Distinct Classes of Complex Structural Variation Uncovered across Thousands of Cancer Genome Graphs.

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g., deletion) or complex (e.g., chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole-genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early-replicating regions, superenhancers, and breast or ovarian cancers. Rigma comprise "chasms" of low-JCN deletions enriched in late-replicating fragile sites and gastrointestinal carcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold-back inversions associated with expressed protein-coding fusions, breakend hypermutation, and acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing.

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.

Patterns of somatic structural variation in human cancer genomes.

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1-7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions-as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2-7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and-in liver cancer-frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. 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) Consortium5 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 drivers6,7, 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.

SvABA: genome-wide detection of structural variants and indels by local assembly.

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ∼4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs.

SeqLib: a C ++ API for rapid BAM manipulation, sequence alignment and sequence assembly.

We present SeqLib, a C ++ API and command line tool that provides a rapid and user-friendly interface to BAM/SAM/CRAM files, global sequence alignment operations and sequence assembly. Four C libraries perform core operations in SeqLib: HTSlib for BAM access, BWA-MEM and BLAT for sequence alignment and Fermi for error correction and sequence assembly. Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence analysis APIs. We demonstrate an example of how minimal SeqLib code can extract, error-correct and assemble reads from a CRAM file and then align with BWA-MEM. SeqLib also provides additional capabilities, including chromosome-aware interval queries and read plotting. Command line tools are available for performing integrated error correction, micro-assemblies and alignment. Availability and Implementation: SeqLib is available on Linux and OSX for the C ++98 standard and later at github.com/walaj/SeqLib. SeqLib is released under the Apache2 license. Additional capabilities for BLAT alignment are available under the BLAT license. Contact: jwala@broadinstitue.org ; rameen@broadinstitute.org.

VariantBam: filtering and profiling of next-generational sequencing data using region-specific rules.

UNLABELLED: We developed VariantBam, a C ++ read filtering and profiling tool for use with BAM, CRAM and SAM sequencing files. VariantBam provides a flexible framework for extracting sequencing reads or read-pairs that satisfy combinations of rules, defined by any number of genomic intervals or variant sites. We have implemented filters based on alignment data, sequence motifs, regional coverage and base quality. For example, VariantBam achieved a median size reduction ratio of 3.1:1 when applied to 10 lung cancer whole genome BAMs by removing large tags and selecting for only high-quality variant-supporting reads and reads matching a large dictionary of sequence motifs. Thus VariantBam enables efficient storage of sequencing data while preserving the most relevant information for downstream analysis. AVAILABILITY AND IMPLEMENTATION: VariantBam and full documentation are available at github.com/jwalabroad/VariantBam CONTACT: rameen@broadinstitute.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrating spatial profiles and cancer genomics to identify immune-infiltrated mismatch repair proficient colorectal cancers.

Predicting the progression of solid cancers based solely on genetics is challenging due to the influence of the tumor microenvironment (TME). For colorectal cancer (CRC), tumors deficient in mismatch repair (dMMR) are more immune infiltrated than mismatch repair proficient (pMMR) tumors and have better prognosis following resection. Here we quantify features of the CRC TME by combining spatial profiling with genetic analysis and release our findings via a spatially enhanced version of cBioPortal that facilitates multi-modal data exploration and analysis. We find that ∼20% of pMMR tumors exhibit similar levels of T cell infiltration as dMMR tumors and that this is associated with better survival but not any specific somatic mutation. These T cell-infiltrated pMMR (tipMMR) tumors contain abundant cells expressing PD1 and PDL1 as well as T regulatory cells, consistent with a suppressed immune response. Thus, like dMMR CRC, tipMMR CRC may benefit from immune checkpoint inhibitor therapy. SIGNIFICANCE: pMMR tumors with high T cell infiltration and active immunosuppression are identifiable with a mid-plex imaging assay whose clinical deployment might double the number of treatment-naïve CRCs eligible for ICIs. Moreover, the low tumor mutational burden in tipMMR CRC shows that MMR status is not the only factor promoting immune infiltration.

Chimeric Antigen Receptor T-Cell Therapy for Solid Tumors.

We review chimeric antigen receptor (CAR) T-cell therapy for solid tumors. We discuss patient selection factors and aspects of clinical management. We describe challenges including physical and molecular barriers to trafficking CAR-Ts, an immunosuppressive tumor microenvironment, and difficulty finding cell surface target antigens. The application of new approaches in synthetic biology and cellular engineering toward solid tumor CAR-Ts is described. Finally, we summarize reported and ongoing clinical trials of CAR-T therapies for select disease sites such as head and neck (including thyroid cancer), lung, central nervous system (glioblastoma, neuroblastoma, glioma), sarcoma, genitourinary (prostate, renal, bladder, kidney), breast and ovarian cancer.

