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Advanced urothelial cancer is a frequently lethal disease characterized by marked genetic heterogeneity. In this study, we investigate the evolution of the genomic signatures caused by endogenous and external mutagenic stimuli and their interplay with complex structural variants. We superimposed mutational signatures and phylogenetic analyses of matched serial tumors from patients with urothelial cancer to define the evolutionary patterns of these processes. We show that APOBEC3-induced mutations are clonal and early, whereas mutational bursts comprising hundreds of late subclonal mutations are induced by chemotherapy. Using a novel genome graph computational paradigm, we observed frequent circular high copy-number amplicons characteristic of extrachromosomal DNA (ecDNA) involving double-minutes, breakage-fusion-bridge, and tyfonas events. We characterized the distinct temporal patterns of APOBEC3 mutations and chemotherapy-induced mutations within ecDNA, gaining new insights into the timing of these events relative to ecDNA biogenesis. Finally, we discovered that mostCCND1amplifications in urothelial cancer arise within circular ecDNA amplicons. TheseCCND1ecDNA amplification events persisted and increased in complexity incorporating additional DNA segments potentially contributing selective fitness advantage to the evolution of treatment resistance. Our findings define fundamental mechanisms driving urothelial cancer evolution and have therapeutic implications for treating this disease.

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Genomic rearrangements are a hallmark of most solid tumors, including medulloblastoma, one of the most common brain tumors in children. Childhood cancers involve dysregulated cell development, but their mutational causes remain largely unknown. One of the most common forms of medulloblastoma is caused by ectopic activation of Sonic Hedgehog (SHH) signaling in cerebellar granule cell progenitors, associated with genetic deletions, amplifications, and other oncogenic chromosomal rearrangements. Here, we show that PiggyBac Transposable Element Derived 5 (Pgbd5) promotes tumor development in multiple developmentally-accurate mouse models of SHH medulloblastoma. Most mice with Pgbd5 deficiency do not develop tumors, while Pgbd5-deficient mice maintain largely normal cerebellar development. Mouse medulloblastomas expressing Pgbd5 exhibit significantly increased numbers of somatic structural DNA rearrangements, with PGBD5-specific transposon sequences at their breakpoints. Similar sequence breakpoints recurrently affect somatic DNA rearrangements of known tumor suppressors and oncogenes in medulloblastomas in 329 children. Therefore, this study identifies PGBD5 as a primary medulloblastoma mutator and provides a genetic mechanism responsible for the generation of somatic oncogenic DNA rearrangements in childhood cancer.One-Sentence SummaryInduction of somatic oncogenic mutations by the DNA transposase PGBD5 in cerebellar progenitor cells promotes medulloblastoma development.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE uses deep learning and a ctDNA-specific feature space to increase SNV signal to noise enrichment in WGS by 300X compared to our previous noise suppression platform MRDetect. MRD-EDGE also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1Gb to 200Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal to noise enrichment in MRD-EDGE enables de novo mutation calling in melanoma without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition.

Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy-resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome RNA and miRNA sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of apparent NUP98 mutations, and additional recurrent variants including those in KMT2C and MLLT10. Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles of FRMD8, DHX32, PIK3R1, SHANK3, MKLN1, as well as persistence of WT1 and TP53 mutant clones, and elimination of FLT3, PTPN11, and NRAS mutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

While the genomes of normal tissues undergo dynamic changes over time, little is understood about the temporal-spatial dynamics of genomes in premalignant tissues that progress to cancer compared to those that remain cancer-free. Here we use whole genome sequencing to contrast genomic alterations in 427 longitudinal samples from 40 patients with stable Barrett’s esophagus compared to 40 Barrett’s patients who progressed to esophageal adenocarcinoma (ESAD). We show the same somatic mutational processes were active in Barrett’s tissue regardless of outcome, with high levels of mutation, ESAD gene and focal chromosomal alterations, and similar mutational signatures. The critical distinction between stable Barrett’s versus those who progress to cancer is acquisition and expansion of TP53-/- cell populations having complex structural variants and high-level amplifications, which were detectable up to six years prior to a cancer diagnosis. These findings reveal the timing of common somatic genome dynamics in stable Barrett’s esophagus and define key genomic features specific to progression to esophageal adenocarcinoma, both of which are critical for cancer prevention and early detection strategies.

