Miller, A. R. | bioRxiv Science

bioRxiv2021

Discovery of Clinically Relevant Fusions in Pediatric Cancer

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPediatric 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. ResultsOur ensemble fusion detection 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 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 ensemble fusion-calling 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 patients medical record, both known and novel fusions provided medically meaningful information. ConclusionsOur ensemble fusion detection 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.

genomics↗

bioRxiv2020

A novel sialic acid-binding adhesin present in multiple species contributes to the pathogenesis of infective endocarditis

Bacterial binding to platelets is a key step in the development of infective endocarditis (IE). Sialic acid, a common terminal carbohydrate on host glycans, is the major receptor for streptococci on platelets. So far, all defined interactions between streptococci and sialic acid on platelets are mediated by serine rich repeat proteins (SRRPs). However, we identified Streptococcus oralis subsp. oralis IE-isolates that bind sialic acid but lack SRRPs. In addition to binding sialic acid, some SRRP-negative isolates also bind the cryptic receptor {beta}-1,4-linked galactose through a yet unknown mechanism. Using comparative genomics, we identified a novel sialic acid-binding adhesin, here named AsaA (associated with sialic acid adhesion A), present in IE-isolates lacking SRRPs. We demonstrated that S. oralis subsp. oralis AsaA is required for binding to platelets in a sialic acid-dependent manner. AsaA comprises a non-repeat region (NRR), consisting of a FIVAR/CBM and two Siglec-like and Unique domains, followed by 31 DUF1542 domains. When recombinantly expressed, Siglec-like and Unique domains competitively inhibited binding of S. oralis subsp. oralis and directly interacted with sialic acid on platelets. We further demonstrated that AsaA impacts the pathogenesis of S. oralis subsp. oralis in a rabbit model of IE. Additionally, we found AsaA orthologues in other IE-causing species and demonstrated that the NRR of AsaA from Gemella haemolysans blocked binding of S. oralis subsp. oralis, suggesting that AsaA contributes to the pathogenesis of multiple IE-causing species. Finally, our findings provide evidence that sialic acid is a key factor for bacterial-platelets interactions in a broader range of species than previously appreciated, highlighting its potential as a therapeutic target. Authors summaryInfective endocarditis (IE) is typically a bacterial infection of the heart valves that causes high mortality. Infective endocarditis can affect people with preexisting lesions on their heart valves (Subacute-IE). These lesions contain platelets and other host factors to which bacteria can bind. Growth of bacteria and accumulation of host factors results in heart failure. Therefore, the ability of bacteria to bind platelets is key to the development of IE. Here, we identified a novel bacterial protein, AsaA, which helps bacteria bind to platelets and contributes to the development of disease. Although this virulence factor was characterized in Streptococcus oralis, a leading cause of IE, we demonstrated that AsaA is also present in several other IE-causing bacterial species and is likely relevant to their ability to cause disease. We showed that AsaA binds to sialic acid, a terminal sugar present on platelets, thereby demonstrating that sialic acid serves as a receptor for a wider range of IE-causing bacteria than previously appreciated, highlighting its potential as a therapeutic target.

microbiology↗