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Supplementary Data from Bone Marrow Surveillance of Pediatric Cancer Survivors Identifies Clones that Predict Therapy-Related Leukemia

Supplementary Figure from Bone Marrow Surveillance of Pediatric Cancer Survivors Identifies Clones that Predict Therapy-Related Leukemia

Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses.MYCgain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such asCCNE1,RAD21,VEGFA, andIGF1R, were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.SignificanceSubclonal copy number clones emerged and dominated in relapsed osteosarcoma, withMYCgain/amplification being the defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy revealed this clone at the time of primary resection, highlighting that genomic profiling at this time may identify clones that are selected for, or determine innate resistance to primary chemotherapy.

High-risk neuroblastoma is generally metastatic and often lethal. Using genomic profiling of 470 sequential and spatially separated samples from 283 patients, we characterize subtype-specific genetic evolutionary trajectories from diagnosis, through progression and end-stage metastatic disease. Clonal tracing timed disease initiation to embryogenesis. Continuous acquisition of structural variants at disease defining loci (MYCN, TERT, MDM2-CDK4) followed by convergent evolution of mutations targeting shared pathways emerged as the predominant feature of progression. At diagnosis metastatic clones were already established at distant sites where they could stay dormant, only to cause relapses years later and spread via metastasis-to-metastasis and polyclonal seeding after therapy.

Objective: The osteosarcoma genome is characterized by high levels of genomic instability, however whether there is pervasive ongoing genomic instability, or instability introduced by an early catastrophic event, is still unsettled. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and one sample from a metastatic or relapse site. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an analysis focused on markers of genomic instability was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 pretreatment biopsies, 10 on therapy primary resections, 20 metastatic sites, 15 of which were from lung metastases. We have previously reported on the clonal evolution regarding SNVs and CNAs within this cohort. TP53 structural variants involving intron 1/2 were seen in 6/8 patients (OSCE2, OSCE3, OSCE4, OSCE6, OSCE9, OSCE10). No new structural variants in consensus driver genes emerged in metastatic or relapse samples. Comparing the earliest sample to most recent sample in each patient, only OSCE1, OSCE9, and OSCE10 demonstrated an increase of ≥100 structural variants at the final timepoint. In OSCE2, OSCE5, and OSCE6, there were less structural variants identified at the final timepoint when compared to the earliest timepoint. Homologous recombination deficiency (HRD) scores were calculated for each sample. Only 4/8 patients (OSCE3, OSCE4, OSCE9, OSCE10) had an HRD score in the most recently acquired sample higher than the score from the primary site. Regions of hypermutation consistent with kataegis were identified for each sample, with the number of kataegis events remaining unchanged or decreasing in some instances. Kataegis events co-localized with rearrangement events a majority of the time (range 50-100%, Avg= 72.6%). Complex rearrangements such as chromothripsis and chromoplexy were assesed. In 6 patients there were > 9 chromosomal arms involved in complex rearrangements that were shared between primary sites and metastatic/recurrent sites, while ≤ 4 chromosomal arms were involved with new complex rearrangements unique to the metastatic sites. Conclusion: The patterns observed in our cohort reveal that osteosarcoma is relatively stable from diagnosis through subsequent relapses, supporting the model that an early catastrophic event accounts for the genomic instability observed in osteosarcoma. Citation Format: Michael David Kinnaman, Simone Zaccaria, Alvin Makohon-Moore, Gunes Gundem, Juan E. Arango Ossa, Filemon S. Dela Cruz, Paul A. Meyers, Meera Hameed, William D. Tap, Julia Lynne Glade Bender, Elli Papaemmanuil, Andrew Kung, Christine Iacobuzio Donahue. Assessing patterns of genomic instability in recurrent osteosarcoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3556.

Despite a detailed understanding of the genes mutated in myelodysplastic syndromes (MDS), diagnostic and treatment decisions for patients with MDS rely primarily on clinical and cytogenetic variables as considered by the Revised International Prognostic Scoring System (IPSS-R). Here we describe the recently developed Molecular IPSS (IPSS-M), a clinico-genomic risk stratification system that considers clinical, cytogenetic and genetic parameters; the implementation of a web portal to facilitate its adoption, a strategy to handle missing variables, and the worldwide utilization of the web calculator as a clinical support tool. The IPSS-M was trained on 2,957 clinically annotated diagnostic MDS samples profiled for mutations in 156 driver genes. To maximize the clinical applicability of the IPSS-M and account for missing genetic data (i.e genes missing from a sequencing panel), we implemented a strategy to calculate a risk score under three scenarios: best, worst and average. Last, we developed an online calculator as a standalone single-page web application using VueJs, and D3Js for the interactive visualizations, deployed through a CI/CD pipeline on AWS, where collection of anonymous usage analytics allows to track adoption and usability of the new proposed model. The model incorporates clinical, morphological, genetic variables informed by cytogenetics and constructed from the presence of oncogenic mutations in 31 genes. It delivers a unique risk score for each individual patient, as well as an assignment to one of six IPSS-M risk strata. Compared to the IPSS-R the IPSS-M re-stratified 46% of MDS patients. The model was validated in an external dataset of 754 MDS patients. We released an open-access IPSS-M web calculator available at https://mds-risk-model.com. By specifying the patient clinical and molecular profiles, the tool returns the patient-specific IPSS-M risk score and category, and the probability estimates over time for three clinical endpoints, i.e. leukemia free survival (LFS), overall survival, and incidence of leukemic transformation. Since its launch in June 2022, the calculator has been used by >6000 users in >75 countries, reaching a daily average of 100 users per day. Risks have been calculated for >45,000 patient profiles. 99.28% of the sessions initiated reach an IPSS-M score, suggesting that the calculator is intuitive and easy to use. We trained and validated the IPSS-M on 3,711 patients, a patient tailored risk stratification tool for patients with MDS that considers clinical, morphological and genetic variables inclusive of cytogenetics and mutations in one of 31 genes. The development of a web based tool was instrumental to the global dissemination of the model, enabling non-expert users to leverage the power of molecular biomarkers in risk stratification for patients with MDS. Citation Format: Elsa Bernard, Juan E. Arango Ossa, Heinz Tuechler, Peter L. Greenberg, Robert P. Hasserjian, Yasuhito Nannya, Sean M. Devlin, Maria Creignou, Philippe Pinel, Lily Monier, Juan S. Medina-Martinez, Dylan Domenico, Martin Jädersten, Ulrich Germing, Guillermo Sanz, Arjan A. van de Loosdrecht, Olivier Kosmider, Matilde Y. Follo, Felicitas Thol, Lurdes Zamora, Ronald F. Pinheiro, Andrea Pellagatti, Detlef Haase, Pierre Fenaux, Monika Belickova, Michael R. Savona, Virginia M. Klimek, Fabio P. Santos, Jacqueline Boultwood, Ioannis Kotsianidis, Valeria Santini, Francesc Solé, Uwe Platzbecker, Michael Heuser, Peter Valent, Kazuma Ohyashiki, Carlo Finelli, Maria Teresa Voso, Lee-Yung Shih, Michaela Fontenay, Joop H. Jansen, José Cervera, Norbert Gattermann, Benjamin L. Ebert, Rafael Bejar, Luca Malcovati, Mario Cazzola, Seishi Ogawa, Eva Hellström-Lindberg, Elli Papaemmanuil. Implementation and adoption of a web tool to support precision diagnostic and treatment decisions for patient with myelodysplastic syndromes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6168.

Stably acquired mutations in hematopoietic cells represent substrates of selection that may lead to clonal hematopoiesis (CH), a common state in cancer patients that is associated with a heightened risk of leukemia development. Owing to technical and sample size limitations, most CH studies have characterized gene mutations or mosaic chromosomal alterations (mCAs) individually. Here we leverage peripheral blood sequencing data from 32,442 cancer patients to jointly characterize gene mutations (n = 14,789) and mCAs (n = 383) in CH. Recurrent composite genotypes resembling known genetic interactions in leukemia genomes underlie 23% of all detected autosomal alterations, indicating that these selection mechanisms are operative early in clonal evolution. CH with composite genotypes defines a patient group at high risk of leukemia progression (3-year cumulative incidence 14.6%, CI: 7–22%). Multivariable analysis identifies mCA as an independent risk factor for leukemia development (HR = 14, 95% CI: 6–33, P, Patients with solid cancers have high rates of clonal haematopoiesis associated with increased risk of secondary leukemias. Here, by using peripheral blood sequencing data from patients with solid non-hematologic cancer, the authors profile the landscape of mosaic chromosomal alterations and gene mutations, defining patients at high risk of leukemia progression.

Background The widespread adoption of high throughput technologies has democratized data generation. However, data processing in accordance with best practices remains challenging and the data capital often becomes siloed. This presents an opportunity to consolidate data assets into digital biobanks—ecosystems of readily accessible, structured, and annotated datasets that can be dynamically queried and analysed. Results We present Isabl, a customizable plug-and-play platform for the processing of multimodal patient-centric data. Isabl's architecture consists of a relational database (Isabl DB), a command line client (Isabl CLI), a RESTful API (Isabl API) and a frontend web application (Isabl Web). Isabl supports automated deployment of user-validated pipelines across the entire data capital. A full audit trail is maintained to secure data provenance, governance and ensuring reproducibility of findings. Conclusions As a digital biobank, Isabl supports continuous data utilization and automated meta analyses at scale, and serves as a catalyst for research innovation, new discoveries, and clinical translation.

