The Specificity of the FOXL2 c.402C>G Somatic Mutation: A Survey of Solid Tumors

A somatic mutation in the FOXL2 gene is reported to be present in almost all (97%; 86/89) morphologically defined, adult-type, granulosa-cell tumors (A-GCTs). This FOXL2 c.402C>G mutation changes a highly conserved cysteine residue to a tryptophan (p.C134W). It was also found in a minority of other ovarian malignant stromal tumors, but not in benign ovarian stromal tumors or unrelated ovarian tumors or breast cancers.Herein we studied other cancers and cell lines for the presence of this mutation. We screened DNA from 752 tumors of epithelial and mesenchymal origin and 28 ovarian cancer cell lines and 52 other cancer cell lines of varied origin. We found the FOXL2 c.402C>G mutation in an unreported A-GCT case and the A-GCT-derived cell line KGN. All other tumors and cell lines analyzed were mutation negative.In addition to proving that the KGN cell line is a useful model to study A-GCTs, these data show that the c.402C>G mutation in FOXL2 is not commonly found in a wide variety of other cancers and therefore it is likely pathognomonic for A-GCTs and closely related tumors

deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes

ALEA: a toolbox for allele-specific epigenomics analysis

The assessment of expression and epigenomic status using sequencing based methods provides an unprecedented opportunity to identify and correlate allelic differences with epigenomic status. We present ALEA, a computational toolbox for allele-specific epigenomics analysis, which incorporates allelic variation data within existing resources, allowing for the identification of significant associations between epigenetic modifications and specific allelic variants in human and mouse cells. ALEA provides a customizable pipeline of command line tools for allele-specific analysis of next-generation sequencing data (ChIP-seq, RNA-seq, etc.) that takes the raw sequencing data and produces separate allelic tracks ready to be viewed on genome browsers. The pipeline has been validated using human and hybrid mouse ChIP-seq and RNA-seq data.AVAILABILITY: The package, test data and usage instructions are available online at http://www.bcgsc.ca/platform/bioinfo/software/alea CONTACT: : [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.</p