Acute Myeloid Leukemia Microenvironment Research Articles

Chimeric antigen receptor T-cell therapy in childhood acute myeloid leukemia: how far are we from a clinical application?

Recurrent and/or refractory (R/R) pediatric acute myeloid leukemia (AML) remains a recalcitrant disease with poor outcomes. Cell therapy with genetically modified immune effector cells holds the promise to improve outcomes for R/R AML since it relies on cytotoxic mechanisms that are distinct from chemotherapeutic agents. While T cells expressing chimeric antigen receptors (CAR T cells) showed significant anti-AML activity in preclinical models, early phase clinical studies have demonstrated limited activity, irrespective of the targeted AML antigen. Lack of efficacy is most likely multifactorial, including: (i) a limited array of AML-specific targets and target antigen heterogeneity; (ii) the aggressive nature of R/R AML and heavy pretreatment of patients; (iii) T-cell product manufacturing, and (iv) limited expansion and persistence of the CAR T cells, which is in part driven by the immunosuppressive AML microenvironment. Here we review the results of early phase clinical studies with AML-specific CAR T cells, and avenues investigators are exploring to improve their effector function.

CAR-T Cells in Acute Myeloid Leukemia: Where Do We Stand?

Despite recent advances, the prognosis of acute myeloid leukemia (AML) remains unsatisfactory due to disease recurrence and the development of resistance to both conventional and novel therapies. Engineered T cells expressing chimeric antigen receptors (CARs) on their cellular surface represent one of the most promising anticancer agents. CAR-T cells are increasingly used in patients with B cell malignancies, with remarkable clinical results despite some immune-related toxicities. However, at present, the role of CAR-T cells in myeloid neoplasms, including AML, is extremely limited, as specific molecular targets for immune cells are generally lacking on AML blasts. Besides the paucity of dispensable targets, as myeloid antigens are often co-expressed on normal hematopoietic stem and progenitor cells with potentially intolerable myeloablation, the AML microenvironment is hostile to T cell proliferation due to inhibitory soluble factors. In addition, the rapidly progressive nature of the disease further complicates the use of CAR-T in AML. This review discusses the current state of CAR-T cell therapy in AML, including the still scanty clinical evidence and the potential approaches to overcome its limitations, including genetic modifications and combinatorial strategies, to make CAR-T cell therapy an effective option for AML patients.

Identification of Prognostic Genes in Acute Myeloid Leukemia Microenvironment: A Bioinformatic and Experimental Analysis.

Acute myeloid leukemia (AML) is a lethal hematologic malignancy with a variable prognosis that is highly dependent on the bone marrow microenvironment. Consequently, a better understanding of the AML microenvironment is crucial for early diagnosis, risk stratification, and personalized therapy. In recent years, the role of bioinformatics as a powerful tool in clarifying the complexities of cancer has become more prominent. Gene expression profile and clinical data of 173 AML patients were downloaded from the TCGA database, and the xCell algorithm was applied to calculate the microenvironment score (MS). Then, the correlation of MS with FAB classification, and CALGB cytogenetic risk category was investigated. Differentially expressed genes (DEGs) were identified, and the correlation analysis of DEGs with patient survival was done using univariate cox. The prognostic value of candidate prognostic DEGs was confirmed based on the GEO database. In the last step, real-time PCR was used to compare the expression of the top three prognostic genes between patients and the control group. During TCGA data analysis, 716 DEGs were identified, and survival analysis results showed that 152 DEGs had survival-related changes. In addition, the prognostic value of 31 candidate prognostic genes was confirmed by GEO data analysis. Finally, the expression analysis of FLVCR2, SMO, and CREB5 genes, the most related genes to patients' survival, was significantly different between patients and control groups. In summary, we identified key microenvironment-related genes that influence the survival of AML patients and may serve as prognostic and therapeutic targets.

Leukemic mutation FLT3-ITD is retained in dendritic cells and disrupts their homeostasis leading to expanded Th17 frequency.