SUMMARY RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(–) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(–) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(–) cases are required to understand this important LUAD subset., In Brief Carrot-Zhang et al. perform whole-genome characterization of lung adenocarcinomas (LUADs) lacking RTK/RAS/RAF pathway alterations (RPAs) and identify mutations or structural variants in both coding and non-coding spaces that define a unique entity of RPA(–) LUADs and potentially explain the underlying biology of this disease., Graphical Abstract

Background Clearance of circulating tumor DNA (ctDNA) following checkpoint blockade (CB) can precede radiographic response,1 2 though current state of the art ctDNA detection via targeted panels faces limited sensitivity in low burden disease (figure 1). We previously showed that whole genome sequencing (WGS) of plasma can overcome low input of ctDNA to dynamically track low volume malignancy using matched tumor tissue.3 We therefore sought to evaluate ctDNA for tracking early response to checkpoint blockade (CB) in melanoma, and developed a novel classifier that allows us to track disease without matched tumor tissue for expanded applicability in immunotherapy. Methods To identify ctDNA sparsely diluted in noncancerous plasma cell free DNA (cfDNA), we developed Phoenix, a deep-learning classifier that uses genomic and epigenomic features to distinguish single nucleotide variants (SNVs) in melanoma from sequencing noise. We evaluated Phoenix on a retrospective cohort of serially sampled plasma from patients with advanced cutaneous melanoma on CB (nivolumab alone or with ipilimumab). Plasma was collected at 0, 3, 6 and 12 weeks after first dose of immunotherapy. ctDNA dynamics were compared to radiographic imaging results at 12 weeks. Results We trained Phoenix on tumor-confirmed SNVs in plasma from a single patient with high tumor mutational burden (TMB) melanoma and cfDNA from age-matched patients without known cancer. Overall ctDNA signal-to-noise enrichment ranged from 100 - 260x in validation patients (n=2) with bulky disease. Phoenix learned key features of melanoma ctDNA including the UV mutational signature and short fragment size (figure 2), and sensitively tracked persistent low burden disease seen on imaging (figure 3). To validate these findings, we expanded our cohort (n= 15) of serially tracked tumors. In our preliminary analysis of 12 patients, Phoenix detected pretreatment ctDNA in 92% of patients at a specificity of 97% (figure 4), compared with only 17% with the benchmark in the field (iChorCNA, a plasma-based WGS liquid biopsy tool; table 1). Phoenix detected a decrease in ctDNA 3 weeks after initiation of CB in 80% of patients (figure 5) with an objective response on imaging. No change in ctDNA was seen in patients who did not respond to treatment. Conclusions Phoenix successfully identified pretreatment melanoma ctDNA without matched tumor tissue and identified response to CB as early as 3 weeks after treatment. Our ongoing studies aim to optimize this technology for early identification of CB response in clinical practice. Acknowledgements Thanks to support from the Conquer Cancer Foundation Ethics Approval Use of human data in this study was approved by Memorial Sloan Kettering’s IRB, Assurance Number FWA0000499 References Zhang Q, Luo J, et al. Prognostic and predictive impact of circulating tumor DNA in patients with advanced cancers treated with immune checkpoint blockade. Cancer Discov 2020 pp: CD-20-0047. doi:10.1158/2159-8290.CD-20-0047 Bratman SV, Yang SYC., Iafolla MAJ, et al. Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab. Nat Cancer (2020). https://doi.org/10.1038/s43018-020-0096-53. Zviran A, Schulman RC, Shah M, et al. Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat Med 2020;26(7):1114–1124. doi:10.1038/s41591-020-0915-3 Adalsteinsson VA, Ha G, Freeman SS, et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat Commun2017;8(1):1324. Published 2017 Nov 6. doi:10.1038/s41467-017-00965-y

