Hematologic Neoplasms As Risk Factor For Severe COVID-19: A Systematic Review Protocol

Background: Patients with hematologic neoplasm may have compromised immunity due to their malignancy and/or treatment, and may be at elevated risk of severe COVID-19. However, the studies bring together patients with hematologic neoplasms and solid tumors into a single group, making no distinction about the types of hematological tumors and their treatments. This systematic review is designed to explore the risk of severe COVID-19 in patients with hematologic neoplasm. Studies about patients, adult or children, with hematologic neoplasm and COVID-19 will be included. Methods: A systematic review according to Joanna Briggs Institute methodology for systematic reviews of etiology and risk will be performed. The review will consider as participants adults or children with COVID-19 infection detected by RT-PCR or serology (SARS-CoV-2 antibody). We will be included studies without routine labs confirmation of COVID-19 if the patients presented clinical/physical exam and computed tomography suggesting COVID-19. The exposure of interest will be hematologic neoplasm, which include lymphomas, acute and chronic leukemias, myeloma, myelodysplastic syndrome, and myeloproliferative diseases. We will consider cohort, case-control, analytical cross-sectional studies. Outcomes among patients with COVID-19 are critical symptoms, hospitalizations, intensive care unit admissions, mechanical ventilation and deaths. We will exclude studies with other neoplasms than hematologic neoplasms. Search strategies have been created for the Embase, Medline and LILACS. Two reviewers independently will assess the studies for their eligibility, will extract data and will evaluate their risk of bias. Similar outcomes measured in at least two studies will be plotted in the meta-analysis using the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information. Discussion: This systematic review aims to evaluate if patients with hematologic neoplasm may be at elevated risk of severe COVID-19. This review will differ from the previous ones because we will include controlled studies and groups with only hematologic neoplasm, excluding other cancers. The main hypothesis of our research is that not all hematological cancer patients have high risk of severe COVID-19. Trial registration number: PROSPERO CRD42020199318.

Automated Comprehensive Diagnostics of Hematologic Neoplasms By Artificial Intelligence Models Using Flow Cytometric Raw Matrix Data

Background: Artificial intelligence (AI) has steadily been entering the field supporting diagnostic workup of hematological neoplasms. Its application in flow cytometry (FC) so far mostly included visualization steps with the potential disadvantage of data reduction. Aim: To implement AI models based on raw matrix data for diagnosing main entities of hematologic neoplasms by FC. Methods: For examination of acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), myelodysplastic syndromes (MDS), multiple myeloma (MM) and mature T- and B-cell neoplasms (T-NHL, B-NHL), six machine learning (ML) models were trained on the respective dataset consisting of uniformly analyzed samples (Navios and Cytoflex cytometers, Kaluza analysis software, Beckman Coulter, Miami, FL) resulting in ".fcs" or ".lmd" files, after being classified and diagnosed by human experts. In total 36,662 cases were included, in detail 3,961 for AML model (3,120 AML, 841 no AML), 2,931 for T-NHL (204 T-NHL, 40 NK-cell neoplasm [NK], 2,687 no NHL), 766 for ALL (364 c-ALL/Pre-B-ALL, 95 Pro-B-ALL, 55 cortical T-ALL, 34 Pre-T-ALL, 11 Pro-T-ALL, 3 mature T-ALL, 15 ETP-ALL, 189 no ALL), 7,503 for MM (1,297 MM, 1,261 consistent with MM (<10% plasma cells by FC), 3,613 consistent with monoclonal gammopathy of undetermined significance (MGUS), 1,332 no MM/MGUS), 9,664 for B-NHL (440 hairy cell leukemia (HCL), 3,771 chronic lymphocytic leukemia (CLL), 3,062 CD5-negative NHL, 1,318 CD5-positive NHL, 1,073 no NHL) and 11,837 for MDS (5,206 consistent with MDS, 6,631 no MDS). For each model, feature engineering (FE) techniques were applied. These included division of values by their maximal values, multiplication by 1024, standardization, arcsinh transformation and one- (for all models) or two- (for T-NHL and ALL) dimensional distribution of marker values using empirical cumulative distribution functions (cdfs), with the number of bins set to two for two-dimensional histograms and between 16 and 128 for one-dimensional histograms optimized for each model. Further expert-based features were applied (for T-NHL, ALL, MM, MDS) including setting positive/negative thresholds on marker values, focusing on cell populations of interest by applying clustering techniques, considering percentages of certain cell types and calculating features to capture their specific properties (e.g. distribution of markers of the subpopulations). For MM, B-NHL and MDS we also calculated covariance between key markers. Taken together, 345 features were applied for AML, 772 features for T-NHL, 339 for ALL, 1,800 for MM, 3,275 for MDS and 3,145 for B-NHL. Following ML models were used: XGBoost, weighted SVC and LinearSVC, hierarchical model (four XGBoost with SMOTE models), AutoGluon (using weighted L2 ensemble of XGBoost, LightGBMXT and CatBoost). For MDS an approach similar to manual gating strategies was implemented dividing cells into five partitions combining predictions for each partition to a final result. Model performance was assessed with stratified five-fold cross validation (training/test set 80/20% of data) repeated 10 times. Test recall (R), precision (P) and prediction probabilities (PP) were recorded. Results: Application of the ML models (see figure 1) detected AML vs no AML with average R (aR) of 99.8% and average P (aP) of 99.9% when considering cases with PP ≥0.9 covering 82% of all cases analyzed for AML. For T-NHL we saw aR of 87% and aP 86.7% for detection of NK, T-NHL and no NHL, respectively. In general PP for NK were low and thus prohibited application of a high PP threshold which would have excluded many cases. With a PP threshold of 0.9 (82% of cases) ALL model resulted in prediction of classes Pro-B-ALL, T-ALL non-cortical, c-ALL, cortical T-ALL and no ALL with aR 91.7% and aP 92.5%. MM model separated consistent with MGUS from consistent with MM and no MM (PP=0.9, 66% of cases) with aR 97.7 % and aP 93.5 %. For MDS aR was 85.6% and aP 84.7% with PP=0.9 (74% of samples). Applying PP of 0.9 (51% of cases) B-NHL model classified CD5 negative, CD5 positive, CLL, HCL and no NHL with aR 84.6% and aP 91.5%. Conclusions: Training AI models for FC using raw matrix data is feasible and yields striking R and P values for various models when restricting to cases with high PP. Besides further improving all models future work will focus on identification of additional sub-entities and application of transfer learning to achieve universal applicability to any FC data. Figure 1 Figure 1. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Kern: MLL Munich Leukemia Laboratory: Other: Part ownership.

