Control of Centrin Stability by Aurora A

Aurora A is an oncogenic serine/threonine kinase which can cause cell transformation and centrosome amplification when over-expressed. Human breast tumors show excess Aurora A and phospho-centrin in amplified centrosomes. Here, we show that Aurora A mediates the phosphorylation of and localizes with centrin at the centrosome, with both proteins reaching maximum abundance from prophase through metaphase, followed by their precipitous loss in late stages of mitosis. Over-expression of Aurora A results in excess phospho-centrin and centrosome amplification. In contrast, centrosome amplification is not seen in cells over-expressing Aurora A in the presence of a recombinant centrin mutant lacking the serine phosphorylation site at residue 170. Expression of a kinase dead Aurora A results in a decrease in mitotic index and abrogation of centrin phosphorylation. Finally, a recombinant centrin mutation that mimics centrin phosphorylation increases centrin's stability against APC/C-mediated proteasomal degradation. Taken together, these results suggest that the stability of centrin is regulated in part by Aurora A, and that excess phosphorylated centrin may promote centrosome amplification in cancer

Expression profiling of formalin-fixed paraffin-embedded primary breast tumors using cancer-specific and whole genome gene panels on the DASL® platform

<p>Abstract</p> <p>Background</p> <p>The cDNA-mediated Annealing, extension, Selection and Ligation (DASL) assay has become a suitable gene expression profiling system for degraded RNA from paraffin-embedded tissue. We examined assay characteristics and the performance of the DASL 502-gene Cancer Panel^v1(1.5K) and 24,526-gene panel (24K) platforms at differentiating nine human epidermal growth factor receptor 2- positive (HER2+) and 11 HER2-negative (HER2-) paraffin-embedded breast tumors.</p> <p>Methods</p> <p>Bland-Altman plots and Spearman correlations evaluated intra/inter-panel agreement of normalized expression values. Unequal-variance <it>t</it>-statistics tested for differences in expression levels between HER2 + and HER2 - tumors. Regulatory network analysis was performed using Metacore (GeneGo Inc., St. Joseph, MI).</p> <p>Results</p> <p>Technical replicate correlations ranged between 0.815-0.956 and 0.986-0.997 for the 1.5K and 24K panels, respectively. Inter-panel correlations of expression values for the common 498 genes across the two panels ranged between 0.485-0.573. Inter-panel correlations of expression values of 17 probes with base-pair sequence matches between the 1.5K and 24K panels ranged between 0.652-0.899. In both panels, <it>erythroblastic leukemia viral oncogene homolog 2 </it>(<it>ERBB2</it>) was the most differentially expressed gene between the HER2 + and HER2 - tumors and seven additional genes had p-values < 0.05 and log2 -fold changes > |0.5| in expression between HER2 + and HER2 - tumors: <it>topoisomerase II alpha </it>(<it>TOP2A</it>), <it>cyclin a2 </it>(<it>CCNA2</it>), <it>v-fos fbj murine osteosarcoma viral oncogene homolog </it>(<it>FOS</it>), <it>wingless-type mmtv integration site family, member 5a </it>(<it>WNT5A</it>), <it>growth factor receptor-bound protein </it><it>7 </it>(<it>GRB7</it>), <it>cell division cycle 2 </it>(<it>CDC2</it>), <it>and baculoviral iap repeat-containing protein 5 </it>(<it>BIRC5</it>). The top 52 discriminating probes from the 24K panel are enriched with genes belonging to the regulatory networks centered around <it>v-myc avian myelocytomatosis viral oncogene homolog </it>(<it>MYC</it>), <it>tumor protein p53 </it>(<it>TP53</it>), and <it>estrogen receptor α </it>(<it>ESR1</it>). Network analysis with a two-step extension also showed that the eight discriminating genes common to the 1.5K and 24K panels are functionally linked together through <it>MYC</it>, <it>TP53</it>, and <it>ESR1</it>.</p> <p>Conclusions</p> <p>The relative RNA abundance obtained from two highly differing density gene panels are correlated with eight common genes differentiating HER2 + and HER2 - breast tumors. Network analyses demonstrated biological consistency between the 1.5K and 24K gene panels.</p

Quantitative miRNA Expression Analysis Using Fluidigm Microfluidics Dynamic Arrays

MicroRNA (miRNA) is a small non-coding RNA that can regulate gene expression in both plants and animals. Studies showed that miRNAs play a critical role in human cancer by targeting messenger RNAs that are positive or negative regulators of cell proliferation and apoptosis. Here, we evaluated miRNA expression in formalin fixed, paraffin embedded (FFPE) samples and fresh frozen (FF) samples using a high throughput qPCR-based microfluidic dynamic array technology (Fluidigm). We compared the results to hybridization-based microarray platforms using the same samples. We obtained a highly correlated Ct values between multiplex and single-plex RT reactions using standard qPCR assays for miRNA expression. For the same samples, the microfluidic technology (Fluidigm 48.48 dynamic array systems) resulted in a left shift towards lower Ct values compared to those observed by standard TaqMan (ABI 7900HT, mean difference, 3.79). In addition, as little as 10ng total RNA was sufficient to reproducibly detect up to 96 miRNAs at a wide range of expression values using a single 96-multiplexing RT reaction in either FFPE or FF samples. Comparison of miRNAs expression values measured by microfluidic technology with those obtained by other array and Next Generation sequencing platforms showed positive concordance using the same samples but revealed significant differences for a large fraction of miRNA targets. The qPCRarray based microfluidic technology can be used in conjunction with multiplexed RT reactions for miRNA gene expression profiling. This approach is highly reproducible and the results correlate closely with the existing singleplex qPCR platform while achieving much higher throughput at lower sample input and reagent usage. It is a rapid, cost effective, customizable array platform for miRNA expression profiling and validation. However, comparison of miRNA expression using different platforms requires caution and the use of multiple platforms