Maia, Alexandre Gaspar

Abstract Background: SARS-Cov-2 infections are associated with increased mortality and morbidity, largely due to inflammatory cascades and cytokine release syndrome (CRS). Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence and subsequent expansion of somatic, leukemia-associated driver mutations in apparently healthy individuals with normal blood counts. CHIP has been associated with increased inflammation, with cytokines such as IL1-b, IL6 and TNF-a being elevated at baseline in affected individuals. We hypothesized that the presence of CHIP in patients with COVID-19 would result in excessive inflammation-related mortality and morbidity. Methods: We used the Mayo Clinic COVID-19 database to identify patients with COVID-19 on whom peripheral blood mononuclear cells (PBMC) were available for research use (IRB approved). We carried out target-capture next generation sequencing for 220 CH related genes, by previously described methods (1000 x coverage, variant allele fraction/VAF detection limit >0.5%; Kusne Y et al AJH 2021). CHIP was defined by the presence of a CH mutation with a VAF>1% in an individual with normal baseline blood counts. Demographics, blood counts, and inflammatory markers (CRP and cytokine levels- ELISA assay) at COVID-19 diagnosis and during follow-up (as clinically indicated) were collected. COVID-19 disease severity was classified based on the presence and severity of CRS, graded using the Penn Grading Scale (Porter et. al., 2018), and the WHO ordinal scale (WHO Blueprint, 2020). We used Fisher's exact test and the Wilcoxon rank sum test to compare categorical and continuous variables. Survival analysis was performed using the Kaplan-Meier method. We accounted for differences in age and sex using multivariable-adjusted proportional hazards regression models. Results: Seventy-two CHIP mutations were detected in 56 (25%) of the 227 patients with COVID-19 that had PBMC available; median age 69 years (range; 42-99 years), 61% male. Fifteen (26%) patients had 2 CHIP mutations, while 1 patient had 3 CHIP mutations. Common mutations encountered included DNMT3A (32%) , TET2 (19%) , SF3B1 (8%) , ASXL1 (6%) , MPL (5%) , and TP53 (5%; Figure 1A). COVID-19 patients with CHIP were older in age (median 69 vs 57 years; p<0.0001) and had higher baseline MCP-1 (p=0.04) levels. However, there were no differences in sex, comorbidities, blood counts, IL1-b, IL6 and TNF-a levels between the two groups. The median follow-up for the entire cohort was 9 months. The relative change from baseline in blood counts and inflammatory markers (CRP and cytokines) during follow-up was similar in CHIP and non-CHIP patients, with the exception that COVID-19-onset neutropenia was more common in CHIP patients (8% vs 1%; p=0.017) compared to those without CHIP. At last follow up neutropenia had resolved in all patients. Both groups had comparable number of patients with CRS (61% CHIP vs 53% non-CHIP patients, p=0.354, Figure 1B), however, CHIP patients had more severe CRS (median Penn Grade 3 versus 2 in non-CHIP, p=0.018, Figure 1C). Based on the WHO ordinal scale, CHIP patients were more likely to experience hospitalization with severe disease and death (61% versus 45% in non-CHIP, p = 0.049). Moreover, COVID-19 CHIP patients experienced worse overall survival in comparison to patients without CHIP (median 13.1 months vs not reached, p<0.001, Figure 1D). This association remained consistent after adjusting for age and sex at the time of COVID-19 diagnosis (HR 3.15, 95% 1.32 - 7.55, p = 0.010). At last follow-up, 22 deaths were documented: 13 (23%) in patients with CHIP and 9 (5%) in the non-CHIP group (p=0.02), with the primary cause for mortality being hypoxic respiratory failure (62% in CHIP vs 44% non-CHIP, p=0.04). Conclusions: In this study, we observe an age-independent impact of CHIP on COVID-19 associated inflammatory morbidity (CRS) and mortality (hypoxemic respiratory failure). We are currently carrying out detailed single cell (ssDNA, RNA and ATAC-seq) and proteomic studies (O-link PEA assays) to better elucidate this pathophysiology. Figure 1 Figure 1. Disclosures Patnaik: Kura Oncology: Research Funding; StemLine: Research Funding.

