Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer

This is the 1st-article of a blog series aiming to introduce Zodiac, a comprehensive tool that reveals genetic interactions in cancer by big-data computation. 


This is a short series introducing our new work, Zodiac (Zhu et al., 2015, JNCI), an online resource for genetic interactions in Cancer. It is a paper coming out in the August 2015 issue of the Journal of National Cancer Institute. Zodiac is a big-data computational project involving complex statistical modeling, massively parallel computation, and user-friendly interface building. It is built by an amazing inter-disciplinary team of statisticians, computational scientists, and biologists. I will provide a series of use cases for Zodiac. The goal is to invite comments, critiques, and discussions on genetic interactions in cancer.

Zodiac is a computational tool and resource to integrate prior biological knowledge and new information contained in The Cancer Genome Atlas (TCGA) data to update genetic interactions between genes under cancer conditions. It is an evolution of our knowledge about genetic interactions in cancer by treating existing knowledge (such as a KEGG pathway) as a prior graph, integrating it with a likelihood model for TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. The main computation is based on Bayesian graphical models (BGM) in Mitra et al. (2013). In short, Zodiac realizes

Prior interaction map + TCGA data —> Posterior interaction map

Zodiac performed such updates for 200 million pairs of genes and produced a new online database. Equally important, Zodiac provides tools that allow users to choose which knowledge they want to update.

Zodiac is publicly available at www.compgenome.org/Zodiac

The main interface is a search bar (like google search) in which users type genes names of interests.

Depending on if one, two, or multiple gene names are provided, Zodiac returns results graphically in different formats, but all containing a genetic network regarding the genes searched. See Figure below. These networks are computational results based on the posterior interaction map using BGM aforementioned.

Zodiac can be formally used to validate existing knowledge about genetic interactions and hypothesize new interactions for future research. It is comprehensive in the sense that any genes measured in the TCGA data are included.

We have found Zodiac handy in occasional usage, including during a seminar (for live query of new genetic interactions being presented), literature review (for query of published new knowledge about genetic interactions), and scientific meetings between collaborators. Since it is accessible anywhere on any devices with internet access, such usage makes Zodiac attractive for spontaneous occasions like these.

Case 1

Zodiac shows significant positive edges between gene expressions of PALB2, BRCA1, and BRCA2 indicating interactions between them. Link: http://compgenome.org/zodiac?Gene_List=palb2+brca1+brca2

A recent publication in The New England Journal of Medicine (A.C. Antoniou et al., 2014) shows that the loss-of-function mutations in PALB2 are an important cause of hereditary breast cancer, with respect both to the frequency of cancer-predisposing mutations and to the risk associated with them. The study suggests that the breast-cancer risk for PALB2 mutation carriers may overlap with that for BRCA2 mutation carriers. PALB2 (partner and localizer of BRCA2) was originally identified as a BRCA2-interacting protein that is crucial for key BRCA2 genome caretaker functions; it was subsequently also shown to interact with BRCA1.

A.C. Antoniou et al., Breast-Cancer Risk in Families with Mutations in PALB2, The New England Journal of Medicine, vol. 371 no. 6, pp. 497-506, 2014


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