How to treat acute myeloid leukemia

Abstract

The present disclosure provides methods of treating acute myeloid leukemia (AML) and determining responsiveness to an AML treatment regimen, which involve identifying the presence or absence of monocytic leukemia stem cells (m-LSCs), including CD70+ m-LSCs, in a sample from a subject.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to and the benefit of U.S. Provisional Application No. 63 / 385,699, filed December 1, 2022, and U.S. Provisional Application No. 63 / 490,270, filed March 15, 2023. The contents of each of the foregoing patent applications are incorporated herein by reference in their entirety.

[0002] Government support This invention was made with government support under Grant No. R35CA242376 awarded by the National Institutes of Health. The government has certain rights in this invention. [Background technology]

[0003] Acute myeloid leukemia (AML) is a blood cancer in which a subject's bone marrow produces abnormal myeloblasts, red blood cells, or platelets. AML is one of the most common acute leukemias in adults. The accumulation of AML cells in the bone marrow and blood can rapidly lead to infection, anemia, excessive bleeding, and death. Venetoclax, a BCL-2 inhibitor, has recently emerged as an important component of acute myeloid leukemia (AML) treatment. Venetoclax, in combination with multiple primary chemotherapy regimens, can induce responses in approximately 60-70% of previously untreated elderly AML patients, the majority of whom are ineligible for conventional induction therapy. However, resistance to venetoclax-based therapy and relapse after initial response have been reported. There is a need in the art for methods to predict response to venetoclax treatment and for methods to treat AML in patients who are refractory to venetoclax or predicted to relapse after venetoclax treatment. There is also a need in the art for methods of treating AML, particularly in elderly patients and patients with relapsed AML who are unsuitable for conventional induction therapy. Summary of the Invention

[0004] The present invention provides a method of treating acute myeloid leukemia (AML) in a subject, the method comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent if at least one m-LSC is identified, or administering to the subject a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent if no m-LSC is identified.

[0005] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) identifying the subject as not responding to the treatment if the presence of at least one m-LSC is identified, or identifying the subject as responding to the treatment if no m-LSC is identified.

[0006] In some aspects of the disclosed methods, step (a) further comprises measuring expression of at least CD117, CD244, and CD64, and the cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+. In some aspects of the disclosed methods, step (a) further comprises measuring expression of at least CD117, CD244, CD64, and GPR56, and the cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-.

[0007] The present invention provides a method of treating acute myeloid leukemia (AML) in a subject, the method comprising: a) measuring expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; and c) administering to the subject a treatment comprising at least one CD70-targeting agent if at least one CD70+ m-LSC is identified, preferably wherein the treatment further comprises at least one BCL-2 inhibitor and at least one hypomethylating agent if no CD70+ m-LSC is identified.

[0008] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a CD70-targeting agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; and c) identifying the subject as responding to the treatment if the presence of at least one CD70+ m-LSC is identified.

[0009] In some aspects of the foregoing methods, step (a) further comprises measuring expression of at least CD117, CD244, and CD64, and the cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70+. In some aspects of the foregoing methods, step (a) further comprises measuring expression of at least CD117, CD244, CD64, and GPR56-, and the cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+.

[0010] In some embodiments, the at least one CD70 targeting agent is i) an anti-CD70 antibody, preferably wherein the anti-CD70 antibody is cusatuzumab; ii) an anti-CD70 immunotherapy, preferably wherein the immunotherapy comprises CAR-T cells and / or NK cells that specifically target CD70; or iii) an agent that inhibits CD70 signaling, preferably wherein the agent that inhibits CD70 signaling prevents binding of CD27 to CD70.

[0011] In some embodiments of the methods of the present disclosure, the at least one m-LSC targeting agent is an agent that modulates one-carbon metabolism, an agent that modulates purine synthesis, an agent that modulates pyrimidine synthesis, or any combination thereof.

[0012] In some embodiments of the methods of the present disclosure, the at least one m-LSC targeting agent is selected from methotrexate, brequinar, and cladribine.

[0013] In some aspects of the disclosed methods, the at least one hypomethylating agent is selected from azacitidine and decitabine.

[0014] In some aspects of the methods of the present disclosure, the at least one BCL-2 inhibitor is selected from venetoclax and navitoclax.

[0015] In some aspects of the disclosed methods, step (a) is performed by PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, This includes performing transcriptomics and Cellular Indexing of Epitopes by Sequencing (CITE-SEQ), or any combination thereof.

[0016] In some aspects of the methods of the present disclosure, the subject is a subject with AML who has not received any treatment for the AML.

[0017] In some embodiments of the methods of the present disclosure, the subject is a subject with AML who has previously received at least one treatment for AML.

[0018] In some embodiments of the methods of the present disclosure, the at least one AML treatment comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0019] In some embodiments of the methods of the present disclosure, identifying the subject as responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as having a long-term remission after receiving treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0020] In some embodiments of the methods of the present disclosure, identifying the subject as non-responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as refractory to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent and / or the subject relapses after treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0021] In some aspects of the methods of the present disclosure, the biological sample comprises blood, a bone marrow biopsy, a bone marrow aspirate, a chloroma biopsy, a tissue biopsy, cerebrospinal fluid, or any combination thereof. In some aspects, the sample is a bone marrow biopsy. In some aspects, the sample is a bone marrow aspirate. In some aspects, the sample is a chloroma biopsy.

[0022] In some aspects of the methods of the present disclosure, step (a) further comprises performing a transcriptomic analysis of a plurality of cells in the sample, and step (b) further comprises identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the transcriptomic analysis performed in step (a), wherein the cell is identified as an m-LSC based on at least one of: i) upregulation of expression of at least one of the biomarkers in Table 5; ii) expression of at least one biomarker in Table 1A; and iii) upregulation of expression of at least one GSEA gene signature in Table 1B.

[0023] In some embodiments of the methods of the present disclosure, transcriptomic analysis is performed using RNA sequencing.

[0024] Some embodiments of the methods of the present disclosure are performed using CITE-SEQ.

[0025] Any of the above aspects or any of the aspects described herein may be combined with any other aspect.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. As used herein, the singular includes the plural unless the context clearly dictates otherwise. By way of example, the terms "a," "an," and "the" are understood to be either singular or plural, and the term "or" is understood to be inclusive. By way of example, "an element" means one or more elements. Throughout this specification, "comprising" or variations thereof (e.g., "comprises" or "comprising") will be understood to mean the inclusion of a stated element, integer, or step, or group of elements, integers, or steps, but not the exclusion of any other element, integer, or step, or group of elements, integers, or steps. About can be understood to be within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from the context, all numerical values ​​provided herein are modified by the term "about." As used herein, the term "or" is inclusive and is understood to include both "or" and "and," unless specifically stated otherwise or clear from the context.

[0027] Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. References cited herein are not considered prior art to the claimed invention. In case of conflict, the present specification, including definitions, will control. Additionally, the materials, methods, and examples are illustrative only and are not intended to be limiting. Other features and advantages of the present disclosure will be apparent from the following detailed description and claims.