Whole Genome Sequencing Identifies Non-KIT Mutations and Cytogenetic Aberrations in Systemic Mastocytosis but Has Limited Sensitivity for Detection of KIT D816V

Background: Systemic mastocytosis (SM) is a hematologic neoplasm characterized by the infiltration of clonal mast cells in the bone marrow or other extra-cutaneous organs. The clinical course varies between advanced and non-advanced (indolent and smoldering SM) forms of SM. The vast majority of patients harbor the activating D816V mutation in the KIT tyrosine kinase. Additional somatic mutations in other genes have been recognized as risk factors in SM. Cytogenetic aberrations are rarely found in SM but have been associated with advanced disease. Whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) have been described as an alternative to cytogenetics and targeted molecular genetic analysis in myeloid cancers. Aim: To assess the ability of WGS/WTS to detect cytogenetic aberrations and recurrent somatic mutations in SM. Methods: 120 patients (51 female, 69 male) diagnosed with SM were analyzed with WGS/WTS and results were compared with orthogonal data of KIT D816V PCR, targeted sequencing, and cytogenetics. 47 patients (39%) were diagnosed with advanced SM (1 mast cell leukemia, 3 aggressive SM, 43 SM with associated hematologic neoplasm). For WGS, 2x151bp paired-end reads were generated on NovaSeq 6000 and HiSeqX machines (Illumina, San Diego, CA). BaseSpace's Tumor/Normal app v3 was used to call variants with Strelka Somatic Variant Caller v2.4.7 and structural variants (aberrations with >50bp in size) with Manta (v0.28.0). Genomic DNA from a mixture of multiple anonymous donors (Promega, Fitchburg, WI, USA) was used as normal. For WTS, 2x101 bp paired-end reads were produced with a median of 50 mio. reads per sample, aligned with STAR v2.5.0, and variants were called using Isaac Variant Caller v2.3.13. Results: WGS/WTS detected cytogenetic aberrations in 21% of patients: 2 patients displayed a complex aberrant karyotype, 3 balanced structural aberrations, 16 copy number alterations, and 6 copy number neutral losses of heterozygosity. Aberrations detected by chromosome banding analysis were also found by WGS in all but three patients (small clones with aberrations present in ≤20% of metaphases and <10% of interphase nuclei as determined by FISH). In contrast, WGS/WTS detected additional aberrations in 16 patients. The frequency of chromosomal aberrations detected by WGS/WTS was higher in advanced compared to non-advanced SM (34% vs. 12%, p<0.05). KIT D816V was detected by PCR in 98%, by WGS in 21% and by WTS in 46% of patients. The detection rate by WGS was significantly higher in advanced (36%) compared to non-advanced SM (12%, p<0.05) while no difference was observed for WTS (45% vs. 47%). Somatic mutations outside of KIT were analyzed within a subset of 121 genes recurrently mutated in hematologic neoplasms. 46% of patients showed non-KIT mutations with a median of 2 mutations per patient. Both frequency of non-KIT mutations as well as the median number of mutations per patient was higher in advanced (83%; n=3) compared to non-advanced SM (22%, n=1, p<0.05). Finally, we analyzed the impact of genetic aberrations on survival in our SM cohort. Patients were grouped according to the presence of chromosomal aberrations and gene mutations (non-KIT) as assessed by WGS/WTS. SM patients with both types of aberrations (n=16), one type of aberration (n=47; gene mutations only n=38; chromosomal aberrations only n=8), or no aberration but KIT D816V (n=57) showed significant differences in overall survival (p<0.05, Figure 1). Con clusions: WGS/WTS has limited sensitivity for detection of KIT D816V in SM. This finding can be explained by the low KIT D816V mutation burden typically found in bone marrow aspirates of SM patients. In line, we observed a slightly higher detection rate in advanced SM and in RNA-based WTS analysis. As WGS/WTS will be applied for the diagnostic workup of myeloid malignancies in the future and SM associated with other hematologic neoplasms may be overlooked if not specifically investigated, additional PCR-based techniques are still mandatory to rule out KIT D816V as a diagnostic criterion for SM. In contrast, WGS/WTS detects both chromosomal aberrations and additional gene mutations in patients with SM and can be used as an alternative to cytogenetics and targeted sequencing for risk assessment. In particular, the absence of genetic aberrations in WGS/WTS identifies SM patients with indolent course of the disease and favorable prognosis. Figure 1 Figure 1. Disclosures Hoermann: Novartis: Honoraria. Kern: MLL Munich Leukemia Laboratory: Other: Part ownership. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership.