Recent genomic research efforts in multiple myeloma have revealed clinically relevant molecular subgroups beyond conventional cytogenetic classifications. Implementing these advances in clinical trial design and in routine patient care requires a new generation of molecular diagnostic tools. Here, we present a custom capture next-generation sequencing (NGS) panel designed to identify rearrangements involving the IGH locus, arm level, and focal copy number aberrations, as well as frequently mutated genes in multiple myeloma in a single assay. We sequenced 154 patients with plasma cell disorders and performed a head-to-head comparison with the results from conventional clinical assays, i.e., fluorescent in situ hybridization (FISH) and single-nucleotide polymorphism (SNP) microarray. Our custom capture NGS panel had high sensitivity (>99%) and specificity (>99%) for detection of IGH translocations and relevant chromosomal gains and losses in multiple myeloma. In addition, the assay was able to capture novel genomic markers associated with poor outcome such as bi-allelic events involving TP53. In summary, we show that a multiple myeloma designed custom capture NGS panel can detect IGH translocations and CNAs with very high concordance in relation to FISH and SNP microarrays and importantly captures the most relevant and recurrent somatic mutations in multiple myeloma rendering this approach highly suitable for clinical application in the modern era.

Purpose: Therapy-related myelodysplastic syndrome and acute leukemias (t-MDS/AL) are a major cause of nonrelapse mortality among pediatric cancer survivors. Although the presence of clonal hematopoiesis (CH) in adult patients at cancer diagnosis has been implicated in t-MDS/AL, there is limited published literature describing t-MDS/AL development in children. Experimental Design: We performed molecular characterization of 199 serial bone marrow samples from 52 patients treated for high-risk neuroblastoma, including 17 with t-MDS/AL (transformation), 14 with transient cytogenetic abnormalities (transient), and 21 without t-MDS/AL or cytogenetic alterations (neuroblastoma-treated control). We also evaluated for CH in a cohort of 657 pediatric patients with solid tumor. Results: We detected at least one disease-defining alteration in all cases at t-MDS/AL diagnosis, most commonly TP53 mutations and KMT2A rearrangements, including involving two novel partner genes (PRDM10 and DDX6). Backtracking studies identified at least one t-MDS/AL-associated mutation in 13 of 17 patients at a median of 15 months before t-MDS/AL diagnosis (range, 1.3–32.4). In comparison, acquired mutations were infrequent in the transient and control groups (4/14 and 1/21, respectively). The relative risk for development of t-MDS/AL in the presence of an oncogenic mutation was 8.8 for transformation patients compared with transient. Unlike CH in adult oncology patients, TP53 mutations were only detectable after initiation of cancer therapy. Last, only 1% of pediatric patients with solid tumor evaluated had CH involving myeloid genes. Conclusions: These findings demonstrate the clinical relevance of identifying molecular abnormalities in predicting development of t-MDS/AL and should guide the formation of intervention protocols to prevent this complication in high-risk pediatric patients.

Objective: Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and one sample from a metastatic or relapse site. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an evolutionary analysis was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 were pretreatment biopsies, 10 from on therapy primary resections. 20 samples came from metastatic sites, 15 of which were from lung metastases. Driver gene SNV’s were identified in 5 of 8 patients, including TP53 (OSCE1), ATRX (OSCE3, OSCE10), RB1 (OSCE4), and CDKN2A (OSCE9). There were no new driver SNV’s that emerged post-therapy in any patient. HATCHet, an algorithm that infers clone-specific copy number alterations, identified subclonal CNAs in all but one patient (OSCE2). In the 7 patients with subclonal CNAs, 6 had two copy number clones identified, and 1 patient (OSCE10) had three copy number clones identified. In 5 patients (OSCE1, OSCE4, OSCE5, OSCE6, OSCE10) there is a copy number clone that is subclonal in the primary tumor which emerges and dominates at subsequent relapses. The resistant clone in each of these cases had either MYC gain/amplification. Amplifications in CCNE1 (OSCE1), RAD21 (OSCE4, OSCE5, OSCE10), VEGFA (OSCE1, OSCE9), IGF1R (OSCE6) were also identified as potential drivers in the resistant copy number clones. In two of these patients (OSCE1, OSCE6), this treatment-resistant subclone becomes the dominant copy number clone by the time of primary resection. SNV based phylogenies revealed a heterogenous mix of monoclonal and polyclonal seeding of metastases and monophyletic and polyphyletic modes of dissemination. Over half the new mutations acquired in recurrent disease were attributed to HRD or cisplatin mutational signatures. TP53 structural variants were seen in 6/8 patients (OSCE2, OSCE3, OSCE4, OSCE6, OSCE9, OSCE10). New structural variants involving driver genes were only detected in one relapse sample from patient OSCE10 (DMD deletion). Conclusion: Subclonal copy number clones emerge and dominate in relapsed osteosarcoma, with MYC gain/amplification a defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy reveals this clone at the time of primary resection, highlighting that genomic profiling at this time point may be more reflective of its metastatic potential. Citation Format: Michael D. Kinnaman, Simone Zaccaria, Alvin Makohon-Moore, Gunes Gundem, Juan E. Arango Ossa, Nancy Bouvier, Filemon S. Dela Cruz, Meera Hameed, Julia Lynne Glade Bender, William D. Tap, Paul Meyers, Elli Papaemmanuil, Andrew Kung, Christine A. Iacobuzio-Donahue. Subclonal somatic copy number alterations emerge and dominate in relapsed/refractory osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B022.

The goal of therapy for essential thrombocythemia (ET) and polycythemia vera (PV) patients is to reduce thrombotic events by normalizing blood counts. Hydroxyurea (HU) and interferon-α (IFN-α) are the most frequently used cytoreductive options for ET and PV patients at high-risk for vascular complications. Myeloproliferative Disorders Research Consortium 112 was an investigator-initiated, phase 3 trial comparing HU to pegylated IFN-α (PEG) in treatment naïve, high-risk ET/PV patients. The primary endpoint was complete response (CR) rate at 12 months. A total of 168 patients were treated for a median of 81.0 weeks. CR for HU was 37% and 35% for PEG (p=0.80) at 12 months. At 24/36 months, CR was 20%/17% for HU and 29%/33% for PEG. PEG led to a greater reduction in JAK2V617F at 24 months, but histopathologic responses were more frequent with HU. Thrombotic events and disease progression were infrequent in both arms, while grade 3/4 adverse events were more frequent with PEG (46% vs. 28%). At 12 months of treatment there was no significant difference in CR rates between HU and PEG. This study indicates that PEG and HU are both effective treatments for PV and ET. With longer treatment PEG was more effective in normalizing blood counts and reducing driver mutation burden, while HU produced more histopathologic responses. Despite these differences, both agents did not differ in limiting thrombotic events and disease progression in high-risk ET/PV patients. (Funded by the National Cancer Institute, 5P01CA108671-09; clinicaltrials.gov number (NCT01259856). [Abstract copyright: Copyright © 2022 American Society of Hematology.]

