The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal. Database URL:http://dcc.icgc.org

The HLA gene complex on human chromosome 6 is one of the most polymorphic regions in the human genome and contributes in large part to the diversity of the immune system. Accurate typing of HLA genes with short-read sequencing data has historically been difficult due to the sequence similarity between the polymorphic alleles. Here, we introduce an algorithm, xHLA, that iteratively refines the mapping results at the amino acid level to achieve 99–100% four-digit typing accuracy for both class I and II HLA genes, taking only $\sim$3 min to process a 30× whole-genome BAM file on a desktop computer. Significance Regulation of the human immune system is largely controlled by the HLA gene complex on chromosome 6 and is important in infectious disease immunity, graft rejection, autoimmunity, and cancer. HLA typing is traditionally performed by serotyping and/or targeted sequencing. However, the advent of precision medicine and cheaper personal genome sequencing has sprung an unmet need for a fast and accurate way of predicting HLA types from short-read sequencing data. Here, we present xHLA, an algorithm for HLA typing based on translated short reads, exhaustive multiple sequence alignment-based alignment expansion, and iterative solution set refinement that is also faster and more accurate than existing methods. Results are achievable within minutes and could greatly benefit individuals who have had their genome sequenced.

Genes encoding TRK are oncogenic drivers in multiple tumour types including infantile fibrosarcoma, papillary thyroid cancer and high-grade gliomas (HGG). TRK fusions have a critical role in tumourigenesis in 40% of infant HGG. Here we report the first case of a TRK fusion-driven HGG treated with larotrectinib—the first selective pan-TRK inhibitor in clinical development. This 3-year-old girl had failed multiple therapies including chemotherapy and radiotherapy. Tumour profiling confirmed an ETV6–NTRK3 fusion. Treatment with larotrectinib led to rapid clinical improvement with near total resolution of primary and metastatic lesions on MRI imaging. This is the first report of a TRK fusion glioma successfully treated with a TRK inhibitor.

Recent research showed that precision medicine can identify new treatment strategies for patients with childhood cancers. However, it is unclear which patients will benefit most from precision-guided treatment (PGT). Here we report consecutive data from 384 patients with high-risk pediatric cancer (with an expected cure rate of less than 30%) who had at least 18 months of follow-up on the ZERO Childhood Cancer Precision Medicine Program PRecISion Medicine for Children with Cancer (PRISM) trial. A total of 256 (67%) patients received PGT recommendations and 110 (29%) received a recommended treatment. PGT resulted in a 36% objective response rate and improved 2-year progression-free survival compared with standard of care (26% versus 12%; P = 0.049) or targeted agents not guided by molecular findings (26% versus 5.2%; P = 0.003). PGT based on tier 1 evidence, PGT targeting fusions or commenced before disease progression had the greatest clinical benefit. Our data show that PGT informed by comprehensive molecular profiling significantly improves outcomes for children with high-risk cancers. ClinicalTrials.gov registration: NCT03336931