Dendritic cells (DC) are mediators between innate and adaptive immune responses to pathogens and tumors. DC development is determined by signaling through the receptor tyrosine kinase Fms-like tyrosine kinase 3 (FLT3) in bone marrow myeloid progenitors. Recently the naming conventions for DC phenotypes have been updated to distinguish between "Conventional" DCs (cDCs) and plasmacytoid DCs (pDCs). Activating mutations of FLT3, including Internal Tandem Duplication (FLT3-ITD), are associated with poor prognosis for acute myeloid leukemia (AML) patients. Having a shared myeloid lineage it can be difficult to distinguish bone fide DCs from AML tumor cells. To date, there is little information on the effects of FLT3-ITD in DC biology. To further elucidate this relationship we utilized CITE-seq technology in combination with flow cytometry and multiplex immunoassays to measure changes to DCs in human and mouse tissues. We examined the cDC phenotype and frequency in bone marrow aspirates from patients with AML to understand the changes to cDCs associated with FLT3-ITD. When compared to healthy donor (HD) we found that a subset of FLT3-ITD+ AML patient samples have overrepresented populations of cDCs and disrupted phenotypes. Using a mouse model of FLT3-ITD+ AML, we found that cDCs were increased in percentage and number compared to control wild-type (WT) mice. Single cell RNA-seq identified FLT3-ITD+ cDCs as skewed towards a cDC2 T-bet- phenotype, previously shown to promote Th17 T cells. We assessed the phenotypes of CD4+ T cells in the AML mice and found significant enrichment of both Treg and Th17 CD4+ T cells in the bone marrow and spleen compartments. Ex vivo stimulation of CD4+ T cells also showed increased Th17 phenotype in AML mice. Moreover, co-culture of AML mouse-derived DCs and naïve OT-II cells preferentially skewed T cells into a Th17 phenotype. Together, our data suggests that FLT3-ITD+ leukemia-associated cDCs polarize CD4+ T cells into Th17 subsets, a population that has been shown to be negatively associated with survival in solid tumor contexts. This illustrates the complex tumor microenvironment of AML and highlights the need for further investigation into the effects of FLT3-ITD mutations on DC phenotypes and their downstream effects on Th polarization.

5-methylcytosine RNA modification regulators-based patterns and features of immune microenvironment in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a highly heterogeneous malignant disease of the blood cell. The current therapies for AML are unsatisfactory and the molecular mechanisms underlying AML are unclear. 5-methylcytosine (m5C) is an important posttranscriptional modification of mRNA, and is involved in the regulation of mRNA stability, translation, and other aspects of RNA metabolism. However, based on our knowledge of published literature, the role of the m5C regulators has not been explored in AML till date. In this study, we clarified the expression and gene variants of m5C regulators in AML and found that most m5C regulators were differentially expressed and correlated with disease prognosis. We also found that the methylation status of certain m5C regulators (e.g., DNMT3A, DNMT3B) affects the survival of AML patients. Two m5C modification subtypes, and high- and low-risk subgroups identified based on the expression of m5C regulators showed significant differences in the prognosis as well as immune cell infiltration. In addition, most of the m5C regulators were found to be correlated with miRNA expression in AML, as well as IC50 values of many drugs. The miRNA and GSVA analysis were used to identify the different miRNAs and KEGG or hallmark pathways between high- and low-risk subgroups. We also built a prognostic model based on m5C regulators, which was validated by two GSE databases. To verify the reliability of our analysis and conclusions, qPCR was used to identify the expressions of m5C regulators between normal and AML. In summary, we comprehensively explored the molecular characteristics of m5C regulators and built a prognostic model in AML. We proposed new mechanistic insights into the role of m5C in multiple databases and clinical data, which may pave novel ways for the development of therapeutic strategies.

NAD metabolism-related genes provide prognostic value and potential therapeutic insights for acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear. We utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature. An 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target. Our study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

Recent advances in CAR-T therapy for the treatment of acute myeloid leukemia.

