Arsana, Arini

Abstract Introduction TP53-mutated (TP53mut) myeloid neoplasms (MN) are a distinct entity of myeloid neoplasms with no effective therapies and poor survival (Grob et al, Blood 2022). The TP53-deficient state facilitates the downstream dysfunction of the spindle assembly checkpoint (SAC), predisposing to genomic instability. Recently, a SAC protein, threonine tyrosine kinase (TTK), has emerged as an attractive therapeutic target. Upregulation of TTK has been described in various solid tumors. It is stipulated that targeting SAC proteins might result in extreme level of genomic instability that even cancer cells could not tolerate. We hypothesized that inhibition of TTK with a small molecular inhibitor—TTKi may offer a promising therapeutic strategy for TP53mut MN. Method We evaluated relative TTK mRNA expression and its association with TP53mut and complex karyotypes (CK) in the BEAT AML cohort (Tyner et al., 2018). We used myeloid cell lines, OCI-AML-3, THP-1, and U937 cell lines that harbor-near diploid, moderately aneuploid, and highly aneuploid karyotype, respectively. The efficacy of TTKi CFI-402257 (AbMole) was tested using cell viability, apoptosis, and colony-forming unit (CFU) assays using the standard protocol. Finally, we tested the efficacy of CFI-402257 using the diagnostic bone marrow mononuclear cell (BMMC) cells from TP53mut MN patients. Results Among 591 AML patients in the BEAT AML cohort (41.6% diploid, 35.9% non-CK, 22.7% CK), TTK mRNA expression was progressively higher with increasing chromosomal abnormality burden. TTK expression was 1.96-fold higher in TP53mut AML compared to TP53wt AML (P=0.0008). Further stratified by TP53mut VAF, there was a trend towards higher expression of TTK in TP53mut VAF≥50 compared to the cases with VAF<50 (P=0.06). Next, the treatment with TTKi (CFI-402257) led to a dose-dependent reduction in cell viability across all cell lines, with TP53mut cells (U937 and THP-1) being more sensitive than TP53-wildtype (TP53wt) OCI_AML-3 cells. Similarly, TTKi inhibited the CFU potential of THP-1, U937, and OCI-AML-3 cells. Finally, TTKi induced dose-dependent apoptosis in TP53mut MN patient BMMC but not in healthy donors, resulting in a significant reduction in colony-forming potential. Conclusion Overexpression of TTK was strongly associated with TP53mut and CK in AML. Inhibition of TTK-induced dose-dependent apoptosis in all myeloid cell lines tested with TP53mut highly aneuploid cell line (U937)—traditionally the most chemorefractory phenotype—being the most sensitive. TTKi induced preferential and dose-dependent inhibition of viability and cell proliferation potential in TP53mut MN compared to healthy donor cells, implying a therapeutic window. Further pre-clinical and clinical studies are indicated to evaluate SAC inhibition as a therapeutic strategy for TP53mut MN. Citation Format: Arini Arsana, Huixing Huang, Arief Al-Kali, Mithun Shah. Spindle assembly checkpoint as a therapeutic target for TP53-mutated myeloid neoplasms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3179.