Abstract Background: Chronic myelomonocytic leukemia (CMML) is an aging disease that arises on the background of clonal hematopoiesis, commonly involving multiple TET2 mutations or TET2/SRSF2 co-mutations. In a prior study of 1084 CMML patients (Leukemia 2020; 34:1407-1421), we demonstrated a high prevalence of TET2 mutations (56%) in CMML, with approximately 30% of patients having >1 TET2 mutation. The cell-type and allele specific distribution of these mutations remains of great interest and are thus far poorly defined. To visualize the genotypic and immunophenotypic correlates, we performed single-cell DNA analysis and simultaneous protein profiling on 2 CMML patients with multiple TET2 mutations. Methods: After Mayo Clinic IRB approval, two CMML patients with dual TET2 mutations and available peripheral blood mononuclear cells were included in the study. Patient samples were labeled with TotalSeq TM -D Heme Oncology Cocktail (BioLegend, San Diego, CA) consisting of 45 unique oligo-conjugated cell surface markers. The samples were then washed and loaded into a Tapestri microfluidics cartridge, where single cells (3,500 cells/µL) were encapsulated, lysed and barcoded using the MissionBio Myeloid custom amplicon panel consisting of 312 amplicons in 45 genes relevant to myeloid disorders (MissionBio, San Francisco, CA). The individual barcoded DNA and protein for each cell was purified, recovered, and labeled with Illumina i5/i7 indices, quanitifed by Agilent Bioanalyzer and pooled for sequencing. The libraries were sequenced via Illumina NovaSeq by the Mayo Genomics Core, and data was recovered and analyzed using MissionBio Tapestri Insights v3.0.2. Results: Two dual TET2 mutated CMML patients were included in the study, both male, ages 79 and 83, and both with CMML-0. Case 1 had TET2 p.G1172Efs*53 (variant allele fraction/VAF-6%) and p.H1732Tfs*13 (VAF-13%) mutations, while case 2 had TET2 p.Y620Ffs* (VAF-85%), p.G898* (VAF-82%), and SRSF2 p.95H (VAF-45%) mutations, respectively. In both patients, TET2 mutations were found to be preferentially distributed in monocytes (CD11b+, CD14+, CD64+, CD13+, CD33+, HLA-DR+), with very few classically defined granulocyte (CD16+,CD13+.CD33+, HLA-DR neg), B (CD19+,CD22+)/T (CD2+,CD4+,CD5+,CD7+) lymphocytes, NK cells (CD16+/CD56+/HLA-DR neg) and plasma cells (CD38+/CD138+), demonstrating mutant TET2. Among monocytes, TET2 mutations were enriched in classical/M01 (CD11b+, CD14+,CD16-) and intermediate/M02 monocytes and were infrequent in the MO3 fraction, commensurate with monocyte repartitioning seen in CMML. Interestingly, a large number of single cells with TET2 mutations also demonstrated an aberrant surface phenotype, with universal expression of CD14+ and CD11b+, along with a mixture of other markers (CD163+, CD11c, CD4+, CD2+, and/or CD56+). With regards to allelic distribution, while several permutations and combination were seen involving heterozygosity and homozygosity for the TET2 mutations identified on bulk sequencing, data was corroborative for both TET2 mutations being located on trans alleles. Conclusions: In this study, we demonstrate that TET2 mutations in CMML are highly enriched in classical circulating monocytes and infrequently occur in classical granulocytes, B/T and NK cells; with multiple TET2 mutations most commonly co-existing on trans alleles. Analyses on additional samples along with copy number variation assessments are ongoing. Figure 1: Lollipop plot of TET2 exons with dual TET2 mutations labeled above and oxygenase domain labeled in green; below are number of cells identified with each genotype for Case 1 (A) and Case 2 (B). Mutations are labeled proximal (yellow) and distal (red) and alleles are in grey. The directionality of the arrows to different genotypes is based on decreasing cell number and genotype. Uniform manifold approximation and projection (UMAP) plot of Case 1 (C) and Case 2 (D) with cells clustered by immunophenotype and labeled by genotype (non TET-2 mutated purple, heterozygous TET2 in green, homozygous TET2 in yellow). Relative protein expression of T-cell phenotype (CD14-, CD3+, CD4+/-,CD8+/-, CD5+, CD7+, CD2+), or classical monocytes (CD14+/CD16-) for Case 1 (E & F) and Case 2 (G & H) overlayed on UMAP. Royal blue represents non TET2-mutated cells, and mutated cells are labeled in pastel blue, green and light orange by mutation type. Figure 1 Figure 1. Disclosures Durruthy-Durruthy: Mission Bio Inc.: Current Employment. Arribas-Layton: Mission Bio, Inc.: Current Employment. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding.