[0028] These and other features will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0029] [Figure 1A] This figure shows the developmentally heterogeneous characteristics of LSCs. It summarizes engraftment rate data for Uni-MMP AML-12, AML-08, and AML-14, and Multi-MMP AML-07 and AML-13. Bulk represents unsorted bulk tumor, Prime represents the primary subpopulation, and Mono represents the monocytic subpopulation. Each dot represents a mouse. AML-12 (bulk, n=7; prime, n=6; mono, n=6). AML-08 (prime, n=7; mono, n=9). AML-14 (prime, n=9; mono, n=7). AML-07 (bulk, n=7; prime, n=5; mono, n=6). AML-13 (prime, n=8; mono, n=8). Median + / - interquartile range. A two-tailed Mann-Whitney test was used to compare two groups, and the Kruskal-Wallis test was used when comparing three or more groups. ns indicates no significant difference. [Figure 1B]This figure shows the developmentally heterogeneous characteristics of LSCs. It summarizes engraftment rate data for Uni-MMP AML-12, AML-08, and AML-14, and Multi-MMP AML-07 and AML-13. Bulk represents unsorted bulk tumor, Prime represents the primary subpopulation, and Mono represents the monocytic subpopulation. Each dot represents a mouse. AML-12 (bulk, n=7; prime, n=6; mono, n=6). AML-08 (prime, n=7; mono, n=9). AML-14 (prime, n=9; mono, n=7). AML-07 (bulk, n=7; prime, n=5; mono, n=6). AML-13 (prime, n=8; mono, n=8). Median + / - interquartile range. A two-tailed Mann-Whitney test was used to compare two groups, and the Kruskal-Wallis test was used when comparing three or more groups. ns indicates no significant difference. [Figure 2A] This figure illustrates the distinct nature of disease arising from primed and monocytic subpopulations of multi-MMP AML. It depicts the workflow used to isolate AML-07 primary and monocytic subpopulations for infusion into PDX mice and subsequently determine their relative sensitivity to the VEN+AZA regimen in vivo. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow cells. Each dot represents a unique mouse. PDX-07-prime (control, n=10; VEN / AZA, n=10), PDX-07-mono (control, n=10, VEN / AZA, n=10). Box plots show median + / - quartiles. A two-tailed Mann-Whitney test was used. ns indicates no significant difference. [Figure 2B]The figures show the distinct characteristics of disease arising from primed and mono subpopulations of multi-MMP AML. The VEN / AZA in vivo regimen (VEN, 100 mg / kg, orally administered (OG), 5 days / week for 2 weeks, and AZA, 3 mg / kg, intraperitoneally injected (IP), 3 days / week for 2 weeks) was used. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow cells. Each dot represents a unique mouse. PDX-07-prime (control, n=10; VEN / AZA, n=10), PDX-07-mono (control, n=10; VEN / AZA, n=10). Box plots show median + / - quartile values. A two-tailed Mann-Whitney test was used. ns indicates no significant difference. [Figure 2C] This figure demonstrates the distinct nature of disease arising from primed and mono subpopulations of multi-MMP AML. It shows the effect of in vivo VEN+AZA treatment on leukemia engrafted from primed and mono subpopulations of AML-07. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow cells. Each dot represents a unique mouse. PDX-07-prime (control, n=10; VEN / AZA, n=10), PDX-07-mono (control, n=10, VEN / AZA, n=10). Box plots show median + / - quartiles. A two-tailed Mann-Whitney test was used. ns indicates no significant difference. [Figure 3A] Figure 1 shows clinical outcome as a function of m-LSC, illustrating the leukemogenic process and predicted clinical response to VEN+AZA therapy in Uni-MMP and Multi-MMP AML patients. [Figure 3B]Clinical outcome as a function of m-LSCs is shown for representative cases of Uni-MMP and Multi-MMP AML patients receiving VEN+AZA therapy. The left panel shows the sorting strategy for obtaining diagnostic-prime (Dx-plasm) and diagnostic-mono (Dx-mono) subpopulations from diagnostic bulk disease (Dx-bulk), and relapse-mono (R1-mono) subpopulations from relapse bulk disease (R1-bulk), when applicable. The right panel shows the percent engraftment (engraftment rate) in NSG-S mice, determined by the % hCD45+ / mCD45- ratio within total viable bone marrow cells. Each dot represents a unique mouse. Median + / - quartile. Mann-Whitney test. ns indicates no significant difference. *p<0.05, **p<0.01, ***p<0.001. This shows Patient 20 (Pt-20), a case of Uni-MMP AML showing long-term remission after over 3.5 years of VEN+AZA treatment. Dx-bulk (n=9), Dx-plasm (n=7), Dx-mono (n=7). Box plots represent median + / - quartiles. Kruskal-Wallis test was used. [Figure 3C] Clinical outcome as a function of m-LSCs is shown for representative cases of Uni-MMP and Multi-MMP AML patients receiving VEN+AZA therapy. The left panel shows the sorting strategy for obtaining diagnostic-prime (Dx-plasm) and diagnostic-mono (Dx-mono) subpopulations from diagnostic bulk disease (Dx-bulk), and relapse-mono (R1-mono) subpopulations from relapse bulk disease (R1-bulk), when applicable. The right panel shows the percent engraftment (engraftment rate) in NSG-S mice, determined by the % hCD45+ / mCD45- ratio within total viable bone marrow cells. Each dot represents a unique mouse. Median + / - quartile. Mann-Whitney test. ns indicates no significant difference. *p<0.05, **p<0.01, ***p<0.001. This shows Patient 12 (Pt-12), a case of multi-MMP AML, showing a predominantly monocytic relapse 12 months after receiving VEN+AZA therapy. Dx-plasm (n = 10), Dx-mono (n = 9), R1-mono (n = 8). Box plots represent median + / - quartiles. Kruskal-Wallis test was used. [Figure 3D] Clinical outcome as a function of m-LSCs is shown for representative cases of Uni-MMP and Multi-MMP AML patients receiving VEN+AZA therapy. The left panel shows the sorting strategy for obtaining diagnostic-prime (Dx-plasm) and diagnostic-mono (Dx-mono) subpopulations from diagnostic bulk disease (Dx-bulk), and relapse-mono (R1-mono) subpopulations from relapse bulk disease (R1-bulk), when applicable. The right panel shows the percent engraftment (engraftment rate) in NSG-S mice, determined by the % hCD45+ / mCD45- ratio within total viable bone marrow cells. Each dot represents a unique mouse. Median + / - quartile. Mann-Whitney test. ns indicates no significant difference. *p<0.05, **p<0.01, ***p<0.001. This study presents Patient 69 (Pt-69), a case of multi-MMP AML showing rapid relapse 3 months after venous infusion and azacitidine therapy. In this particular case, prime and mono subpopulations were gated using different sorting strategies based on the primitive antigen CD34 and the monocyte antigen CD11b. In the patient's diagnostic sample, the CD34+ / CD11b-, CD34+ / CD11b+, and CD34- / CD11b-pp subpopulations were sorted into Dx-plasm-A, Dx-plasm-B, and Dx-mono subpopulations, respectively. In the patient's relapse sample, the CD34- / CD11b-pp subpopulation was sorted as the predominant R1-mono subpopulation: Dx-bulk (n = 9), Dx-plasm-A (n = 3), Dx-plasm-B (n = 7), Dx-mono (n = 7), R1-bulk (n = 9), and R1-mono (n = 9). Box plots represent median + / - quartiles. Kruskal-Wallis test was used. [Figure 3E] 2A and 2B show clinical outcome as a function of m-LSC, which shows phenotypic changes from diagnosis to relapse in a cohort of AML patients receiving VEN+AZA therapy (N=25, Tables 2A and 2B). [Figure 3F]Figure 1 shows clinical outcome as a function of m-LSC. It shows the duration of remission in AML patients with monocytic relapse (N=9) vs. non-monocytic relapse (N=16). Box plots represent median + / - quartiles. One-sided Mann-Whitney test was used. ns indicates no significant difference. [Figure 3G] Clinical outcomes are shown as a function of m-LSC. It shows the duration of remission for AML patients with VEN / AZA relapse. A bar graph showing duration of remission in days for a cohort of 25 AML patients who received VEN / AZA therapy and experienced a relapse response is shown. The cohort includes five patients who maintained a monocytic phenotype from diagnosis to relapse (mono-to-mono), four patients who transitioned from a primary phenotype at diagnosis to a monocytic phenotype at relapse (prime-to-mono), 15 patients who maintained a primary phenotype from diagnosis to relapse (prime-to-prime), and one patient who transitioned from a monocytic phenotype at diagnosis to a primary phenotype at relapse (mono-to-prime). Each dot represents a unique patient. Median duration for both groups is shown in days. [Figure 4A] 1 shows m-LSC immunophenotyping, which is a stacked bar graph showing the relative proportion of each subcluster within the highlighted "bone marrow" region of the UMAP. [Figure 4B] Figure 1 shows the characterization of m-LSC immunophenotype, which shows the protein expression of surface antigens CD45, CD34, CD4, CD14, CD11b, and CD36. The area enriched for m-LSCs is highlighted by a dotted line. [Figure 5A] Functional validation of m-LSC immunophenotypes is shown. It illustrates the gating strategy for sorting various subpopulations of mono AML-16 to determine m-LSC activity using xenotransplantation studies. The sorting is shown in detail in Figures 12A-12C. Briefly, for AML-16 and AML-20, viable cells / mono were sorted and transplanted. For AML-07, CD4 was not included in the sort due to cell restriction. [Figure 5B]Functional validation of m-LSC immunophenotypes is shown. It illustrates the gating strategy for sorting various subpopulations of mono AML-20 to determine m-LSC activity using xenotransplantation studies. The sorting is shown in detail in Figures 12A-C. Briefly, for AML-16 and AML-20, live cells / mono / CD34- / CD4+ / CD14- were sorted and transplanted. For AML-07, CD4 was not included in the sort due to cell restriction. [Figure 5C] Functional validation of m-LSC immunophenotypes is shown. It illustrates the gating strategy for sorting various subpopulations of Multi-MMP AML-07 to determine m-LSC activity using xenotransplantation studies. The sorting is detailed in Figures 12A-C. Briefly, for AML-16 and AML-20, live cells / mono / CD34- / CD4+ / CD14+ were sorted and transplanted. For AML-07, CD4 was not included in the sort due to cell restriction. [Figure 5D] Briefly, for AML-16 and AML-20, live cells / mono / CD34- / CD4+ / CD14- / CD11b-CD36- were sorted and transplanted. For AML-07, CD4 was not included in the sort due to cell limitations. [Figure 5E] Figure 1 shows the results of transplantation of AML-16 (A (n = 8), B (n = 6), C (n = 7), D (n = 7), E (n = 6)), AML-20 (A (n = 9), B (n = 8), C (n = 7), D (n = 12), E (n = 10)), and AML-07 (A (n = 10), B (n = 10), C (n = 9), D (n = 10), E (n = 8)) subpopulations, designated PDX-16, PDX-20, and PDX-07, respectively. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow cells. Each dot represents a unique mouse. Box plots represent the median + / - quartile values. Results are based on a two-tailed Mann-Whitney test. [Figure 5F]Figure 1 shows the results of transplantation of AML-16 (A (n = 8), B (n = 6), C (n = 7), D (n = 7), E (n = 6)), AML-20 (A (n = 9), B (n = 8), C (n = 7), D (n = 12), E (n = 10)), and AML-07 (A (n = 10), B (n = 10), C (n = 9), D (n = 10), E (n = 8)) subpopulations, designated PDX-16, PDX-20, and PDX-07, respectively. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow cells. Each dot represents a unique mouse. Box plots represent the median + / - quartile values. Results are based on a two-tailed Mann-Whitney test. [Figure 6A] We demonstrate the molecular characteristics and targets of m-LSCs by showing the effects of the TYMS inhibitor methotrexate (MTX), the DT-IODI-T inhibitor brequinar (BRQ), and the purine analog cladribine (CdA) on the colony-forming unit (CFU) potential of CD34+ HSPCs isolated from two normal mobilized peripheral blood samples (MPB-1, 2) versus mono LSCs isolated from mono AML-20 and mono AML-16. [Figure 6B] 1 shows the molecular characteristics and targets of m-LSCs, which shows representative images of CFU assays measuring the efficacy of CdA on normal CD34+ HSPCs and m-LSCs. [Figure 6C] We present the molecular characteristics and targets of m-LSCs, which show the effects of the chemotherapeutic agents AraC, DNR, the DHODH inhibitor brequinar (BRQ), and the TYMS inhibitor methotrexate (MTX) on the CFU potential of m-LSCs, p-LSCs, and CD34+ HSPCs. [Figure 6D] We present the molecular characteristics and targets of m-LSCs, which show the effects of the chemotherapeutic agents AraC, DNR, the DHODH inhibitor brequinar (BRQ), and the TYMS inhibitor methotrexate (MTX) on the CFU potential of m-LSCs, p-LSCs, and CD34+ HSPCs. [Figure 6E] The molecular characteristics and targets of m-LSC are shown. It shows a diagram illustrating the workflow and design of the regimen used for in vivo treatment. IP is intraperitoneal and OG is oral administration. [Figure 6F] The molecular characteristics and targets of m-LSCs are shown. It illustrates the effect of in vivo VEN+AZA, CdA, or triple combination treatment on bone marrow tumor burden in PDXs. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable bone marrow mononuclear cells. Each dot represents a unique mouse. For AML-13 PDXs, control (n=11), VEN+AZA (n=9), CdA (n=10), and VEN+AZA+CdA (n=10). For AML-07 PDXs, control (n=11), VEN+AZA (n=9), CdA (n=12), and VEN+AZA+CdA (n=9). Box plots represent median ± interquartile range. Kruskal-Wallis test was used. ns indicates no significant difference. [Figure 6G] The molecular characteristics and targets of m-LSCs are shown. It also shows the effect of VEN+AZA, CdA, or combination treatment on bone marrow tumor burden in PDXs. hCD45+ counts were determined by directly quantifying cells within a constant hCD45+ / mCD45- ratio within bone marrow harvests using flow cytometry. [Figure 6H] The molecular characteristics and targets of m-LSCs are shown. It also shows the effect of VEN+AZA, CdA, or combination treatment on splenic tumor burden in PDXs. Engraftment rates were determined by the percentage of hCD45+ / mCD45- cells within total viable splenic mononuclear cells, and hCD45+ counts were determined by directly quantifying hCD45+ / mCD45- cells within a fixed amount of spleen harvest using flow cytometry. Each dot represents a unique mouse: control (n=6), VEN+AZA (n=6), CdA (n=6), VEN+AZA+CdA (n=6). Box plots represent median + / - quartiles. Kruskal-Wallis test was used. ns indicates no significant difference. [Figure 7A] A model illustrating the interplay between LSC activity, immunophenotype, disease progression, and clinical response to venetoclax plus azacitidine therapy in AML patients is presented, showing a first group of AML patients with disease driven exclusively by p-LSCs captured at various maturation stages, with predominantly prime, MMP, and Mono immunophenotypes. [Figure 7B] A model illustrating the interplay between LSC activity, immunophenotype, disease progression, and clinical response to venetoclax plus azacitidine therapy in AML patients is presented, which shows a second group of AML patients with multiple LSC activity (including both p-LSC and m-LSC) that exhibit primed, MMP, or mono immunophenotypes, depending on their relative maturity and the proportion of the two diseases attributable to the two different LSC subtypes. [Figure 7C] A model illustrating the interplay between LSC activity, immunophenotype, disease progression, and clinical response to venetoclax plus azacitidine therapy in AML patients is shown. It shows the last group of AML patients driven exclusively by m-LSCs, which typically exhibit a predominantly single immunophenotype due to the inherent nature of m-LSCs, which are already quiescent at a relatively more mature promyelocytic developmental stage. In all graphs, cyan symbols represent p-LSCs and their progeny, pink symbols represent m-LSCs and their progeny, and circular arrows represent self-renewal capacity. [Figure 8A] Figure 1 shows the sorting strategy for determining m-LSC immunophenotype. It shows the immunophenotype of A, B, C, D, and E subpopulations sorted from mono AML-16 cells and used to inject them into NSG-S mice to determine their m-LSC potential. [Figure 8B] Figure 1 shows the sorting strategy for determining m-LSC immunophenotype. It shows the immunophenotype of A, B, C, D, and E subpopulations sorted from mono AML-20 cells and used to inject them into NSG-S mice to determine their m-LSC potential. [Figure 8C] Figure 1 shows the sorting strategy for determining m-LSC immunophenotype. It shows the immunophenotype of A, B, C, D, and E subpopulations sorted from Multi-MMP AML-07 and used to inject into NSG-S mice to determine m-LSC potential. [Figure 8D] 1 shows the sorting strategy for determining m-LSC immunophenotype, which shows tumor burden in primary and secondary transplants as indicated by human CD45 and mouse CD45 staining. [Figure 8E] 1 shows the sorting strategy for determining m-LSC immunophenotype, which shows tumor burden in primary and secondary transplants as indicated by human CD45 and mouse CD45 staining. [Figure 8F] 1 shows the sorting strategy for determining m-LSC immunophenotype, which shows tumor burden in primary and secondary transplants as indicated by human CD45 and mouse CD45 staining. [Figure 9A] It shows that M5 patients, but not M4 patients, were significantly more likely to be refractory to VEN / AZA therapy.It shows a circular pie chart showing the number of patients identified in different FAB subclasses. [Figure 9B] It shows that M5 patients, but not M4 patients, were significantly more likely to be refractory to VEN / AZA therapy.It shows a bar graph showing the proportion of patients who had a refractory or non-refractory response to VEN+AZA therapy according to the ELN criteria. [Figure 10A] 1 shows an analysis of CD70+ m-LSCs in AML samples, which is a graph showing the percentage of total blast cells and the percentage of m-LSCs that were CD70+ in AML samples. [Figure 10B] 1 shows an analysis of CD70+ m-LSCs in AML samples, which show the percentage of total blast cells and the percentage of m-LSCs that were CD70+ in AML samples that were resistant to treatment with venetoclax and azacitidine in combination or responsive to treatment with venetoclax and azacitidine in combination. DETAILED DESCRIPTION OF THE INVENTION

