Mutual exclusion statistics and data events in Gitools

We’re pleased to announce another incremental release of Gitools, version 2.2. Amongst the many improvements (listed at the bottom of this post) we’d like to highlight the effort that we put into improving performance, specifically with genomic data: mutual exclusion and co-occurrence statistics coupled with a new feature called “data events” – which helps to get a quick grasp of the data.

Low expression events ordered by mutual exclusion

Low expression data events events ordered by mutual exclusion

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Alba is a PhD!

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Last Monday, April 29th, Alba defended her PhD thesis at the PRBB. It was the highest point of a story that started some five years ago, when she joined our group to do her Master’s thesis. From there, she moved on to do her PhD, tackling a very ambitious project trying to unravel the possible roles of the Polycomb complex in tumorigenesis. The title of her thesis, “Integrative study of the regulatory and epigenomic programs involved in cancer development”  is only the tip of the iceberg of what her PhD project has covered. Moving on from her Biology degree, she has taken up all the bioinformatics and computational skills required for the endeavor. Although she always worked intensively, the last six months, after she returned from a four-mont stay in Chicago, at Elizaveta Benevolentskaya‘s group, were particularly intense. During this time she finished writing one paper that she’d been working on in Chicago, and wrote three others, one of which has been already submitted for publication.

 

For Alba, it’s been four years of struggle and learning, but for the group it’s been four very enriching years. Not only has she been an accomplished PhD student (and now graduate), but also an amazing colleague and friend to all of us. A new stage of her professional life starts now, and we wish her the best in this new journey.

 

Congratulations, Alba!

Insights into 14-3-3σ-mediated NF-κB role in breast cancer

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

 

Sample Level Enrichment Analysis (SLEA) in Gitools to assess the transcriptional status of pathways per tumor

From an expression profile of a set of tumor samples, in Gitools you can perform SLEA to assess the transcriptional status of modules (ie. pathways) per sample.

The identification of molecular biomarkers from expression data is a major objective in cancer research. It is clear that there is a benefit in pathway biomarkers (ie. measuring the activity of the pathway instead of individual genes). One easy way to analyze the transcriptional status of pathways (or other gene sets) is using Sample Level Enrichment Analysis (SLEA) in Gitools. This way you can assess the status of each pathway in each sample. This can be used to identify tumor subtypes and to correlate molecular features with clinical features.

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Barcelona Biomedical Genomics Lab on Twitter

During our last retreat we decided to open a twitter account. Some of us (@nlbigas, @chris_zen, @elbioc)  are already using twitter, but we found useful to have one group account where we can tweet and retweet our blog posts and other things related to biomedical genomics field.

It was not easy to find a username, in the end @bbglab is our twitter account. It’s an acronym of Barcelona Biomedical Genomics Lab.

Last year blog statistics

 Since we started our blog one year ago we have received 2200 unique visitors with a returning rate of 37%. We think that this is a good returning rate but we want to make it easy to follow us, this is why we are opening this twitter account and also giving the option to follow us through email. And of course you can still use RSS if you prefer.