Gene Expression Custom Arrays
Gene Expression Custom Arrays
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Note: This is a review of the published article listed below. All information, quotes, figures, methods, and findings mentioned in this review are from that article, and are the property of its authors and/or the publication in which the article originally appeared.
Take control of your gene expression experimental design and cost by selecting from multiple array formats, pre-designed and validated probe sequences, and probe sequence design tools. You can use your own uploaded sequences for probe design or choose from our extensive database of probes featuring a wide range of organisms and source databases that have been optimized for premium sensitivity and specificity. Customize using genome-wide or zoom-in designs, multiple format options, and kit quantities for unparalleled resolution, flexibility, and convenience.
Microarray technology has enabled scientists to investigate changes in transcription on a global scale, providing new and exciting insights into the world of genes and genetic regulation. Custom options provide researchers with the ability to hone in on specific processes of interest, gleaning information on plants and animals in a whole new light. Robert Stull and colleagues (2005) used Agilent’s gene expression microarray for a customized expression analysis of secreted and cell surface genes in five transformed human cell lines and derivative xenograft tumors. Using the custom designed arrays, the group was able to demonstrate that xenograft models using multiple cell lines of diverse tissue origins can be used to identify common tumorigenic cell surface or secreted molecules that may be important biomarker and therapeutic discoveries. By identifying genes known to participate in angiogenesis and tumorigenesis, this work helps establish a baseline to evaluate and compare the full spectrum of gene profile changes in xenografts and clinical specimens.
Figure 1. Principal components analysis of array data.
The mean expression values of all samples from all arrays were analyzed by principal components analysis. The first 3 principal components of the analysis are shown from the best vantage point to show separation of the three classes. Open circles represent the parental cell lines, "X" denotes the various xenograft tumors, and the small solid dots are the reference cDNA sample (derived from the Universal RNA) co-hybridized with all experimental samples. The cell lines corresponding to the various tissue sources of the parental cell lines were: Ovary, SKOV3; Prostate, PC3; Breast, MDA MB-231; Colon, HCT116; and Lung, A549.
Figure 2. Comparison of differential expression of genes in parental cells versus reference cDNA synthesized from universal RNA (left) and all tumors versus parental cell lines (right).
Genes differentially expressed in the parental cells relative to the reference cDNA were analyzed by a 2-way ANOVA (Pcorr < .001). A subset of the differentially expressed genes is shown. The corresponding cognate tumors with differential expression at a 99.9% confidence level by ANOVA analysis of tumors vs. parental cell line data are shown. The heat maps indicate relative fold-induction or suppression in a linear color-encoded scale shown at the bottom. Mean ratios are indicated by X, C = colon, B = breast, L = lung, P = prostate, O = ovary.
Original Research Paper:
Title: Expression analysis of secreted and cell surface genes of five transformed human cell lines and derivative xenograft tumors.
Authors: Stull RA, Tavassoli R, Kennedy S, Osborn S, Harte R, Lu Y, Napier C, Abo A, Chin DJ.
Journal: BMC Genomics. 2005; 6:55.
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