Introduction: Truncating mutations in Additional Sex Combs-Like 1 (ASXL1) are associated with a high-risk disease phenotype in myeloid malignancies. In chronic myelomonocytic leukemia (CMML), truncating ASXL1 mutations are known to increase transcriptional activity of leukemic driver genes and have been associated with gene body hypermethylation. We interrogated the transcriptome and methylome of patients with ASXL1-mutant (MT) and -wildtype (WT) CMML using a multi-omics approach to test the hypothesis that gene expression is mediated through gene body methylation. Methods: Bone marrow mononuclear cells from patients with ASXL1 WT (n=8) and MT (n=8) CMML were subjected to targeted NGS of DNA, whole transcriptome shotgun sequencing (RNA-seq), and immunoprecipitation of DNA methyl residues (DIP-seq). After quality control all samples were sequenced on an Illumina HiSeq 4000 before further processing and data analysis. Differential gene expression analysis was performed to identify genes up-regulated in MT CMML. The samples in the two groups were treated as biological replicates and subjected to a consensus peak calling strategy requiring an overlap of at least 30% between samples and an adjusted p-value < 5x10-5 for a methylation peak to be considered statistically significant. For validation purposes methylation analysis was performed on 3 ASXL1 MT and 3 WT CMML patients using Illumina Infinium MethylationEPIC microarrays and differentially methylated regions were identified using a bump hunting strategy. Gene body methylation was defined as methylation in gene bodies (outside the promoter region, i.e. transcription start site ±2kb). Gene body methylation was compared between WT and MT CMML for the up-regulated genes and correlated with expression of all genes in MT CMML. Results: Sixteen WHO-defined CMML patients were included, median age 69 years (48-77), 63% male, 50% had truncating ASXL1 frame shift mutations. Abnormal karyotypes were observed in the same number of patients and the burden of co-mutations was similar between the two groups (median number per group 3 vs. 3, p=0.508). This included several modulators of DNA methylation including TET2, DNMT3A, and IDH2 (median number per group 1 vs. 1, p=0.699). There was a predominant up-regulation of gene expression in MT CMML: 707 genes up- and 124 down-regulated (FDR<0.050) without evidence of differential methylation in promoter regions of the differentially expressed genes. There was no difference in the number of genes with consensus methylation peaks in the gene body or the extent of gene body methylation (area under the consensus peaks) between MT and WT CMML for the differentially expressed genes (Figure 1a). We further validated these results using methylation microarrays (Figure 1b). Among the MT CMML patients, there was a curvilinear relationship between gene body methylation and gene expression across all genes with intermediate gene body methylation being associated with the highest gene expression (Figure 1c). As an alternative unbiased approach, we identified 1595 differentially methylated regions (DMR, regions with FDR<0.05) in the validation data set. We mapped all hypermethylated regions to gene bodies requiring that there was no concurrent hypermethylation of the promoter region of the same gene. With this approach we identified one of the 707 up-regulated genes (0.14%) with evidence of isolated gene body hypermethylation (HBZ, log2-fold change in gene expression 4.25, FDR=0.0008, DMR area=1.61, DMR FDR=0.018). Representative examples of up-regulated mitotic kinases without evidence of differential gene body methylation are shown in Figure 1d (pie charts represent the mean β-values of microarray probes, p-values represent the comparisons of mean β-values between MT and WT CMML per gene). Conclusions: Gene body methylation was positively associated with gene expression in MT CMML. However, the lack of differential gene body methylation between WT and MT CMML for the up-regulated genes make it an unlikely explanation for the observed increase in transcriptional activity among patients with MT CMML. Figure 1 Disclosures Ordog: Millipore Sigma: Patents & Royalties.