Introduction The advent of venetoclax (VEN) based chemotherapy has revolutionized the treatment of elderly acute myeloid leukemia (AML), with improvement in remission rates from historical 10%-20% to 60%-70%. However, remission duration is short-lived in patients (pts) with high-risk AML with consequent dismal outcome. As our knowledge of genomic landscape of AML expands and more immunotherapies become available, exploration of the immune tumor microenvironment (TME) of AML may allow identification of subsets of pts that may benefit from immune based therapy. We conducted an investigator initiated prospective study to evaluate TME of pts receiving VEN plus hypomethylating agent (HMA; azacitidine or decitabine) combination. We hypothesize that these pts will cluster into immune-infiltrated vs. immune-depleted sub-types by high-definition immune cell profiling. Methods In 26 newly diagnosed AML pts, who were planned to receive VEN plus HMA therapy, we isolated bone marrow (BM) and peripheral blood (PB) derived mononuclear cells (MC) by density gradient centrifugation and cryopreserved. We performed CyTOF (cytometry time-of-flight) analysis to study their immune signatures. Thawed cells were labeled with metal-conjugated antibodies that bind CD33, CD196, CD19, CD127, CD11b, CD4, IgD, CD11c, CD14, CD56, CD123, TCRgd, CD185/CXCR5, CD45RA, CD27, CD28, CD66b, CD183 (CXCR3), CD161, CD45RO, CD197 (CCR7), CD8a, CD25, CD3, CD20, CD38, HLA-DR, CD194 (CCR4), CD57, CD16 and CD45. We performed a Rphenograph clustering on 25 paired BMMC and PBMC samples (one patient only had PBMC) to create 35 unique clusters for each ( Figure 1). Then we broke down the distribution of cluster by two different groupings: pts with TP53 mutation (m) and those who achieve complete remission. Statistical significance of clusters calculated using t-test. We performed Pearson correlation test on the paired BMMC and PBMC samples to assess correlation between BMMC and PBMC samples. Results Baseline characteristics The median age of the pts was 74 years (range, 53-88), and 17 (65%) pts were male. Ten (37%) pts had secondary AML, and 12 (46%) pts had ELN adverse risk disease (n=6; TP53m). There was no significant difference in median age (p= >0.99), proportion of pts with secondary AML (p= 0.64), acute myelomonocytic leukemia (p= 0.14) white blood cell count (WBC) ≥ 100 (10 9/L) (p= >0.99), and frequency of commonly occurring co-mutations ( ASXL1 [p=0.35]), FLT3 ITD [p=0.54], splicing [p=0.29], IDH1/2 [p=0.28], DNMT3A [p=0.29], NPM1 [p=0.29], TET2 [p=0.35]) in TP53m and TP53 wild-type group. Response 12/20 (60%) evaluable pts achieved complete remission with or without count recovery (CR/CRi). There was no significant difference in median age (p= 0.06), proportion of pts with secondary AML (p= 0.16), therapy related AML (p= 0.60) WBC ≥ 100 (10 9/L) (p= 0.40), and frequency of commonly occurring mutations ( TP53 [p=0.60], ASXL1 [p > 0.99]), FLT3 ITD [p=0.54], splicing [p > 0.99], IDH1/2 [p=0.60], DNMT3A [p=>0.99], NPM1 [p=0.61], TET2 [p >0.99]) in CR/CRi and no-CR/CRi group. CyTOF analysis and Rphenograph clustering on 25 paired BMMC and PBMC samples We found significant clustering with high expression of B-cell activated (cluster 2; p= 0.005), NK cell rich (cluster 1; p= 0.005, cluster 35; p= 0.0009), CD8 T-cells (cluster 31; p= 0.01) and CD4 effector cells (cluster 17; p= 0.005) phenotype among TP53m AML ( Table 1). Among pts who achieved CR/CRi, significant clustering with low expression of B-cell activated (cluster 29; p= 0.01), CD8 cytotoxic (cluster 14; p= 0.01) CD4 activated (cluster 21; p= 0.03) phenotypes observed. Correlation between BMMC and PBMC clustering Among clusters which showed significance for a particular phenotype, we performed Pearson correlation (R 2) and observed strong correlation between BMMC and PBMC samples clustering in cluster 1 (R 2 = 0.99), cluster 2 (R 2 = 0.95), cluster 17 (R 2 = 0.96), cluster 21 (R 2 = 0.99) and cluster 29 (R 2 = 0.93). Conclusion In this single institutional study using CyTOF analysis we have identified novel clustering with immune- infiltrated phenotype among pts with TP53m AML and conversely immune-depleted phenotype among AML pts who responded to VEN plus HMA. Moreover, we found strong correlation in CyTOF analysis conducted from BMMC and PBMC samples. Future studies with larger sample size needed to validate our findings.