Summary We present a new version of the popular somatic variant caller, Lancet, that supports the analysis of linked-reads sequencing data. By seamlessly integrating barcodes and haplotype read assignments within the colored De Bruijn graph local-assembly framework, Lancet computes a barcode-aware coverage and identifies variants that disagree with the local haplotype structure. Availability and implementation Lancet is implemented in C++ and available for academic and non-commercial research purposes as an open-source package at https://github.com/nygenome/lancet. Supplementary information Supplementary data are available at Bioinformatics online.

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10−5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care. A new approach for whole-genome sequencing of plasma circulating tumor DNA allows for dynamic monitoring of disease burden and ultra-sensitive detection of minimal residual disease.

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we sequenced 3 common cancer cell lines along with their matched normal cell lines to great sequencing depths (up to 278X coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, it improves the accuracy of somatic calls. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.

The tumor genome of a patient with advanced pancreatic cancer was sequenced to identify potential therapeutic targetable mutations after standard of care failed to produce any significant overall response. Matched tumor-normal whole-genome sequencing revealed somatic mutations in BRAF, TP53, CDKN2A, and a focal deletion of SMAD4. The BRAF variant was an in-frame deletion mutation (ΔN486_P490), which had been previously demonstrated to be a kinase-activating alteration in the BRAF kinase domain. Working with the Novartis patient assistance program allowed us to treat the patient with the BRAF inhibitor, dabrafenib. The patient's overall clinical condition improved dramatically with dabrafenib. Levels of serum tumor marker dropped immediately after treatment, and a subsequent CT scan revealed a significant decrease in the size of both primary and metastatic lesions. The dabrafenib-induced remission lasted for 6 mo. Preclinical studies published concurrently with the patient's treatment showed that the BRAF in-frame mutation (ΔNVTAP) induces oncogenic activation by a mechanism distinct from that induced by V600E, and that this difference dictates the responsiveness to different BRAF inhibitors. This study describes a dramatic instance of how high-level genomic technology and analysis was necessary and sufficient to identify a clinically logical treatment option that was then utilized and shown to be of clinical value for this individual.

Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome (RNA and miRNA) sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those withNUP98rearrangements, somatic mutations ofWT1in the absence ofNUP98mutations, and additional recurrent variants including those inKMT2CandMLLT10.Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles ofFRMD8,DHX32,PIK3R1,SHANK3,MKLN1, as well as persistence ofWT1andTP53mutant clones, and elimination or contraction ofFLT3,PTPN11, andNRASmutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

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 and superenhancers, enriched in breast and ovarian cancers. Rigma comprise “chasms” of low-JCN deletions at late-replicating fragile sites, enriched in gastrointestinal carcinomas. Tyfonas are “typhoons” of high-JCN junctions and fold-back inversions enriched in expressed protein-coding fusions and breakend hypermutation, frequently found in acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. Methods A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. Results WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. Conclusion These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

