Diffuse large B-cell lymphoma (DLBCL) is the most common form of human lymphoma. While a number of structural alterations have been associated with the pathogenesis of this malignancy, the full spectrum of genetic lesions that are present in the DLBCL genome, and therefore the identity of dysregulated cellular pathways, remains unknown. By combining next-generation sequencing and copy number analysis, we show that the DLBCL coding genome contains on average more than 30 clonally represented gene alterations/case. This analysis also revealed mutations in genes not previously implicated in DLBCL pathogenesis, including those regulating chromatin methylation (MLL2, 24% of cases) and immune recognition by T cells. These results provide initial data on the complexity of the DLBCL coding genome and identify novel dysregulated pathways underlying its pathogenesis.

Oncogenic TACC-tics Human cancers exhibit many types of genomic rearrangements—including some that juxtapose sequences from two unrelated genes—thereby creating fusion proteins with oncogenic activity. Functional analysis of these fusion genes can provide mechanistic insights into tumorigenesis and potentially lead to effective drugs, as famously illustrated by the BCR-ABL gene in chronic myelogenous leukemia. Singh et al. (p. 1231 , published online 26 July) identify and characterize a fusion gene present in 3% of human glioblastomas, a deadly brain cancer. In the resultant fusion protein, the tyrosine kinase region of the fibroblast growth factor receptor (FGFR) is joined to a domain from a transforming acidic coiled-coil (TACC) protein. The TACC-FGFR protein is oncogenic, shows unregulated kinase activity, localizes to the mitotic spindle, and disrupts chromosome segregation. In mice, FGFR inhibitors slowed the growth of tumors driven by the TACC-FGFR gene, suggesting that a subset of glioblastoma patients may benefit from these types of drugs.

Glioblastoma remains one of the most challenging forms of cancer to treat. Here, we develop a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We find mutations with loss of heterozygosity of LZTR-1, an adaptor of Cul3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR-1 function, which restrains self-renewal and growth of glioma spheres retaining stem cell features. Loss-of-function mutations of CTNND2 target a neural-specific gene and are associated with transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 as the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate Stat3 signaling and confer mitogen independency and sensitivity to EGFR inhibition. These results provide important insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.

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Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor