Discovery of clinically relevant fusions in pediatric cancer.

BACKGROUND: Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. RESULTS: Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient's medical record, both known and novel fusions provided medically meaningful information. CONCLUSIONS: The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Pre-clinical Safety and Off-Target Studies to Support Translation of AAV-Mediated RNAi Therapy for FSHD.

RNAi emerged as a prospective molecular therapy nearly 15 years ago. Since then, two major RNAi platforms have been under development: oligonucleotides and gene therapy. Oligonucleotide-based approaches have seen more advancement, with some promising therapies that may soon reach market. In contrast, vector-based approaches for RNAi therapy have remained largely in the pre-clinical realm, with limited clinical safety and efficacy data to date. We are developing a gene therapy approach to treat the autosomal-dominant disorder facioscapulohumeral muscular dystrophy. Our strategy involves silencing the myotoxic gene DUX4 using adeno-associated viral vectors to deliver targeted microRNA expression cassettes (miDUX4s). We previously demonstrated proof of concept for this approach in mice, and we are now taking additional steps here to assess safety issues related to miDUX4 overexpression and sequence-specific off-target silencing. In this study, we describe improvements in vector design and expansion of our miDUX4 sequence repertoire and report differential toxicity elicited by two miDUX4 sequences, of which one was toxic and the other was not. This study provides important data to help advance our goal of translating RNAi gene therapy for facioscapulohumeral muscular dystrophy.

Secondary evolution of a self-incompatibility locus in the Brassicaceae genus Leavenworthia.

Self-incompatibility (SI) is the flowering plant reproductive system in which self pollen tube growth is inhibited, thereby preventing self-fertilization. SI has evolved independently in several different flowering plant lineages. In all Brassicaceae species in which the molecular basis of SI has been investigated in detail, the product of the S-locus receptor kinase (SRK) gene functions as receptor in the initial step of the self pollen-rejection pathway, while that of the S-locus cysteine-rich (SCR) gene functions as ligand. Here we examine the hypothesis that the S locus in the Brassicaceae genus Leavenworthia is paralogous with the S locus previously characterized in other members of the family. We also test the hypothesis that self-compatibility in this group is based on disruption of the pollen ligand-producing gene. Sequence analysis of the S-locus genes in Leavenworthia, phylogeny of S alleles, gene expression patterns, and comparative genomics analyses provide support for both hypotheses. Of special interest are two genes located in a non-S locus genomic region of Arabidopsis lyrata that exhibit domain structures, sequences, and phylogenetic histories similar to those of the S-locus genes in Leavenworthia, and that also share synteny with these genes. These A. lyrata genes resemble those comprising the A. lyrata S locus, but they do not function in self-recognition. Moreover, they appear to belong to a lineage that diverged from the ancestral Brassicaceae S-locus genes before allelic diversification at the S locus. We hypothesize that there has been neo-functionalization of these S-locus-like genes in the Leavenworthia lineage, resulting in evolution of a separate ligand-receptor system of SI. Our results also provide support for theoretical models that predict that the least constrained pathway to the evolution of self-compatibility is one involving loss of pollen gene function.