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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.

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