[0030] Acute myeloid leukemia (AML) is a blood cancer that is the most commonly diagnosed type of leukemia in adults. It is estimated that approximately 11,000 people will die from AML in the United States in 2020, and 20,000 new cases will be diagnosed. The average age of a person diagnosed with AML is approximately 68 years, with the disease occurring most frequently after age 45. However, younger patients, including children, are also diagnosed with AML. The prognosis for patients diagnosed with AML is generally poor, with long-term survival rates of only 40–50% for younger patients and a median overall survival of less than one year for older patients. New therapies aimed at complementing standard induction therapy with infusional cytarabine with intermittent anthracycline have provided some improvement in treatment outcomes, but these improvements remain limited. Therefore, more specialized and personalized treatments are needed, especially for older patients who are not suitable candidates for induction therapy.

[0031] Recent studies have demonstrated that acute myeloid leukemia (AML) exhibits a high level of biological diversity, which may explain the difficulty in identifying effective therapeutic strategies for AML treatment. Furthermore, it has recently been recognized that leukemic stem cells (LSCs), which can give rise to identical daughter cells as well as differentiated cells, perpetuate and maintain AML.

[0032] As an alternative to standard induction therapy, the current FDA-approved standard of care for elderly patients and those unsuitable for such aggressive chemotherapy is the combination of the BCL-2 inhibitor venetoclax with a hypomethylating agent (HMA) such as azacitidine or decitabine. Specifically, venetoclax and azacitidine (hereafter referred to as "Ven / aza therapy" or "Ven / aza-based therapy") are estimated to induce complete remission (CR) of AML in approximately 60-70% of treated patients.

[0033] However, this means that approximately 30-40% of patients ultimately do not respond to Ven / aza treatment and therefore do not achieve complete remission. There is a need in the art for methods to identify this 30-40% of patients who are likely to not respond to Ven / aza treatment. The ability to identify these patients prior to treatment would allow physicians to avoid the toxicity, expense, and reduced quality of life associated with ineffective treatment. Furthermore, these patients could receive alternative therapies, improving their chances of survival. Finally, a reliable method for identifying these patients would enable the design of clinical trials to test personalized therapies for this specific AML patient population.

[0034] Multiple studies have delineated the characteristics of malignant stem cells responsible for the pathogenesis of myeloid leukemia. Analysis of primary human tissue specimens as well as various mouse models consistently demonstrates that leukemic stem cells (LSCs) are biologically distinct from the bulk tumor population and often demonstrate distinct drug sensitivity / resistance profiles from the majority of leukemic cell types. Similar to normal hematopoietic stem cells, conventional LSCs are also thought to be largely quiescent and capable of giving rise to progeny cells that comprise the entire tumor population. As such, LSCs represent an important target for the development of novel therapies. Numerous attempts have been made to target LSC populations, focusing on specific cell surface antigens, metabolic intervention, epigenetic strategies, mutation-targeting approaches, and immunotherapy. While multiple strategies are based on solid experimental evidence, the improvement of clinical outcomes through direct ablation of LSCs remains limited.

[0035] A major challenge in targeting LSCs is the inherent heterogeneity of malignant stem cells. In particular, LSC populations from human AML patients demonstrate significant intra- and interpatient heterogeneity in developmental stage and immunophenotype, which is thought to be caused, at least in part, by basal genetic diversity. Importantly, recent studies have demonstrated that the existence of heterogeneous basal LSC populations can mediate the differential therapeutic outcomes of conventional chemotherapy and venetoclax-based therapy.

[0036] The present disclosure is based, inter alia, on the discovery of a particular subpopulation of leukemia stem cells, termed monocytic leukemia stem cells (m-LSCs), that can be used to predict a subject's response to treatment with a combination of a BCL-2 inhibitor (e.g., venetoclax) and a hypomethylating agent (e.g., azacitidine, cytarabine, and decitabine).

[0037] Thus, the present disclosure provides, inter alia, methods for determining whether a subject will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent based on whether m-LSCs are identified in a sample from a subject with AML, as well as methods for treating AML in a subject, comprising administering a particular treatment to the subject based on whether a sample from the subject contains m-LSCs.

[0038] Additionally, the present disclosure is based, inter alia, on the discovery of a particular subpopulation of leukemia stem cells, termed CD70+ monocytic leukemia stem cells (m-LSCs), which can be used to predict a subject's response to treatment with a CD70-targeting agent.

[0039] Thus, the present disclosure provides, inter alia, methods for determining whether a subject will respond to treatment with a CD70-targeting agent based on whether CD70+ m-LSCs are identified in a sample from a subject with AML, as well as methods for treating AML in a subject, comprising administering a particular treatment to the subject based on whether a sample from the subject contains CD70+ m-LSCs.

[0040] Methods for predicting response to treatment The present invention provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) identifying the subject as not responding to the treatment if the presence of at least one m-LSC is identified, or identifying the subject as responding to the treatment if no m-LSC is identified.

[0041] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further include identifying the presence of at least one m-LSC, identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include identifying the presence of at least m-LSC, wherein cells are identified as m-LSC if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD64+.

[0042] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further comprise identifying the presence of at least one m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and GPR56-.

[0043] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the number and / or proportion of m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) comparing the number and / or proportion of m-LSCs identified in step (b) with a predetermined cutoff value; and d) identifying the subject as not responding to the treatment if the number and / or proportion of m-LSCs is equal to or greater than the predetermined cutoff value, or identifying the subject as responding to the treatment if the number and / or proportion of m-LSCs is less than the predetermined cutoff value.

[0044] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further include determining the number and / or proportion of m-LSCs among the plurality of cells identified based on the immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include determining the number and / or proportion of m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD64+.

[0045] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further comprise identifying the presence of at least one m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and GPR56-.

[0046] In some embodiments of the foregoing methods, the predetermined cutoff value can be determined by comparing the number and / or proportion of m-LSCs in samples obtained from one or more subjects known to be responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent with the number and / or proportion of m-LSC samples obtained from one or more subjects known not to be responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent. One of skill in the art can perform such a comparison using methods known in the art to determine an appropriate predetermined cutoff value that allows for differentiation between responders and non-responders.