NUTM1-rearranged tumors are defined by the presence of a gene fusion between NUTM1 and various gene partners and typically follow a clinically aggressive disease course with poor outcomes despite conventional multimodality therapy. NUTM1-rearranged tumors display histologic features of a poorly differentiated carcinoma with areas of focal squamous differentiation and typically express the BRD4–NUTM1 fusion gene defining a distinct clinicopathologic entity—NUT carcinoma (NC). NCs with mesenchymal differentiation have rarely been described in the literature. In this report, we describe the characterization of two cases of high-grade spindle cell sarcoma harboring a novel MGA–NUTM1 fusion. Whole-genome sequencing identified the presence of complex rearrangements resulting in a MGA–NUTM1 fusion gene in the absence of other significant somatic mutations. Genetic rearrangement was confirmed by fluorescence in situ hybridization, and expression of the fusion gene product was confirmed by transcriptomic analysis. The fusion protein was predicted to retain nearly the entire protein sequence of both MGA (exons 1–22) and NUTM1 (exons 3–8). Histopathologically, both cases were high-grade spindle cell sarcomas without specific differentiation markers. In contrast to typical cases of NC, these cases were successfully treated with aggressive local control measures (surgery and radiation) and both patients remain alive without disease. These cases describe a new subtype of NUTM1-rearranged tumors warranting expansion of diagnostic testing to evaluate for the presence of MGA–NUTM1 or alternative NUTM1 gene fusions in the diagnostic workup of high-grade spindle cell sarcomas or small round blue cell tumors of ambiguous lineage.

Next-generation DNA sequencing (NGS) technologies are currently being applied in both research and clinical settings for the understanding and management of disease. The goal is to use high-throughput sequencing to identify specific variants that drive tumorigenesis within each individual's tumor genomic profile. The significance of copy number and structural variants in glioblastoma makes it essential to broaden the search beyond oncogenic single nucleotide variants toward whole genome profiles of genetic aberrations that may contribute to disease progression. The heterogeneity of glioblastoma and its variability of cancer driver mutations necessitate a more robust examination of a patient's tumor genome. Here, we present patient whole genome sequencing (WGS) information to identify oncogenic structural variants that may contribute to glioblastoma pathogenesis. We provide WGS protocols and bioinformatics approaches to identify copy number and structural variations in 41 glioblastoma patient samples. We present how WGS can identify structural diversity within glioblastoma samples. We specifically show how to apply current bioinformatics tools to detect EGFR variants and other structural aberrations from DNA whole genome sequencing and how to validate those variants within the laboratory. These comprehensive WGS protocols can provide additional information directing more precise therapeutic options in the treatment of glioblastoma.

Next-generation DNA sequencing (NGS) technologies are currently being applied in both research and clinical settings for the understanding and management of disease. The goal is to use high-throughput sequencing to identify specific variants that drive tumorigenesis within each individual's tumor genomic profile. The significance of copy number and structural variants in glioblastoma makes it essential to broaden the search beyond oncogenic single nucleotide variants toward whole genome profiles of genetic aberrations that may contribute to disease progression. The heterogeneity of glioblastoma and its variability of cancer driver mutations necessitate a more robust examination of a patient's tumor genome. Here, we present patient whole genome sequencing (WGS) information to identify oncogenic structural variants that may contribute to glioblastoma pathogenesis. We provide WGS protocols and bioinformatics approaches to identify copy number and structural variations in 41 glioblastoma patient samples. We present how WGS can identify structural diversity within glioblastoma samples. We specifically show how to apply current bioinformatics tools to detect EGFR variants and other structural aberrations from DNA whole genome sequencing and how to validate those variants within the laboratory. These comprehensive WGS protocols can provide additional information directing more precise therapeutic options in the treatment of glioblastoma.

We developed and validated a clinical whole-genome and transcriptome sequencing (WGTS) assay that provides a comprehensive genomic profile of a patient's tumor. The ability to fully capture the mappable genome with sufficient sequencing coverage to precisely call DNA somatic single nucleotide variants, insertions/deletions, copy number variants, structural variants, and RNA gene fusions was analyzed. New York State's Department of Health next-generation DNA sequencing guidelines were expanded for establishing performance validation applicable to whole-genome and transcriptome sequencing. Whole-genome sequencing laboratory protocols were validated for the Illumina HiSeq X Ten platform and RNA sequencing for Illumina HiSeq2500 platform for fresh or frozen and formalin-fixed, paraffin-embedded tumor samples. Various bioinformatics tools were also tested, and CIs for sensitivity and specificity thresholds in calling clinically significant somatic aberrations were determined. The validation was performed on a set of 125 tumor normal pairs. RNA sequencing was performed to call fusions and to confirm the DNA variants or exonic alterations. Here, we present our results and WGTS standards for variant allele frequency, reproducibility, analytical sensitivity, and present limit of detection analysis for single nucleotide variant calling, copy number identification, and structural variants. We show that The New York Genome Center WGTS clinical assay can provide a comprehensive patient variant discovery approach suitable for directed oncologic therapeutic applications.

