Cancer applications using TRAC

Gene expression analysis of human gastric cancer samples

TRAC has been successfully used in numerous studies to analyse gene expression in cancer samples. In one such study carried out at the University of Helsinki in Finland, TRAC was used to investigate gene expression in human gastric cancer tissue samples and cell lines (published in BMC Genetics in 2010 by Junnila et al).

Gastric cancer is one of the most common cancers in the world, causing many deaths. In this malignancy, gene copy number changes often influence the expression of potential oncogenes and tumor suppressor genes, triggering the development of the disease.

To highlight genes of potential relevance, Junnila and colleagues first screened for interesting copy number variations (CNVs) using array comparative genomic hybridization (aCGH), as well as gene expression differences by employing expression microarrays.  The gene expression results were then validated using the FAST TRAC Service.

Results and Conclusions

The researchers identified 256 interesting copy number variations using microarrays, of which 13 genes were differentially expressed in cancerous samples and nonmalignant tissues. The expression of these genes was successfully validated in a cohort of 118 samples using RT-qPCR and TRAC. For nine of these genes, a link between CNV and gene expression was confirmed. A subset of these genes is shown below (see the paper for the full data set and analysis).


TRAC was successfully used in this study to validate 11 of the 13 differentially expressed genes. According to the authors, “the advantage of the TRAC assay was that the expression levels of multiple genes can be measured simultaneously from a single sample thus lowering the amount of sample RNA required for the analysis. This is especially important for the analysis of often scarce clinical tissue samples.”

From their analysis, the researchers were able to link specific CNVs to changes in gene expression. In the future these genes could act as potential biomarkers for gastric cancer, aiding diagnosis and further research into the disease. This is especially relevant given that gastric adenocarcinoma is currently characterized by late stage diagnosis and due to a lack of early detectable physical symptoms. Full details of this interesting project can be found by reading the full text at the BMC Genomics website.