Background: Recapitulation of the full spectrum of genomic changes driving patient tumors have resulted in increased use of patient-derived xenograft (PDX) models in studies of basic cancer biology and preclinical drug development. Given the translational potential of PDXs and limited availability of pediatric cancer models, we established a PDX program to expand the existing collection of pediatric PDXs in the community and enable pre- and post-clinical studies. Methods: PDX generation requests were integrated into clinical workflows to maximize identification of eligible patients for informed consent and tissue collection at Memorial Sloan Kettering Cancer Center. Methodologies for tissue procurement and cryopreservation were optimized to facilitate implantation into host immunodeficient mice and enable multi-institutional tissue exchange for model building. A bioinformatics pipeline was established to allow molecular validation of engrafted PDXs using a next-generation targeted gene panel (MSK-IMPACT) evaluating concordance based on acquired mutations, copy number alterations and clonal structure. Results: Between November 2016 - October 2021, 379 PDX models were developed (265 distinct models) representing 69 discrete diagnoses. Sarcoma represents the most common model type (50 discrete osteosarcoma, 20 desmoplastic small round cell tumor, 14 Ewing sarcoma, 24 rhabdomyosarcoma, 2 CIC/DUX4 and 2 BCOR-rearranged sarcoma) followed by neuroblastoma (n=35), leukemia (n=44), and Wilms tumor (n=15). While the majority of PDXs were established from recurrent or metastatic tissue, 7 paired diagnostic/pre-therapy and post-therapy or relapse models were generated. Genomic characterization of PDXs demonstrate excellent concordance and recapitulation of single nucleotide variants (90%), structural (88%) and copy number variants (94%) between patient tumor and matched PDX. Discrepancies between matched patient/PDX pairs are due to sub-clonal heterogeneity in source tumors with clonal outgrowth in the PDX. Analysis of serial PDX passages also demonstrate stable recapitulation of the genomic profile. Establishment of a diverse PDX collection allowed preclinical evaluation of 10 targeted agents across a spectrum of pediatric tumors and provided the preclinical rationale for 3 investigator-initiated pediatric clinical trials. Conclusions: Investment in the development of a phenotypically diverse and biologically faithful collection of pediatric PDX models enables the goals of precision medicine. Optimization of PDX workflows and methods has also enabled the development of a pediatric PDX consortium (PROXC - Pediatric Research in Oncology Xenografting Consortium) to further support the development of pre- and post-clinical studies for pediatric cancer. Citation Format: Filemon S. Dela Cruz, Joseph G. McCarter, Daoqi You, Nancy Bouvier, Xinyi Wang, Kristina C. Guillan, Armaan H. Siddiquee, Katie B. Souto, Hongyan Li, Teng Gao, Dominik Glodzik, Daniel Diolaiti, Neerav N. Shukla, Joachim Silber, Umeshkumar K. Bhanot, Faruk Erdem Kombak, Diego F. Coutinho, Shanita Li, Juan E. Arango Ossa, Juan S. Medina-Martinez, Michael V. Ortiz, Emily K. Slotkin, Michael D. Kinnaman, Sameer F. Sait, Tara J. O'Donohue, Marissa Mattar, Maximiliano Meneses, Michael P. LaQuaglia, Todd E. Heaton, Justin T. Gerstle, Nicola Fabbri, Chelsey M. Burke, Irene M. Rodriquez-Sanchez, Christine A. Iacobuzio-Donahue, Julia L. Glade Bender, Ryan D. Roberts, Jason T. Yustein, Nino C. Rainusso, Brian D. Crompton, Elizabeth Stewart, Alejandro Sweet-Cordero, Leanne C. Sayles, Andrika D. Thomas, Michael H. Roehrl, Elisa de Stanchina, Elli Papaemmanuil, Andrew L. Kung. Development of a patient-derived xenograft (PDX) modeling program to enable pediatric precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 704.

11533 Background: Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. Methods: We performed 30-80x whole genome sequencing (WGS) of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. A set of high confidence single nucleotide variants (SNV), copy number alterations (CNA), structural variations (SV) were called for each sample using our pediatric expanded genomics pipeline and an evolutionary analysis was performed using a custom pipeline of computational tools. Results: Of the 8 patients in our cohort, 4 had localized disease at diagnosis (OSCE4, OSCE5, OSCE6, OSCE9) and 4 had metastatic disease at diagnosis (OSCE1, OSCE2, OSCE3, OSCE10). There were 17 samples from primary sites, 7 were pretreatment biopsies, 10 from on therapy primary resections. 20 samples came from metastatic sites, 15 of which were from lung metastases. Driver gene SNV’s were identified in 5 of 8 patients, including TP53 (OSCE1), ATRX (OSCE3, OSCE10), RB1 (OSCE4), and CDKN2A (OSCE9). No new driver SNV’s emerged post-therapy in any patient. HATCHet, an algorithm which infers clone specific copy number alterations, identified subclonal CNAs in all but one patient (OSCE2). In the 7 patients with subclonal CNAs, 6 had two copy number clones identified, and 1 patient (OSCE10) had three copy number clones identified. In 5 patients (OSCE1, OSCE4, OSCE5, OSCE6, OSCE10) there is a copy number clone that is subclonal in the primary tumor which emerges and dominates at subsequent relapses. The resistant clone in each of these cases had either MYC gain/amplification. Amplifications in CCNE1 (OSCE1), RAD21 (OSCE4, OSCE5, OSCE10), VEGFA (OSCE1, OSCE9), IGF1R (OSCE6) were also identified as potential drivers in the resistant copy number clones. In two of these patients (OSCE1, OSCE6), the treatment resistant subclone becomes the dominant copy number clone by the time of primary resection. SNV based phylogenies revealed monoclonal and polyclonal seeding of metastases and monophyletic and polyphyletic modes of dissemination. Over half the new mutations acquired in recurrent disease were attributed to HRD or cisplatin mutational signatures. Conclusions: Subclonal copy number clones emerge and dominate in relapsed osteosarcoma, with MYC gain/amplification a defining characteristic in our cohort. Selective pressure from neoadjuvant chemotherapy reveals this clone at the time of primary resection, implying genomic profiling at this timepoint may be more reflective of its metastatic potential. [Table: see text]

Multiple myeloma (MM) progression is characterized by the seeding of cancer cells in different anatomic sites. To characterize this evolutionary process, we interrogated, by whole genome sequencing, 25 samples collected at autopsy from 4 patients with relapsed MM and an additional set of 125 whole exomes collected from 51 patients. Mutational signatures analysis showed how cytotoxic agents introduce hundreds of unique mutations in each surviving cancer cell, detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature. Thus, a unique, single-cell genomic barcode can link chemotherapy exposure to a discrete time window in a patient's life. We leveraged this concept to show that MM systemic seeding is accelerated at relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high-dose melphalan therapy and autologous stem cell transplant.

Myeloproliferative neoplasms (MPN) that have evolved into accelerated or blast phase disease (MPN-AP/BP) have poor outcomes with limited treatment options and therefore represent an urgent unmet need. We have previously demonstrated in a multicenter, phase 1 trial conducted through the Myeloproliferative Neoplasms Research Consortium that the combination of ruxolitinib and decitabine is safe and tolerable and is associated with a favorable overall survival (OS). In this phase 2 trial, 25 patients with MPN-AP/BP were treated at the recommended phase 2 dose of ruxolitinib 25 mg twice daily for the induction cycle followed by 10 mg twice daily for subsequent cycles in combination with decitabine 20 mg/m2 for 5 consecutive days in a 28-day cycle. Nineteen patients died during the study follow-up. The median OS for all patients on study was 9.5 months (95% confidence interval, 4.3-12.0). Overall response rate (complete remission + incomplete platelet recovery + partial remission) was 11/25 (44%) and response was not associated with improved survival. We conclude that the combination of decitabine and ruxolitinib was well tolerated, demonstrated favorable OS, and represents a therapeutic option for this high-risk patient population. This trial was registered at www.clinicaltrials.gov as #NCT02076191.

Tumor protein p53 (TP53) is the most frequently mutated gene in cancer1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease3,4, rapid transformation to acute myeloid leukemia (AML)5, resistance to conventional therapies6–8 and dismal outcomes9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono- and biallelic mutations10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R)11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response. Clinical sequencing across a large prospective cohort of patients with myelodysplasic syndrome uncovers distinct associations between the mono- and biallelic states of TP53 and clinical presentation

Acquired mutations are pervasive across normal tissues. However, understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMNs). We find that mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response genes (TP53, PPM1D, CHEK2). Sequential sampling provides definitive evidence that DNA damage response clones outcompete other clones when exposed to certain therapies. Among cases in which CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies. Environmental exposures shape patterns of selection for mutations in clonal hematopoiesis. Cancer therapies promote the growth of clones with mutations that are strongly enriched in treatment-related myeloid neoplasms.

Multiple myeloma (MM) progression is characterized by the seeding of cancer cells in different anatomic sites. To characterize this evolutionary process, we interrogated, by whole genome sequencing, 25 samples collected at autopsy from 4 patients with relapsed MM and an additional set of 125 whole exomes collected from 51 patients. Mutational signatures analysis showed how cytotoxic agents introduce hundreds of unique mutations in each surviving cancer cell, detectable by bulk sequencing only in cases of clonal expansion of a single cancer cell bearing the mutational signature. Thus, a unique, single-cell genomic barcode can link chemotherapy exposure to a discrete time window in a patient′s life. We leveraged this concept to show that MM systemic seeding is accelerated at relapse and appears to be driven by the survival and subsequent expansion of a single myeloma cell following treatment with high-dose melphalan therapy and autologous stem cell transplant., In multiple myeloma, disease progresses via seeding to different anatomic sites and clonal expansion. Here, utilising autopsy material, the authors show that systemic seeding accelerates at relapse following treatment.

Clonal hematopoiesis (CH) is frequent in cancer patients and associated with increased risk of therapy related myeloid neoplasms (tMN). To define the relationship between CH, oncologic therapy, and tMN progression, we studied 24,439 cancer patients. We show that previously treated patients have increased rates of CH, with enrichment of mutations in DNA Damage Response (DDR) genes (TP53, PPM1D, CHEK2). Exposure to radiation, platinum and topoisomerase II inhibitors have the strongest association with CH with evidence of dose-dependence and gene-treatment interactions. We validate these associations in serial sampling from 525 patients and show that exposure to cytotoxic and radiation therapy imparts a selective advantage specifically in hematopoietic cells with DDR mutations. In patients who progressed to tMN, the clone at CH demarcated the dominant clone at tMN diagnosis. CH mutational features predict risk of therapy-related myeloid neoplasm in solid tumor patients with clinical implications for early detection and treatment decisions.