[0047] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if the cell is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; and c) identifying the subject as not responding to the treatment if the presence of at least one m-LSC is identified, or identifying the subject as responding to the treatment if no m-LSC is identified.

[0048] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further include identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, and CD64+.

[0049] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD70, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, and GPR56-.

[0050] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method comprising the steps of: a) measuring expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; b) identifying the number and / or proportion of CD70+ m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as CD70+ LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; c) comparing the number and / or proportion of CD70+ m-LSCs identified in step (b) with a predetermined cutoff value; and d) identifying the subject as not responding to treatment if the number and / or proportion of CD70+ m-LSCs is equal to or greater than the predetermined cutoff value. and identifying the subject as responding to the treatment if the number and / or proportion of m-LSCs is below a predetermined cutoff value.

[0051] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further include identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, and CD64+.

[0052] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD70, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD70+, and GPR56-.

[0053] In some embodiments of the foregoing methods, the predetermined cutoff value can be determined by comparing the number and / or percentage of CD70+ m-LSCs in samples obtained from one or more subjects known to be responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent with the number and / or percentage of CD70+ m-LSCs in samples obtained from one or more subjects known not to be responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent. One of skill in the art can perform such a comparison using methods known in the art to determine an appropriate predetermined cutoff value that allows for the distinction between responders and non-responders.

[0054] The above methods can further include providing a treatment recommendation to the clinician and / or the subject. Thus, if the subject is identified as a subject who will not respond to the combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method can further include providing a treatment recommendation that includes administering an alternative treatment. In some embodiments, the alternative treatment can include administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent. In some embodiments, the alternative treatment can be free of at least one BCL-2 inhibitor and / or free of at least one hypomethylating agent. If the subject is identified as a subject who will respond to treatment with the combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, the method can further include providing a treatment recommendation that includes administering to the subject the combination.

[0055] In some embodiments of the aforementioned methods, identifying the subject as responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent includes identifying the subject as having a long-term remission after receiving treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0056] In some embodiments of the foregoing methods, identifying the subject as non-responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as refractory to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent and / or the subject relapses after treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0057] Methods for predicting response to anti-CD70 therapy The present invention provides methods for identifying whether a subject with AML will respond to treatment with a CD70-targeting agent, the methods comprising: (a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; (b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; and (c) identifying the subject as responding to the treatment if at least one CD70+ m-LSC is identified. In some embodiments, the methods can further comprise identifying the subject as not responding to the treatment if no CD70+ m-LSC is identified.

[0058] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further include identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD64, and CD70, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD64+, and CD70+.

[0059] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, GPR56, and CD70, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, GPR56-, and CD70+.

[0060] The present invention provides a method for identifying whether a subject with AML will respond to treatment with a CD70-targeting agent, the method comprising the steps of: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; b) identifying the number and / or proportion of CD70+ m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as CD70+ m-LSCs if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; c) comparing the number and / or proportion of CD70+ m-LSCs identified in step (b) with a predetermined cutoff value; and d) identifying the subject as responding to treatment if the number and / or proportion of CD70+ m-LSCs is equal to or greater than the predetermined cutoff value. In some aspects, the above-described methods can further comprise identifying the subject as not responding to the treatment if the number and / or percentage of CD70+ m-LSCs is below a predetermined cutoff value.

[0061] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further include identifying the number and / or proportion of CD70+ m-LSCs among the plurality of cells identified based on their CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70 immunophenotypes. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD64, and CD70, and step (b) can include identifying the number and / or proportion of CD70+ m-LSCs, wherein cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD64+, and CD70.

[0062] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, GPR56, and CD70, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, GPR56-, and CD70+.

[0063] In some embodiments of the foregoing methods, the predetermined cutoff value can be determined by comparing the number and / or percentage of CD70+ m-LSCs in samples from one or more subjects known to respond to treatment with a CD70-targeting agent with the number and / or percentage of CD70+ m-LSCs in samples from one or more subjects known not to respond to treatment with a CD70-targeting agent. One of skill in the art can perform such a comparison using methods known in the art to determine an appropriate predetermined cutoff value that allows for the distinction between responders and non-responders.

[0064] The above methods can further include providing a treatment recommendation to the clinician and / or the subject. Thus, if the subject is identified as one who will respond to treatment with a CD-70 targeting agent, the method can further include providing a treatment recommendation that includes administering the CD70 targeting agent. In some embodiments, the treatment recommendation can include administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one CD-70 targeting agent.

[0065] In some embodiments of the foregoing methods, identifying the subject as unresponsive to treatment with a CD70 targeting agent includes identifying the subject as refractory to treatment with at least one CD70 targeting agent and / or identifying the subject as relapsing after treatment with at least one CD70 targeting agent.

[0066] In some embodiments of the aforementioned methods, identifying the subject as responsive to treatment with a CD70 targeting agent includes identifying the subject as having a long-term remission after receiving treatment with the CD70 targeting agent.

[0067] How to Treat AML The present disclosure provides a method of treating AML in a subject, the method comprising: a) measuring expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent if at least one m-LSC is identified, or administering to the subject a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent if no m-LSC is identified.

[0068] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further include identifying the presence of at least one m-LSC, identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include identifying the presence of at least m-LSC, wherein cells are identified as m-LSC if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD64+.

[0069] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further comprise identifying the presence of at least one m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and GPR56-.

[0070] The present disclosure provides a method of treating AML in a subject, the method comprising: a) measuring expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the number and / or proportion of m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) identifying the number and / or proportion of m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-. and d) comparing the determined number and / or proportion of m-LSCs with a predetermined cutoff value; and d) administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent if the number and / or proportion of m-LSCs is equal to or greater than the predetermined cutoff value, or administering to the subject a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent if the number and / or proportion of m-LSCs is less than the predetermined cutoff value.

[0071] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further include determining the number and / or proportion of m-LSCs among the plurality of cells identified based on the immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and CD64, and step (b) can include determining the number and / or proportion of m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD64+.

[0072] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, and CD36), and step (b) can further comprise identifying the presence of at least one m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, and GPR56, and step (b) can include identifying the presence of at least m-LSCs, wherein cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, and GPR56-.

[0073] The present disclosure provides a method of treating a subject with AML, the method comprising administering to the subject with AML a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent.

[0074] The present disclosure provides a method of treating a subject having AML, wherein the subject has AML exhibiting the presence of at least one m-LSC, the method comprising administering to the subject at least one m-LSC targeting agent.

[0075] The present disclosure provides a method of treating a subject having AML, wherein the subject has AML exhibiting a number and / or percentage of m-LSC cells that is equal to or greater than a predetermined cutoff value, the method comprising administering to the subject at least one m-LSC targeting agent.

[0076] The present disclosure provides a method of treating a subject having AML, wherein the subject has AML exhibiting the presence of at least one m-LSC, the method comprising administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent.

[0077] The present disclosure provides a method of treating a subject having AML, wherein the subject has AML exhibiting a number and / or percentage of m-LSC cells that is equal to or greater than a predetermined cutoff value, the method comprising administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent.

[0078] The present disclosure provides a method of treating AML in a subject, the method comprising: (a) measuring expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; (b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if the cell is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; and (c) if at least one CD70+ m-LSC is identified, administering to the subject a treatment comprising at least one CD70-targeting agent. In some aspects, the treatment can further comprise at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0079] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70+), and step (b) can further include identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD64, and CD70+, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD64+, and CD70+.

[0080] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, GPR56, and CD70, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, GPR56-, and CD70+.

[0081] The present disclosure provides a method for treating AML in a subject, the method comprising: (a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 in a plurality of cells in a sample from the subject; (b) identifying the number and / or proportion of CD70+ m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; (c) comparing the number and / or proportion of CD70+ m-LSCs identified in step (b) with a predetermined cutoff value; and (d) administering to the subject a treatment comprising at least one CD70-targeting agent if the number and / or proportion of CD70+ m-LSCs is equal to or greater than the predetermined cutoff value. In some embodiments, the treatment can further comprise at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0082] In some aspects of the foregoing methods, step (a) can further include measuring expression of at least one of CD117, CD244, and CD64 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further include identifying the number and / or proportion of CD70+ m-LSCs among the plurality of cells identified based on their CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70 immunophenotypes. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, CD64, and CD70, and step (b) can include identifying the number and / or proportion of CD70+ m-LSCs, wherein cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD64+, and CD70+.

[0083] In some aspects of the foregoing methods, step (a) can further comprise measuring expression of at least one of CD117, CD244, CD64, and GPR56 (i.e., in addition to CD34, CD4, CD11b, CD14, CD36, and CD70), and step (b) can further comprise identifying the presence of at least one CD70+ m-LSC identified based on an immunophenotype of CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+. Thus, in a non-limiting example, step (a) can include measuring expression of CD34, CD4, CD11b, CD14, CD36, GPR56, and CD70, and step (b) can include identifying the presence of at least one CD70+ m-LSC, wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, GPR56-, and CD70+.

[0084] The present disclosure provides methods of treating a subject with AML, the methods comprising administering to the subject with AML a treatment comprising at least one anti-CD70 targeting agent, wherein the subject has at least one CD70+ m-LSC. In some embodiments, the treatment further comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0085] The present disclosure provides methods of treating a subject with AML, the methods comprising administering to the subject with AML a treatment comprising at least one anti-CD70 targeting agent, wherein the subject has AML exhibiting a percentage count of CD70+ m-LSCs equal to or greater than a predetermined cutoff value. In some embodiments, the treatment further comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0086] Identification of m-LSC From the description of the methods provided herein, it will be understood that the methods of the present disclosure include identifying at least one, number and / or proportion of monocytic leukemia stem cells (m-LSCs) among a plurality of cells in a sample from a subject.

[0087] It will be appreciated that the step of identifying at least one m-LSC in a plurality of cells can result in the identification of no m-LSC (i.e., the user can determine that no m-LSC is, in fact, present in the plurality of cells).

