Michael Lankerovich

Anatomically correct tumor genomics Glioblastoma is the most lethal form of human brain cancer. The genomic alterations and gene expression profiles characterizing this tumor type have been widely studied. Puchalski et al. created the Ivy Glioblastoma Atlas, a freely available online resource for the research community. The atlas, a collaborative effort between bioinformaticians and pathologists, maps molecular features of glioblastomas, such as transcriptional signatures, to histologically defined anatomical regions of the tumors. The relationships identified in this atlas, in conjunction with associated databases of clinical and genomic information, could provide new insights into the pathogenesis, diagnosis, and treatment of glioblastoma. Science , this issue p. 660

BACKGROUND: RNA-seq has spurred important gene fusion discoveries in a number of different cancers, including lung, prostate, breast, brain, thyroid and bladder carcinomas. Gene fusion discovery can potentially lead to the development of novel treatments that target the underlying genetic abnormalities. RESULTS: In this study, we provide comprehensive view of gene fusion landscape in 185 glioblastoma multiforme patients from two independent cohorts. Fusions occur in approximately 30-50% of GBM patient samples. In the Ivy Center cohort of 24 patients, 33% of samples harbored fusions that were validated by qPCR and Sanger sequencing. We were able to identify high-confidence gene fusions from RNA-seq data in 53% of the samples in a TCGA cohort of 161 patients. We identified 13 cases (8%) with fusions retaining a tyrosine kinase domain in the TCGA cohort and one case in the Ivy Center cohort. Ours is the first study to describe recurrent fusions involving non-coding genes. Genomic locations 7p11 and 12q14-15 harbor majority of the fusions. Fusions on 7p11 are formed in focally amplified EGFR locus whereas 12q14-15 fusions are formed by complex genomic rearrangements. All the fusions detected in this study can be further visualized and analyzed using our website: http://ivygap.swedish.org/fusions. CONCLUSIONS: Our study highlights the prevalence of gene fusions as one of the major genomic abnormalities in GBM. The majority of the fusions are private fusions, and a minority of these recur with low frequency. A small subset of patients with fusions of receptor tyrosine kinases can benefit from existing FDA approved drugs and drugs available in various clinical trials. Due to the low frequency and rarity of clinically relevant fusions, RNA-seq of GBM patient samples will be a vital tool for the identification of patient-specific fusions that can drive personalized therapy.

The molecular and cellular landscape of glioblastoma is highly complex and its relationship to histologic features routinely used for diagnosis is unclear. To investigate this relationship, we generated an anatomic transcriptional atlas of human glioblastoma, adopting a highly-systematized, large-scale, histology-driven approach to the characterization of anatomic features and cancer stem cell populations. The atlas of 42 tumors consists of several data modalities, including 270 transcriptomes, ∼11,500 semi-annotated pathology images registered to ∼23,000 in situ hybridization gene expression images, ∼400 MRI scans, tumor-derived cell lines and xenografts, and supporting longitudinal clinical information. We show that gene expression varies considerably by anatomic feature and cancer stem cell population, exhibiting molecular signatures that are more highly conserved within tumors than between tumors, and reflecting the cell types and microenvironment of each feature and population. These freely-accessible online data resources of the Ivy Glioblastoma Atlas Project (Ivy GAP), one for the fully-annotated anatomic transcriptional atlas (http://glioblastoma.alleninstitute.org/), and one for the detailed clinical and genomic data (http://ivygap.org/), constitute a unique platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels. This project was supported by grants from the Ben and Catherine Ivy Foundation to the Allen Institute (PI, RBP) and Swedish Neuroscience Institute (PIs, GDF and NS).