Background: Patients treated with cytotoxic chemotherapies and/or autologous stem-cell transplantation (ASCT) are at risk for therapy-related myeloid neoplasms (tMN). As these agents yield increased mutation burden in relapsed malignancies and leave evidence of exposure via mutational signatures, we studied the genomic and temporal relationship between chemo exposure and progression of clonal hematopoiesis (CH) to tMN. Methods: We analyzed 32 tMN whole genomes (WG) from 31 patients [27 acute myeloid leukemias (AML), 4 myelodysplastic syndromes]. For 7 patients with tMN post-high-dose melphalan/ASCT, we investigated the presence of antecedent CH using targeted sequencing (MSK-IMPACT; Bolton et al. Nat Gen 2020) on pre-melphalan blood mononuclear cells, granulocytes, or CD34+ apheresis samples. Results: TMN was diagnosed a median of 4.2 years (IQR, 2.6-6.6) following primary treatment. When compared to data from 200 de novo AML from TCGA (NEJM, 2013), tMNs had fewer mutations in FLT3 (9.7% v 28.0%; p = 0.028) and NPM1 (3.2% v 27.0%; p = 0.003). TP53 loss was enriched in tMNs (25.8% v 10.5%; p = 0.035 ). Mutational signature analysis revealed 5 known single base substitution (SBS) signatures in tMN: the hematopoietic stem-cell (SBS-HSC), aging (SBS1), melphalan (SBS-MM1), and platinum signatures (E-SBS1, E-SBS20) (Rustad et al. Nat Comm 2020, Pich et al. Nat Gen 2019). Complex structural variants (SV), defined as ≥3 breakpoint pairs involved in simultaneous copy number changes (Rustad et al. Blood Can Disc 2020), were observed in 7 tMNs; including chromothripsis in 6 tumors (19.4%), chromoplexy in 2 (6.5%), templated insertion in 1 (3.2%), and unspecified complex SV in 2 (6.5%). Chromothripsis has not been previously reported in de novo AML and, in 4 cases, involved chromosome 19 with hyper-amplification of the SMARCA4 locus (≥5 copies). CH variants that became clonal in tumor were seen in 5/7 pre-melphalan/ASCT samples and included mutations in TP53, RUNX1, NCOR1, NF1, CREBBP, DNMT3A, and PPM1D. Chemotherapy introduces hundreds of mutations, leaving each exposed cell with a unique catalogue (i.e., barcode). In fact, TMNs with evidence of chemo signatures had a higher mutation burden (median 1574 single nucleotide variants) than those without (median 938; p = 0.004). Detection of chemo signatures in bulk genome sequencing relies on one cell, with its catalogue of mutations, to expand to clonal dominance (Fig 1a, Landau et al. Nat Comm 2020). Given the long latency between exposure and tMN diagnosis, this single-cell expansion model was expected for all samples exposed to melphalan or platinum-based regimens (i.e., agents with a measurable signature). Strikingly, all patients with pre-tMN platinum exposure (n=7) had evidence of platinum SBS signatures whereas only 2 of 7 patients with prior melphalan/ASCT had a melphalan signature (SBS-MM1). As all platinum-exposed tMN had mutational evidence of exposure, a CH clone must have existed prior to exposure, supporting a single-cell expansion model. Absence of a chemo signature for 5/7 post-melphalan/ASCT tumors despite exposure implies tumor progression driven either by multiple clones in parallel (Fig 1b) or by an unexposed clone. As latency largely excludes the former, this suggests pre-tMN CH clones were re-infused during SCT, thus avoiding chemo exposure (Fig 1c). This is supported by two lines of evidence: 1) tMNs from 2 patients exposed to sequential platinum and melphalan/ASCT had platinum but not melphalan signatures confirming single-cell expansion of the pre-tMN CH clone post-platinum but with escape from exposure to melphalan in the ASCT (Fig 1d); 2) targeted sequencing of pre-tMN samples from melphalan/ASCT patients identified tMN genomic mutations at the CH level in 5/7 cases, including in all 3 tested apheresis samples - one of which (TP53) expanded to dominance without a melphalan signature. Conclusion: WG sequencing identified novel features of tMN revealing the key driver role of complex SV. Mutational signature analyses and targeted sequencing of pre-tMN samples can increase our understanding of tMN pathogenesis and demonstrate that tMNs arising post-ASCT are often driven by CH clones that re-engraft after escaping melphalan exposure. This mode of expansion suggests that a permissive, immunosuppressed, post-transplant environment might play a more important role than chemotherapy-induced mutagenesis in tMN pathogenesis. Figure 1 Figure 1. Disclosures Diamond: Sanofi: Honoraria; Medscape: Honoraria. Watts: Rafael Pharmaceuticals: Consultancy; Genentech: Consultancy; Bristol Myers Squibb: Consultancy; Takeda: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; Aptevo Therapeutices: Research Funding. Kazandjian: Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bradley: AbbVie: Consultancy, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Bolli: Amgen: Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria; Celgene/BMS: Consultancy, Honoraria. Papaemmanuil: Isabl Technologies: Divested equity in a private or publicly-traded company in the past 24 months; Kyowa Hakko Kirin Pharma: Consultancy. Scordo: Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; i3 Health: Other: Speaker; Omeros Corporation: Consultancy; Angiocrine Bioscience: Consultancy, Research Funding; McKinsey & Company: Consultancy. Lahoud: MorphoSys: Membership on an entity's Board of Directors or advisory committees. Stein: Jazz Pharmaceuticals: Consultancy; Foghorn Therapeutics: Consultancy; Blueprint Medicines: Consultancy; Gilead Sciences, Inc.: Consultancy; Abbvie: Consultancy; Janssen Pharmaceuticals: Consultancy; Genentech: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Agios Pharmaceuticals, Inc: Consultancy; Novartis: Consultancy; Astellas: Consultancy; Syndax Pharmaceuticals: Consultancy; PinotBio: Consultancy; Daiichi Sankyo: Consultancy; Syros Pharmaceuticals, Inc.: Consultancy. Sauter: Precision Biosciences: Consultancy; Kite/Gilead: Consultancy; Bristol-Myers Squibb: Research Funding; GSK: Consultancy; Gamida Cell: Consultancy; Celgene: Consultancy, Research Funding; Genmab: Consultancy; Novartis: Consultancy; Spectrum Pharmaceuticals: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding. Hassoun: Celgene, Takeda, Janssen: Research Funding. Mailankody: Bristol Myers Squibb/Juno: Research Funding; Physician Education Resource: Honoraria; Plexus Communications: Honoraria; Takeda Oncology: Research Funding; Jansen Oncology: Research Funding; Fate Therapeutics: Research Funding; Allogene Therapeutics: Research Funding; Legend Biotech: Consultancy; Evicore: Consultancy. Korde: Medimmune: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding. Hultcrantz: Daiichi Sankyo: Research Funding; Intellisphere LLC: Consultancy; Curio Science LLC: Consultancy; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding. Shah: Bristol Myers Squibb: Research Funding; Janssen: Research Funding. Shah: Janssen Pharmaceutica: Research Funding; Amgen: Research Funding. Park: Servier: Consultancy; Affyimmune: Consultancy; Autolus: Consultancy; Minerva: Consultancy; PrecisionBio: Consultancy; BMS: Consultancy; Novartis: Consultancy; Kura Oncology: Consultancy; Curocel: Consultancy; Artiva: Consultancy; Innate Pharma: Consultancy; Intellia: Consultancy; Amgen: Consultancy; Kite Pharma: Consultancy. Landau: Genzyme: Honoraria; Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Sekeres: BMS: Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Ho: Blueprint Medicine: Membership on an entity's Board of Directors or advisory committees. Roshal: Celgene: Other: Provision of services; Auron Therapeutics: Other: Ownership / Equity interests; Provision of services; Physicians' Education Resource: Other: Provision of services. Lesokhin: pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding; Iteos: Consultancy; Serametrix, Inc: Patents & Royalties; Genetech: Research Funding; Trillium Therapeutics: Consultancy; bristol myers squibb: Research Funding; Behringer Ingelheim: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Landgren: Janssen: Other: IDMC; Janssen: Research Funding; Amgen: Honoraria; Celgene: Research Funding; Janssen: Honoraria; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria. Maura: OncLive: Honoraria; Medscape: Consultancy, Honoraria.