Introduction: Additional Sex Combs-Like 1 (ASXL1) is a chromatin modifier frequently affected by truncating mutations in myeloid malignancies. In chronic myelomonocytic leukemia (CMML), truncating ASXL1 mutations are associated with the overexpression of leukemogenic driver genes, however the molecular mechanisms underlying this transcriptional activation remain controversial. We performed single-cell chromatin accessibility studies of ASXL1-mutant (MT) and -wildtype (WT) CMML to identify cis-regulatory elements (CREs) such as distal enhancer elements that may explain the observed transcriptional activity in MT CMML. Methods: Bone marrow mononuclear cells from a patient with WT and a patient with MT CMML were subjected to single-cell DNA transposase accessibility studies (scATAC-seq). The cryopreserved cells were thawed and resuspended and approximately 100000 viable mononuclear cells per sample were subjected to transposase assays before proceeding to single-cell partitioning into gel beads in emulsion, barcoding, library construction, and sequencing following an established 10X Genomics workflow. The target cell recovery was approximately 2000 cells per sample. Genomic libraries were sequenced on an Illumina HiSeq 4000 before demultiplexing, alignment to the reference genome, and post-alignment quality control. The 10X Genomics Cell Ranger ATAC software was used for demultiplexing, alignment of the reads to the GRCh38 reference genome, filtering and quality control, counting of barcodes and unique molecular identifiers, identification of transposase cut sites, detection of accessible chromatin peaks, count matrix generation for peaks and transcription factors, clustering, and differential accessibility analysis. The two-sample Kolmogorov-Smirnov test for equality of distribution functions was used to compare the distributions of single-cell entropies. Single-cell cis-co-accessibility scores were estimated using Cicero. Results: To mitigate potential effects on the analysis introduced by unequal cell recovery due to experimental conditions, we randomly sampled 1500 single cells from each genotype. Visualizing the first two principal components of the chromatin accessibility data revealed the differences in chromatin conformation between genotypes and also the increased heterogeneity within the MT sample (Figure 1a). To quantify this increase in intratumoral heterogeneity of chromatin accessibility in MT CMML, we calculated the single-cell entropies for both genotypes. There was an increase in the dispersion of single-cell entropy values (mean 0.793±0.026 versus 0.811±0.012, p=6.19x10-151) in MT compared to WT disease (Figure 1b). To leverage the power of the single-cell chromatin accessibility data, we estimated cis-co-accessibility scores (two-way chromatin interactions). There were 631 genes involved in two-way chromatin interactions that were either specific to MT CMML or were shared between MT and WT CMML and showed an increase in co-accessibility in MT CMML. Co-accessibility was higher in MT compared to WT CMML, regardless whether the chromatin interaction was MT-specific or shared between the genotypes (Figure 1c). Gene ontology analysis revealed increased chromatin accessibility in genes involved in the regulation of cell cycle, nuclear division, chromosome organization, cell cycle phase transition, DNA conformation change, and DNA replication (FDR<1.00x10-5). The construction of cis-co-accessibility networks demonstrated a remodeling of the chromatin landscape with MT-specific chromatin interactions involving key mitotic kinases such as MAP2K3 (Figure 1d). Conclusions: MT CMML is characterized by an increase in intratumoral heterogeneity and increased chromatin accessibility. The increased chromatin co-accessibility involved key mitotic kinases and may serve as a plausible explanation for the increased transcriptional activity observed in MT CMML. Figure 1 Disclosures Ordog: Millipore Sigma: Patents & Royalties.

