CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer.

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance.

Low pH induces co-ordinate regulation of gene expression in oesophageal cells.

The development of gastro-oesophageal reflux disease (GORD) is known to be a causative risk factor in the evolution of adenocarcinoma of the oesophagus. The major component of this reflux is gastric acid. However, the impact of low pH on gene expression has not been extensively studied in oesophageal cells. This study utilizes a transcriptomic and bioinformatic approach to assess regulation of gene expression in response to low pH. In more detail, oesophageal adenocarcinoma cell lines were exposed to a range of pH environments. Affymetrix microarrays were used for gene-expression analysis and results were validated using cycle limitation and real-time RT-PCR analysis, as well as northern and western blotting. Comparative promoter transcription factor binding site (TFBS) analysis (MatInspector) of hierarchically clustered gene-expression data was employed to identify the elements which may co-ordinately regulate individual gene clusters. Initial experiments demonstrated maximal induction of EGR1 gene expression at pH 6.5. Subsequent array experimentation revealed significant induction of gene expression from such functional categories as DNA damage response (EGR1-4, ATF3) and cell-cycle control (GADD34, GADD45, p57). Changes in expression of EGR1, EGR3, ATF3, MKP-1, FOSB, CTGF and CYR61 were verified in separate experiments and in a variety of oesophageal cell lines. TFBS analysis of promoters identified transcription factors that may co-ordinately regulate gene-expression clusters, Cluster 1: Oct-1, AP4R; Cluster 2: NF-kB, EGRF; Cluster 3: IKRS, AP-1F. Low pH has the ability to induce genes and pathways which can provide an environment suitable for the progression of malignancy. Further functional analysis of the genes and clusters identified in this low pH study is likely to lead to new insights into the pathogenesis and therapeutics of GORD and oesophageal cancer.

Multiple markers for melanoma progression regulated by DNA methylation: insights from transcriptomic studies.

The incidence of melanoma is increasing rapidly, with advanced lesions generally failing to respond to conventional chemotherapy. Here, we utilized DNA microarray-based gene expression profiling techniques to identify molecular determinants of melanoma progression within a unique panel of isogenic human melanoma cell lines. When a poorly tumorigenic cell line, derived from an early melanoma, was compared with two increasingly aggressive derivative cell lines, the expression of 66 genes was significantly changed. A similar pattern of differential gene expression was found with an independently derived metastatic cell line. We further examined these melanoma progression-associated genes via use of a tailored TaqMan Low Density Array (LDA), representing the majority of genes within our cohort of interest. Considerable concordance was seen between the transcriptomic profiles determined by DNA microarray and TaqMan LDA approaches. A range of novel markers were identified that correlated here with melanoma progression. Most notable was TSPY, a Y chromosome-specific gene that displayed extensive down-regulation in expression between the parental and derivative cell lines. Examination of a putative CpG island within the TSPY gene demonstrated that this region was hypermethylated in the derivative cell lines, as well as metastatic melanomas from male patients. Moreover, treatment of the derivative cell lines with the DNA methyltransferase inhibitor, 2'-deoxy-5-azacytidine (DAC), restored expression of the TSPY gene to levels comparable with that found in the parental cells. Additional DNA microarray studies uncovered a subset of 13 genes from the above-mentioned 66 gene cohort that displayed re-activation of expression following DAC treatment, including TSPY, CYBA and MT2A. DAC suppressed tumor cell growth in vitro. Moreover, systemic treatment of mice with DAC attenuated growth of melanoma xenografts, with consequent re-expression of TSPY mRNA. Overall, our data support the hypothesis that multiple genes are targeted, either directly or indirectly, by DNA hypermethylation during melanoma progression.

Interaction of soft condensed materials with living cells: phenotype/transcriptome correlations for the hydrophobic effect.

The assessment of biomaterial compatibility relies heavily on the analysis of macroscopic cellular responses to material interaction. However, new technologies have become available that permit a more profound understanding of the molecular basis of cell-biomaterial interaction. Here, both conventional phenotypic and contemporary transcriptomic (DNA microarray-based) analysis techniques were combined to examine the interaction of cells with a homologous series of copolymer films that subtly vary in terms of surface hydrophobicity. More specifically, we used differing combinations of N-isopropylacrylamide, which is presently used as an adaptive cell culture substrate, and the more hydrophobic, yet structurally similar, monomer N-tert-butylacrylamide. We show here that even discrete modifications with respect to the physiochemistry of soft amorphous materials can lead to significant impacts on the phenotype of interacting cells. Furthermore, we have elucidated putative links between phenotypic responses to cell-biomaterial interaction and global gene expression profile alterations. This case study indicates that high-throughput analysis of gene expression not only can greatly refine our knowledge of cell-biomaterial interaction, but also can yield novel biomarkers for potential use in biocompatibility assessment.