The somatic hotspot mutation SF3B1K700E is characteristically found in myelodysplastic syndrome with ring sideroblasts (MDS-RS) and frequently occurs as an isolated mutation. However, our understanding of how this mutation drives MDS pathogenesis remains limited. To explore the downstream consequences of the SF3B1K700E mutation and its role in disease pathogenesis, we generated a panel of isogenic SF3B1K700E and SF3B1WT induced pluripotent stem cell (iPSC) lines from 3 MDS-RS patients with isolated SF3B1K700E mutation (3 SF3B1K700E and 3 SF3B1WT lines per patient, total 18). Upon hematopoietic differentiation, SF3B1K700E cells exhibited lower growth and colony-forming ability, compared to SF3B1WTcells, recapitulating hallmark phenotypes of MDS cells. To investigate the effects of the SF3B1K700E mutation on the transcriptome and chromatin landscape, we performed RNA- and ATAC- sequencing in purified CD34+/CD45+ hematopoietic stem/progenitor cells (HSPCs) derived from the panel of the 18 isogenic SF3B1K700E and SF3B1WT iPSC lines. Principal component analysis (PCA) and hierarchical clustering based on gene expression grouped the iPSC lines primarily by genotype (SF3B1K700E vs SF3B1WT) and secondarily by genetic background. To assess the impact of the SF3B1K700E mutation at the exon, transcript and gene level, we developed an analytical framework integrating differential splicing with differential transcript usage and differential gene expression analyses. We thus discovered 59 splicing events linked to 34 genes (most statistically significant events that also mapped to differentially used transcripts and differentially expressed genes). This SF3B1K700E splicing signature includes genes previously reported as mis-spliced in SF3B1K700E cells (e.g BRD9, ABCB7), as well as novel genes. We tested this signature against a published dataset of primary MDS patient samples (Pellagatti et al.). PCA based on the inclusion level of the splicing events of our signature separated SF3B1-mutated MDS patients from patients without splicing factor mutations (SF-WT) or healthy individuals. Furthermore, it identified one patient erroneously annotated as SF-WT that clustered together with the SF3B1-mutated patients, who had a, previously overlooked, 6bp in-frame deletion spanning the K700E hotspot. By comparing the chromatin accessibility profiles of SF3B1K700E and SF3B1WT iPSC-HSPCs to those defined in primary human cell types along the hematopoietic hierarchy (Corces et al.), we found that the chromatin landscape of SF3B1K700E HSPCs resembled more this of megakaryocyte-erythroid progenitor cells (MEPs) and erythroid cells, whereas that of SF3B1WT HSPCs resembled more granulocyte-monocyte progenitors (GMPs) and monocytes. This finding may underlie the more prominent involvement of the erythroid lineage in the pathology and clinical presentation of MDS-RS. To interrogate transcriptional programs in SF3B1K700E mutant cells, we performed transcription factor (TF) motif enrichment analysis. Motifs enriched in ATAC-Seq peaks more accessible in SF3B1K700E cells that were linked to genes upregulated in SF3B1K700E cells, included motifs of several TFs with known roles in hematopoiesis (GATA, ETS, STAT, AP-1). Unexpectedly, motifs of the TEAD TFs were also enriched. The TEAD family of TFs are best known as effectors of the Hippo signaling pathway, with important roles in various biological processes and malignancies, albeit no clear links to adult hematopoiesis or hematologic disease. TEAD2 and TEAD4 were upregulated in SF3B1-mutant, compared to the WT, iPSC-HSPCs and TEAD transcriptional activity, measured with a luciferase reporter construct, was higher in SF3B1K700E, compared to SF3B1WTiPSC-HSPCs. We did not find expression or activation of YAP or TAZ, which bind to DNA as a complex with TEAD upon Hippo pathway activation. These results support a Hippo-independent increase of TEAD expression and activity in SF3B1K700E cells. In summary, we generated a panel of isogenic patient-derived iPSCs that allowed us to comprehensively characterize the transcriptome and chromatin landscape of SF3B1K700E HSPCs in an isogenic system, derive a splicing signature of SF3B1K700E and identify the TEAD TF as a new transcriptional regulator of SF3B1K700Emutant HSPCs. G. Asimomitis, A.G. Deslauriers: shared 1 st authorship E. Papaemmanuil, E.P. Papapetrou: shared senior authorship Disclosures Deslauriers: Novo Nordisk A/S: Current Employment. Hellström-Lindberg: Celgene: Research Funding. Papaemmanuil: Isabl Technologies: Divested equity in a private or publicly-traded company in the past 24 months; Kyowa Hakko Kirin Pharma: Consultancy.

TGFβ plays a pivotal role in the pathobiology of myelofibrosis (MF) by not only promoting bone marrow fibrosis (BMF) but also by enhancing the dormancy of normal but not MF hematopoietic stem cells (HSCs). TGFβ has also previously been reported to inhibit normal megakaryocyte (MK) production (Bruno et al Blood 1998). TGFβ1 promotes the synthesis of collagen by normal human mesenchymal stromal cells (MSCs). Treatment of MSCs with AVID200, a potent TGFβ1/3 protein trap, significantly decreased MSC proliferation, phosphorylation of SMAD2, and collagen expression. Robust expression of pSMAD2 was observed in the absence of exogenous TGFβ in normal donor or MF-MKs, Addition of AVID200 to MKs decreased pSMAD2 without affecting total SMAD2/3 and led to increased numbers of MKs. Treatment of MF MNCs with AVID200 also led to increased numbers of progenitor cells with wild type JAK2 and a reduction of mutated colonies. A phase 1b trial of AVID200 (NCT03895112) was performed and completed in INT-2/high risk MF patients resistant/intolerant to ruxolitinib (rux); baseline platelet count of ≥ 25 x 10 9/L, and grade 2/3 BMF. Subjects received AVID200 intravenously on Day 1 of a 21 day cycle. Response was assessed by IWG/ELN criteria after 6 cycles of AVID200. Subjects attaining at least a CI or SD with a decrease in BMF by ≥1 grade, continued AVID200. We previously presented the results of the dose escalation study (Mascarenhas ASH 2020) demonstrating that AVID200 was well tolerated without dose limiting toxicities at 3 tested dose levels (Lots A and B) in dose cohorts of 180 mg (A), 550 mg (A)/70 mg (B), and 180 mg (B). Here we report updated safety and efficacy results of the phase 1b dose expansion stage at the two highest doses tested (70 mg (B) and 180 mg (B). Twenty-two subjects were enrolled (1 withdrew before receiving treatment) and 9 were treated with AVID200 in the dose escalation phase and 12 in the dose expansion phase [Table1]. Median time after rux discontinuation was 7.4 months (0.5-59.9). The most common mutations observed at baseline in this cohort included JAK2V617F (71%), TET2 (29%) ASXL1 (24%) and CALR (19%). (Fig 1) No DLTs were observed and Grade 3/4 AEs were observed in 16 (76.2%) subjects. Grade 3/4 non-hematologic AEs were observed in 8 (38.1%) subjects and included one subject in each case (epistaxis, mucositis, extraocular muscle paresis, fatigue, rash, duodenal hemorrhage, gastric hemorrhage, urinary tract infection, and syncope). Grade 3/4 hematologic AEs were anemia (6; 28.3%) and thrombocytopenia (2; 14.3%) [Table 2]. No fatal events were observed. The median number of cycles received was 5 (range 2 - 13) and 7 (33%) patients received more than 6 cycles. For dose levels 2-3 at cycle 7, a CI was attained in one subject at dose level 2 [anemia, spleen and TSS], 5 subjects had SD, 3 subjects had PD and two subjects with 10% and 15% blasts at screening developed MPN-BP while on study based on central review. Reasons for discontinuation by local PI included PD (n=8), lack of response (n=5), study completed (n=2), other (n=2), patient decision (n=1). Median % change in palpable spleen length was +10% (range -70% to +150%) and TSS change was -50% (-100% to +185.7%) The median platelet count at baseline was 114 x 10 9/L (range: 28-695) and 215 x 10 9/L (range: 66-263) after cycle 6 in 7 evaluable subjects (Fig 2A). Notably, 17 subjects had an increase in platelets from baseline during treatment and two subjects normalized their platelet counts. Maximum changes in platelets from baseline across all cycles was +63.8% [range -15.7%, +505.5%] (Fig 2B). Paired bone marrow biopsy pathology samples for 12 subjects were available for central review and showed no significant changes in BMF score or MK histo topography at end of treatment compared to baseline. All patients had elevated plasma levels of TGF β1, but not TGFβ2/β3 levels as detected by ELISA, which were dramatically reduced 21 days after the last dose of AVID200. AVID200 a TGFβ1/3 protein trap is well tolerated and clinical responses at cycle 7 of therapy in this advanced MF patient population were limited as judged by IWG/MRT response criteria. However, AVID200 therapy resulted in significant reduction in serum TGFβ levels and improvements in platelet counts indicating that TGF β1 plays a pivotal role in MF leading to thrombocytopenia which can be reversed with AVID200 therapy. We conclude that AVID200 may best be employed in combination therapy approaches in thrombocytopenic MF patients. Figure 1 Figure 1. Disclosures Mascarenhas: Constellation: Consultancy, Membership on an entity's Board of Directors or advisory committees; Promedior: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Geron: Consultancy, Research Funding; Forbius: Research Funding; Genentech/Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; PharmaEssentia: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Galecto: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Prelude: Consultancy; Kartos: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; CTI Biopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Geron: Consultancy; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merus: Research Funding. Palmer: PharmaEssentia: Research Funding; Sierra Oncology: Consultancy, Research Funding; Incyte: Research Funding; CTI BioPharma: Consultancy, Research Funding; Protagonist: Consultancy, Research Funding. Kuykendall: Celgene/BMS: Honoraria; Pharmaessentia: Honoraria; Novartis: Honoraria, Speakers Bureau; Protagonist: Consultancy, Research Funding; Incyte: Consultancy; Abbvie: Honoraria; Blueprint: Honoraria. Mesa: Genentech: Research Funding; Promedior: Research Funding; Samus: Research Funding; Gilead: Research Funding; CTI: Research Funding; Abbvie: Research Funding; Sierra Oncology: Consultancy, Research Funding; Celgene: Research Funding; Novartis: Consultancy; Pharma: Consultancy; CTI: Research Funding; Constellation Pharmaceuticals: Consultancy, Research Funding; AOP: Consultancy; La Jolla Pharma: Consultancy; Incyte Corporation: Consultancy, Research Funding. Rampal: Stemline: Consultancy, Research Funding; Memorial Sloan Kettering: Current Employment; BMS/Celgene: Consultancy; Abbvie: Consultancy; CTI: Consultancy; Novartis: Consultancy; Disc Medicine: Consultancy; Blueprint: Consultancy; Pharmaessentia: Consultancy; Incyte: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; Constellation: Research Funding; Kartos: Consultancy; Sierra Oncology: Consultancy. Gerds: PharmaEssentia Corporation: Consultancy; Sierra Oncology: Consultancy; CTI BioPharma: Research Funding; Constellation: Consultancy; Celgene/Bristol Myers Squibb: Consultancy; AbbVie: Consultancy; Novartis: Consultancy. Yacoub: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CTI Biopharma: Membership on an entity's Board of Directors or advisory committees; ACCELERON PHARMA: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Dynavex: Current equity holder in publicly-traded company; Cara: Current equity holder in publicly-traded company; Ardelyx: Current equity holder in publicly-traded company; Seattle Genetics: Honoraria, Speakers Bureau; Incyte: Consultancy, Honoraria, Speakers Bureau; Hylapharm: Current equity holder in publicly-traded company. Talpaz: Imago: Consultancy; Constellation: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Other: Grant/research support ; Celgene: Consultancy. Komrokji: Acceleron: Consultancy; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy; Jazz: Consultancy, Speakers Bureau. Kremyanskaya: Astellas: Research Funding; Astex: Research Funding; Chimerix: Research Funding; Bristol Myers Squibb: Research Funding; Constellation: Research Funding; Protagonist Therapeutics: Consultancy, Research Funding; Incyte: Research Funding. Salama: Mayo Clinic: Current Employment, Other: Mayo Clinic had the contractual work for the central pathology review for this study and I was one of the reviewing pathologists; Constellation Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Hoffman: Kartos Therapeutics, Inc.: Research Funding; Protagonist Therapeutics, Inc.: Consultancy; Novartis: Other: Data Safety Monitoring Board, Research Funding; AbbVie Inc.: Other: Data Safety Monitoring Board, Research Funding. OffLabel Disclosure: AVID200 is a TGFb trap and is in clinical testing for fibrotic diseases. It does not have an approved indication at this time.