Chimeric antigen receptor T-cell (CAR-T) therapy, which has demonstrated notable efficacy against B-cell malignancies and is approved by the US Food and Drug Administration for clinical use in this context, represents a significant milestone in cancer immunotherapy. However, the efficacy of CAR-T therapy for the treatment of acute myeloid leukemia (AML) is poor. The challenges associated with the application of CAR-T therapy for the clinical treatment of AML include, but are not limited to, nonspecific distribution of AML therapeutic targets, difficulties in the production of CAR-T cells, AML blast cell heterogeneity, the immunosuppressive microenvironment in AML, and treatment-related adverse events. In this review, we summarize the recent findings regarding various therapeutic targets for AML (CD33, CD123, CLL1, CD7, etc.) and the results of the latest clinical studies on these targets. Thereafter, we also discuss the challenges related to CAR-T therapy for AML and some promising strategies for overcoming these challenges, including novel approaches such as gene editing and advances in CAR design.

Relationship between Sarcopenia and the Heterogeneity and Microenvironment of Acute Myeloid Leukemia Based on Single-Cell Transcriptome Sequencing

Background: High intratumoral heterogeneity heterogeneity (ITH) and changes in bone marrow microenvironment (BMM) components are important for drug resistance and recurrence in patients with acute myeloid leukemia (AML), and may also influence the phenotype of sarcopenia. This study aims to determine the relationship between sarcopenia and the heterogeneity and microenvironment of AML. Method: Body composition was assessed by bioelectrical impedance analysis before treatment. Sarcopenia was diagnosed by low muscle quantity according to European Working Group on Sarcopenia in Older People 2 (EWGSOP2). Bone marrow samples from 9 patients with relapsed or refractory AML were used to perform single-cell transcriptome sequencing (scRNA-seq) to analyze the differences in tumor cell subsets and microenvironmental components between AML patients with or without sarcopenia. The samples of 19 newly diagnosed AML patients were further collected for bulk RNA-seq, and deconvolution was done. Bioinformatics methods were used to verify the differences in cell subsets of microenvironmental components in patients with and without sarcopenia, as well as the genes and signaling pathways of tumor cells with differential expression. Results: Nine leukemia-like cell subsets were identified in AML patients by scRNA-seq. In AML patients with sarcopenia, hematopoietic stem cell (HSC) subsets accounted for a significantly higher proportion of malignant cells, while progenitor cells and monocytes showed a higher proportion in patients without sarcopenia. In sarcopenic group, there were significantly fewer neutrophils, megakaryocytes, and CD8 + Tcm cells in the microenvironment component, while significantly more immunosuppressed Treg cells. After deconvolution of bulk RNA-seq data from 19 newly diagnosed AML patients, it was confirmed that Treg cells were more distributed in sarcopenic patients. Among them, 167 genes were significantly up-regulated, and the most significantly up-regulated 5 genes were ME3, UBE2E3, PCSK5, LAMC1 and PTPRF. A total of 224 significantly down-regulated genes were identified, including RNF18B, TNFAIP3, GALNT2, ORM2 and IL1R2. Pathway enrichment of differentially expressed genes was found, including signaling pathways regulating pluripotency of stem cells, Hippo signaling pathway, protein digestion and absorption pathway, etc. Conclusion: Sarcopenia may be related to immunosuppressive microenvironment and affect the prognosis of AML patients.

T-Cells Immune Cluster Analysis Using Cytof Identifies Unique Patient Subgroups with TP53 Mutation and Predicts Complete Remission (CR) in Patients with Acute Myeloid Leukemia (AML) Receiving Venetoclax Plus Hypomethylating Agent Therapy

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.

Genome-Wide Methylome and Transcriptome Profiling of Acute Myeloid Leukemia Derived Bone Marrow Mesenchymal Cells Identify Age Group Specific Biological Pathway Dysregulation in the Bone Marrow Microenvironment of AML