Early Treatment Intensification in Metastatic Hormone-Sensitive Prostate Cancer.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in the Journal of Clinical Oncology, to patients seen in their own clinical practice.For generations, oncologists and urologists have used androgen deprivation therapy (ADT) to manage metastatic hormone-sensitive prostate cancer (mHSPC). Until recently, ADT monotherapy was standard. Within the past decade, a series of trials have clearly demonstrated improved outcomes with a more aggressive up-front approach. Doublet intensification therapy, involving either ADT plus docetaxel or ADT plus any of several second-generation oral androgen-receptor pathway inhibitors (ARPIs), provide considerable survival advantages compared with ADT alone. In 2022, two trials, PEACE-1 and ARASENS, demonstrated the potential of triplet therapy, adding an ARPI to an ADT-docetaxel doublet. In the Original Report that accompanies this article, the authors provide a post hoc analysis of ARASENS (ADT plus docetaxel, with or without darolutamide), identifying the subpopulations of patients with mHSPC who might benefit most from a triplet regimen. They segment the ARASENS cohort by disease volume and disease risk profile, finding that triplet therapy is associated with improved outcomes regardless of category (although with limited power in the low-volume cohort). Meanwhile, trials are ongoing examining the role of radiotherapy (RT) in mHSPC, a modality previously reserved for localized disease or isolated, symptomatic metastases. Here, we present a mHSPC case and discuss our approach to mHSPC considering recent studies. We recommend triplet therapy for patients who are suitable candidates for chemotherapy, especially for patients with high-volume disease. We also favor aggressive use of RT, when feasible, for patients with low-volume mHSPC.

Multicriteria VMAT optimization.

PURPOSE: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. METHODS: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. RESULTS: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average. CONCLUSIONS: VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

Structural variants shape driver combinations and outcomes in pediatric high-grade glioma.

We analyzed the contributions of structural variants (SVs) to gliomagenesis across 179 pediatric high-grade gliomas (pHGGs). The most recurrent SVs targeted MYC isoforms and receptor tyrosine kinases (RTKs), including an SV amplifying a MYC enhancer in 12% of diffuse midline gliomas (DMG), indicating an underappreciated role for MYC in pHGG. SV signature analysis revealed that tumors with simple signatures were TP53 wild type (TP53WT) but showed alterations in TP53 pathway members PPM1D and MDM4. Complex signatures were associated with direct aberrations in TP53, CDKN2A and RB1 early in tumor evolution and with later-occurring extrachromosomal amplicons. All pHGGs exhibited at least one simple-SV signature, but complex-SV signatures were primarily restricted to subsets of H3.3K27M DMGs and hemispheric pHGGs. Importantly, DMGs with complex-SV signatures were associated with shorter overall survival independent of histone mutation and TP53 status. These data provide insight into the impact of SVs on gliomagenesis and the mechanisms that shape them.

Haplotype-resolved germline and somatic alterations in renal medullary carcinomas.

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.

Author Correction: A robust benchmark for detection of germline large deletions and insertions.

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

A robust benchmark for detection of germline large deletions and insertions.

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.

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition.

About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

Renal medullary carcinomas depend upon SMARCB1 loss and are sensitive to proteasome inhibition.

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.

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Diffuse large B cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is a clinically and genetically heterogeneous disease that is further classified into transcriptionally defined activated B cell (ABC) and germinal center B cell (GCB) subtypes. We carried out a comprehensive genetic analysis of 304 primary DLBCLs and identified low-frequency alterations, captured recurrent mutations, somatic copy number alterations, and structural variants, and defined coordinate signatures in patients with available outcome data. We integrated these genetic drivers using consensus clustering and identified five robust DLBCL subsets, including a previously unrecognized group of low-risk ABC-DLBCLs of extrafollicular/marginal zone origin; two distinct subsets of GCB-DLBCLs with different outcomes and targetable alterations; and an ABC/GCB-independent group with biallelic inactivation of TP53, CDKN2A loss, and associated genomic instability. The genetic features of the newly characterized subsets, their mutational signatures, and the temporal ordering of identified alterations provide new insights into DLBCL pathogenesis. The coordinate genetic signatures also predict outcome independent of the clinical International Prognostic Index and suggest new combination treatment strategies. More broadly, our results provide a roadmap for an actionable DLBCL classification.