Background: Upfront autologous stem cell transplant (ASCT) is the standard-of-care for newly diagnosed multiple myeloma (MM) patients. However, relapse and the development of therapy-related myeloid neoplasms (t-MN) post ASCT results in considerable morbidity and mortality. We hypothesized that enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in peripheral blood stem cells (PBSCs) of patients with MM is associated with a higher risk of relapse and development of t-MN. Methods: After institutional review board approval, we screened patients with active MM that were evaluated at Mayo Clinic, Rochester, MN between 01/01/2003 and 12/31/2020. Patients that underwent an ASCT and had cryopreserved PBSC product available for research were included. Using mass cytometry, we performed a comprehensive immunophenotyping of mobilized cryopreserved PBSCs from 54 MM patients undergoing 1 st ASCT, using validated antibody panel of 37 lymphoid- and myeloid-based markers each. Flow cytometry standard files were normalized and concatenated using the Fluidigm acquisition software. Flow cytometry standard files were uploaded to the OMIQ software from Dotmatics (www.omiq.ai, www.dotmatics.com), where transformation and cleaning (doublets, debris) were performed. To correct for between-sample technical variations (“batch effects”), we used fdaNorm within the omiq.ai platform. Clustering and visualization of normalized and concatenaded flowcytometry files were performed within the omiq.ai platform using PhenoGraph and UMAP, respectively. We performed principal component analysis (PCA) to identify major immunomic drivers of variability across patients. We explored the associations between immune subsets and the dichotomized clinical outcomes of interest: progression-free (PFS), myeloid neoplasm-free (MNFS) and overall survival (OS) from ASCT. A 2-sided false discovery rate adjusted P-value of <0.05 was considered significant when multiple comparisons were performed; otherwise, a P-value of <0.05 was considered significant. Results: The most abundant cell populations were T-cells (49% of the CD45 +) and myeloid cells (43% of the CD45 + cells). Clustering on the CD45 + cells revealed 30 unique lymphoid clusters and 27 unique myeloid clusters. Subclustering on NK-cells identified an additional 16 NK-cell clusters. On PCA, principal components-1 (PC-1) and 2 (PC-2) explained 15.2% and 12.5% of the variability in the data, respectively. A high PC-2 score was associated with inferior median PFS (20 vs. 52 months; P=0.005, Figure 1A), MNFS (52 vs. 85 months, P=0.03, Figure 1B) and OS (64 vs. 106 months, P=0.01) from ASCT. Immune subsets enriched in the high PC-2 cohort included the ‘NKT-like’ (CD56 +) T-cell subset which expressed the inhibitory CD159a receptor and TIGIT; a terminally differentiated (CD27/CD28 -, CD57/KLRG1 +) and exhausted (TIGIT/PD-1 +) T cell subset, 2 exhausted (TIGIT/PD-1 +) T cell subsets; an immunosenescent (CD27/CD28 -, CD57/KLRG1 +) T cell subset as well as a terminally exhausted (C27/C28 -, KLRG1/PD-1/TIGIT +) TCRgamma-delta subset. Immune subsets with high loadings within PC-1 (associated with improved clinical outcomes) consisted exclusively of CD4 + cells with early memory phenotypes (CD27/CD28/CD127 +). Abnormal expression of CD7 and HLA-DR expression on myeloid progenitor cell subsets was associated with an inferior PFS, MNFS, and OS. A NK-cell subcluster, characterized by an immature (CD56 high), inhibitory (CD159a +, NKG2A) phenotype, was enriched in patients developing t-MN (0.33% vs. 0.17%, P=0.006). Conclusion: We identify abnormal myeloid and immune effector cells in the PBSCs of patients with MM, even prior to ASCT. Patients with a PBSC product that is enriched in immunosuppressive T and myeloid cell subsets, and with a lower proportion of antigen presenting cells, progenitor populations, and anti-tumor macrophages have a shorter PFS and MNFS. This suggests that the predisposition to t-MN and inferior outcomes for MM are possibly determined early in the disease course. These findings need external validation and have the potential to guide sequencing of future treatment modalities.