The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Nineteen benign [World Health Organization (WHO) grade I; MI], 21 atypical (WHO grade II; MII), and 19 anaplastic (WHO grade III; MIII) sporadic meningiomas were screened for chromosomal imbalances by comparative genomic hybridization (CGH). These data were supplemented by molecular genetic analyses of selected chromosomal regions and genes. With increasing malignancy grade, a marked accumulation of genomic aberrations was observed; i.e., the numbers (mean ± SEM) of total alterations detected per tumor were 2.9 ± 0.7 for MI, 9.2 ± 1.2 for MII, and 13.3 ± 1.9 for MIII. The most frequent alteration detected in MI was loss on 22q (58%). In MII, aberrations most commonly identified were losses on 1p (76%), 22q (71%), 14q (43%), 18q (43%), 10 (38%), and 6q (33%), as well as gains on 20q (48%), 12q (43%), 15q (43%), 1q (33%), 9q (33%), and 17q (33%). In MIII, most of these alterations were found at similar frequencies. However, an increase in losses on 6q (53%), 10 (68%), and 14q (63%) was observed. In addition, 32% of MIII demonstrated loss on 9p. Homozygous deletions in the CDKN2A gene at 9p21 were found in 4 of 16 MIII (25%). Highly amplified DNA sequences were mapped to 12q13–q15 by CGH in 1 MII. Southern blot analysis of this tumor revealed amplification of CDK4 and MDM2 . By CGH, DNA sequences from 17q were found to be amplified in 1 MII and 8 MIII, involving 17q23 in all cases. Despite the high frequency of chromosomal aberrations in the MII and MIII investigated, none of these tumors showed mutations in exons 5–8 of the TP53 gene. On the basis of the most common aberrations identified in the various malignancy grades, a model for the genomic alterations associated with meningioma progression is proposed.

Summary: Through sequencing projects and, more recently, array-based expression analysis experiments, a wealth of genetic data has become accessible via online resources. In contrast, few of the (molecular-) cytogenetic aberration data collected in the last decades are available in a format suitable for data mining procedures. www.progenetix.net is a new online repository for previously published chromosomal aberration data, allowing the addition of band-specific information about chromosomal imbalances to oncologic data analysis efforts. Availability: http://www.progenetix.net Contact: mbaudis@stanford.edu * To whom correspondence should be addressed.

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

Purpose: Neuroblastoma is a genetically heterogeneous pediatric tumor with a remarkably variable clinical behavior ranging from widely disseminated disease to spontaneous regression. In this study, we aimed for comprehensive genetic subgroup discovery and assessment of independent prognostic markers based on genome-wide aberrations detected by comparative genomic hybridization (CGH). Materials and Methods: Published CGH data from 231 primary untreated neuroblastomas were converted to a digitized format suitable for global data mining, subgroup discovery, and multivariate survival analyses. Results: In contrast to previous reports, which included only a few genetic parameters, we present here for the first time a strategy that allows unbiased evaluation of all genetic imbalances detected by CGH. The presented approach firmly established the existence of three different clinicogenetic subgroups and indicated that chromosome 17 status and tumor stage were the only independent significant predictors for patient outcome. Important new findings were: (1) a normal chromosome 17 status as a delineator of a subgroup of presumed favorable-stage tumors with highly increased risk; (2) the recognition of a survivor signature conferring 100% 5-year survival for stage 1, 2, and 4S tumors presenting with whole chromosome 17 gain; and (3) the identification of 3p deletion as a hallmark of older age at diagnosis. Conclusion: We propose a new regression model for improved patient outcome prediction, incorporating tumor stage, chromosome 17, and amplification/deletion status. These findings may prove highly valuable with respect to more reliable risk assessment, evaluation of clinical results, and optimization of current treatment protocols.