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New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.Detection of structural variants in the human genome is facilitated by a benchmark set of large deletions and insertions.

Rameen Beroukhim and colleagues analyzed somatic structural alterations in 12 tumor types. Whole-genome doubling was found in over a third of all cancers, associated with TP53 mutation. Fifteen new significantly mutated candidate driver genes were found associated with recurrently amplified or deleted regions. Determining how somatic copy number alterations (SCNAs) promote cancer is an important goal. We characterized SCNA patterns in 4,934 cancers from The Cancer Genome Atlas Pan-Cancer data set. Whole-genome doubling, observed in 37% of cancers, was associated with higher rates of every other type of SCNA, TP53 mutations, CCNE1 amplifications and alterations of the PPP2R complex. SCNAs that were internal to chromosomes tended to be shorter than telomere-bounded SCNAs, suggesting different mechanisms underlying their generation. Significantly recurrent focal SCNAs were observed in 140 regions, including 102 without known oncogene or tumor suppressor gene targets and 50 with significantly mutated genes. Amplified regions without known oncogenes were enriched for genes involved in epigenetic regulation. When levels of genomic disruption were accounted for, 7% of region pairs were anticorrelated, and these regions tended to encompass genes whose proteins physically interact, suggesting related functions. These results provide insights into mechanisms of generation and functional consequences of cancer-related SCNAs.

High-grade meningiomas frequently recur and are associated with high rates of morbidity and mortality. To determine the factors that promote the development and evolution of these tumors, we analyzed the genomes of 134 high-grade meningiomas and compared this information with data from 595 previously published meningiomas. High-grade meningiomas had a higher mutation burden than low-grade meningiomas but did not harbor any significantly mutated genes aside from NF2 . High-grade meningiomas also possessed significantly elevated rates of chromosomal gains and losses, especially among tumors with monosomy 22. Meningiomas previously treated with adjuvant radiation had significantly more copy number alterations than radiation-induced or radiation-naïve meningiomas. Across serial recurrences, genomic disruption preceded the emergence of nearly all mutations, remained largely uniform across time, and when present in low-grade meningiomas correlated with subsequent progression to a higher grade. In contrast to the largely stable copy number alterations, mutations were strikingly heterogeneous across tumor recurrences, likely due to extensive geographic heterogeneity in the primary tumor. While high-grade meningiomas harbored significantly fewer overtly targetable alterations than low-grade meningiomas, they contained numerous mutations that are predicted to be neoantigens, suggesting that immunologic targeting may be of therapeutic value. Brain tumors: uncovering genomic disruption in meningiomas Meningiomas, which arise from the tissue surrounding the brain and spinal cord, are the most common primary brain tumor in adults. The majority of these are slow-growing and amenable to surgical resection, if treatment is indicated. However, a subset of aggressive meningiomas are considered high-grade, producing significantly worse mortality. In a first study of its kind, Drs. Wenya Linda Bi, Ian Dunn, Sandro Santagata, Rameen Beroukhim, and colleagues at Harvard Medical School sequenced the genomes of 134 high-grade meningiomas and compared their makeup with lower-grade meningiomas. They found that aggressive tumors were more likely to harbor mutations in the NF2 gene and exhibit widespread genomic disruption. They also harbored an elevated rate of predicted immunogenic mutations, with implications for the use of immuno-modulatory therapies.

Background Renal medullary carcinomas (RMCs) are rare kidney cancers that occur in adolescents and young adults of African ancestry. Although RMC is associated with the sickle cell trait and somatic loss of the tumor suppressor, SMARCB1 , the ancestral origins of RMC remain unknown. Further, characterization of structural variants (SVs) involving SMARCB1 in RMC remains limited. Methods We used linked-read genome sequencing to reconstruct germline and somatic haplotypes in 15 unrelated patients with RMC registered on the Children’s Oncology Group (COG) AREN03B2 study between 2006 and 2017 or from our prior study. We performed fine-mapping of the HBB locus and assessed the germline for cancer predisposition genes. Subsequently, we assessed the tumor samples for mutations outside of SMARCB1 and integrated RNA sequencing to interrogate the structural variants at the SMARCB1 locus. Results We find that the haplotype of the sickle cell mutation in patients with RMC originated from three geographical regions in Africa. In addition, fine-mapping of the HBB locus identified the sickle cell mutation as the sole candidate variant. We further identify that the SMARCB1 structural variants are characterized by blunt or 1-bp homology events. Conclusions Our findings suggest that RMC does not arise from a single founder population and that the HbS allele is a strong candidate germline allele which confers risk for RMC. Furthermore, we find that the SVs that disrupt SMARCB1 function are likely repaired by non-homologous end-joining. These findings highlight how haplotype-based analyses using linked-read genome sequencing can be applied to identify potential risk variants in small and rare disease cohorts and provide nucleotide resolution to structural variants.

