Analyzing the regulation of metabolic pathways in human breast cancer

Abstract

Background: Tumor therapy mainly attacks the metabolism to interfere the tumor's anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer.

Methods: For this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network. We used Haar Wavelet transforms on optimally arranged grid representations of metabolic pathways as a pattern recognition method to detect orchestrated regulation of neighboring enzymes in the network. Significant combined expression patterns were used to select metabolic pathways showing shifted regulation of the aggressive tumors.

Results: Besides up-regulation for energy production and nucleotide anabolism, we found an interesting cellular switch in the interplay of biosynthesis of steroids and bile acids. The biosynthesis of steroids was up-regulated for estrogen synthesis which is needed for proliferative signaling in breast cancer. In turn, the decomposition of steroid precursors was blocked by down-regulation of the bile acid pathway.

Conclusion: We applied an intelligent pattern recognition method for analyzing the regulation of metabolism and elucidated substantial regulation of human breast cancer at the interplay of cholesterol biosynthesis and bile acid metabolism pointing to specific breast cancer treatment.

Figure 1

The workflow. Samples were divided into patients with favorable and unfavorable prognosis according to their time of recurrence (time period of relapse after the first event of breast cancer, denoted in years) and event of metastasis (favorable: time recurrence above 5 years, unfavorable: time recurrence of less than three years and the occurrence of metastasis). Expression data were mapped onto the reactions from KEGG and analyzed. Pathways with significant expression patterns were ranked according to the significance of the patterns and compared with the literature.

Figure 2

Compiling the features. A. We sketch the method with a simple example pathway consisting of six reactions R1-R6 and six metabolites M1-M6. B. To apply the pattern analysis method (wavelet transforms), the pathway needed to be represented on a two dimensional lattice grid. Reactions were optimally arranged to preserve next nearest neighborhoods while minimizing the distances of neighboring reactions. Metabolites didn't need to be displayed in this representation but rather used to determine the neighborhoods (e.g. R1 is a neighbor of R2 because it produces M1 which is needed as a substrate for R2 or vice versa). C. Gene expression data was mapped onto the corresponding enzymatic reactions. In this example genes of enzymes for reactions R1, R4, R5 were high expressed and of enzymes for reactions R2 and R6 low expressed. D. Combined gene expression features were assembled by Haar wavelet transforms which basically calculated additive and subtractive combinations of 2 × 2 pixels of the grid (pixels without reactions were filled with zeros). The figure shows all four possible arrangements of 2 × 2 pixels for which the wavelet transforms were calculated. The same procedure was done for all tumor samples. The feature which best separated the tumor entities (favorable from unfavorable) was selected for the significance of this pathway.

Figure 3

Regulation of the pathway for bile acid biosynthesis of both analyzed datasets. Red frame indicates up-regulation in at least one dataset, green frame down-regulation in at least one dataset, yellow frame up-regulation in the two respective datasets, and grey frame down-regulation in the two datasets, respectively, and grey frame no differential regulation in both datasets. The map was taken from KEGG [11]. The lower part of this pathway was mainly down-regulated to prevent degradation of steroids into bile acids, whereas the upper part was mainly up-regulated to support steroid metabolism.