Background Stably acquired mutations in hematopoietic cells represent substrates of selection that may lead to clonal hematopoiesis (CH), a common state in cancer patients that is associated with a heightened risk of leukemia development. Owing to technical and sample size limitations most CH studies have characterized gene mutations or mosaic chromosomal alterations (mCAs) individually. The relationship between acquired gene mutations and mCAs in CH and their joint roles in leukemia development have not been systematically investigated. Methods We developed a method to reliably map mCAs at low cell fractions from deep targeted sequencing data. We applied this method in a cohort of 32,442 solid tumor patients who have undergone prospective clinical sequencing (MSK-IMPACT). We characterized gene mutations in our patient cohort using an established variant calling procedure from our previous studies. Results We jointly characterized 383 mCA events (median aberrant cell fraction 32%, range 10%-90%) and 14,789 mutations across 457 genes. mCA was significantly associated with age (OR=1.8, P20% VAF, compared to 1% of the general cohort. We identify co-mutational patterns characteristic of diverse mechanisms of clonal selection. We observe that mutations in DNMT3A, TET2, JAK2, MPL, EZH2, TP53 and ATM form recurrent double-hits with deletions or CNLOHs, resulting in either oncogene mutant dosage adjustment or inactivation of tumor suppressors. Notably, certain mCA events were highly directed events acting on previously acquired gene mutations in the corresponding loci. Of six events of 7qCNLOH, all six co-localized with an EZH2 (7q36.1) mutation (q During patient follow-up, the 3-year cumulative incidence of leukemias was significantly higher in patients with composite CH genotypes (14.6%, CI: 7-22%) as compared to patients with either mCA, gene mutation alone or no CH, of which all had a 3-year cumulative incidence of Conclusions Our joint characterization of gene mutations and mCAs in a large prospective sequencing cohort reveals a previously unrecognized layer of complexity in the evolutionary dynamics of clonal hematopoiesis that converges towards characteristic genotypes associated with distinct leukemia subtypes. This puts mCAs in the context of the continuous evolutionary process of oncogenesis that can often span years and sheds new lights on its patterns of acquisition and progression. We demonstrate that the integration of chromosomal aberrations provides additional resolution to risk stratification as well as interpretation of clinical phenotypes and that mCAs should be screened in conjunction with gene mutations to improve existing CH surveillance programs in cancer patients. Disclosures Bolton: GRAIL: Research Funding. Medina:Isabl: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees. Mantha:MJH Associates: Honoraria; Physicians Education Resource: Honoraria. Solit:Pfizer: Honoraria; Loxo Oncology: Honoraria; Lilly Oncology: Honoraria; Illumina: Honoraria; Vivideon Therapeutics: Honoraria. Diaz:Neophore: Consultancy, Current equity holder in private company; Merck: Consultancy; Johns Hopkins University: Patents & Royalties; Jounce Therapeutics: Current equity holder in private company; Thrive Earlier Detection: Current equity holder in private company; Personal Genome Diagnostics: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees. Berger:Illumina: Research Funding; Roche: Consultancy; Grail: Research Funding. Levine:Lilly: Consultancy, Honoraria; Janssen: Consultancy; Roche: Consultancy, Honoraria, Research Funding; Loxo: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Imago: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Isoplexis: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Research Funding; Prelude Therapeutics: Research Funding; Gilead: Honoraria; Amgen: Honoraria; Morphosys: Consultancy; Novartis: Consultancy; Astellas: Consultancy; Qiagen: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Zehir:Memorial Sloan Kettering Cancer Center: Current Employment; Illumina: Honoraria. Papaemmanuil:Celgene: Consultancy, Honoraria, Research Funding; Prime Oncology: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Illumina: Consultancy, Honoraria; Kyowa Hakko Kirin: Consultancy, Honoraria; Isabl: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; MSKCC: Patents & Royalties.

7028 Background: Hematological neoplasms are often characterized by acute onset and rapid disease progression. Cytogenetics, FISH, SNP arrays, targeted DNA and RNA sequencing are performed to inform diagnosis, risk stratification and guide treatment decisions. Whole genome sequencing (WGS) offers the opportunity to comprehensively characterize all putative biomarkers in a single assay. However, a limitation in current WGS implementation is the requirement for a germline sample, as sources of control tissue are frequently contaminated with leukemic cells resulting in false negative calls. Methods: To evaluate the clinical utility and feasibility of WGS in the diagnostic work up of leukemias, we analyzed 57 B-cell acute lymphoblastic leukemia (B-ALL) from the UKALL14 trial (NCT01085617) with no informative biomarkers at diagnosis. WGS analysis was performed on the leukemic sample and a matching control sample (with minimal residual disease level of

3063 Background: Next generation sequencing (NGS) assays have accelerated the identification of mutations and potential matched targeted therapies for patients with cancer. However, a significant proportion of patients do not derive clinical benefit from targeted panel sequencing approaches. Cancer whole genome and transcriptome sequencing (cWGTS) offers the opportunity to fully characterize tumors, but are challenged by significant cost and computational resource requirements, concerns of assay sensitivity, and the need to deliver curated results within clinically relevant time frames. We performed a prospective study to evaluate the feasibility and utility of cWGTS in pediatric and young adults with solid tumors. Methods: We developed an automated analytical workflow (Isabl) for the QC and processing of cWGTS data to include ensembl variant calling for germline and somatic substitutions, indels, and structural variants; fusion genes; gene expression; and mutation signatures. Treatment biomarkers were annotated using OncoKB with generation of a clinical prototype report. We tested the feasibility of cWGTS implementation, evaluated its analytical validity compared to standard diagnostic assays, and characterized the clinical utility of incremental findings in a prospective study of children and young adults treated at Memorial Sloan Kettering Cancer Center. Results: A total of 114 patients were enrolled. Standard NGS assays (MSK-IMPACT, MSK-Fusion) identified clinically relevant biomarkers in 22% of cases. The cWGTS process was completed, from sample acquisition to summary report, in less than 12 days. Comparison against clinically reported NGS results demonstrated high precision and recall for reported mutations (98.8%) with high concordance across variant allele representations (r2> 0.73). cWGTS identified additional oncogenic mutations not captured by targeted sequencing in 49% of patients. Furthermore, incremental findings, beyond those identified by NGS assays, of direct clinical relevance (diagnostic, prognostic, therapy guiding) were identified in 26% of patients. Importantly, < 5% of the incremental findings would have been captured by whole exome or transcriptome sequencing alone. Of possible therapeutic relevance, cWGTS analyses revealed a significantly higher tumor mutation burden than previously reported (range: 0 - 11.23). Conclusions: We demonstrate feasibility, analytical validity and clinical utility of cWGTS approaches in pediatric and young adult cancer patients, with nearly half of all patients having incremental findings that were not captured by standard targeted NGS approaches.