Reliable detection of somatic variations is of critical importance in cancer research. Here we present Lancet, an accurate and sensitive somatic variant caller, which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored de Bruijn graphs. We demonstrate, through extensive experimental comparison on synthetic and real whole-genome sequencing datasets, that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system, which is essential for variant prioritization, and detects low-frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local-assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

Reliable detection of somatic variations is of critical importance in cancer research. Lancet is an accurate and sensitive somatic variant caller which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored DeBruijn graphs. Extensive experimental comparison on synthetic and real whole-genome sequencing datasets demonstrates that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system which is essential for variant prioritization and detects low frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

Genomic rearrangements are a hallmark of human cancers. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an active DNA transposase expressed in the majority of childhood solid tumors, including lethal rhabdoid tumors. Using assembly-based whole-genome DNA sequencing, we found previously undefined genomic rearrangements in human rhabdoid tumors. These rearrangements involved PGBD5-specific signal (PSS) sequences at their breakpoints, recurrently inactivating tumor suppressor genes. PGBD5 was physically associated with genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. Ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote cell transformation in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced structural rearrangements with PSS breakpoints. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

Objective:To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each.Methods:Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs.Results:More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts.Conclusions:The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible.ClinicalTrials.gov identifier:NCT02725684.

Following publication of the original article [1], it was reported that the given name of the fourteenth author was incorrectly published. The incorrect and the correct names are given below.

Survival for children with acute myeloid leukemia (AML) remains low, with a primary induction remission failure rate of 10-15%. Although some mutations have been identified that are associated with increased relapse risk, the genomic landscape of pediatric AML resistant to primary chemotherapy is not well characterized. As part of the TARGET initiative (Therapeutically Applicable Research To Generate Effective Treatments), we assembled a cohort of 28 pediatric AML patients with primary chemotherapy resistance and failure of induction chemotherapy, uniformly treated as part of the COG AAML0531 study. We analyzed whole-genome DNA, mRNA, and miRNA sequence data obtained at diagnosis and after induction chemotherapy. At least three genetically distinct groups were apparent in this cohort, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of NUP98 variants, and additional recurrent variants including those in KMT2C and MLLT10. Comparisons of mutations before and after chemotherapy revealed both common and distinct gene expression programs. On chemotherapy exposure, these leukemias exhibited diverse forms of clonal evolution. We observed selection for mutant alleles of FRMD8, DHX32, PIK3R1, SHANK3, MKLN1, as well as persistence of WT1 and TP53 mutant clones, and elimination or contraction of FLT3, PTPN11, and NRAS mutant clones. These findings suggest diverse genetic mechanisms for primary chemotherapy resistance in pediatric AML, which should guide new approaches for its diagnosis and therapy. Citation Format: Nicole McNeer, John Philip, Heather Geiger, Rhonda E. Ries, Vincent-Philippe Lavallee, Michael Walsh, Minita Shah, Kanika Arora, Anne-Katrin Emde, Nicolas Robine, Todd A. Alonzo, E. Anders Kolb, Alan S. Gamis, Malcom Smith, Daniela Se Gerhard, Jaime Guidry-Auvil, Soheil Meshinchi, Alex Kentsis. Genetic mechanisms of primary chemotherapy resistance in pediatric acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2870.

