62 research outputs found

    Merging transcriptomics and metabolomics - advances in breast cancer profiling

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    Background Combining gene expression microarrays and high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) of the same tissue samples enables comparison of the transcriptional and metabolic profiles of breast cancer. The aim of this study was to explore the potential of combining these two different types of information. Methods Breast cancer tissue from 46 patients was analyzed by HR MAS MRS followed by gene expression microarrays. Two strategies were used to combine the gene expression and metabolic data; first using multivariate analyses to identify different groups based on gene expression and metabolic data; second correlating levels of specific metabolites to transcripts to suggest new hypotheses of connections between metabolite levels and the underlying biological processes. A parallel study was designed to address experimental issues of combining microarrays and HR MAS MRS. Results In the first strategy, using the microarray data and previously reported molecular classification methods, the majority of samples were classified as luminal A. Three subgroups of luminal A tumors were identified based on hierarchical clustering of the HR MAS MR spectra. The samples in one of the subgroups, designated A2, showed significantly lower glucose and higher alanine levels than the other luminal A samples, suggesting a higher glycolytic activity in these tumors. This group was also enriched for genes annotated with Gene Ontology (GO) terms related to cell cycle and DNA repair. In the second strategy, the correlations between concentrations of myo-inositol, glycine, taurine, glycerophosphocholine, phosphocholine, choline and creatine and all transcripts in the filtered microarray data were investigated. GO-terms related to the extracellular matrix were enriched among the genes that correlated the most to myo-inositol and taurine, while cell cycle related GO-terms were enriched for the genes that correlated the most to choline. Additionally, a subset of transcripts was identified to have slightly altered expression after HR MAS MRS and was therefore removed from all other analyses. Conclusions Combining transcriptional and metabolic data from the same breast carcinoma sample is feasible and may contribute to a more refined subclassification of breast cancers as well as reveal relations between metabolic and transcriptional levels. See Commentary: http://www.biomedcentral.com/1741-7015/8/7

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

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    <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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).</p> <p>The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses.</p> <p>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.</p> <p>Results</p> <p>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 (<it>CHKA</it>, <it>CHKB</it>) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (<it>PLA2G4A</it>) and phospholipase B1 (<it>PLB1</it>) 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.</p> <p>Conclusions</p> <p>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.</p

    The added value of quantitative multi-voxel MR spectroscopy in breast magnetic resonance imaging

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    To determine whether quantitative multivoxel MRS improves the accuracy of MRI in the assessment of breast lesions. Twenty-five consecutive patients with 26 breast lesions a parts per thousand yen1 cm assessed as BI-RADS 3 or 4 with mammography underwent quantitative multivoxel MRS and contrast-enhanced MRI. The choline (Cho) concentration was calculated using the unsuppressed water signal as a concentration reference. ROC analysis established the diagnostic accuracy of MRI and MRS in the assessment of breast lesions. Respective Cho concentrations in 26 breast lesions re-classified by MRI as BI-RADS 2 (n = 5), 3 (n = 8), 4 (n = 5) and 5 (n = 8) were 1.16 +/- 0.43 (mean +/- SD), 1.43 +/- 0.47, 2.98 +/- 2.15 and 4.94 +/- 3.10 mM. Two BI-RADS 3 lesions and all BI-RADS 4 and 5 lesions were malignant on histopathology and had Cho concentrations between 1.7 and 11.8 mM (4.03 +/- 2.72 SD), which were significantly higher (P = 0.01) than that in the 11 benign lesions (0.4-1.5 mM; 1.19 +/- 0.33 SD). Furthermore, Cho concentrations in the benign and malignant breast lesions in BI-RADS 3 category differed (P = 0.01). The accuracy of combined multivoxel MRS/breast MRI BI-RADS re-classification (AUC = 1.00) exceeded that of MRI alone (AUC = 0.96 +/- 0.03). These preliminary data indicate that multivoxel MRS improves the accuracy of MRI when using a Cho concentration cut-off a parts per thousand currency sign1.5 mM for benign lesions. Key Points aEuro cent Quantitative multivoxel MR spectroscopy can improve the accuracy of contrast-enhanced breast MRI. aEuro cent Multivoxel-MRS can differentiate breast lesions by using the highest Cho-concentration. aEuro cent Multivoxel-MRS can exclude patients with benign breast lesions from further invasive diagnostic procedures

    Early Transcriptional Divergence Marks Virus-Specific Primary Human CD8+ T Cells in Chronic versus Acute Infection.

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    Distinct molecular pathways govern the differentiation of CD8+ effector T cells into memory or exhausted T cells during acute and chronic viral infection, but these are not well studied in humans. Here, we employed an integrative systems immunology approach to identify transcriptional commonalities and differences between virus-specific CD8+ T cells from patients with persistent and spontaneously resolving hepatitis C virus (HCV) infection during the acute phase. We observed dysregulation of metabolic processes during early persistent infection that was linked to changes in expression of genes related to nucleosomal regulation of transcription, T cell differentiation, and the inflammatory response and correlated with subject age, sex, and the presence of HCV-specific CD4+ T cell populations. These early changes in HCV-specific CD8+ T cell transcription preceded the overt establishment of T cell exhaustion, making this signature a prime target in the search for the regulatory origins of T cell dysfunction in chronic viral infection

    Map depicting sampling sites (black dots) within the historical range of regent honeyeaters.

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    <p>Gray dots indicate 2227 geographic sites for 4542 observational records of regent honeyeaters, data taken from Atlas of Living Australia [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143746#pone.0143746.ref040" target="_blank">40</a>].</p

    Mean r-values for birds at each site.

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    <p>Wild-bred founders of the captive population and captive-bred birds released into the wild were included in calculations as members of both Taronga Zoo and the wild site at which they were (re)captured. An asterisk (*) indicates an r-value is significantly (p < 0.05) different from zero.</p

    R-value distributions of regent honeyeaters of known pedigree at Taronga Zoo for a) parents and offspring (mean R-value 0.3367); b) full-sibs (mean R-value 0.3498); c) half-sibs (mean R-value 0.0578); and d) unrelated birds (mean R-value -0.0369).

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    <p>R-value distributions of regent honeyeaters of known pedigree at Taronga Zoo for a) parents and offspring (mean R-value 0.3367); b) full-sibs (mean R-value 0.3498); c) half-sibs (mean R-value 0.0578); and d) unrelated birds (mean R-value -0.0369).</p

    Geographic locations of sampling sites, sample sizes for each individual location, and pooled sample sizes.

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    <p>The birds at Sutton were pooled with those from Canberra, birds from Indigo Valley and Lurg were pooled with those from Chiltern, and birds captured at Cumbo Rd, Goulburn River, and Munghorn Gap were pooled together under the name Goulburn River for analyses.</p
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