Journal:

Article Title: Malignancy-Associated Regions of Transcriptional Activation: Gene Expression Profiling Identifies Common Chromosomal Regions of a Recurrent Transcriptional Activation in Human Prostate, Breast, Ovarian, and Colon Cancers 1

doi:

Figure Lengend Snippet: RT-PCR confirmation analysis of the upregulation of two genes representing Xq28 transcription activation cluster in human prostate carcinoma cell lines [MAGEA12 (top panel) and MAGEA3 transcripts (bottom panel)]. Standard RT-PCR protocol was used to amplify fragments of corresponding genes from mRNA of the normal human prostate epithelial cells (PrEc) and highly metastatic PC3MLN4 and LNCaPLN3 human prostate carcinoma cell lines. To control PCR amplification efficiency and loading, the experiments were carried out using coamplification in the same tube with each experimental gene of a fragment of control gene (SYBL1) that was selected to have a similar chromosomal location but distinct amplification product size and regulation pattern. In the control experiments (C), PCR amplification was carried out only for corresponding control genes. H2O—negative control of PCR amplification; M—molecular weight markers.

Article Snippet: Two primary human prostate epithelial and one primary human prostate stromal cell line were obtained from Clonetics/BioWhittaker (San Diego, CA ) and grown in complete prostate epithelial and stromal growth medium provided by the supplier.

Techniques: Reverse Transcription Polymerase Chain Reaction, Activation Assay, Control, Amplification, Negative Control, Molecular Weight

Journal:

Article Title: Malignancy-Associated Regions of Transcriptional Activation: Gene Expression Profiling Identifies Common Chromosomal Regions of a Recurrent Transcriptional Activation in Human Prostate, Breast, Ovarian, and Colon Cancers 1

doi:

Figure Lengend Snippet: Profiles of the chromosomal distribution of human breast cancer-associated transcripts (a), dsRNA-induced genes (b), and cell cycle-activated genes (c) residing on chromosome 17. A total of 132 estrogen receptor-negative breast cancer-associated transcripts was obtained from Ref. [5] by combining the lists of genes comprising basal epithelial cell clusters 1 and 2, Erb-B2 overexpression cluster, and a proliferative cluster. A total of 144 ovarian cancer-associated transcripts was derived from Ref. [6] as a sum of the top 100 biomarker genes, proliferative and tumor clusters. The redundant entries were eliminated from the final gene lists. A total of 165 prostate cancer-associated transcripts was identified by comparing gene expression profiles of two human prostate carcinoma cell lines (PC3MLN4 and LNCaPLN3) to the gene expression pattern of cultured normal human prostate epithelial cells using the Affymetrix GeneChip system. A concordant set of 165 genes upregulated in cancer cell lines was generated utilizing the Affymetrix software for pairwise comparisons of duplicate cancer mRNA samples from each cell line versus a triplicate normal mRNA samples derived from two different normal prostate epithelial cell lines. Thus, each differentially expressed gene was required to be called in the same direction in 12 pairwise comparisons. The list of 378 genes comprising the human cell cycle transcriptome was obtained from Ref. [19]. The list of the dsRNA-induced genes was derived from Ref. [20]. RH mapping data were retrieved using the LocusLink database and utilized to generate the chromosome-specific map of gene distribution. One unit value on the Y-axis corresponds to a single gene with a placement resolution of 1 Mb along the length of the chromosome. The complete lists of genes and RH mapping data are presented in the supplement (Tables 1S-8S).

Article Snippet: Two primary human prostate epithelial and one primary human prostate stromal cell line were obtained from Clonetics/BioWhittaker (San Diego, CA ) and grown in complete prostate epithelial and stromal growth medium provided by the supplier.

Techniques: Over Expression, Derivative Assay, Biomarker Discovery, Gene Expression, Cell Culture, Generated, Software