, univariate and multivariate Cox regressions with interaction were determined for each candidate gene. Gene expression was examined in relationship to estrogen (ER) or progestin receptor (PR) status. Kaplan-Meier plots of receptor genes ADORA2B and RYR1 indicated that over-expression was related to diminished over-survival (OS). ER+ or PR+ carcinomas exhibited lower ADORA2B and RYR1 expression. Of enzymes involved in methylxanthine metabolism, elevated CYP2E1 gene expression was associated with increased disease-free survival (DFS) and OS of breast cancer patients. CYP2E1 gene expression was significantly higher in ER+ and PR+ breast cancers compared to ER- and PR- lesions. Of molecular targets, PDE4A gene over-expression was significant for predicting improved DFS and OS, particularly in ER+ breast cancers. In contrast, PDE1A gene over expression was significant for predicting decreased DFS and OS of breast cancer patients regardless of ER/PR status. Collectively, these results suggest that expression of several genes involved in methylxanthine action and metabolism may be used as a molecular signature for predicting breast carcinoma behavior.
Deciphering the Molecular Basis of Breast Cancer Behavior using Proteomics and Genomics: STUDY 2 (Sereff): Novel Relationships of Methylxanthine Alkaloid Receptor Genes and Risk of Breast Carcinoma Recurrence
Consumption of methylxanthine alkaloids such as caffeine, theophylline and theobromine may induce breast pain. Caffeine may have induced its biological activities by antagonizing adenosine receptors, which have been implicated in breast cancer cell behavior in vitro. Our goal was to evaluate relationships between genes for methylxanthine receptors and metabolizing enzymes in relationship to risk of recurrence. Expression of 8 xanthine receptors, 8 metabolizing enzymes and various phosphodiesterases were measured by microarray analyses of RNA isolated from LCM-procured carcinoma cells from 247 breast biopsies. Using statistical software R, univariate and multivariate Cox regressions with interaction were determined for each candidate gene. Gene expression was examined in relationship to estrogen (ER) or progestin receptor (PR) status. Kaplan-Meier plots of receptor genes ADORA2B and RYR1 indicated that over-expression was related to diminished over-survival (OS). ER+ or PR+ carcinomas exhibited lower ADORA2B and RYR1 expression. Of enzymes involved in methylxanthine metabolism, elevated CYP2E1 gene expression was associated with increased disease-free survival (DFS) and OS of breast cancer patients. CYP2E1 gene expression was significantly higher in ER+ and PR+ breast cancers compared to ER- and PR- lesions. Of molecular targets, PDE4A gene over-expression was significant for predicting improved DFS and OS, particularly in ER+ breast cancers. In contrast, PDE1A gene over expression was significant for predicting decreased DFS and OS of breast cancer patients regardless of ER/PR status. Collectively, these results suggest that expression of several genes involved in methylxanthine action and metabolism may be used as a molecular signature for predicting breast carcinoma behavior.