In the version of this article initially published, the affiliation provided for author Matteo Giovanni Della Porta (37Cancer Center, Humanitas Research Hospital & Humanitas University, Milan, Italy) was incorrect, and a second affiliation was missing. The correct affiliations are as follows (with subsequent affiliations renumbered accordingly): 37Humanitas Clinical and Research Center–IRCCS, Humanitas Cancer Center, Milan, Italy. 38Department of Biomedical Sciences, Humanitas University, Milan, Italy. The errors have been corrected in the HTML and PDF versions of the article.

Background In patients with Myelodysplastic Syndromes (MDS), TP53 mutations associate with high-risk presentation, complex karyotype, acute myeloid leukemia (AML) progression and poor response to hematopoietic stem cell transplantation. These associations highlight the relevance of TP53 as a prognostic and predictive biomarker. Consistent with its role as a tumor suppressor, bi-allelic targeting of the TP53 locus is a frequent but not an obligatory event. Despite the central role of TP53 in MDS, the clinical implications of TP53 mutations in the context of allelic state have not been extensively studied. Methods Under the auspices of the International Working Group for Prognosis in MDS, we sequenced a representative cohort of 3,324 peri-diagnosis MDS patients on a next generation sequencing (NGS) panel optimized for myeloid disease. Conventional G-banding analysis (CBA) was available for 2,931 patients. Focal (~3MB) gains and deletions and regions of NGS-derived copy-neutral loss of heterozygosity (cnLOH) were assessed using an in-house algorithm CNACS. Putative oncogenic mutations in TP53 were characterized by consideration of normal controls and established population databases. A validation cohort of 1,120 samples with independent but comparable molecular and clinical annotation was sourced from a compendium of Japanese MDS data to include JALSG-MDS212, JMDP registry, and regional registries. Results NGS-derived ploidy alterations and CBA show a high genome-wide concordance. From NGS profiles, 11% of patients (n=360) are subject to cnLOH, of which 80 target the TP53 locus. We characterize 490 TP53 mutations in 380 patients, representing 11% of the cohort. Amongst those patients, 22% (n=85) and 21% (n=78) have a deletion or a cnLOH involving the TP53 locus, respectively. Taken together, these segregate patients into two TP53 states: a mono-allelic state where one wild type allele remains (33% of TP53 mutated patients, n=126); and a multi-hit state where TP53 is altered multiple times by either mutations, deletions or cnLOH (67% of TP53 mutated patients, n=254). We find that TP53 state shapes clinical presentation and outcomes. Mono-allelic TP53 patients present with more favorable disease than multi-hit TP53 patients: they are less cytopenic, have lower bone marrow blasts (median 4 vs. 9%, p Conclusions TP53 is a natural candidate for incorporation in molecularly informed risk stratification schemas (molecular IPSS-R). We show that TP53 state rather than mutation alone is an independent diagnostic and prognostic biomarker in MDS. We propose that ascertainment of TP53 state is critical in prospective clinical sequencing for risk estimation, disease monitoring and future correlative research into predictors of response to established and investigational therapies. Disclosures Bernard: Celgene: Research Funding. Hasserjian:Jazz Pharmaceuticals: Consultancy; Promedior, Inc.: Consultancy. Germing:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria; Amgen: Honoraria. Cargo:Celgene: Research Funding. Santini:Acceleron: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Menarini: Membership on an entity's Board of Directors or advisory committees; Johnson & Johnson: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kotsianidis:Celgene: Research Funding. Takaori-Kondo:Pfizer: Honoraria; Chugai: Research Funding; Janssen: Honoraria; Kyowa Kirin: Research Funding; Takeda: Research Funding; Ono: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria. Savona:Selvita: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm Therapeutics: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Patents & Royalties; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sunesis: Research Funding. Ades:Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Silence Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Helsinn Healthcare: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees; Jazz: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding. Neuberg:Pharmacyclics: Research Funding; Madrigal Pharmaceuticals: Equity Ownership; Celgene: Research Funding. Stevenson:Celgene: Research Funding. Fenaux:Jazz: Honoraria, Research Funding; Astex: Honoraria, Research Funding; Aprea: Research Funding; Celgene Corporation: Honoraria, Research Funding. Platzbecker:Novartis: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Heuser:Synimmune: Research Funding; Bayer Pharma AG, Berlin: Research Funding. Valent:Blueprint: Research Funding; Pfizer: Honoraria; Celgene: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Deciphera: Honoraria, Research Funding. Miyazaki:Nippon-Shinyaku: Honoraria; Dainippon-Sumitomo: Honoraria; Otsuka: Honoraria; Chugai: Research Funding; Novartis: Honoraria; Kyowa-Kirin: Honoraria. Finelli:Novartis: Consultancy, Speakers Bureau; Celgene Corporation: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Speakers Bureau. Atsuta:CHUGAI PHARMACEUTICAL CO., LTD.: Honoraria; Kyowa Kirin Co., Ltd: Honoraria. Gattermann:Novartis: Honoraria; Takeda: Research Funding; Alexion: Research Funding. Ebert:Broad Institute: Other: Contributor to a patent filing on this technology that is held by the Broad Institute.; Celgene: Research Funding; Deerfield: Research Funding. Bejar:Celgene: Consultancy; Takeda Pharmaceuticals: Research Funding; AbbVie/Genentech: Consultancy, Honoraria; Astex/Otsuka: Consultancy; Modus Outcomes: Consultancy; Daiichi-Sankyo: Consultancy. Greenberg:Notable Labs: Research Funding; Celgene: Research Funding; Genentech: Research Funding; H3 Biotech: Research Funding; Aprea: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Ogawa:Qiagen Corporation: Patents & Royalties; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; RegCell Corporation: Equity Ownership; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; Kan Research Laboratory, Inc.: Consultancy; Asahi Genomics: Equity Ownership. Papaemmanuil:Celgene: Research Funding.

Background The Myeloproliferative Neoplasms, including Essential Thrombocythemia (ET), Polycythemia Vera (PV), and Myelofibrosis (MF) are stem cell disorders which carry the risk of progression to accelerated phase or blast-phase (MPN-AP/BP). Among the risk factors for transformation to MPN-AP/BP are TP53 mutations. TP53 mutations are a risk factor for progression to MPN-AP/BP in chronic-phase myeloproliferative neoplasms (MPN) and indeed 30% of patients with MPN-LT bear TP53 mutations. A recent study indicated that TP53 mutations may persist at low levels for years without an immediate risk of progression in some chronic-phase MPN patients [Kubesova et al. Leukemia 2017]. These observations raise the question as to whether the types of TP53 mutations, their frequency, or co-occurring variants differ between MPN subtypes. TP53 mutations are characterized by frameshift, missense, nonsense or silent mutations. Mutations in TP53 have traditionally been considered functionally equivalent in many prognostic studies, but an increased understanding of the effects of distinct mutations on TP53 activity has led to the recognition of the distinct functional significance of these different mutations. The understanding of the landscape of TP53 mutations in MPN and the association between different TP53 mutations and mutational burdens among MPN subtypes may allow more accurate prognostic evaluation and personalized treatment for patients. We therefore sought to assess the landscape of TP53 mutations in MPN subtypes. Methods We performed Next-Generation Sequencing (NGS) on a cohort of 651 samples derived from 439 MPN patients with ET, PV, MF and MPN-AP/BP. The data were from 3 targeted panels with 576, 585 and 156 genes (with 91, 241 and 319 samples; median coverage 500x). Samples were obtained from Memorial Sloan Kettering Cancer Center and the Myeloproliferative Neoplasms Research Consortium. Putative oncogenic mutations were called using a combination of 4 variant callers and by comparison to established cancer databases. The final variants were manually reviewed to guarantee high quality of downstream analysis. Results We identified somatic mutations in 428/439 patients (157 MPN-AP/BP, 140 MF, 67 ET and 64 PV). Of these, 55 patients (~13%) had at least one TP53 mutation with variant allele frequency (VAF) >= 2% (median TP53 VAF= 28%). In total, 68 TP53 somatic mutations were identified. Majority of these patients had a single TP53 mutation (46/55) and some had multiple mutations (7 had two and 2 had four mutations). Mutations were enriched in MPN-AP/BP with 45/68 (66%) occurring in this group followed by 10/68 (15%) in ET, 9/68 (13%) in MF and 4/68 (6%) in PV (panel A). Missense mutations were the most common type of TP53 variants and constituted ~80-90% of all mutations in ET, MF and MPN-AP/BP. Most stop-gains and frameshifts were observed in MF or MPN-AP/BP group. Furthermore, 92% of TP53 mutations are localized on DNA-binding domain (exons 5 to 8; panel B). The latter observation is consistent with results from other human cancers and highlights the role of these mutations in reducing TP53 DNA binding affinity. About 8% of mutations occur in the tetramerization domain of TP53, which is also critical for DNA binding, as well as protein-protein interactions and post-translational modification. We did not identify a significant association between a specific TP53 mutation type and any particular MPN subtype. However, we identified a significant association between TP53 VAF and MPN subtype (panel C); TP53 VAF was significantly higher in MPN-AP/BP compared to ET (p =0.0001) and MF (p =0.016). Conclusion TP53 mutations have important prognostic significance in patients with MPN. However, subgroups of patients with TP53 mutant chronic-phase disease have been observed to have relatively stable clinical course. Our data demonstrate that the spectrum of TP53 mutations, in terms of type and location within the gene, does not appear to differ between ET, PV, MF, or MPN-AP/BP. However, we observe significant difference with regard to the VAF of TP53 mutations, with an association of higher VAF and MPN-AP/BP state. This data argues that the VAF may be an important consideration in assessing the prognostic impact of a TP53 mutation identified in an MPN patient. Data regarding copy number variations in this cohort, co-occurring mutations, and the impact of TP53 mutations on treatment outcomes will be presented. Figure Disclosures Papaemmanuil: Celgene: Research Funding. Rampal:Agios, Apexx, Blueprint Medicines, Celgene, Constellation, and Jazz: Consultancy; Constellation, Incyte, and Stemline Therapeutics: Research Funding. Levine:Prelude Therapeutics: Research Funding; Novartis: Consultancy; Gilead: Consultancy; Loxo: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Research Funding; Qiagen: Membership on an entity's Board of Directors or advisory committees; Lilly: Honoraria; Amgen: Honoraria; Celgene: Consultancy, Research Funding; Isoplexis: Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Imago Biosciences: Membership on an entity's Board of Directors or advisory committees. Mascarenhas:Novartis: Research Funding; Roche: Consultancy, Research Funding; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; CTI Biopharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Promedior: Research Funding; Merus: Research Funding; Pharmaessentia: Consultancy, Membership on an entity's Board of Directors or advisory committees. Hoffman:Merus: Research Funding.