NUTM1-rearranged tumors are defined by the presence of a gene fusion between NUTM1 and various gene partners and typically follow a clinically aggressive disease course with poor outcomes despite conventional multimodality therapy. NUTM1-rearranged tumors display histologic features of a poorly differentiated carcinoma with areas of focal squamous differentiation and typically express the BRD4–NUTM1 fusion gene defining a distinct clinicopathologic entity—NUT carcinoma (NC). NCs with mesenchymal differentiation have rarely been described in the literature. In this report, we describe the characterization of two cases of high-grade spindle cell sarcoma harboring a novel MGA–NUTM1 fusion. Whole-genome sequencing identified the presence of complex rearrangements resulting in a MGA–NUTM1 fusion gene in the absence of other significant somatic mutations. Genetic rearrangement was confirmed by fluorescence in situ hybridization, and expression of the fusion gene product was confirmed by transcriptomic analysis. The fusion protein was predicted to retain nearly the entire protein sequence of both MGA (exons 1–22) and NUTM1 (exons 3–8). Histopathologically, both cases were high-grade spindle cell sarcomas without specific differentiation markers. In contrast to typical cases of NC, these cases were successfully treated with aggressive local control measures (surgery and radiation) and both patients remain alive without disease. These cases describe a new subtype of NUTM1-rearranged tumors warranting expansion of diagnostic testing to evaluate for the presence of MGA–NUTM1 or alternative NUTM1 gene fusions in the diagnostic workup of high-grade spindle cell sarcomas or small round blue cell tumors of ambiguous lineage.

Genomic rearrangements are a hallmark of human cancers. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as encoding an active DNA transposase expressed in the majority of childhood solid tumors, including lethal rhabdoid tumors. Using assembly-based whole-genome DNA sequencing, we found previously undefined genomic rearrangements in human rhabdoid tumors. These rearrangements involved PGBD5-specific signal (PSS) sequences at their breakpoints and recurrently inactivated tumor-suppressor genes. PGBD5 was physically associated with genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. Ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote cell transformation in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain as well as end-joining DNA repair and induced structural rearrangements with PSS breakpoints. These results define PGBD5 as an oncogenic mutator and provide a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

e21534Background: Uveal melanoma (UM) is characterized by a long latency period between the time of initial diagnosis and the development of metastatic disease, with a limited understanding of geno...

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. Thus, PGBD5 defines a distinct class of oncogenic mutators and induces site-specific somatic DNA rearrangements in human cancer. Citation Format: Anton G. Henssen, Richard Koche, Jiali Zhuang, Eileen Jiang, Casie Reed, Amy Eisenberg, Eric Still, Elias Rodríguez-Fos, Santiago Gonzalez, Montserrat Puiggròs, Andrew N. Blackford, Christopher E. Mason, Elisa de Stanchina, Mithat Gönen, Anne-Katrin Emde, Minita Shah, Kanika Arora, Catherine Reeves, Nicholas D. Socci, Elizabeth Perlman, Cristina R. Antonescu, Charles W. Roberts, Hanno Steen, Elizabeth Mullen, Stephen P. Jackson, David Torrents, Zhiping Weng, Scott A. Armstrong, Alex Kentsis. Human PGBD5 DNA transposase promotes site-specific oncogenic mutations in rhabdoid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4888. doi:10.1158/1538-7445.AM2017-4888

