Technical note: development of a 3D printed subresolution sandwich phantom for validation of brain SPECT analysis

Purpose: To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using clinical acquisition and reconstruction protocols. This will allow the characterization and correction of scanner characteristics, and improve the accuracy of clinical image analysis, including the application of databases of normal subjects. Methods: A fused deposition modeling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. The attenuation of the printed polylactide (PLA), measured by means of the Hounsfield unit on CT scanning, was set to match that of the brain by adjusting the proportion of plastic filament and air (fill ratio). Transmission measurements were made to verify the attenuation of the printed slabs. The radionuclide distribution within the phantom was created by adding 99mTc pertechnetate to the ink cartridge of a paper printer and printing images of gray and white matter anatomy, segmented from the same MRI data. The complete subresolution sandwich phantom was assembled from alternate 3D printed slabs and radioactive paper sheets, and then imaged on a dual headed gamma camera to simulate an HMPAO SPECT scan. Results: Reconstructions of phantom scans successfully used automated ellipse fitting to apply attenuation correction. This removed the variability inherent in manual application of attenuation correction and registration inherent in existing cylindrical phantom designs. The resulting images were assessed visually and by count profiles and found to be similar to those from an existing elliptical PMMA phantom. Conclusions: The authors have demonstrated the ability to create physically realistic HMPAO SPECT simulations using a novel head-shaped 3D printed subresolution sandwich method phantom. The phantom can be used to validate all neurological SPECT imaging applications. A simple modification of the phantom design to use thinner slabs would make it suitable for use in PET

Semiautomated isolation and molecular characterisation of single or highly purified tumour cells from CellSearch enriched blood samples using dielectrophoretic cell sorting

Background: Molecular characterisation of single circulating tumour cells (CTCs) holds considerable promise for predictive biomarker assessment and to explore CTC heterogeneity. We evaluate a new method, the DEPArray system, that allows the dielectrophoretic manipulation and isolation of single and 100% purified groups of CTCs from pre-enriched blood samples and explore the feasibility of their molecular characterisation.Methods:Samples containing known numbers of two cell populations were used to assess cell loss during sample loading. Cultured breast cancer cells were isolated from spiked blood samples using CellSearch CTC and Profile kits. Single tumour cells and groups of up to 10 tumour cells were recovered with the DEPArray system and subjected to transcriptional and mutation analysis.Results:On average, 40% cell loss was observed when loading samples to the DEPArray system. Expected mutations in clinically relevant markers could be obtained for 60% of single recovered tumour cells and all groups of tumour cells. Reliable gene expression profiles were obtained from single cells and groups of up to 10 cells for 2 out of 3 spiked breast cancer cell lines.Conclusion:We describe a semiautomated workflow for the isolation of small groups of 1 to 10 tumour cells from whole blood samples and provide proof of principle for the feasibility of their comprehensive molecular characterisation

The X-ray diffraction structure of a glycosyl hydrolase family 32 protein: 1-fructan exohydrolase IIa of<i>Cichorium intybus</i>

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Array-Based DNA Methylation Profiling for Breast Cancer Subtype Discrimination

BACKGROUND: Abnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics. METHODOLOGY/PRINCIPAL FINDINGS: We performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes. CONCLUSIONS/SIGNIFICANCE: A subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC

NF-κB activation in inflammatory breast cancer is associated with oestrogen receptor downregulation, secondary to EGFR and/or ErbB2 overexpression and MAPK hyperactivation

Activation of NF-κB in inflammatory breast cancer (IBC) is associated with loss of estrogen receptor (ER) expression, indicating a potential crosstalk between NF-κB and ER. In this study, we examined the activation of NF-κB in IBC and non-IBC with respect to ER and EGFR and/or ErbB2 expression and MAPK hyperactivation. A qRT–PCR based ER signature was evaluated in tumours with and without transcriptionally active NF-κB, as well as correlated with the expression of eight NF-κB target genes. Using a combined ER/NF-κB signature, hierarchical clustering was executed. Hyperactivation of MAPK was investigated using a recently described MAPK signature (Creighton et al, 2006), and was linked to tumour phenotype, ER and EGFR and/or ErbB2 overexpression. The expression of most ER-modulated genes was significantly elevated in breast tumours without transcriptionally active NF-κB. In addition, the expression of most ER-modulated genes was significantly anticorrelated with the expression of most NF-κB target genes, indicating an inverse correlation between ER and NF-κB activation. Clustering using the combined ER and NF-κB signature revealed one cluster mainly characterised by low NF-κB target gene expression and a second one with elevated NF-κB target gene expression. The first cluster was mainly characterised by non-IBC specimens and IHC ER+ breast tumours (13 out of 18 and 15 out of 18 respectively), whereas the second cluster was mainly characterised by IBC specimens and IHC ER− breast tumours (12 out of 19 and 15 out of 19 respectively) (Pearson χ2, P<0.0001 and P<0.0001 respectively). Hyperactivation of MAPK was associated with both ER status and tumour phenotype by unsupervised hierarchical clustering using the MAPK signature and was significantly reflected by overexpression of EGFR and/or ErbB2. NF-κB activation is linked to loss of ER expression and activation in IBC and in breast cancer in general. The inverse correlation between NF-κB activation and ER activation is due to EGFR and/or ErbB2 overexpression, resulting in NF-κB activation and ER downregulation