33
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Distinct choline metabolic profiles are associated with differences in gene expression for basal-like and luminal-like breast cancer xenograft models

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood.

          Methods

          The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS).

          The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses.

          The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer.

          Results

          In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase ( CHKA, CHKB) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A ( PLA2G4A) and phospholipase B1 ( PLB1) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer.

          Conclusions

          The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: not found

          Modelling breast cancer: one size does not fit all.

          Breast cancer is not a single disease, but is instead a collection of diseases that have distinct histopathological features, genetic and genomic variability, and diverse prognostic outcomes. Thus, no individual model would be expected to completely recapitulate this complex disease. Here, the models commonly used to investigate breast cancer including cell lines, xenografts and genetically engineered mice, are discussed to help address the question: what is the most powerful way to investigate this heterogeneous disease?
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells.

            Transduction of mitogenic signals in cells can be mediated by molecules derived from the synthesis and breakdown of the major membrane phospholipid, phosphotidylcholine. Studies were performed on human mammary epithelial cells in culture to understand the impact of malignant transformation and progression on membrane phospholipid metabolism. In the model system used here, phosphocholine levels and total choline-containing phospholipid metabolite levels increased with progression from normal to immortalized to oncogene-transformed to tumor-derived cells. These changes occurred independently of cell doubling time. A "glycerophosphocholine to phosphocholine switch" was apparent with immortalization. This alteration in phenotype of increased phosphocholine relative to glycerophosphocholine was observed in oncogene-transformed and for all human breast tumor cell lines analyzed. The results demonstrate that progression of human mammary epithelial cells from normal to malignant phenotype is associated with altered membrane choline phospholipid metabolism.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms

              Background Gene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms. Results Expression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilent's Whole Human Genome Oligo Microarrays, and the resulting gene expression patterns were analyzed. Both unsupervised and supervised analyses identified the different clinically relevant subtypes of breast tumours, and the results were consistent across all three platforms. Gene classification and biological pathway analyses of the genes differentially expressed between the two main subtypes revealed different molecular mechanisms descriptive of the two expression-based subtypes: Signature genes of the luminal A subtype were over-represented by genes involved in fatty acid metabolism and steroid hormone-mediated signaling pathways, in particular estrogen receptor signaling, while signature genes of the basal-like subtype were over-represented by genes involved in cell proliferation and differentiation, p21-mediated pathway, and G1-S checkpoint of cell cycle-signaling pathways. A minimal set of 54 genes that best discriminated the two subtypes was identified using the combined data sets generated from the three different array platforms. These predictor genes were further verified by TaqMan® Gene Expression assays. Conclusion We have identified and validated the two main previously defined clinically relevant subtypes, luminal A and basal-like, in a small set of early stage breast carcinomas. Signature genes characterizing these two subtypes revealed that distinct molecular mechanisms might have been pre-programmed at an early stage in different subtypes of the disease. Our results provide further evidence that these breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies. Finally, validated by multiple gene expression platforms, including quantitative PCR, the set of 54 predictor genes identified in this study may define potential prognostic molecular markers for breast cancer.
                Bookmark

                Author and article information

                Journal
                BMC Cancer
                BMC Cancer
                BioMed Central
                1471-2407
                2010
                17 August 2010
                : 10
                : 433
                Affiliations
                [1 ]Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
                [2 ]Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
                [3 ]Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
                [4 ]Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
                Article
                1471-2407-10-433
                10.1186/1471-2407-10-433
                2931488
                20716336
                800f54a2-e8ef-4357-947a-2eb340d616e6
                Copyright ©2010 Moestue et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 April 2010
                : 17 August 2010
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

                Comments

                Comment on this article