Transcriptome analysis of colon cancer progression

The following tutorial walks through a comparison of gene expression in a primary tumor colon cell line to that in a metastatic colon cancer cell line. Genes involved in distinct biological processes, including cell cycle and telomere maintenance, are differentially regulated in the progression from primary tumor growth to metastasis.

Before you begin, we recommend that you review the analysis summary. The top button of the four on the right will download it if you haven't already.

When you are ready to begin this hands-on tutorial, click the third button down on the right, labeled "Log in to the dataset with tutorial."

1. Select Pairwise in the menu bar on the left side of the screen labeled Control Panel. You will see “Pairwise” under the heading marked “Analysis.”

2. Select the magnifying glass icon next to “U133A” in the list. There are approximately 20,000 transcripts represented on this array.

3. At the top of the page is a list of the different experiment groups contained in this analysis. We’ll be comparing expression between the primary and metastic cell lines, both untreated. Select the three replicates for the primary cell line to place them in Group 1.

4. Select the three replicates for the metastatic line for Group 2.

5. Pairwise analysis combines a fold-change cutoff with a quality filter and comparison statistics to generate a list of differentially expressed genes. Select the following settings:

Normalization: All Median
Normalizes each array to its median intensity.

Statistics: t-test
Performs a two-sample, unpaired t-test for each gene that passes the quality and fold-change cutoffs.

Quality: P
Filters out genes that received absent or marginal detection calls in both groups.

Threshold: Lower = 1.5; Upper = None.
Filters out genes with less than a 1.5 fold change in expression.

Correction: Benjamini and Hochberg
Calculates a false discovery rate from the raw p-values using the method of Benjamini and Hochberg.

Data transformation: Log Transform Data
This setting log base2 transforms the signal values.

6. Select the Analyze button.

7. After the analysis is performed a gene list will be returned. This list contains the genes that are differentially expressed based on the pairwise analysis setting selected. 1863 genes passed the filtering criteria – a 1.5 fold or greater change in expression, present calls in at least one of the groups and a raw p-value of at least 0.05 from the t-test. The genes are sorted by fold change and the first 20 genes in the list are displayed.

8. To filter the list using the adjusted p-value (false discovery rate), select “adjusted p” from the pull-down menu and then click the Search button.

9.The list filtered on the adjusted p value contains 1534 genes with a false discovery rate less than 5%.

10. To view data and a gene summary for any gene in the list, click the Gene Name.

10. This will bring up a data summary and a One-Click Gene Summary™ (OCGS) for the gene. The One-Click Gene Summary provides a synopsis of current UniGene and Entrez Gene (formerly known as LocusLink) information for the gene.

11. Go back to the gene list by clicking the “Back” button in your browser.

12. Select the Ontology link at the top of the screen to view a summary of the Gene Ontology terms associated with the genes in the list. See the online help system for information about the other reports.

Note: To the view page-specific online help documents for any page, select the question mark icon located in the upper right corner of each page.

13. The Ontology Report lists the Gene Ontology terms associated with the 1534 genes in the pairwise results gene list. See the help documents for this page for more information about the Ontology Report.

14. Click on Z-score report in the upper right corner of the Ontology Report window.

15. The z-score report lists the biological process ontologies that are significantly over or under-represented in the gene list (z-score greater than 2 or less than -2, respectively). Select the red arrow in the z-score column (on the right of the screen) to sort the list by z-score for the up-regulated genes.

16. The z-score report shows that there is a significant enrichment of genes involved several biological processes, including cell cycle, RNA processing and telomere maintenance. Near the middle of the list is the “telomerase-dependent telomere maintenance” ontology which is significantly over-represented in the upregulated gene list. Select the icon in the Genes column to view a list of the genes with this ontology.

Z-score reports can be generated for the Molecular Function and Cellular Component ontologies as well.

Only a few specific aspects of the data set have been explored here. Feel free to examine the data further on your own.