Current adjuvant therapeutic options for the treatment of Glioblastoma (GBM) are often determined by limited histological information. Additionally, most GBM clinical trials for targeted chemotherapeutic agents do not distinguish the genetic mutational tumor profiles of the patients recruited and have failed to reach successful treatment endpoints. The New York Genome Center (NYGC) has undertaken a glioblastoma clinical sequencing outcome pilot study to better determine personal treatment options for patients with GBM using integrated genomic data. During the initial phase of this study for 2015 NYGC has performed whole genome sequencing (WGS) on 10 primary GBM tumor-normal pairs, analyzed each patient's tumor for single nucleotide variants, structural variants and copy number alterations. In addition RNA sequencing and a DNA methylation assay were also performed on several of the patients. The patient's genomic profile was then compared to a database of known targeted therapeutic approaches. A final tumor board composed of NYGC scientists, GBM consortium scientists and treating oncologists then reviewed all data prior to identifying a final therapeutic strategy. Data from the first 10 patients revealed RB1 variants to be predominant in half of the patients. SNV's in NF1 or PIK3R1 were also discovered in 4 out of 10 samples. Remaining lower frequency variants occurred in TP53, PDGFRA, PTEN, PIK3CA, ERBB3, SMO, STAG2, ACVR1, NFKB1 and JAK3. Analysis of copy number alterations resulted in 8 of 10 patients containing the characteristic chromosome 7 amplification combined with chromosome 10 deletion, affecting EGFR and PTEN, respectively. Extreme amplification with potential double minute structural variation of EGFR containing the A289V mutation was observed in 2 of 10 samples. Two samples contained a potentially targetable over-amplification of the PDGFRA/KIT/KDR chromosome 4 locus. Predominant deletions resided in CDKN2A, ESR2, PTEN and FLT3. Hemizygous deletions of RB1 combined with RB1 nonsense or missense variants were observed in 4 samples. To date, RNA sequencing was performed on 5 patient samples. Most strikingly the combination of DNA and RNA sequencing revealed the presence of a putative activating MET exon skipping event in the extracellular domain. This MET variant was considered as a potential targetable variant. Therapeutic options resulting from WGS genomic profiles were the PI3K inhibitor BKM120 (60%), half of these had an additional aberration in MET and were recommended for the combinatorial trial NCT01870726. Drug recommendations for the treatment of GBM based on specific N = 1 patient genomic profiles were also made for nilotinib, vismodegib and palbociclib. Here, we present the first phase of the NYGC GBM clinical outcome study demonstrating how patient WGS information can provide more precise therapeutic options in the treatment of glioblastoma. Citation Format: Kazimierz O. Wrzeszczynski, Nicolas Robine, Vladimir Vacic, Anne-Katrin Emde, Bo-Juen Chen, Will Liao, Kanika Arora, Minita Shah, Ewa A. Grabowska, Vanessa Felice, Esra Dikoglu, Catherine Reeves, Mayu Frank, Vaidehi Jobanputra, Michael C. Zody, Toby Bloom, Robert B. Darnell. NYGC glioblastoma clinical outcomes pilot study: Discovering therapeutic potential in glioblastoma through integrative genomics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4497.