Introduction: Truncating mutations in the Additional Sex Combs-Like 1 (ASXL1) gene are associated with a proliferative disease phenotype and poor survival outcomes across the spectrum of myeloid malignancies including chronic myelomonocytic leukemia (CMML). ASXL1 is thought to act as a chromatin modifier regulating transcriptional activity, however the exact mechanisms and resulting chromatin states remain controversial. We interrogated the epigenome of 16 patients with ASXL1-mutant and -wildtype CMML using a multiomics approach. Methods: Bone marrow mononuclear cells from patients with CMML (8 ASXL1-mutant, 8 -wildtype) were subjected to targeted NGS of DNA, whole transcriptome shotgun sequencing (RNA-seq), immunoprecipitation (IP) of DNA (hydroxy-)methyl residues (DIP-seq), IP of the histone modifications H3K4me1, H3K4me3, and H3K27me3 (ChIP-seq), and DNA transposase accessibility studies (ATAC-seq). After quality control all samples were sequenced on an Illumina HiSeq 4000 before further processing and data analysis. Global assessments of DNA (hydroxy-)methylation, DNA accessibility, and histone modifications between ASXL1-mutant and -wildtype CMML were performed. Differential gene expression was performed to define the up-regulated genes in ASXL1-mutant disease. The promoter regions of these up-regulated genes (defined as transcription start site ±3kb) were compared using the aforementioned multiomics approach. Epigenomic modification of the promoter region facilitating up-regulation of transcription was defined as the presence of a signal peak in ASXL1-mutant disease (in the absence of a signal peak in -wildtype disease) or 25% increase in a common signal peak (H3K4me1/3, 5hmC), the presence of a unique signal peak in ASXL1-mutant disease (ATAC), or the absence of a signal peak in ASXL1-mutant disease (in the presence of a signal peak in -wildtype disease), or 25% decrease in a common signal peak (H3K27me3, 5mC). Results: Sixteen patients with CMML, median age 69 years (48 - 77), 63% male, were included. Half of the patients had proliferative disease (pCMML) and half of them had truncating frameshift mutations in ASXL1 (heatmap). All ASXL1 variant allele frequencies were compatible with heterozygosity (31 - 48%). The burden of co-mutations was similar between ASXL1-wildtype and ASXL1-mutant disease (21 versus 23 per group; no difference in the median number of co-mutations, p = 0.684). The spectrum of co-mutations was typical for CMML, involving spliceosome components, epigenetic regulators, chromatin regulators, and cell signaling molecules (heatmap). There was a predominant up-regulation of gene expression in ASXL1-mutant patients: 707 genes up- and 124 down-regulated (volcano plot, FDR < 0.05 for all genes). Functional annotation of the up-regulated genes showed cell division, mitotic nuclear division, sister chromatid cohesion, DNA replication, and G1/S transition to be the 5 most enriched processes (accounting for 29% of all up-regulated genes, FDR < 1x10-10 for all terms). The up-regulated genes included several potential therapeutic targets and HOXA family members (including HOXA9). There were global increases in H3K4me1/3, 5mC, and 5hmC, decreases in H3K27me3, as well as a more relaxed chromatin conformation (bar graphs). Many of these epigenomic changes affected non-coding regions. When focusing on the promoter regions of the 707 up-regulated genes there was evidence of one or more of the interrogated epigenomic mechanisms facilitating transcription for 519 of the genes (73%). The most abundant mechanism was histone modification, followed by changes in DNA (hydroxy-)methylation, and increased chromatin accessibility, with considerable overlap (Venn diagram). For HOXA9, a known driver of leukemogenesis, the data supported a loss of H3K27me3 as the most prominent among the interrogated epigenomic regulatory mechanisms (average signal tracks). Conclusions: The transcriptome and chromatin conformation of ASXL1-mutant CMML are skewed towards proliferation and mirror the aggressive disease phenotype observed in practice. There is evidence of histone modification as well as changes in DNA methylation, and chromatin conformation facilitating transcriptional activity including known leukemogenic drivers. Additional regulatory mechanisms such as gene body methylation and enhancer elements require further