Adult patients with acute myeloid leukemia (AML) have a proportionate increase in mortality from their disease and therapy as age increases. In great part, this mortality is due to disease relapse that occurs at a higher rate irrespective of genetic assigned risk. While intensification of therapy in patients with favorable genomics such as core-binding-factor AML (CBF-AML) has yielded a high proportion of long-term remission and potential cure, this benefit has been less frequently observed in patients with AML age 60 and older despite receipt of similar therapy. Moreover, even less benefit has been observed in patients with unfavorable genomics such when bearing a complex karyotype (karyotype with ≥ 3 chromosome abnormalities). Reasons for this unfavorable outcome among older patients is unknown. We hypothesized that tumor-induced aging in cells of bone marrow microenvironment, specifically, in bone marrow mesenchymal stromal cells (BMSCs) plays a significant role in AML survival and progression in older compared to younger patients and that the difference in prognosis may depend on specific aging induced changes in the BMSCs. We expanded BMSCs under physiologic hypoxic conditions (91% nitrogen, 4% oxygen and 5% CO 2) to mimic the bone marrow microenvironment, isolated DNA and RNA from early passaged cells and performed methylation analysis using 850k Illumina DNAmehtylation arrays and gene expression analysis using mRNAseq. We used the Horvath Skin and Blood clock to calculate epigenetic age (DNA methylation age). We determined differentially expressed genes with increasing epigenetic or chronological age in the different AML genetic risk groups (n=9 CBF-AML, n=11 CK-AML and n=7 Normal donor BMSC) as well as in older (>60) and younger (<60) AML-BMSCs, and performed Gene Set Enrichment Analysis (GSEA) for the Hallmarks as well as aging and senescence related genesets (n=33 genesets). We found that BMSCs derived from AML bone marrow cells are more age accelerated than normal donor BMSCs. Our GSEA analysis revealed enrichment for age-associated gene networks that reflected hallmarks of aging, including mitochondrial dysfunction, inflammation, and cellular senescence. Specifically, we observed a positive enrichment for the SenMayo gene signature ( Saul et al. 2022, Nature Communications) and a negative enrichment of proliferation and mitotic gene sets with increasing epigenetic and chronological age (padj<0.05). Gene sets that are related to inhibition of adipogenesis were positively enriched in the CBF-AML BMSCs compared to the CK-AML BMSCs. Our integrated analysis revealed novel observations regarding the cellular changes that occur in the AML stromal microenvironment with increasing age. Most interestingly, our findings suggest that AML derived BMSCs have increased epigenetic age compared to normal donor BMSCs. Additional experiments are ongoing to functionally validate the findings predicted by the enrichment analysis. Our study is the first to suggest an increased epigenetic age in the stromal bone marrow microenvironment of older AML patients.

Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes.

One of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors. The AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The "limma" R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR). Based on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis. In summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.

FLT3-ITD Induces Immune Escape in AML Via up-Regulating CD47 Expression and Decreased Phagocytic Ability of Macrophages

The FLT3-ITD mutation is frequently observed in acute myeloid leukemia (AML) and confer a poor prognosis. FLT3 inhibitors such as Quizartinib could prolong survival. However, very few relapsed patients are cured. Little attention has been paid to the characteristics of the immune microenvironment in FLT3-ITD AML. Within the bone marrow, Flt3/ITD animals demonstrated significantly increased dendritic cells and T cells levels compared to Flt3/WT mice, which suggested that FLT3-ITD can modulate the immune microenvironment in AML. Here, we found that FLT3-ITD cell lines (MV-4-11 and MOLM-13) induced less LDH release compared to FLT3-WT cell lines (HEL and K562) ( Figure a), indicating less macrophage killing. CD47 gene is an integrin related protein, which acts as an “anti phagocytosis” signal, and it interacts with signal-regulatory protein alpha (SIRPalpha) on macrophages, so that tumor cells expressing CD47 can escape being destroyed by macrophages. Further Flow Cytometry results showed that the CD47 Mean fluorescent intensity (MFI) of the FLT3-ITD group was significantly higher than those of the control group ( Figure b). Therefore, we can ask a hypothesis that FLT3-ITD in tumor cells may leads to decreased phagocytic capacity of macrophages and immune tolerance. To test our hypothesis, the FLT3 wildtype (FLT3-OE, FLT3 over expression) or ITD mutant (FLT3-ITD) stable overexpression HEL/K562 cells were constructed by means of lentiviral transfections. In the FLT3-ITD group, the MFI levels of CD47 was higher than FLT3-OE group and FLT3 NC (FLT3 Normal control) group ( Figure c and d). Green-fluorescent (CFSE-stained) Hel and K562 were then added to cultures of macrophages induced by Peripheral Blood Mononuclear Cell stained with the red dye PKH26 (ratio tumor cell:macrophages, 5:1). Flow Cytometry results showed FLT3-ITD decreased the Phagocytic Capacity of Macrophages ( Figure e and f). The TRANSFAC database was used to predict the transcription factor binding sites of the CD47 promoter. We found that HOXB5 may regulate the expression of CD47 at the transcriptional level. Compared with the FLT3-NC and FLT3-OE group, the relative expression level of the CD47 gene in the FLT3-ITD group was significantly upregulated ( Figure g, p < 0.05). To ascertain the mechanism that HOXB5 regulated CD47, we analysed the location CD47 gene on the chromosome, as well as the sequence of promoter and first non-encoding exon of HOXB5 (−2000 ~ 100 bp) by Jaspar online tool (http://jaspar.genereg.net/). Mechanistically, Dual luciferase reporter gene assay and ChIP experiments suggest HOXB5 directly activate CD47( Figure h and i). Compared to the monotherapy group, Combination therapy with CD47 inhibitor and Quizartinib (AC220) significantly promoted the phagocytic ability of M1-like macrophages against MOLM13 cells ( Figure j and k). The mouse model of AML was constructed by injection of 5x106 FLT3-ITD cells via the tail vein. Mouse models further demonstrate that combination therapy with CD47 inhibitor and Quizartinib significantly reduces the tumor burden and improves survival rate. We first revealed that FLT3-ITD can up-regulates CD47 to promote immune escape of macrophages. These evidences indicates that combination therapy with CD47 inhibitor and FLT3-ITD inhibitor can be a promising therapeutic method for impressive treatment of FLT3-ITD AML patients.