Whole genome and targeted sequencing data have just started to revolutionize clinical care for cancer patients. Based on genetic variants in each tumor, clinicians can tailor treatment options for patients. While genomic sequencing data provide the landscapes of genetic variants, RNA-seq data can provide complementary information and allow us to interpret the functional effects of discovered variants. However, N-of-1 analysis with RNA-seq data poses several challenges, including integration with DNA data and normalization of gene expression. To tackle these challenges, we developed RNA analytics for integrative analysis for tumor samples in a clinical setting. For variant analysis, we use RNA to validate somatic variants (both SNVs and indels) and to elucidate potential functional effects of the variants. Because RNA-seq has different coverage patterns from WGS, we developed tools to calculate and compare variant allele frequency in both DNA and RNA data, which allows us to validate variants and evaluate allelic expression. Additionally, leveraging on RNA-seq, our tools look for evidence of aberrant splicing events, such as exon skipping and intron retention that are caused by genetic variants. These analyses not only provide an integrative view of the data, but also prioritize variants and potentially reveal variant effects. Because many cancers are driven by fusion genes and some fusion genes are recurrent in GBM, we use our data to detect gene fusion supported by RNA-Seq, and if possible by WGS. We use FusionCatcher and STAR-Fusion, coupled with OncoFuse to discover and annotate fusions in RNA-Seq. We subsequently look for supporting evidence by any of the structural variant callers we use. Gene expression quantification is most valuable as a comparative measurement. However, this is challenging for N-of-1 analysis, since such assessment requires proper normalization and comparison to a proper cohort. Batch-effects due to library preparation and other covariates exacerbate the issue of normalization. We tackle this issue with various normalization and correction strategies. Utilizing GC-bias correction, batch-effect adjustment, and public datasets, our analytic provides gene expression measurement that allows researcher to interpret whether the gene is up- or down-regulated compared to a cohort (such as TCGA). Our RNA analytics comprehensively utilize transcriptomic data and provides solutions to integrative analysis. We have applied our tools to sequence data from five glioblastoma patients and showed how RNA-seq can compliment WGS. Our integrative analysis helps identify an exon-skipping event in MET in one patient, which was validated with Sanger sequencing. The expression analysis also helps identify potential aberrant activity of the SMO pathway, possibly driven by a SMO missense mutation and loss of SUFU. Citation Format: Bo-Juen R. Chen, Nicolas Robine, Kazimierz Wrzeszczynski, Vladimir Vacic, Anne Katrin Emde, Kanika Arora, Minita Shah, Ewa A. Grabowska, Vanessa Felice, Esra Dikoglu, Catherine Reeves, Mayu Frank, Vaidehi Jobanputra, Michael C. Zody, Toby Bloom, Robert Darnell. RNA-Seq in the NYGC GBM Clinical Outcomes Pilot Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4498.

Detection and characterization of somatic structural variants (SVs) and copy-number variants (CNVs) from whole genome sequencing remains a challenging part of cancer analysis. Many callers have been developed that use different detection strategies, but most methods suffer from high rates of false positives and false negatives, and agreement between different callers is usually low. We have developed a flexible pipeline that combines the results of multiple callers, filters calls to remove likely artifacts, and functionally annotates the resulting variants. We employ a diverse set of variant callers utilizing a combination of read depth, read pair, and split read detection methods: NBIC-seq (Xi et al., 2011), Crest (Wang et al., 2011), Delly (Rausch et al., 2012), and BreakDancer (Chen et al., 2009). To remove artifact calls due to mis-mapping, we apply filters that discard predicted SVs whose breakpoints exhibit certain sequence features (e.g. extensive mapping ambiguity, high repeat content). SVs corresponding to known germline variants (1000G, DGV, in-house database) are marked and removed as unlikely somatic variants: this greatly helps to prevent both sequencing protocol- and caller-specific artifacts as well as false positive somatic calls arising from missed calls in the matched germline sample. Finally, we employ our sensitive split read mapper SplazerS to identify SV breakpoints with base pair precision. In this step, we are also able to remove remaining germline variants for which we find split read support in the matched normal sample. The final predicted structural variants are annotated for overlap with SVs in COSMIC, overlap with known cancer genes and potential impact on gene structure. We use a public synthetic data set (DREAM challenge; Boutros et al., 2014) to demonstrate that using our selected ensemble of tools significantly improves sensitivity as compared to any single caller and that our filters effectively remove artifacts. Further, we show results from a set of colorectal cancer samples (Brannon et al., 2014) in which highly similar primary and metastatic tumors show excellent agreement in somatic SV calls in the absence of overlap between unrelated samples. Results from testing our pipeline on TCGA glioblastoma multiforme tumors, for which validated genomic rearrangements are available, will also be presented. In conclusion, our pipeline improves detection of SVs by integrating orthogonal calling methods and facilitates identification of clinically relevant SVs through effective filters and cancer-specific functional annotation. Citation Format: Minita Shah, Dayna M. Oschwald, Soren Germer, Michael C. Zody, Toby Bloom, Anne-Katrin Emde. An integrated pipeline for detecting and characterizing structural variation in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4876. doi:10.1158/1538-7445.AM2015-4876