Atypical Kinase RIOK2 Is a Master Regulator of Hematopoietic Cell Fate

Here we report the discovery of a new master regulator of cell fate during hematopoietic differentiation, one whose function has major implications for the treatment of blood disorders such as anemia. Anemia is a major comorbidity in aging, chronic diseases such as renal failure and inflammation, bone marrow failure disorders and in hematologic neoplasms such as myelodysplastic syndromes (MDS), affecting roughly one third of the world population. Anemia is also often diagnosed in patients treated with chemotherapy or other cytotoxic agents. The comorbidities of peripheral blood cytopenias especially in elderly patients with MDS often outweigh the treatment benefits from allogeneic stem cell transplants leaving only a handful of FDA-approved drugs/therapies for treatment of such disorders. There is thus a dire need to revisit the origins of hematopoietic differentiation defects underlying these hematologic disorders to identify additional targets for novel therapies in treating anemia. We present evidence establishing that right open reading frame kinase 2 (RIOK2), an understudied atypical kinase associated with pre-40S ribosome biogenesis (Ferreira-Cerca et al., Nat. Str. Biol. 2012), is also a master transcriptional regulator of hematopoietic lineage commitment that simultaneously drives erythroid differentiation and represses myeloid and megakaryocytic lineages. We show that ablation of RIOK2 expression leads to hematopoietic differentiation defects in primary human hematopoietic stem and progenitor cells, the cells of origin for hematologic neoplasms. We identity RIOK2 as an integral player in governing major blood cell differentiation processes: erythropoiesis, megakaryopoiesis and myelopoiesis. Analyses in primary human CD34+ hematopoietic stem and progenitor cells (HSPCs) revealed that CRISPR/Cas9-mediated depletion of RIOK2 led to impaired erythropoiesis and a concomitant elevation in megakaryopoiesis and myelopoiesis. A more comprehensive analysis revealed that RIOK2 regulates the transcriptomic profiles of several key transcription factors that determine hematopoietic cell fate, including GATA1, GATA2, SPI1, RUNX3 and KLF1. Most importantly, we also observed a significant correlation between mRNA levels of RIOK2 and GATA1, GATA2, RUNX3 and KLF1 in MDS patient-derived bone marrow cells. We also demonstrate that loss of RIOK2 causes massive alterations in chromatin accessibility, both globally and specifically at the promoters of its putative target genes. This places RIOK2 at the apex of a transcriptional regulatory network controlling hematopoietic differentiation. We identify a previously unappreciated DNA-binding winged helix-turn-helix (wHTH) domain in RIOK2 conferring the protein with the properties and activities of a transcription factor. Transcriptomic profiling, structural modeling, chromatin immunoprecipitation-sequencing and a range of domain-deleted mutants reveal that RIOK2 functions as a bona-fide master transcription factor in hematopoiesis. We also identify two transactivation domains within the wHTH motif of RIOK2 that play integral roles in associating with the core transcriptional complex at promoter regions of genes. To the best of our knowledge, we present the first evidence of a protein that not only controls 40S ribosome biogenesis governing translation but also functions in the nucleus as a master transcription factor by regulating the expression of key transcription factors that determine hematopoietic cell fate. Our discovery of a novel master transcriptional regulator governing a multitude of hematopoietic lineages significantly advances our current understanding of the transcriptomic landscape underlying hematopoietic differentiation. We hope that our findings may lead to new approaches to target these newly identified regulatory networks in hematopoiesis that may be relevant not just for malignancies, but for other hematologic disorders as well, such as the anemia of aging, chronic and inflammatory diseases and aplastic anemias. We are hopeful that this study will also lay a foundation to discovering how proteins, like RIOK2, may integrate transcriptional processes with translational outcomes to drive cellular functions. Disclosures Raundhal: Jnana Therapeutics: Current Employment. Petsko: Amicus Therapeutics, MeiraGTx, Annovis Bio, Retromer Therapeutics, and Proclara Bioscience: Membership on an entity's Board of Directors or advisory committees; Denali Therapeutics, MeiraGTx, Annovis Bio, Retromer Therapeutics and Proclara Biosciences: Current equity holder in publicly-traded company. Glimcher: Kaleido Therapeutics: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Other: Former Director; Repare Therapeutics: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Abpro Therapeutics: Membership on an entity's Board of Directors or advisory committees.

P.158 Feeling Green

Background: Myeloid sarcoma (MS) is a rare solid tumour made of myeloblasts or immature myeloid cells in an extramedullary site or in bone, associated with systemic hematologic neoplasms. When they occur in the brain parenchyma, they can often be misdiagnosed. Methods: The authors report a case of a 4-year old boy 6 months out of remission from AML, presenting with a short history of headaches and vomiting, and found to have a heterogenous contrast-enhancing lesion in the right cerebellar hemisphere, with differential diagnosis of myeloid sarcoma, astrocytoma, medulloblastoma and ATRT. Preliminary diagnosis was made flow cytometry from an intraoperative biopsy. The patient had a long course of chemotherapy and radiation, but eventually died from the systemic burden of his AML. Results: The authors present a literature review on 178 published cases of CNS myeloid sarcomas, and their radiological presentation and the basis of immunohistochemical and pathological diagnosis is discussed. Conclusions: Diagnosis rests on a combination of immunohistochemistry and histopathology of biopsied tissue. Surgical resection is controversial, especially given the efficacy of chemotherapy and radiation, and prognosis remains unclear. As with all uncommon and rare clinical entities, further investigation is warranted to determine prognosis and optimal management of CNS myeloid sarcomas.

CCR7 in Blood Cancers – Review of Its Pathophysiological Roles and the Potential as a Therapeutic Target

According to the classical paradigm, CCR7 is a homing chemokine receptor that grants normal lymphocytes access to secondary lymphoid tissues such as lymph nodes or spleen. As such, in most lymphoproliferative disorders, CCR7 expression correlates with nodal or spleen involvement. Nonetheless, recent evidence suggests that CCR7 is more than a facilitator of lymphatic spread of tumor cells. Here, we review published data to catalogue CCR7 expression across blood cancers and appraise which classical and novel roles are attributed to this receptor in the pathogenesis of specific hematologic neoplasms. We outline why novel therapeutic strategies targeting CCR7 might provide clinical benefits to patients with CCR7-positive hematopoietic tumors.