Self-Supporting Human Acute Myeloid Leukemia (AML) Bone Marrow Organoids Established from Patient-Derived Xenografts Mimic the Human AML Microenvironment, with Distinct Cytokine Kinetics Correlating with Dynamic Cell Proliferation and Metabolic Shifts

Hallmarks of acute myeloid leukemia (AML) include (1) formation of a self-supporting and self-regulating tumor microenvironment (TME) in the bone marrow (BM) rendering pathological niches that orchestrate retention, proliferation and survival of AML blasts, and (2) a dynamic metabolism that promotes therapy resistance and disease progression. Efforts to understand AML biology and enhance current therapies are hampered by the paucity of state-of-the-art human models that can recreate the three-dimensional (3D) BM TME and recapitulate the heterogeneity, complexity, dynamics, and metabolic shifts observed in human disease. Previously, we described the development of the first long-term self-propagating serum- and cytokine-free human BM organoid generated from an AML patient-derived xenograft (PDX) that captured metabolic shifts during AML progression. Here, we characterize the dynamic changes observed in the self-constituted TME with respect to AML proliferation, metabolism, and upon reconstitution of secondary organoids. BM was collected from NSG mice engrafted with human primary AML cells (PDX-AML model) or naïve control mice and seeded into polyurethane scaffolds in serum- and cytokine-free medium at 4e6 cells per scaffold, optimized previously. Scaffolds were recharged with autologous PDX-AML BM on day (D) 13 and cultured until D70. Organoids were assessed for (1) inter- and intra-scaffold AML kinetics, (2) the TME, (3) metabolic composition and (4) propagation into secondary organoids. AML cell kinetics from organoid culture supernatants reflected those of scaffold-extracted populations (n=3). CD33 +CD44 + AML cells expanded and/or were maintained from 7% (D0) to >10% (D70), being >15% at most culture timepoints. Confocal microscopy revealed reconstitution of typical AML-TME niche interactions within organoids, including expression of fibronectin, VCAM-1 and N-Cadherin, and formation of proliferative niches composed of AML cells with heterogeneous Osteopontin- and Osterix-expressing support cells. Human AML-supportive cytokines were consistently observed in organoid supernatants (N=3), with SDF-1, IL-1α, IL-8, GM-CSF, FGF-2 and Osteopontin present throughout the culture; some cytokines had biphasic kinetics with factors critical for TME formation present early (e.g. Osteopontin, GM-CSF), and those required for AML proliferation dominant later (e.g. FLT3L, IL-8), coinciding also with metabolic shifts during culture. Despite the absence of IL-6, single molecule RNA fluorescence in situ hybridization confirmed IL-6 expression by niche-resident AML blasts suggesting autocrine signaling networks beyond those identified in supernatants. Cells from D70 organoids were able to re-establish secondary organoids (n=2) which also exhibited long-term (D70) AML maintenance (>11% blasts), and regenerated the AML TME. Previously, we identified 3 culture stages defined by metabolic shifts: 1) pre/early recharge (D4-D19), (2) intermediate (D25-D40) and, (3) late (from D55) where organoids exhibited highest proliferation. To further characterize these shifts, intracellular metabolites were extracted from organoids (n=5) at D10, D25, D40, D55 and D70, analyzed with gas-chromatography mass spectrometry (GC-MS) and evaluated through unsupervised hierarchical clustering and multivariate analysis. Significance Analysis of Microarrays (SAM) analysis demonstrated dysregulation of alanine, serine, isoleucine, glycolate, hexanoic acid and glycolysis when comparing stage 1 with stage 2, and in isoleucine, leucine, serine, succinate and tryptophan metabolism when comparing stage 2 with stage 3. When proliferative and non-proliferative timepoints were compared, amino acid and glycolysis-driven metabolic switches were identified, typical of AML metabolism. We have characterized a long-term 3D human AML BM biomimicry in serum- and cytokine-free conditions with a self-organizing TME that recapitulates many features of AML BM, including robust human AML cell maintenance within niches, cytokine and metabolic kinetics to support different phases of progression, and the ability to propagate into secondary organoids. This dynamic, physiologically-relevant ex vivo platform can enable studies in human AML pathogenesis/progression and is poised to test novel therapeutics directed towards AML cells, the TME and metabolic targets.

