MEK1/2 (Phospho-Ser221) ELISA Kit

Context: Hurthle cell cancer (HCC) is an understudied cancer with poor prognosis. Objective: Our objective was to elucidate the genomic foundations of HCC. Design and Setting: We conducted a large-scale integrated analysis of mutations, gene expression profiles, and copy number alterations in HCC at a single tertiary-care cancer institution. Methods: Mass spectrometry-based genotyping was used to interrogate hot spot point mutations in the most common thyroid oncogenes: BRAF, RET, NRAS, HRAS, KRAS, PIK3CA, MAP2K1, and AKT1. In addition, common oncogenic fusions of RET and NTRK1 as well as PAX8/PPAR gamma and AKAP9-BRAF were also assessed by RT-PCR. Global copy number changes and gene expression profiles were determined in the same tumor set as the mutational analyses. Results: We report that the mutational, transcriptional, and copy number profiles of HCC were distinct from those of papillary thyroid cancer and follicular thyroid cancer, indicating HCC to be a unique type of thyroid malignancy. Unsupervised hierarchical clustering of gene expression showed the 3 groups of Hurthle tumors (Hurthle cell adenoma [HA], minimally invasive Hurthle cell carcinoma [HMIN], and widely invasive Hurthle cell carcinoma [HWIDE] clustered separately with a marked difference between HWIDE and HA. Global copy number analysis also indicated distinct subgroups of tumors that may arise as HWIDE and HMIN. Molecular pathways that differentiate HA from HWIDE included the PIK3CA-Akt-mTOR and Wnt/beta-catenin pathways, potentially providing a rationale for new targets for this type of malignancy. Conclusions: Our data provide evidence that HCC may be a unique thyroid cancer distinct from papillary and follicular thyroid cancer.

Background: Members of the ErbB family of growth factor receptors are intricately linked with epithelial cell biology, development and tumourigenesis; however, the mechanisms involved in their downstream signalling are poorly understood. Indeed, it is unclear how signal specificity is achieved and the relative contribution each receptor has to specific gene expression. Methods: Gene expression profiling of a human mammary luminal epithelial cell model of ErbB2-overexpression was carried out using cDNA microarrays with a common RNA reference approach to examine long-term overlapping and differential responses to EGF and heregulin beta1 treatment in the context of ErbB2 overexpression. Altered gene expression was validated using quantitative real time PCR and/or immunoblotting. One gene of interest was targeted for further characterisation, where the effects of siRNA-mediated silencing on IGF1-dependent signalling and cellular phenotype were examined and compared to the effects of loss of ErbB2 expression. Results: 775 genes were differentially expressed and clustered in terms of their growth factor responsiveness. As well as identifying uncharacterized genes as novel targets of ErbB2-dependent signalling, ErbB2 overexpression augmented the induction of multiple genes involved in proliferation (e. g. MYC, MAP2K1, MAP2K3), autocrine growth factor signalling (VEGF, PDGF) and adhesion/cytoskeletal regulation (ZYX, THBS1, VCL, CNN3, ITGA2, ITGA3, NEDD9, TAGLN), linking them to the hyper-poliferative and altered adhesive phenotype of the ErbB2-overexpressing cells. We also report ErbB2-dependent down-regulation of multiple interferon-stimulated genes that may permit ErbB2-overexpressing cells to resist the anti-proliferative action of interferons. Finally, IGFBP3 was unique in its pattern of regulation and we further investigated a possible role for IGFBP3 down-regulation in ErbB2-dependent transformation through suppressed IGF1 signalling. We show that IGF1-dependent signalling and proliferation were enhanced in ErbB2-overexpressing cells, whilst loss of ErbB2 expression by siRNA silencing reduced IGF1 signalling. Furthermore, IGFBP3 knockdown resulted in basal ERK and Akt activation in luminal epithelial cells and increased invasiveness and anchorage-independent colony formation in SKBR3 cells. Conclusions: These data show IGFBP3 as a negative regulator of transformation and that its down-regulation enhances IGF1-dependent signalling. They also show that ErbB2 can up-regulate IGF1-dependent signalling, possibly via the regulated expression of IGFBP3.