Helga Salvesen, Rameen Beroukhim, Scott Carter and colleagues study the evolutionary landscape of endometrial cancer by performing whole-exome sequencing of complex atypical hyperplasias, primary tumors and metastases. They identify recurrent alterations in primary tumors and suggest that driver events are generally shared by primary and metastatic tumors. Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Renal medullary carcinoma (RMC) is a rare and deadly kidney cancer in patients of African descent with sickle cell trait. We have developed faithful patient-derived RMC models and using whole-genome sequencing, we identified loss-of-function intronic fusion events in one SMARCB1 allele with concurrent loss of the other allele. Biochemical and functional characterization of these models revealed that RMC requires the loss of SMARCB1 for survival. Through integration of RNAi and CRISPR-Cas9 loss-of-function genetic screens and a small-molecule screen, we found that the ubiquitin-proteasome system (UPS) was essential in RMC. Inhibition of the UPS caused a G2/M arrest due to constitutive accumulation of cyclin B1. These observations extend across cancers that harbor SMARCB1 loss, which also require expression of the E2 ubiquitin-conjugating enzyme, UBE2C . Our studies identify a synthetic lethal relationship between SMARCB1 -deficient cancers and reliance on the UPS which provides the foundation for a mechanism-informed clinical trial with proteasome inhibitors. Renal medullary carcinoma (RMC for short) is a rare type of kidney cancer that affects teenagers and young adults. These patients are usually of African descent and carry one of the two genetic changes that cause sickle cell anemia. RMC is an aggressive disease without effective treatments and patients survive, on average, for only six to eight months after their diagnosis. Recent genetic studies found that most RMC cells have mutations that prevent them from producing a protein called SMARCB1. SMARCB1 normally acts as a so-called tumor suppressor, preventing cells from becoming cancerous. However, it was not clear whether RMCs always have to lose SMARCB1 if they are to survive and grow. Often, diseases are studied using laboratory-grown cells and tissues that have certain features of the disease. No such models had been created for RMC, which has slowed efforts to understand how the disease develops and find new treatments for it. Hong et al. therefore worked with patients to develop new lines of cells that can be used to study RMC in the laboratory. These RMC cells started dying when they were given copies of the SMARCB1 gene, which supports the theory that RMCs have to lose SMARCB1 in order to grow. Hong et al. then used a set of genetic reagents that can suppress or delete genes that are targeted by drugs, and followed this by testing a range of drugs on the RMC cells. Drugs and genetic reagents that reduced the activity of the proteasome – the structure inside cells that gets rid of old or unwanted proteins – caused the RMC cells to die. These proteasome inhibitor drugs also killed other kinds of cancer cells with SMARCB1 mutations. Proteasome inhibitors are already used to treat different types of cancer. Potentially, a clinical trial could be run to see if they will treat patients whose cancers lack SMARCB1. Further work is also needed to determine the exact link between SMARCB1 and the proteasome.

Disruptions in 3D genomic architecture allow cancer genes to evade transcriptional silencing [Also see Report by Hnisz et al. ] Far from a random tangle, cellular DNA is packed into the nucleus with astounding precision. Indeed, there is growing appreciation for how the three-dimensional (3D) organization of the genome contributes to controlling gene expression. For instance, loops of DNA called insulated neighborhoods can protect small groups of genes from silencing or activation ( 1 ). If cancer can result from dysregulation of gene expression ( 2 ), then an enticing hypothesis is that disrupting insulated neighborhoods may lead to increased transcription of cancer genes. On page 1454 of this issue, Hnisz et al. ( 3 ) use tumor-derived sequencing data and targeted deletions in cells to show that disruption of insulated neighborhoods leads to activation of proto-oncogenes—genes with the potential to cause cancer. These findings strongly support disruption of chromatin structure as causally linked to tumorigenesis, and suggest that such disruptions may be the hidden culprit driving many tumors.

The discovery of drivers of cancer has traditionally focused on protein-coding genes 1 – 4 . Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers 6 , 7 , raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53 , in the 3′ untranslated regions of NFKBIZ and TOB1 , focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available. Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.