[0088] In the methods of the present disclosure, m-LSCs can be identified based on a novel immunophenotype: CD34-, CD4+, CD11b-, CD14-, and CD36-. In some embodiments, this immunophenotype can be optionally supplemented with one or more markers selected from CD117-, CD244-, and CD64+. Thus, in methods for identifying m-LSCs via immunophenotype, a user practicing the method can measure the expression of CD34, CD4, CD11b, CD14, and CD36 (and optionally one or more of CD117, CD244, and CD64) on cells from a sample from a subject to determine the presence or absence of m-LSCs in the sample, and optionally the proportion and / or number of m-LSCs in the sample. In some embodiments, the CD34-, CD4+, CD11b-, CD14-, and CD36- immunophenotype can optionally be further complemented with one or more markers selected from CD117-, CD244-, CD64+, and GPR56. Thus, in methods of identifying m-LSCs via immunophenotype, a user practicing the method can measure expression of CD34, CD4, CD11b, CD14, and CD36 (and optionally one or more of CD117, CD244, CD64, and GPR56) on cells from a sample from a subject to determine whether m-LSCs are present in the sample, and optionally the proportion and / or number of m-LSCs in the sample.

[0089] Expression of the above biomarkers, or any other biomarkers described herein, can be achieved by one of skill in the art using any suitable method known in the art, including, but not limited to, PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, transcriptomics and cellular indexing of epitopes by sequencing (CITE-SEQ), or any combination thereof.

[0090] In addition to the immunophenotypes described above, m-LSCs can alternatively or additionally be identified by one or more transcriptomic characteristics described herein.

[0091] In some embodiments of the methods of the present disclosure, the transcriptomic signature identifying m-LSCs can be upregulation of expression of at least one of the biomarkers set forth in Table 5. One skilled in the art will understand that upregulation corresponds to a higher expression level than the control expression value found in other types of cells.

[0092] In some embodiments of the methods of the present disclosure, the transcriptomic signature identifying m-LSCs can be at least one or any combination of the biomarkers shown in Table 1A. [Table 1A-1] [Table 1A-2]

[0093] In some embodiments of the methods of the present disclosure, the transcriptomic signature identifying an m-LSC can be upregulation in at least one of the GSEA gene signatures shown in Table 1B. One of skill in the art would readily recognize the biomarkers for each of the GSEA gene signatures shown in Table 1B. [Table 1B] Table 1B - GSEA gene signature upregulated in m-LSCs

[0094] Any of the transcriptomic signatures shown in Tables 1A, 1B, and 5 can be combined together in any combination. In a non-limiting example, m-LSC cells may be identified by upregulation of two of the biomarkers shown in Table 1A and three of the biomarkers shown in Table 5.

[0095] Those skilled in the art will understand that identifying m-LSCs using the transcriptomic signature described herein can include measuring the expression of one or more biomarkers that make up the transcriptomic signature. This expression measurement can be accomplished using any suitable method known to those skilled in the art. Such methods include, but are not limited to, PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, RNA sequencing, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, Cellular Indexing of Transcriptomics and Epitopes by Sequencing (CITE-SEQ), or any combination thereof.

[0096] Identifying m-LSCs using the transcriptomic signatures described herein can also include performing transcriptomic analysis using any of the standard methods known in the art for transcriptomic analysis, including, but not limited to, methods described herein, such as CITE-SEQ.

[0097] Identification of CD70+ m-LSCs From the description of the methods provided herein, it will be understood that the methods of the present disclosure include identifying at least one, number and / or proportion of CD70+ monocytic leukemia stem cells (m-LSCs) among a plurality of cells in a sample from a subject.

[0098] It will be appreciated that the step of identifying at least one CD70+ m-LSC in a plurality of cells can result in the identification of no CD70+ m-LSC (i.e., the user can determine that no CD70+ m-LSC is, in fact, present in the plurality of cells).

[0099] In the disclosed methods, m-LSCs can be identified based on a novel immunophenotype: CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+. In some embodiments, this immunophenotype can be optionally supplemented with one or more markers selected from CD117-, CD244-, and CD64+. Thus, in methods for identifying CD70+ m-LSCs via immunophenotype, a user practicing the method can measure the expression of CD34, CD4, CD11b, CD14, CD36, and CD70 (and optionally one or more of CD117, CD244, and CD64) on cells from a sample from a subject to determine the presence or absence of CD70+ m-LSCs in the sample, and optionally the proportion and / or number of CD70+ m-LSCs in the sample. In some embodiments, this immunophenotype can optionally be further complemented with one or more markers selected from CD117-, CD244-, CD64+, and GPR56-. Thus, in methods for identifying CD70+ m-LSCs via immunophenotype, a user practicing the method can measure expression of CD34, CD4, CD11b, CD14, CD36, and CD70 (and optionally one or more of CD117, CD244, CD64, and GPR56) on cells from a sample from a subject to determine whether CD70+ m-LSCs are present in the sample, and optionally the proportion and / or number of CD70+ m-LSCs in the sample.

[0100] Expression of the above biomarkers, or any other biomarkers described herein, can be achieved by one of skill in the art using any suitable method known in the art, including, but not limited to, PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, transcriptomics and cellular indexing of epitopes by sequencing (CITE-SEQ), or any combination thereof.

[0101] In addition to the immunophenotypes described above, CD70+ m-LSCs can alternatively or additionally be identified by one or more transcriptomic characteristics described herein.

[0102] In some embodiments of the disclosed methods, the transcriptomic signature identifying CD70+ m-LSCs can be upregulated expression of at least one of the biomarkers shown in Table 5. One of skill in the art will understand that upregulation corresponds to a higher expression level than the control expression value seen in other types of cells.

[0103] In some embodiments of the methods of the present disclosure, the transcriptomic signature identifying CD70+ m-LSCs can be at least one or any combination of the biomarkers shown in Table 1A.

[0104] Any of the transcriptomic signatures shown in Tables 1A, 1B, and 5 can be combined together in any combination. In a non-limiting example, CD70+ m-LSC cells may be identified by upregulation of two of the biomarkers shown in Table 1A and three of the biomarkers shown in Table 5, in addition to measuring CD70 expression.

[0105] Those skilled in the art will understand that identifying CD70+ m-LSCs using the transcriptomic signature described herein can include measuring the expression of one or more biomarkers that make up the transcriptomic signature. This measurement of expression can be accomplished using any suitable method known to those skilled in the art. Such methods include, but are not limited to, PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, RNA sequencing, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, PCR, Western blot, Cellular Indexing of Transcriptomics and Epitopes by Sequencing (CITE-SEQ), or any combination thereof.

[0106] Identifying CD70+ m-LSCs using the transcriptomic signatures described herein can also include performing transcriptomic analysis using any standard method known in the art for transcriptomic analysis, including, but not limited to, methods described herein, such as CITE-SEQ.

[0107] hypomethylating agents As will be appreciated by those skilled in the art, a hypomethylating agent is an agent that inhibits DNA methylation. In some aspects of the methods described herein, the hypomethylating agent can be selected from azacitidine, cytarabine, and decitabine. In some aspects of the methods described herein, the hypomethylating agent can be any hypomethylating agent known in the art.

[0108] In some embodiments, the hypomethylating agent is azacitidine, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that azacitidine can be identified by any one of the following names: 5-azacytidine, azacytidine, ladakamycin, 4-amino-1-β-D-ribofuranosyl-s-triazin-2(1H)-one, U-18496, CC-486, and 4-amino-1-β-D-ribofuranosyl-1,3,5-triazin-2(1H)-one. As will be understood by those skilled in the art, azacitidine can be identified by its CAS number 320-67-2.

[0109] In some embodiments, the hypomethylating agent is decitabine, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that decitabine can be identified by any one of the following names: 5-aza-2'-deoxycytidine, 4-amino-1-(2-deoxy-β-D-erythro-pentofuranosyl)-1,3,5-triazin-2(1H)-one, 5-aza-2'-deoxycytidine, 5-azadeoxycytidine, 2-deoxy-5-azacytidine, and 2'-deoxy-5-azacytidine. As will be understood by those skilled in the art, decitabine can be identified by CAS number 2353-33-5.

[0110] Substitution of hypomethylating agents In any of the methods described herein, the hypomethylating agent may be cytarabine, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that cytarabine can be identified by any one of the names 4-amino-1-[(2R,3S,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)oxolan-2-yl]pyrimidin-2-one, aracytidine, and cytosine arabinoside. As those skilled in the art will understand, cytarabine can be identified by CAS number 147-94-4.

[0111] Thus, in a non-limiting example, the present disclosure provides a method for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and cytarabine, the method comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) identifying the subject as not responding to the treatment if the presence of at least one m-LSC is identified, or identifying the subject as responding to the treatment if no m-LSC is identified.

[0112] In another non-limiting example, a method is provided for identifying whether a subject with AML will respond to treatment with a combination of at least one BCL-2 inhibitor and cytarabine, the method comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the number and / or proportion of m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) comparing the number and / or proportion of m-LSCs identified in step (b) with a predetermined cutoff value; and d) identifying the subject as not responding to the treatment if the number and / or proportion of m-LSCs is equal to or greater than the predetermined cutoff value, or identifying the subject as responding to the treatment if the number and / or proportion of m-LSCs is less than the predetermined cutoff value.

[0113] In another non-limiting example, the disclosure provides a method of treating AML in a subject, the method comprising: a) measuring expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; and c) administering to the subject a combination of at least one BCL-2 inhibitor, cytarabine, and at least one m-LSC targeting agent if at least one m-LSC is identified, or administering to the subject a combination of at least one BCL-2 inhibitor and cytarabine if no m-LSC is identified.

[0114] In another non-limiting example, the disclosure provides a method of treating AML in a subject, the method comprising: a) measuring expression of at least CD34, CD4, CD11b, CD14, and CD36 in a plurality of cells in a sample from the subject; and b) identifying the number and / or proportion of m-LSCs in the plurality of cells based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34−, CD4+, CD11b−, CD14−, and CD36−. c) comparing the number and / or proportion of m-LSCs identified in step (b) with a predetermined cutoff value; and d) administering to the subject a combination of at least one BCL-2 inhibitor, cytarabine, and at least one m-LSC targeting agent if the number and / or proportion of m-LSCs is equal to or greater than the predetermined cutoff value, or administering to the subject a combination of at least one BCL-2 inhibitor and cytarabine if the number and / or proportion of m-LSCs is less than the predetermined cutoff value.

[0115] BCL-2 inhibitors In some aspects of the methods provided herein, the BCL-2 inhibitor can be selected from venetoclax and navitoclax. In some aspects of the methods provided herein, the BCL-2 inhibitor can be any BCL-2 inhibitor known in the art.

