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Purpose:Biomarkers of response and resistance to FLT3 tyrosine kinase inhibitors (TKI) are still emerging, and optimal clinical combinations remain unclear. The purpose of this study is to identify co-occurring mutations that influence clinical response to the novel FLT3 inhibitor pexidartinib (PLX3397).Experimental Design:We performed targeted sequencing of pretreatment blasts from 29 patients with FLT3 internal tandem duplication (ITD) mutations treated on the phase I/II trial of pexidartinib in relapsed/refractory FLT3-ITD+ acute myeloid leukemia (AML). We sequenced 37 samples from 29 patients with available material, including 8 responders and 21 non-responders treated at or above the recommended phase II dose of 3,000 mg.Results:Consistent with other studies, we identified mutations in NRAS, TP53, IDH2, and a variety of epigenetic and transcriptional regulators only in non-responders. Among the most frequently mutated genes in non-responders was Cyclin D3 (CCND3). A total of 3 individual mutations in CCND3 (Q276*, S264R, and T283A) were identified in 2 of 21 non-responders (one patient had both Q276* and S264R). No CCND3 mutations were found in pexidartinib responders. Expression of the Q276* and T283A mutations in FLT3-ITD MV4;11 cells conferred resistance to apoptosis, decreased cell-cycle arrest, and increased proliferation in the presence of pexidartinib and other FLT3 inhibitors. Inhibition of CDK4/6 activity in CCND3 mutant MV4;11 cells restored pexidartinib-induced cell-cycle arrest but not apoptosis.Conclusions:Mutations in CCND3, a gene not commonly mutated in AML, are a novel cause of clinical primary resistance to FLT3 inhibitors in AML and may have sensitivity to CDK4/6 inhibition.

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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.

Purpose: Biomarkers of response and resistance to FLT3 tyrosine kinase inhibitors (TKI) are still emerging, and optimal clinical combinations remain unclear. The purpose of this study is to identify co-occurring mutations that influence clinical response to the novel FLT3 inhibitor pexidartinib (PLX3397). Experimental Design: We performed targeted sequencing of pretreatment blasts from 29 patients with FLT3 internal tandem duplication (ITD) mutations treated on the phase I/II trial of pexidartinib in relapsed/refractory FLT3-ITD+ acute myeloid leukemia (AML). We sequenced 37 samples from 29 patients with available material, including 8 responders and 21 non-responders treated at or above the recommended phase II dose of 3,000 mg. Results: Consistent with other studies, we identified mutations in NRAS, TP53, IDH2, and a variety of epigenetic and transcriptional regulators only in non-responders. Among the most frequently mutated genes in non-responders was Cyclin D3 (CCND3). A total of 3 individual mutations in CCND3 (Q276*, S264R, and T283A) were identified in 2 of 21 non-responders (one patient had both Q276* and S264R). No CCND3 mutations were found in pexidartinib responders. Expression of the Q276* and T283A mutations in FLT3-ITD MV4;11 cells conferred resistance to apoptosis, decreased cell-cycle arrest, and increased proliferation in the presence of pexidartinib and other FLT3 inhibitors. Inhibition of CDK4/6 activity in CCND3 mutant MV4;11 cells restored pexidartinib-induced cell-cycle arrest but not apoptosis. Conclusions: Mutations in CCND3, a gene not commonly mutated in AML, are a novel cause of clinical primary resistance to FLT3 inhibitors in AML and may have sensitivity to CDK4/6 inhibition.

Refereed/Peer-reviewed

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.

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.

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.

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.

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.

Although erythrocytes readily metabolize fructose, it has not been known how this sugar gains entry to the red blood cell. We present evidence indicating that human erythrocytes express the fructose transporter GLUT5, which is the major means for transporting fructose into the cell. Immunoblotting and immunolocalization experiments identified the presence of GLUT1 and GLUT5 as the main facilitative hexose transporters expressed in human erythrocytes, with GLUT2 present in lower amounts. Functional studies allowed the identification of two transporters with different kinetic properties involved in the transport of fructose in human erythrocytes. The predominant transporter (GLUT5) showed an apparent Km for fructose of approximately 10 mmol/L. Transport of low concentrations of fructose was not affected by 2-deoxy–D-glucose, a glucose analog that is transported by GLUT1 and GLUT2. Similarly, cytochalasin B, a potent inhibitor of the functional activity of GLUT1 and GLUT2, did not affect the transport of fructose in human erythrocytes. The functional properties of the fructose transporter present in human erythrocytes are consistent with a central role for GLUT5 as the physiological transporter of fructose in these cells.