Gene Expression
Identifying Important Biomarkers from Tumorigenic Cell Surfaces
A review of Expression analysis of secreted and cell surface genes of five transformed human cell lines and derivative xenograft tumors.
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.
Stull et al (2005) performed expression analysis of secreted and cell surface genes for transformed human cell lines and derivative xenograft tumors from lung (A549), breast (MDA MB-231), colon (HCT-116), ovarian (SK-OV-3) and prostate (PC3) carcinomas. In order to optimize their experimentation, the group established several criteria necessary for their microarray design: 1) allow rapid changes to the master template even for small production batches, 2) possess relative high density, 3) exhibit strong signal-to-noise properties and 4) have high reproducibility (CV < 10%). Based upon these requirements, the group chose Agilent’s custom oligonucleotide microarray in conjunction with the curated collection of secreted and cell surface proteins with human-specific 60-mer probes derived from the 3' 1500 nt region of each mRNA sequence. Results of this work can be used in combination or as a filter with other biomarker technologies such as tissue arrays or mass spectroscopy to fully characterize clinical specimens for diagnostic or prognostic purposes. By identifying genes known to participate in angiogenesis and tumorigenesis, this work establishes a baseline to evaluate and compare the full spectrum of gene profile changes in xenografts and clinical specimens for identifying biomarkers and new therapeutic strategies.
Figure 1. Gene ontology of custom chip probes.
The ontological classification of 3531 cell surface or secreted genes was extracted from the Gene Ontology at the third level. Genes lacking GO annotations at this level were derived from level 2.
Figure 2. Genes identified by linear discriminant analysis.
The top 70 PCA coefficients along the third principal component were selected.
Panel A: Plot of linear discriminant profile of 70 probes that distinguish xenograft tumors from parental cell lines. Positive values in orange indicate "Xenograft tumor" while negative values in blue indicate "Parental Cell line". The y-axis shows either numbered tumor (left) or parental cell (right) samples and the x-axis is an arbitrarily scaled output reflecting the accuracy in assigning a sample as a xenograft tumor or parental cell line. The numbered tumors were grouped according to tissue type as indicated by C for colon (HCT116), B for breast (MDA MB-231), L for lung (A549), P for prostate (PC3) and O for ovary (SKOV-3). Panel B: Graphical representation of the LD-p54 genes expression profiles. For genes with multiple probes, the highest value is shown. Classified by a non-redundant filtering of the Gene Ontology biological process terms, the genes are shown with a color scale representing relative fold induction to all parental cell line data. The left-most color column designated by 'X' is the average ratio, while the remaining five columns correspond to Colon (HCT116), Breast (MDA MB-231), Lung (A549), Prostate (PC3) and Ovarian (SKOV-3) carcinoma xenografts respectively.
Title: Expression analysis of secreted and cell surface genes of five transformed human cell lines and derivative xenograft tumors.
Journal: BMC Genomics. 2005; 6: 55.
Authors: Stull RA, Tavassoli R, Kennedy S, Osborn S, Harte R, Lu Y, Napier C, Abo A, Chin DJ.
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