Tim-3 facilitates immune escape in benzene-induced acute myeloid leukemia mouse model by promoting macrophage M2 polarization

Benzene poisoning can cause acute myeloid leukemia (AML) through a variety of passways. Tim-3 has gained prominence as a potential candidate in mediating immunosuppression in tumor microenvironments. The macrophage polarization is also related to immune escape. Herein, we reported that Tim-3 and macrophage M2 polarization play a vital role in benzene-induced AML. First, the benzene-induced AML C3H/He mouse model was constructed by subcutaneously injecting 250 mg/kg of benzene. After six months, macrophage phenotype, cytokines, and Tim-3 expression levels were investigated. Flow cytometry assay revealed that the T-cell inhibitory receptor Tim-3 was significantly upregulated in both bone marrow and spleen of the benzene-induced AML mouse model. Elisa's results displayed a decreased serum level of IL-12 while increased TGF-β1. Mechanistically, changes in cytokine secretion promote the growth of M2-type macrophages in the bone marrow and spleen, as determined by immunofluorescence assay. The increased levels of PI3K, AKT, and mTOR in the benzene-exposure group further proved the crucial role of Tim-3 in regulating the functional status of macrophages in the AML microenvironment. These results demonstrate that Tim-3 and macrophage polarization may play a vital role during the immune escape of the benzene-induced AML. This study provides a new potential intervention site for immune checkpoint-based AML therapeutic strategy.

CAR-T cells dual-target CD123 and NKG2DLs to eradicate AML cells and selectively target immunosuppressive cells

ABSTRACT Chimeric antigen receptor (CAR)-T cells have not made significant progress in the treatment of acute myeloid leukemia (AML) in earlyclinical studies. This lack of progress could be attributed in part to the immunosuppressive microenvironment of AML, such as monocyte-like myeloid-derived suppressor cells (M-MDSCs) and alternatively activated macrophages (M2 cells), which can inhibit the antitumor activity of CAR-T cells. Furthermore, AML cells are usually heterogeneous, and single-target CAR-T cells may not be able to eliminate all AML cells, leading to disease relapse. CD123 and NKG2D ligands (NKG2DLs) are commonly used targets for CAR-T therapy of AML, and M-MDSCs and M2 cells express both antigens. We developed dual-targeted CAR-T (123NL CAR-T) cells targeting CD123 and NKG2DL by various structural optimization screens. Our study reveals that 123NL CAR-T cells eradicate AML cells and selectively target immunosuppressive cells. A highly compact marker/suicide gene, RQR8, which binds targeting epitopes of CD34 and CD20 antigens, was also incorporated in front of the CAR structure. The binding of Rituximab to RQR8 leads to the elimination of 123NL CAR-T cells and cessation of their cytotoxicity. In conclusion, we successfully developed dual effects of 123NL CAR-T cells against tumor cells and immunosuppressive cells, which can avoid target escape and resist the effects of immunosuppressive microenvironment.

