Dean, Christopher

6513 Background: PTPN11 (Ch12q24) is a proto-oncogene that codes for SHP2, a regulatory protein tyrosine phosphatase that impacts RAS/MAPK signaling. Germline variants have been described in juvenile myelomonocytic leukemia, while somatic variants have been associated with inferior survival in acute myeloid leukemia. PTPN11 variants are infrequent in chronic myelomonocytic leukemia (CMML), and their impact on disease phenotype and survival remains unclear. Methods: After IRB approval, 396 molecularly annotated CMML patients at Mayo Clinic were screened for somatic PTPN11 variants within 12 months of diagnosis while still in chronic phase disease. Overall (OS), acute myeloid leukemia (AML)-free survival (LFS), and predictors of survival were estimated using standard statistical measures. Results: 396 patients (median age 71 years; males 67%) with CMML were considered; pathogenic PTPN11 variants were seen in 12 (3%) with a median VAF of 20.5% (range: 4-50): A72T (n = 2), F285S (n = 2), and A72S (n = 2). Variants were most likely to be seen in the N-terminal SH2 domain (n = 7), followed by the PTP domain (n = 6), and the C-terminal SH2 domain (n = 1). PTPN11 variants clustered with CMML-2 (p = 0.02), higher absolute neutrophil count (p = 0.04), peripheral blood (p = 0.06) and bone marrow (p = 0.02) blast %, older age (p <0.01), and were less likely to have SRSF2 comutations (p = 0.02). After a median follow-up of 18 months (range 0-193), 253 (64%) deaths and 68 (17%) AML transformations were recorded. PTPN11 variants negatively and independently impacted both OS (median 13 vs. 31 months; p <0.01) and LFS (AML events: 42% (5/12) vs. 16% (63/384); p <0.01). In age-adjusted multivariate analysis restricted to genetic risk factors, survival was negatively affected by abnormal karyotype and mutations involving PTPN11, DNMT3A, and SETBP1, and positively by TET2 mutations. All but SETBP1 retained significance in the presence of additional independent risk factors, namely male sex (p <0.01) and leukocyte count (p <0.01); HR in the latter analysis was 4.3 for PTPN11, 2.8 for DNMT3A, and 1.6 for abnormal karyotype. A similar analysis for LFS identified, as risk factors, PTPN11 (p = 0.01), DNMT3A (p <0.01), and ASXL1 (p = 0.03) mutations, as well as bone marrow blast % (p <0.01), absolute monocyte count ≥10 (p = 0.02), and immature circulating myeloid cells (p <0.01). Conclusions: The current study identifies PTPN11 and DNMT3A mutations as independent risk factors for both OS and LFS in CMML. In regard to additional genetic risk factors, OS was positively affected by TET2 mutations and negatively by abnormal karyotype, while LFS was negatively affected by ASXL1 mutations.

Introduction: Clonal dendritic cell (DC) aggregates in chronic myelomonocytic leukemia (CMML) are seen in approximately 20-30% patients at diagnosis. Previously, these were thought to be comprised of CD123+ plasmacytoid DCs but our data has suggested that these are heterogenous and comprise of myeloid DCs, monocytes, and myeloid-derived suppressor cells. Furthermore, these aggregates uniformly express immune checkpoints such as indoleamine 2,3-dioxygenase-1 (IDO), associate with an IDO-specific systemic impact (increased trytophan catabolism), and expanded regulatory T cell population in CMML, suggesting a role in inducing immune tolerance. DC aggregates are also associated with increased risk of acute myeloid leukemia (AML) transformation and resistance to hypomethylating agents, highlighting that they are important for disease progression in CMML (Mangaonkar A et al. Blood Adv 2020). We performed this study to decipher the architecture of a CMML DC aggregate to understand the complex inter-cellular interactions, and assess their impact on the adaptive immune system. Methods: In this study, we used archival fresh-frozen paraffin-embedded (FFPE) bone marrow biopsy specimens obtained from CMML patients, and isolated monocytes (CD14+ magnetic bead sorting) and lymphocytes (CD14-ve fraction) from untreated CMML and age-matched normal control (NC) peripheral blood mononuclear cells (PBMCs). DCs were cultured from monocytes using a commercial protocol. Spatial architecture of the CMML BM microenvironment was interrogated through multiplex imaging of FFPE samples by co-detection by indexing (CODEX) using 30 markers (CCR6, CD107a, CD11c, CD20, CD21, CD31, CD3e, CD4, CD44, CD45, CD45RO CD56, CD68, CD8, E-Cadherin, FoxP3, HLA-DR, CD14, CD16, CD11b, CD33, CD15, CD66b, CD123, CD303, CD34, CD163 and IDO). Single-cell transcriptomic signatures were analyzed using the 10X single cell Fixed RNA profiling platform, and validated using bulk RNA seq (Illumina stranded mRNA prep) from isolated and cultured cells. Impact of DCs on lymphocytes was assessed via autologous mixed DC-T culture experiments. Results: BM FFPE samples from 5 CMML cases (3 with DC aggregates) were included for multiplex imaging via CODEX. Results confirm the significant interactions of CD8+ and CD4+ T cells with CD123+/HLA-DR+ DCs within a CMML DC aggregate (Fig. 1A). Upon quantitative assessment of cell-cell interactions, IDO+/CD8+T ( P=0.006), IDO+/MDSC ( P=0.005), and IDO+/macrophage ( P=0.001) interactions were significantly increased in CMML samples with versus without DC aggregates . Specific findings were validated using single-stain immunohistochemistry and multiplex immunoflourescence staining. Next, in order to assess transcriptomic signatures within BM at the single-cell level, we chose two cases; CMML (BM aspirate blast% 1, WBC 49.6 x 10 9/L, ASXL1/GATA2/SETBP1/SRSF2 mutations) and AML transformed from CMML (BM aspirate blast% 81, WBC 152 x 10 9/L, NPM1/DNMT3A/TET2 mutations). Approximately, 10,000 cells were obtained and analyzed with cell type annotation through human PBMC reference (Azimuth). Results show an expanded regulatory T cell population in AML compared to CMML (UMAP plot, Fig. 1B), suggestive of immune tolerance. In order to validate findings and perform functional experiments, we used sorted monocytes and cutured DCs from CMML and NC. DC phenotype was confirmed both through visual inspection and flow cytometry, and clonality was confirmed through Sanger sequencing (for previously identified mutations). Differential gene expression analysis through bulk RNAseq showed significant differences between CMML and NC lymphocytes with immunoinhibitory receptor, LILRB2 (log2fold change=7.05, adjusted P=0.0002) being one of the top five significantly upregulated genes, further confirming immune tolerance. Finally, mixed autologous DC-lymphocyte reaction (1:4 ratio) experiments demonstrated that DCs induce T cell tolerance in CMML (expansion of exhausted PD1/TIM3/LAG3+ CD8 T cells) when compared to NC. Conclusion: Clonal dendritic cell aggregates within the CMML bone marrow microenviroment interact with T cells and induce immune tolerance. This represents a novel mechanism of disease progression in CMML with potential therapeutic targets (IDO, LILRB2, and/or CD123).

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values &lt; 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p &lt; 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p &lt; 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.