[0116] In some embodiments, the BCL-2 inhibitor is venetoclax, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that venetoclax can also be identified by any one of the following names: GDC-0199, ABT-199, RG-7601, 4-(4-{[2-(4-chlorophenyl)-4,4-dimethyl-1-cyclohexen-1-yl]methyl}-1-piperazinyl)-N-({3-nitro-4-[(tetrahydro-2H-pyran-4-ylmethyl)amino]phenyl}sulfonyl)-2-(1H-pyrrolo[2,3-b]pyridin-5-yloxy)benzamide, Venklekta, and Venklixt. As those skilled in the art will understand, venetoclax can also be identified by CAS number 1257044-40-8.

[0117] In some embodiments, the BCL-2 inhibitor is navitoclax, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that navitoclax can be identified by any one of the following names: ABT263, ABT-263, and 4-(4-{[2-(4-chlorophenyl)-5,5-dimethylcyclohex-1-en-1-yl]methyl}piperazin-1-yl)-N-(4-{[(2R)-4-(morpholin-4-yl)-1-(phenylsulfanyl)butan-2-yl]amino}-3-(trifluoromethanesulfonyl)benzene-1-sulfonyl)benzamide. As will be understood by those skilled in the art, navitoclax can be identified by its CAS number 923564-51-6.

[0118] In some embodiments, the BCL-2 inhibitor can be BGB-11417.

[0119] In some embodiments, the BCL-2 inhibitor can be ZN-d5.

[0120] CD70 targeting agent In some embodiments, the CD70 targeting agent can be: i) an anti-CD70 antibody; ii) an anti-CD70 immunotherapy, preferably wherein the immunotherapy comprises CAR-T cells and / or NK cells that specifically target CD70; and iii) an agent that inhibits CD70 signaling, preferably wherein the agent that inhibits CD70 signaling prevents binding of CD27 to CD70.

[0121] In some embodiments, the CD70 targeting agent can be cusatuzumab.

[0122] In some aspects of the methods of the present disclosure, the immunotherapy can include administering a therapeutically effective amount of at least one antibody, at least one checkpoint inhibitor, at least one chimeric antigen receptor modified T cell (CAR-T cell), or any combination thereof. The immunotherapy can include adoptive cell transfer therapy.

[0123] In some embodiments, the immunotherapy can be an immunotherapy that specifically targets CD70. Thus, a non-limiting example of an immunotherapy that specifically targets at least one monocyte antigen can be a CAR-T cell comprising a chimeric antigen receptor that includes an antigen-binding domain that binds to CD70.

[0124] m-LSC targeting agent In some embodiments of the methods presented herein, the m-LSC targeting agent can be an agent that modulates one-carbon metabolism.

[0125] In some aspects of the methods presented herein, the m-LSC targeting agent can be an agent that modulates at least one of purine synthesis and pyrimidine synthesis.

[0126] The agent that modulates one-carbon metabolism is selected from methotrexate, brequinar, and cladribine.

[0127] In some embodiments, the m-LSC targeting agent is cladribine, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that cladribine can also be identified by any one of the following names: 5-(6-amino-2-chloropurin-9-yl)-2-(hydroxymethyl)oxolan-3-ol, 2-chloro-2'-deoxyadenosine, 2-chloro-2'-deoxy-β-adenosine, 2-chloro-6-amino-9-(2-deoxy-β-D-erythro-pentofuranosyl)purine, and 2-chlorodeoxyadenosine. Those skilled in the art will understand that cladribine can also be identified by CAS number 4291-63-8.

[0128] In some embodiments, the m-LSC targeting agent is brequinar, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that brequinar can be identified by any one of the names 6-fluoro-2-(2'-fluoro-1,1'-biphenyl-4-yl)-3-methyl-4-quinolinecarboxylic acid, bifenquinate, and BPQ. Those skilled in the art will understand that brequinar can be identified by CAS number 96187-53-0.

[0129] In some embodiments, the m-LSC targeting agent is methotrexate, [ka] or a pharmaceutically acceptable salt, analog, derivative, salt, or ester thereof. Those skilled in the art will understand that methotrexate can be identified by any one of the names (2S)-2-[(4-{[(2,4-diaminopteridin-6-yl)methyl](methyl)amino}benzoyl)amino]pentanedioic acid, MTX, 4-amino-N10-methylpteroylglutamic acid, and N-[p-[[2,4-diamino-6-pteridinyl)methyl]methylamino]benzoyl]-L-(+)-glutamic acid. Those skilled in the art will understand that methotrexate can be identified by CAS number 59-05-2.

[0130] In some embodiments, the m-LSC targeting agent can be an agent that inhibits MCL1. Non-limiting examples of agents that inhibit MCL1 include VU661013 and S63845.

[0131] In some embodiments, the m-LSC targeting agent can be an immunotherapy.

[0132] In some embodiments, the m-LSC targeted therapy can be an antifolate. Non-limiting examples of antifolates include methotrexate, pralatrexate, and pemetrexed.

[0133] In some aspects of the methods of the present disclosure, the immunotherapy can include administering a therapeutically effective amount of at least one antibody, at least one checkpoint inhibitor, at least one chimeric antigen receptor modified T cell (CAR-T cell), or any combination thereof. The immunotherapy can include adoptive cell transfer therapy.

[0134] In some aspects, the immunotherapy can be an immunotherapy that specifically targets at least one monocyte antigen, including, but not limited to, CD64 and LILRB4. Thus, a non-limiting example of an immunotherapy that specifically targets at least one monocyte antigen can be a CAR-T cell comprising a chimeric antigen receptor that comprises an antigen-binding domain that binds to CD64 and / or LILRB4.

[0135] The term "antibody" as used herein is used in the broadest sense and encompasses a variety of antibody structures, including, but not limited to, monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments, so long as they exhibit the desired antigen-binding activity. An antibody that binds to a target refers to an antibody that can bind to a target with sufficient affinity such that the antibody is useful as a diagnostic and / or therapeutic agent targeted to the target. In one embodiment, the extent to which an anti-target antibody binds to an unrelated non-target protein is less than about 10% of the binding of the antibody to the target, as measured, for example, by radioimmunoassay (RIA) or Biacore assay. In certain embodiments, an antibody that binds to a target has a dissociation constant (Kd) of <1 μM, <100 nM, <10 nM, <1 nM, <0.1 nM, <0.01 nM, or <0.001 nM (e.g., 10 8 M or less, e.g., 10 8 M~10 13 M, e.g., 10 9 M~10 13 M). In certain embodiments, the anti-target antibody binds to an epitope of the target that is conserved among different species.

[0136] A "blocking antibody" or "antagonist antibody" is an antibody that partially or completely blocks, inhibits, interferes with, or neutralizes the normal biological activity of an antigen to which it binds. For example, an antagonistic antibody may block signaling through an immune cell receptor (e.g., a T cell receptor) to restore a dysfunctional functional response by T cells to antigenic stimulation (e.g., proliferation, cytokine production, target cell killing).

[0137] An "agonist antibody" or "activating antibody" is an antibody that mimics, promotes, stimulates, or enhances the normal biological activity of an antigen to which it binds. Agonist antibodies can also enhance or initiate signaling by the antigen to which they bind. In some embodiments, agonist antibodies cause or activate signaling without a natural ligand. For example, agonist antibodies may increase memory T cell proliferation, increase cytokine production by memory T cells, inhibit regulatory T cell function, and / or inhibit regulatory T cell suppression of effector T cell function, such as effector T cell proliferation and / or cytokine production.

[0138] "Antibody fragment" refers to a molecule other than an intact antibody that contains a portion of the intact antibody that binds to the antigen to which the intact antibody binds. Examples of antibody fragments include, but are not limited to, Fv, Fab, Fab', Fab'-SH, F(ab')2; diabodies; linear antibodies; single-chain antibody molecules (e.g., scFv); and multispecific antibodies formed from antibody fragments.

[0139] CAR-T cells are T cells genetically engineered to stably express at least one chimeric antigen receptor (CAR). The CAR can comprise an extracellular domain, a transmembrane domain, and a cytoplasmic domain. The CAR can comprise an antigen-binding domain. The antigen-binding domain can be located in the extracellular domain. In some embodiments of the methods of the present disclosure, the antigen-binding domain binds to at least one AML cell surface protein. In some embodiments of the methods of the present disclosure, the antigen-binding domain binds to CD64 and / or LILRB4. The CAR can also comprise an extracellular spacer (hinge) domain. The extracellular spacer can be located in the extracellular domain. The CAR can comprise a signaling domain. The signaling domain can be a T cell activation domain. The signaling domain can be located in the cytoplasmic domain. The CAR can comprise at least one costimulatory domain. The CAR can comprise at least two costimulatory domains. The CAR can comprise at least three costimulatory domains. The costimulatory domain can be located in the cytoplasmic domain.

[0140] In some embodiments of the disclosed methods, the CAR-T cells can be autologous to the subject. In some embodiments, the CAR-T cells can be allogeneic to the subject.

[0141] In some forms of the methods of the present invention, CAR-T cells can be administered alone or as a pharmaceutical composition in combination with other components, such as diluents and / or IL-2 or other cytokines or cell populations. Briefly, a pharmaceutical composition can include a plurality of CAR-T cells in combination with one or more pharmaceutically or physiologically acceptable carriers, diluents, or excipients. Such compositions can include buffers such as neutral buffered saline, phosphate buffered saline, carbohydrates such as glucose, mannose, sucrose, or dextran, mannitol, proteins, polypeptides, or amino acids such as glycine, antioxidants, chelating agents such as EDTA or glutathione, adjuvants (e.g., aluminum hydroxide), and preservatives. CAR-T cells and related compositions can be administered intravenously to a subject.

[0142] The CAR-T cell can comprise a chimeric antigen receptor. The chimeric antigen receptor can comprise an antigen-binding domain. The antigen-binding domain can bind to CD64 and / or LILRB4.

[0143] subject As used herein, the term "subject" includes human and non-human animals, as well as cell lines, cell cultures, tissues, and organs. In some aspects, the subject is a mammal. The mammal can be, for example, a human or a suitable non-human mammal, such as a primate, mouse, rat, dog, cat, cow, horse, goat, camel, sheep, or pig. The subject can also be a bird or poultry. In some aspects, the subject is a human.

