A challenge to all cancer genomic studies is to visually explore the generated complex data in a meaningful way to extract relevant knowledge. We have written a review on that topic which has been published last week in Genome Medicine.
14-3-3σ is an adaptor protein that regulates multiple signal transduction pathways. It has been described as a tumour suppressor in breast cancer, where it is often lost or repressed. Anna Bigas and Lluís Espinosa lab, from IMIM, had reported before that 14-3-3 proteins facilitated the nuclear export of p65 and were essential to regulate NF-κB signalling, after stimulation by TNFα.
Last week a paper came out where the role of 14-3-3σ in cancer relapse and metastasis is further investigated, and the kinetics of nuclear p65 export after TNFα stimulation are described. This work has been led by Anna Bigas and Lluís Espinosa and is the result of a collaboration between reserach groups from the IRB the Hospital del Mar and our group at the UPF. In this publication we contributed in the microarray data interpretation, to describe a genetic signature that responds to TNFα in a 14-3-3σ-dependent manner in MCF7 breast cancer cells. Its over-expression moreover correlates with poor relapse-free survival breast cancer patients. We used IntOGen and Gitools to determine that those genes are associated to breast, intestinal, ovarian and lung cancer. These findings identify a genetic signature that is moreover important for breast cancer prognosis and for future personalized treatments based on NF-κB targeting.
It is always exciting to blend computational biology analyses and molecular genetics experiments to build a solid story such as this one. I am very glad we had the chance to contribute to it with our knowledge, since I could learn thanks to that.
Inglés-Esteve J, Morales M, Dalmases A, Garcia-Carbonell R, Jené-Sanz A, Lopez-Bigas N, Iglesias M, Ruiz-Herguido C, Rovira A, Rojo F, Albanell J, Gomis RR, Bigas A, Espinosa L. Inhibition of specific NF-kappaB activity contributes to the tumor suppressor function of 14-3-3sigma in breast cancer. PLoS ONE, 7(5): e38347. doi:10.1371/journal.pone.0038347
Few months ago, Xavi and Michi wrote a post titled SVGmap: Configurable image browser for experimental data, which described a new tool developed in our lab. SVGmap is useful to create browsers for individualized high-quality images which change the color of some regions according to some values. For example, let’s say that you have expression data for various cell types in a particular tissue (or for various tissues in Drosophila, as in the image), you can draw an SVG image of the tissue showing each of the cell types and provide a tabulated file with the expression data, after few steps you can have a browser that allows you to search for particular genes and display the SVG image with the colors corresponding to the expression of each gene for each cell type. You can see some examples in the SVGmap web.