Genome profiling represents a critical pillar for clinical, translational, and basic research studies. Hospitals, core facilities, and research enterprises invest significant resources to generate genomic data sets. Yet, data management and analysis is frequently manual, which demands significant operator time and often results in siloed resources rendering them as single-use assets. Centralization of the genomic capital in a framework that enables automated processing, metadata integration and continuous interrogation maximizes return for investment and serves as the critical catalyst for research innovation, clinical translation and reproducible research. We developed Isabl, a plug-and-play infrastructure for scalable bioinformatics operations. Isabl provides solutions for databasing, assets management, tracking, automated and reproducible data processing. Dynamic reporting and meta-analysis across data assets is enabled. Isabl is built on four main components. First, an individual-centric and extensible relational database with tracking support for samples (temporal, spatial, aliquot), experimental data (assays, platforms, sequencing runs), cohorts (clinical trials, research projects) and versioned bioinformatics applications (assembly aware, tools, results). Second, the database is exposed through a fully featured RESTful API that enables horizontal integration with information systems such as sequencing cores LIMS, variant visualization platforms like cBioPortal, and where applicable, clinical and biospecimen institutional databases. Third, a Software Development Kit (SDK) built for Next Generation Sequencing assets management. The SDK enables automated execution of data import and language-agnostic bioinformatics applications (alignment, variant calling, post-processing) with support for cohort and individual level reporting features. Furthermore, the SDK facilitates dynamic retrieval of results using vertical and horizontal queries (individual and cohort level, respectively). Lastly, Isabl comes with a Single Page Web Application that fosters user interaction with multidisciplinary teams (i.e. researchers, project coordinators, engineers, clinicians) facilitating tracking of analyses, results visualization, and dynamic query processing. Isabl is currently supporting the Memorial Sloan Kettering Genome Pediatrics Precision Medicine Initiative, a prototype platform that delivers integrated, real-time automated reporting of clinical targeted gene re-sequencing, research whole genome and transcriptome profiling data; as well as linked data from pre-clinical models (i.e. PDX) and single cells studies. As an open-source tool, Isabl democratizes access to a purpose built, automated, scalable and fully integrable bioinformatics architecture. Isabl will be available at https://github.com/isabl-io. Citation Format: Juan S. Medina-Martínez, Juan E. Arango-Ossa, Gunes Gundem, Max F. Levine, Minal Patel, Noushin R. Farnoud, Venkata D. Yellapantula, Gao Teng, Joseph G. Mccarter, Elsa Bernard, Franck Rapaport, Dominik Glodzik, Ross L. Levine, Andrew Kung, Elli Papaemmanuil. A plug-and-play infrastructure for scalable bioinformatics operations [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 5105.

Background Therapy-related myelodysplastic syndrome (MDS) and acute leukemias represent a major cause of non-relapse morbidity and mortality in childhood cancer survivors, and have been associated with exposure to cytotoxic therapies (e.g. radiation, alkylators, topoisomerase inhibitors). Neuroblastoma (NB) patients receive multimodality therapy with intensive chemotherapy, radiation, and immunotherapy, and have had high rates of treatment-related leukemias (Kushner, Cheung et al. 1998). Whilst specific therapeutic modalities have been associated with distinct cytogenetic and molecular abnormalities, our understanding of the relationships between timing of mutation acquisition, dynamics of clonal selection in relation to specific therapeutic modalities, and how these in unison result in overt leukemia, remains limited. Motivated to study these relationships and inform future screening guidelines, we characterized serial bone marrow (BM) samples obtained during surveillance for NB recurrence and therapy-related leukemias. Methods We studied a total of 219 serial samples from 55 NB patients treated at MSKCC over a 21-year period. These included 19 patients with MDS or leukemic transformation (median time following NB diagnosis 4.4 years), 15 with transient cytogenetic abnormalities (median time to abnormality 3.1 years), and 21 matched controls (median disease-free follow-up 8.1 years). On average, we analyzed 4 samples per transformation patient, representative of pre-treatment timepoints at NB diagnosis, during NB treatment, and throughout follow-up, with a lead time of 18 years - 1 month prior to transformation, and at time of leukemic transformation. Comprehensive genomic profiling with targeted gene sequencing (MSK-IMPACT Heme), RNA-seq, and Archer FusionPlex was performed to capture acquired gene mutations, chromosome-level copy number alterations (CNA), and fusion genes at the time of diagnosis. Backtracking studies were performed in longitudinal samples with complete molecular and clonal characterization. Results We detected at least one disease-defining alteration in all cases with MDS or leukemic transformation at time of diagnosis, with a total of 61 putative oncogenic events across all patients (median 3 alterations per patient, range 1-12). As expected, the most frequent events were MLL fusions (n=6 patients), and mutations in TP53 (n=5 patients). The remaining cases harbored chromosomal aneuploidies or acquired gene mutations in NPM1, IDH1, PTPN11, NRAS, BCOR, CUX1, STAG2, WT1, amongst other genes, at a median variant allele frequency 24% (range 4-68%). Backtracking studies identified at least one of these mutations in 81% of patients at a sampling time point prior to diagnosis. In contrast, only two patients (2/15) from the cohort with transient cytogenetic abnormalities had acquired somatic mutations detected at a median VAF of 3%, with resolution of the molecular alterations in subsequent samples. One of the control cases also had an identified mutation, though this patient died of NB with limited hematologic follow-up. The median time of detection of a putative driver alteration was 6 months prior to leukemic transformation, with the earliest identified at 2.8 years prior to disease transformation. At least 3 cases of MLL fusions were detected 2.2, 14.5, and 20.9 months prior to diagnosis. Mutations in TP53 co-occurred with CNAs in all patients in our cohort, and has been shown to be predictive of chemoresistant disease. Mutations in TP53 were also identified in at least 2 pre-leukemic samples per patient in 4 of 5 cases, at a median VAF 5% (range 5-20%). In all of these cases, TP53 mutations preceded clinically detectable CNA. Genetic evolution led clonal dominance, which, intriguingly, often preceded disease presentation in the context of normal hematopoeisis. We also found evidence of clonal drifts, possibly as a consequence of treatment effects. Conclusions Our preliminary data demonstrate that NB patients at risk of developing secondary leukemia can be identified by molecular profiling of BM aspirates obtained during routine disease surveillance for NB. These findings present an opportunity for the development of early detection studies for patients with pediatric malignancies undergoing intensive therapy and importantly inform studies into mechanisms of leukemic transformation and specific gene-treatment effects. Disclosures Cheung: Ymabs: Patents & Royalties.

Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such as CCNE1 , RAD21 , VEGFA , and IGF1R , were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.