[0144] As used herein, the term "subject in need thereof" refers to a subject having a disease or a subject at high risk of developing a disease. "Subject" includes mammals. A mammal can be, for example, a human or a suitable non-human mammal, such as a primate, mouse, rat, dog, cat, cow, horse, goat, camel, sheep, or pig. A subject can also be a bird or poultry. In some embodiments, a mammal is a human. A subject in need thereof can be a subject previously diagnosed or identified as having a disease or disorder disclosed herein. A subject in need thereof can also be a subject suffering from a disease or disorder disclosed herein. Alternatively, a subject in need thereof can be a subject at high risk of developing such a disease or disorder compared to the general population (i.e., a subject who is more susceptible to developing such a disorder compared to the general population). A subject in need thereof can have a refractory or resistant disease or disorder disclosed herein (i.e., a disease or disorder disclosed herein that does not respond, or has not yet responded, to treatment). The subject may be resistant to treatment at the start of the treatment or may become resistant during treatment. In some embodiments, the subject in need thereof has undergone all known effective therapies for the disease or disorder disclosed herein, none of which have been effective. In some embodiments, the subject in need thereof has undergone at least one previous therapy.

[0145] In some aspects of the methods of the present disclosure, the subject is a human.

[0146] In some aspects of the methods of the present disclosure, the subject is a subject with AML who has not received any treatment for the AML.

[0147] In some embodiments of the methods of the present disclosure, the subject has AML and has previously received at least one AML treatment, in some embodiments, the at least one treatment comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0148] In some embodiments of the method of the present disclosure, the subject is the subject that has at least one m-LSC in AML cell population.In some embodiments of the method of the present disclosure, the subject is the subject that has AML cell population comprises m-LSC proportion that is greater than predetermined cut-off proportion.In some embodiments of the method of the present disclosure, the subject is the subject that has AML cell population comprises m-LSC number that is greater than predetermined cut-off number.

[0149] In some embodiments of the disclosed methods, the subject is a subject in which at least one CD70+ m-LSC is present in the AML cell population. In some embodiments of the disclosed methods, the subject is a subject in which the AML cell population contains a proportion of CD70+ m-LSCs greater than a predetermined cutoff percentage. In some embodiments of the disclosed methods, the subject is a subject in which the AML cell population contains a number of CD70+ m-LSCs greater than a predetermined cutoff number.

[0150] sample In some aspects of the disclosed methods, the sample can include blood, a bone marrow biopsy, a bone marrow aspirate, a chloroma biopsy, a tissue biopsy, cerebrospinal fluid, or any combination thereof.

[0151] In some aspects, the sample can be a bone marrow biopsy.

[0152] In some embodiments, the sample can be a bone marrow aspirate.

[0153] In some aspects, the sample can be a chloroma biopsy.

[0154] General definition As used herein, phrases such as "one or more of A, B, or C," "one or more of A, B, or C," "one or more of A, B, and C," "one or more of A, B, and C," "selected from the group consisting of A, B, and C," "selected from A, B, and C," and the like are used interchangeably and, unless otherwise specified, all refer to a selection from the group consisting of A, B, and / or C, i.e., one or more A, one or more B, one or more C, or any combination thereof.

[0155] Unless otherwise specified, any reference to a method of treatment should be understood to include the use of an agent to provide treatment as described herein. Furthermore, unless otherwise specified, any reference to a method of treatment should be understood to include the use of an agent to prepare a medicament for treating such a condition. Treatment includes treatment of humans or non-human animals, including rodents and other disease models used herein.

[0156] As used herein, the term "treating" or "treat" refers to the management and care of a patient for the purpose of combating a disease, condition, or disorder, and includes administering an agent described in the present disclosure, or a pharmaceutically acceptable salt, polymorph, or solvate thereof, to alleviate the symptoms or complications of the disease, condition, or disorder, or to eliminate the disease, condition, or disorder. The term "treat" may also include treatment of a cell or animal model in vitro. It should be understood that reference to "treating" or "treat" includes the alleviation of established symptoms of the condition. "Treating" or "treating" the condition, disorder, or condition includes (1) preventing the onset of clinical symptoms of the condition or delaying the onset of clinical symptoms of the condition, disorder, or condition in a person who may be affected by or predisposed to the condition, disorder, or condition, but who has not yet experienced or exhibited clinical or subclinical symptoms of the condition, disorder, or condition; (2) inhibiting the condition, disorder, or condition, i.e., arresting, alleviating, or delaying the onset of the disease or its recurrence (in the case of maintenance therapy) or the progression of at least one clinical or subclinical symptom thereof; or (3) palliating or alleviating the disease, i.e., causing regression of the condition, disorder, or condition or at least one clinical or subclinical symptom thereof.

[0157] It is understood that the agents described in this disclosure or pharmaceutically acceptable salts, polymorphs or solvates thereof can also be or may be used to prevent associated diseases, conditions or disorders or to identify suitable candidates for such purposes.

[0158] As used herein, the terms "prevent," "prevent," or "protect from" mean reducing or eliminating the onset of symptoms or complications of such disease, condition, or disorder.

[0159] As used herein, the phrase "pharmaceutically acceptable" refers to compounds, anions, cations, materials, compositions, carriers, and / or dosage forms that are suitable for use in contact with the tissues of human beings and animals without excessive toxicity, irritation, allergic response, or other problem or complication, within the scope of sound medical judgment, commensurate with a reasonable benefit / risk ratio.

[0160] It is understood that the agents described herein can be administered to a subject in at least one therapeutically effective amount. As used herein, the term "therapeutically effective amount" refers to an amount of a pharmaceutical agent to treat, ameliorate, or prevent a specified disease or condition, or to exhibit a detectable therapeutic or inhibitory effect. This effect can be detected by any assay method known in the art. The precise effective amount for a subject will depend on the subject's weight, height, and health, the nature and extent of the condition, and the therapeutic agent or combination of therapeutic agents selected for administration. The therapeutically effective amount for a given situation can be determined by routine experimentation, which is within the skill and judgment of the clinician. Clinicians can also determine therapeutically effective amounts of the agents described herein using established dosages and administration protocols for the agents described herein.

[0161] It is understood that for any agent, the therapeutically effective amount can be estimated initially either in cell culture assays, for example, of tumor cells, or in animal models, usually rats, mice, rabbits, dogs, or pigs. Animal models can also be used to determine appropriate concentration ranges and routes of administration. Such information can then be used to determine effective doses and routes of administration in humans. For example, ED 50 (the dose that is therapeutically effective in 50% of the population) and LD 50 Therapeutic / prophylactic efficacy and toxicity (the dose lethal to 50% of the population) may be determined by standard pharmaceutical procedures in cell cultures or experimental animals. The dose ratio between toxic and therapeutic effects is the therapeutic index, and the ratio LD 50 / ED 50Pharmaceutical compositions that exhibit high therapeutic indices are preferred. The dosage can vary within this range depending on the dosage form used, sensitivity of the patient, and the route of administration.

[0162] Dosage and administration are adjusted to provide sufficient levels of the active agent(s) or to maintain the desired effect. Factors that may be considered include the severity of the disease state, the subject's general health, the subject's age, weight, and sex, diet, time and frequency of administration, drug combination(s), reaction sensitivities, and tolerability / response to therapy. Long-acting pharmaceutical compositions may be administered every 3-4 days, every week, or once every two weeks, depending on the half-life and clearance rate of the particular formulation.

[0163] As used herein, the term "pharmaceutically acceptable salts" refers to derivatives of the agents described herein, wherein the agent is modified by making its acid or base salt. Examples of pharmaceutically acceptable salts include, but are not limited to, mineral or organic acid salts of basic residues such as amines, alkali or organic salts of acidic residues such as carboxylic acids, and the like. Pharmaceutically acceptable salts include conventional non-toxic salts as well as, for example, quaternary ammonium salts of the parent agent formed from non-toxic inorganic or organic acids. For example, such conventional non-toxic salts include 2-acetoxybenzoic acid, 2-hydroxyethanesulfonic acid, acetic acid, ascorbic acid, benzenesulfonic acid, benzoic acid, bicarbonate, carbonic acid, citric acid, edetic acid, ethanedisulfonic acid, 1,2-ethanesulfonic acid, fumaric acid, glucoheptonic acid, gluconic acid, glutamic acid, glycolic acid, glycolic acid arsanilic acid, hexylresorcylic acid, hydrabamic acid, hydrobromic acid, hydrochloric acid, hydroiodic acid, hydroxymaleic acid, hydroxynaphthoic acid, isethionic acid, lactic acid, and lactobionic acid. , laurylsulfonic acid, maleic acid, malic acid, mandelic acid, methanesulfonic acid, napsylic acid, nitric acid, oxalic acid, pamoic acid, pantothenic acid, phenylacetic acid, phosphoric acid, polygalacturonic acid, propionic acid, salicylic acid, stearic acid, acetic acid, succinic acid, sulfamic acid, sulfanilic acid, sulfuric acid, tannic acid, tartaric acid, toluenesulfonic acid, and commonly occurring amino acids such as glycine, alanine, phenylalanine, arginine, and the like.

[0164] In some embodiments, the pharmaceutically acceptable salt is a sodium salt, a potassium salt, a calcium salt, a magnesium salt, a diethylamine salt, a choline salt, a meglumine salt, a benzathine salt, a tromethamine salt, an ammonia salt, an arginine salt, or a lysine salt.

[0165] Other examples of pharmaceutically acceptable salts include hexanoic acid, cyclopentanepropionic acid, pyruvic acid, malonic acid, 3-(4-hydroxybenzoyl)benzoic acid, cinnamic acid, 4-chlorobenzenesulfonic acid, 2-naphthalenesulfonic acid, 4-toluenesulfonic acid, camphorsulfonic acid, 4-methylbicyclo-[2.2.2]-oct-2-ene-1-carboxylic acid, 3-phenylpropionic acid, trimethylacetic acid, tert-butylacetic acid, muconic acid, etc. The present disclosure also relates to salts formed when an acidic proton present in the parent drug is either replaced by a metal ion, e.g., an alkali metal ion, alkaline earth ion, or aluminum ion, or coordinated with an organic base such as ethanolamine, diethanolamine, triethanolamine, tromethamine, N-methylglucamine, etc. In the salt form, it is understood that the ratio of drug to salt cation or anion can be 1:1 or any ratio other than 1:1, for example, 3:1, 2:1, 1:2, or 1:3.

[0166] It should be understood that all references to pharmaceutically acceptable salts include the solvent addition forms (solvates) or crystal forms (polymorphs) defined herein of the same salt.

[0167] As used herein, the term "refractory" is used in its broadest sense to refer to when the disease present in a subject is unresponsive to a particular therapy, i.e., when the therapy provides no or diminishing clinical benefit to that particular subject.