The m6A modulator-mediated cytarabine sensitivity and immune cell infiltration signature in acute myeloid leukemia.

The study aims to investigate the impact of m6A modulators on drug resistance and the immune microenvironment in acute myeloid leukemia (AML). The emergence of drug resistance is a significant factor that contributes to relapse and refractory AML, leading to a poor prognosis. The AML transcriptome data were retrieved from the TCGA database. The "oncoPredict" R package was utilized to assess the sensitivity of each sample to cytarabine (Ara-C) and classify them into distinct groups. Differential expression analysis was performed to identify m6A modulators differentially expressed between the two groups. Select Random Forest (RF) to build a predictive model. Model performance was evaluated using calibration curve, clinical decision curve, and clinical impact curve. The impacts of METTL3 on Ara-C sensitivity and immune microenvironment in AML were examined using GO, KEGG, CIBERSORT, and GSEA analyses. Seventeen out of 26 m6A modulators exhibited differential expression between the Ara-C-sensitive and resistant groups, with a high degree of correlation. We selected the 5 genes with the highest scores in the RF model to build a reliable and accurate prediction model. METTL3 plays a vital role in m6A modification, and further analysis shows its impact on the sensitivity of AML cells to Ara-C through its interaction with 7 types of immune-infiltrating cells and autophagy. This study utilizes m6A modulators to develop a prediction model for the sensitivity of AML patients to Ara-C, which can assist in treating AML drug resistance by targeting mRNA methylation.

Defining the immune microenvironment in myelodysplastic syndrome and acute myeloid leukemia using machine learning.

7060 Background: Changes in the bone marrow microenvironment are believed to play a major role in the biology of Myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). To study the bone marrow microenvironment (BME) in MDS and AML and to compare it with normal BME, we studied the expression profile of 43 immune biomarkers and evaluated the differences in the BME between AML and MDS and compared it to that of normal BME. These 43 immune biomarkers included B- and T-cell markers, cytokines and chemokines. Methods: RNA was extracted from fresh bone marrow aspiration samples from 626 patients with AML, 564 patients with MDS, and 1449 individuals having bone marrow without any mutations or having low level mutations determined to be CHIP (clonal hematopoiesis of indeterminate potential) and considered normal. RNA levels of 42 immune biomarkers were quantified using next generation sequencing. Using a machine learning algorithm, we first selected the relative genes that distinguish between two classes using K-fold cross-validation (K = 12). The selected genes were used to predict one class from the other using random forest classifier. Samples were divided into a training set (67%) and testing set (33%) for each classification. Results: The random forest showed that MDS can easily be distinguished from normal using the expression of 15 genes (CYFIP2, CXCR4, IL1RAP, CD58, CD36, CD19, PAX5, CD79B, ID1, IL8, CD44, IL1R1, CD79A, IL21R, and CD74). The AUC for distinguishing MDS from normal was 0.996 in the training set and 0.931 (95% CI: 0.912-0.949) in the testing set. Distinguishing between AML and normal was also robust and achievable using the expression of only 10 genes (CYFIP2, IL1R1, CXCR4, IL8, IL21R, CD44, CD28, CD79A, and IL7R, and CD8A). The AUC for the training set was 0.994 and 0.972 (95% CI: 0.961-0.983) for the testing set. Eight of these 10 markers were shared with MDS algorithm. Only CD28 and IL7R were specifically needed for AML classification. Distinguishing between MDS And AML was achievable with high reliability with AUC of 0.994 (95% CI:0.992-0.997) in training set and 0.924 (95% CI: 0.896-0.952) in testing set). Only 10 biomarkers were used for distinguishing MDS from AML, nine of which (IL1R1, CYFIP2, CD44, IL1RAP, CXCR4, IL21R, CD74, IL8, and CD36) were used in distinguishing MDS from normal. The only unique biomarker was CD28. Comparing levels of these biomarkers, most of which showed highest level in normal BM, significantly lower level in MDS but the level was even significantly lower in AML (deeper reduction) than in MDS. Conclusions: This data suggests that the BME is significantly different in MDS from AML and both are different from normal. Few immune biomarkers play major role in defining each BME. However, relative increase or decrease between these immune biomarkers dictate the uniqueness of each microenvironment.