exploration. Figure Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Introduction: Additional Sex Combs-Like 1 (ASXL1) is a chromatin modifier frequently affected by truncating mutations in myeloid malignancies. These mutations are associated with poor survival outcomes and increased rates of acute leukemic transformation. In chronic myelomonocytic leukemia (CMML), ASXL1 mutations are thought to affect transcriptional activity mainly by modifying histone marks, however additional epigenomic mechanisms have not been fully explored. We interrogated the epigenome of patients with ASXL1-mutant (MT) and -wildtype (WT) CMML using a multiomics approach to define cis-regulatory elements (CREs) such as distal enhancers (DEs). Methods: Bone marrow mononuclear cells from patients with CMML were subjected to targeted NGS of DNA, whole transcriptome shotgun sequencing (RNA-seq), immunoprecipitation (IP) of DNA (hydroxy-)methyl residues (DIP-seq), IP of the histone modifications H3K4me1, H3K4me3, and H3K27me3 (ChIP-seq), and DNA transposase accessibility studies (ATAC-seq). After quality control all samples were sequenced on an Illumina HiSeq 4000 before further processing and data analysis. Global assessments of DNA (hydroxy-)methylation, DNA accessibility, and histone modifications between ASXL1 MT and WT CMML were performed. The samples in the two groups were treated as biological replicates and subjected to a consensus peak calling strategy requiring an overlap of at least 30% between samples and an adjusted p-value < 5x10-5 for a signal peak to be considered statistically significant. Differential gene expression was estimated to define the up-regulated genes in ASXL1 MT CMML. Potential CREs were defined as sites with statistically significant signal peaks overlapping in at least two of the three epigenomic marks: H3K4me1, 5hmC, and ATAC. Potential DEs were defined as CREs in non-coding regions outside promoter regions (defined as transcription start site ±3kb) that were annotated in GeneHancer. Annotated DEs only present in ASXL1 MT but not WT CMML (specific DEs) were intersected with the list of up-regulated genes and the ReMap atlas. Results: Sixteen WHO-defined CMML patients were included, median age 69 years (48 - 77), 63% male; of which 8 patients (50%, all truncating frame shift mutations) were ASXL1 MT and 8 (50%) WT. The burden and spectrum of co-mutations was similar between ASXL1 WT and MT CMML (21 versus 23 per group; p = 0.684; heatmap). There was a predominant up-regulation of gene expression in ASXL1 MT CMML: 707 genes up- and 124 down-regulated (volcano plot, FDR < 0.050 for all genes). There were 64336 potential CREs, the vast majority (97%) being present in both ASXL1 MT and WT CMML (left Venn diagram). These CREs were most commonly located in introns, promoter regions, and distal non-coding regions (bar graph and pie chart). There were 1303 CREs unique to ASXL1 MT CMML (specific DEs), 1161 (90%) of which were annotated in GeneHancer (left Euler diagram). Of these 1161 annotated specific DEs 859 (74%) were located outside promoter regions and 34 (4%) of them were known to be associated with genes up-regulated in ASXL1 MT CMML (Euler diagrams). These specific DEs were characterized by an increase in H3K4me1 occupancy and DNA accessibility (average signal tracks, purple bars indicating annotated DEs, thin bars below peaks indicating statistical significance). We previously observed epigenomic modification of promoter regions in 519 of the 707 up-regulated genes (73%) facilitating transcriptional activity in ASXL1 MT CMML. For 13 of the up-regulated genes (right Venn diagram, blue genes in volcano plot) the specific DEs were the sole identified mechanism, while for the other 21 genes there were additional mechanisms noted in the promoter region. The top five transcription factor candidates binding the 34 specific DEs included JMJD1C, MYC, KDM5B, RCOR1, and HDAC2 (-log10(E) > 40 for all candidates). Conclusions: Using a multiomics approach based on H3K4me1, 5hmC, and ATAC data we identified potential CREs in ASXL1 MT CMML and characterized potential DEs using publicly available annotation data. Specific DEs were associated with up-regulated genes serving as a possible explanation for the observed transcriptional activity, shedding further light on the adverse prognostic impact associated with ASXL1 mutations. Figure 1 Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.