TARGETgene 2.0beta

A fusion gene that results from chromosome rearrangements is a hybrid gene formed from distinct genes, either in the same chromosome or in different chromosomes. Many recurring gene fusions, such as BCR-ABL in chronic myelogenous leukemia, EWS-FIL1 in Ewing’s Sarcoma, and TMPRSS2-ERG in prostate cancer, play important roles in cancer progression. As such, they have become important therapeutic targets.

Gene fusions are currently being discovered at an increasing rate using massively parallel sequencing technologies. Prioritization of important cancer fusion drivers for validation and  as therapeutic targets cannot be performed using traditional single-gene based methods because fusions involve portions of two partner genes. To address this problem, Wu et al (Wu et al., 2013) have introduced a novel network analysis method called fusion centrality that is specifically tailored for prioritizing gene fusions. This fusion centrality approach is now integrated into the TARGETgene software developed previously, to prioritize fusion drivers from hundreds or thousands of fusion candidates identified in sequencing data.

Users can download the file TARGETgene.zip from the downloads page. After unzipping it, you will find three sub-sub-directories (EX1, EX2, EX3) under the sub-directory “Examples”. “EX3” contains files illustrating this new fusion gene capability. Two set of fusions are used for demonstration analysis. One is a set of 289 known fusions downloaded from cancer gene census (Fusions_CancerGeneCensus.txt). The other is a set of newly discovered fusions (New_Fusions.txt).  Users can follow the process demonstrated in the included PDF file (TARGETgene_EX3.pdf) to generate the results.

TARGTgene 2.0beta is still under development. If you find any problem regarding TARGETgene, please kindly contact us (perwu777@gmail.com). Your help is appreciated.

Reference

Wu et al. (2013) Identification of cancer fusion drivers using network fusion centrality. Bioinformatics doi:10.1093.

2 Responses

  1. Li says:

    this is Li. I want to download the targetGene for internal medical research.

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