Analysis of prognostic biomarker models and immune microenvironment in acute myeloid leukemia by integrative bioinformatics.

Acute myeloid leukemia (AML) is a hematological cancer driven on by aberrant myeloid precursor cell proliferation and differentiation. A prognostic model was created in this study to direct therapeutic care. Differentially expressed genes (DEGs) were investigated using the RNA-seq data from the TCGA-LAML and GTEx. Weighted Gene Coexpression Network Analysis (WGCNA) examines the genes involved in cancer. Find the intersection genes and construct the PPI network to discover hub genes and remove prognosis-related genes. A nomogram was produced for predicting the prognosis of AML patients using the risk prognosis model that was constructed using COX and Lasso regression analysis. GO, KEGG, and ssGSEA analysis were used to look into its biological function. TIDE score predicts immunotherapy response. Differentially expressed gene analysis revealed 1004 genes, WGCNA analysis revealed 19,575 tumor-related genes, and 941 intersection genes in total. Twelve prognostic genes were found using the PPI network and prognostic analysis. To build a risk rating model, RPS3A and PSMA2 were examined using COX and Lasso regression analysis. The risk score was used to divide the patients into two groups, and Kaplan-Meier analysis indicated that the two groups had different overall survival rates. Univariate and multivariate COX studies demonstrated that risk score is an independent prognostic factor. According to the TIDE study, the immunotherapy response was better in the low-risk group than in the high-risk group. We eventually selected out two molecules to construct prediction models that might be used as biomarkers for predicting AML immunotherapy and prognosis.

Abstract A20: Inflammation remodels the immune microenvironment in acute myeloid leukemia

Abstract Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive single cell RNA-Sequencing census of the bone marrow immune microenvironment in adult and pediatric AML patients. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B cell subtype enriched in high-inflammation AML patients, as well as an increase in CD8+ GZMK+ and regulatory T cells, accompanied by a reduction in T cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in AML patients. Addition of the iScore refines current risk stratifications for AML patients and may enable identification of patients in need of more aggressive treatment. This work provides a first framework for classifying AML patients based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings. Citation Format: Audrey Lasry, Bettina Nadorp, Maarten Fornerod, Deedra Nicolet, Huiyun Wu, Christopher J Walker, Zhengxi Sun, Matthew T Witkowski, Anastasia N Tikhonova, Maria Guillamot, Geraldine Cayanan, Anna Yeaton, Tanja A Gruber, Ann-Kathrin Eisfeld, Iannis Aifantis. Inflammation remodels the immune microenvironment in acute myeloid leukemia [abstract]. In: Proceedings of the AACR Special Conference: Acute Myeloid Leukemia and Myelodysplastic Syndrome; 2023 Jan 23-25; Austin, TX. Philadelphia (PA): AACR; Blood Cancer Discov 2023;4(3_Suppl):Abstract nr A20.

Construction of a prognostic model of acute myeloid leukemia associated with immunogenic cell death

ABSTRACT Background Immunogenic cell death (ICD)is a kind of regulatory cell death, which causes a series of antigen-specific adaptive immune responses by generating and emitting some danger signals or damage-associated molecular patterns (DAMPs). At present, little is known about the prognostic value of ICD and its related processes in acute myeloid leukemia (AML). The aim of the study was to explore the relationship between ICD and tumor immune microenvironment changes in AML. Research Design & Methods In the study, AML samples were divided into two groups by consensus clustering analysis, and then gene enrichment analysis and GSEA analysis were performed on the ICD high expression group. Furthermore, CIBERSORT was used to analyze the tumor microenvironment and immune characteristics of AML. Finally, a prognostic model related to ICD was constructed by using univariate and multivariate regression analysis. Results ICD was divided into two groups according to the level of ICD gene expression. The ICD high expression group was associated with good clinical results and high levels of immune cell infiltration. Conclusions The study constructed and verified the prognostic characteristics of AML related to ICD, which has important value in predicting the overall survival time of AML patients.