[0168] As used herein, the terms "combination therapy" or "concurrent therapy" include the administration of an agent disclosed herein or a pharmaceutically acceptable salt, polymorph, or solvate thereof, and at least a second agent as part of a specific treatment regimen intended to provide a beneficial effect due to the interaction of these therapeutic agents. The beneficial effect of the combination includes, but is not limited to, a pharmacokinetic or pharmacodynamic interaction resulting from the combination of therapeutic agents.

[0169] As used herein, the term "proximity in time" refers to the administration of one therapeutic agent occurring within a period of time before or after the administration of another therapeutic agent, such that the therapeutic effects of one therapeutic agent overlap with the therapeutic effects of the other therapeutic agent. In some embodiments, the therapeutic effects of one therapeutic agent completely overlap with the therapeutic effects of the other therapeutic agent. In some embodiments, "proximity in time" means that the administration of one therapeutic agent occurs within a period of time before or after the administration of another therapeutic agent, such that there is a synergistic effect between the one therapeutic agent and the other therapeutic agent. "Proximity in time" may vary depending on various factors, including, but not limited to, the age, sex, weight, genetic background, health status, medical history, and treatment history of the subject to whom the therapeutic agent is administered, the disease or condition being treated or ameliorated, the therapeutic outcome being achieved, the dosage, frequency, and duration of administration of the therapeutic agent, the pharmacokinetics and pharmacodynamics of the therapeutic agent, and the route(s) by which the therapeutic agent is administered. In some embodiments, "proximity in time" means within 15 minutes, within 30 minutes, within 1 hour, within 2 hours, within 4 hours, within 6 hours, within 8 hours, within 12 hours, within 18 hours, within 24 hours, within 36 hours, within 2 days, within 3 days, within 4 days, within 5 days, within 6 days, within 1 week, within 2 weeks, within 3 weeks, within 4 weeks, within 6 weeks, or within 8 weeks. In some embodiments, multiple administrations of one therapeutic agent can be administered in close temporal proximity to a single administration of another therapeutic agent. In some embodiments, the temporal proximity can vary during a treatment cycle or dosing regimen.

[0170] Illustrative Embodiments Embodiment 1. A method of treating acute myeloid leukemia (AML) in a subject, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 on a plurality of cells in a sample from a subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) if at least one m-LSC is identified, administering to the subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent; or and if no m-LSC is identified, administering to the subject a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0171] Embodiment 2. A method of identifying whether a subject having AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 on a plurality of cells in a sample from a subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as an m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) identifying the subject as not responding to the treatment if the presence of at least one m-LSC is identified; or and identifying the subject as responding to the treatment if no m-LSC is identified.

[0172] Embodiment 3a. Step (a) further comprises measuring the expression of at least CD117, CD244, and CD64; 3. The method of embodiment 1 or embodiment 2, wherein the cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, and CD64+.

[0173] Embodiment 3b. Step (a) further comprises measuring the expression of at least CD117, CD244, CD64 and GPR56; 3. The method of embodiment 1 or embodiment 2, wherein the cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and GPR56-.

[0174] Embodiment 4. The method of any one of embodiments 1-3, wherein the at least one m-LSC targeting agent is an agent that modulates one-carbon metabolism, an agent that modulates purine synthesis, an agent that modulates pyrimidine synthesis, or any combination thereof.

[0175] Embodiment 5. The method of any one of embodiments 1-4, wherein the at least one m-LSC targeting agent is selected from methotrexate, brequinar, and cladribine.

[0176] Embodiment 6. The method of any one of embodiments 1 to 5, wherein the at least one hypomethylating agent is selected from azacitidine and decitabine.

[0177] Embodiment 7. The method of any one of embodiments 1 to 6, wherein the at least one BCL-2 inhibitor is selected from venetoclax and navitoclax.

[0178] Embodiment 8. The method of any one of embodiments 1 to 7, wherein step (a) comprises performing PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, Cell-Indexed Sequencing of Transcriptome and Epitopes (CITE-SEQ), or any combination thereof.

[0179] Embodiment 9. The method of any one of embodiments 1 to 8, wherein the subject has AML and has not received any treatment for the AML.

[0180] Embodiment 10. The method of any one of embodiments 1 to 9, wherein the subject is a subject with AML who has previously received at least one AML treatment.

[0181] Embodiment 11. The method of embodiment 10, wherein the at least one AML treatment comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0182] Embodiment 12. The method of any one of embodiments 1-11, wherein identifying the subject as responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as having a long-term remission after receiving treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0183] Embodiment 13. The method of any one of embodiments 1-12, wherein identifying the subject as non-responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as refractory to treatment with a combination of said at least one BCL-2 inhibitor and said at least one hypomethylating agent, and / or the subject relapses after treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0184] Embodiment 14. The method of any one of embodiments 1 to 13, wherein the biological sample comprises blood, a bone marrow biopsy, a bone marrow aspirate, a chloroma biopsy, a tissue biopsy, cerebrospinal fluid, or any combination thereof.

[0185] Embodiment 15. The method of embodiment 14, wherein the sample is a bone marrow biopsy.

[0186] Embodiment 16. The method of embodiment 14, wherein the sample is a bone marrow aspirate.

[0187] Embodiment 17. The method of embodiment 14, wherein the sample is a chloroma biopsy.

[0188] Embodiment 18. Step (a) further comprises performing a transcriptomic analysis of a plurality of cells in the sample; and Step (b) further comprises identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the transcriptomic analysis performed in step (a), wherein the cell is: i) upregulation of expression of at least one of the biomarkers in Table 5; and ii) expression of at least one biomarker in Table 1A; and iii) upregulation of expression of at least one GSEA gene signature of Table 1B.

[0189] Embodiment 19. The method of embodiment 18, wherein the transcriptomics analysis is performed using RNA sequencing.

[0190] Embodiment 20. The method of embodiment 19, wherein RNA sequencing is performed using CITE-SEQ.

[0191] Embodiment 21. A method of treating acute myeloid leukemia (AML) in a subject, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 on a plurality of cells in a sample from a subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; c) if at least one CD70+ m-LSC is identified, administering to the subject a treatment comprising at least one CD70 targeting agent, preferably wherein the treatment further comprises at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0192] Embodiment 22. A method of identifying whether a subject with AML will respond to treatment with a CD70 targeting agent, the method comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 on a plurality of cells in a sample from a subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+; c) identifying the subject as responding to the treatment if the presence of at least one CD70+ m-LSC is identified.

[0193] Embodiment 23. Step (a) further comprises measuring the expression of at least CD117, CD244 and CD64; 23. The method of embodiment 21 or embodiment 22, wherein the cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, and CD70+.

[0194] Embodiment 24. At least one CD70 targeting agent is i) an anti-CD70 antibody, preferably wherein the anti-CD70 antibody is cusatuzumab; ii) anti-CD70 immunotherapy, preferably wherein the immunotherapy comprises CAR-T cells and / or NK cells that specifically target CD70; or iii) An agent that inhibits CD70 signaling, preferably an agent that inhibits CD70 signaling that prevents binding of CD27 to CD70.

[0195] Embodiment 25. The method of any one of embodiments 1 to 24, wherein the at least one hypomethylating agent is selected from azacitidine and decitabine.

[0196] Embodiment 26. The method of any one of embodiments 1 to 25, wherein the at least one BCL-2 inhibitor is selected from venetoclax and navitoclax.

[0197] Embodiment 27. The method of any one of embodiments 1 to 26, wherein step (a) comprises performing PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, transcriptomics and cellular indexing of epitopes by sequencing (CITE-SEQ), or any combination thereof.

[0198] Embodiment 28 The method of any one of embodiments 1 to 27, wherein the subject has AML and has not received any treatment for the AML.

[0199] Embodiment 29. The method of any one of embodiments 1 to 28, wherein the subject is a subject with AML who has previously received at least one AML treatment.

[0200] Embodiment 30. The method of embodiment 29, wherein the at least one AML treatment comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

[0201] Embodiment 31. The method of any one of embodiments 1 to 30, wherein the biological sample comprises blood, a bone marrow biopsy, a bone marrow aspirate, a chloroma biopsy, a tissue biopsy, cerebrospinal fluid, or any combination thereof.

[0202] Embodiment 32. The method of embodiment 31, wherein the sample is a bone marrow biopsy.

[0203] Embodiment 33. The method of embodiment 31, wherein the sample is a bone marrow aspirate.

[0204] Embodiment 34. The method of embodiment 31, wherein the sample is a chloroma biopsy specimen.

[0205] Embodiment 35. Step (a) further comprises performing a transcriptomic analysis of a plurality of cells in the sample; and Step (b) further comprises identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the transcriptomic analysis performed in step (a), wherein the cell is: i) upregulation of expression of at least one of the biomarkers in Table 5; and ii) expression of at least one biomarker in Table 1A; and iii) identified as m-LSCs based on at least one of: upregulation of expression of at least one GSEA gene signature in Table 1B;

[0206] Embodiment 36. The method of embodiment 35, wherein the transcriptomics analysis is performed using RNA sequencing.

[0207] Embodiment 37. The method of embodiment 36, wherein RNA sequencing is performed using CITE-SEQ. [Example]

[0208] Example 1 In the following non-limiting example, an experiment was conducted to characterize developmentally heterogeneous LSCs. A cohort of 20 human patient primary specimens, selected to represent the spectrum of phenotypes commonly seen in AML, was analyzed by standard flow cytometry with blood cell gating (see Table 1C for patient and specimen information). Analysis revealed the definition of three broad classes of specimens: 1) predominantly primary (Prim), 2) mixed monocytic-primary (MMP), and 3) predominantly monocytic (Mono). As indicated by the nomenclature, Prime specimens displayed few (<1%) differentiated monocytic features and a predominantly blastoid profile (intermediate CD45 and low internal side scatter (SSC) compared to lymphocytes from the same patient). Primed specimens expressed high levels (mostly >90%) of canonical stem / progenitor cell-associated markers (CD34 and CD117) and low levels of monocyte antigens (CD11b, CD64, CD14, CD36, and LILRB4). In contrast, at the most differentiated end of the spectrum, mono specimens showed very few blastoid cells (<1%) and a predominantly monocytoid profile (CD45 bright and SSC high compared to lymphocytes). Mono specimens downregulated CD34 and CD117 and upregulated monocyte markers, including CD64, to varying degrees. Finally, MMP specimens were characterized as having distinct blastoid and monocytic subpopulations (ranging from 26% to 79% primary and 14% to 35% monocytic subpopulations), evident in both CD45 / SSC gating and stem / progenitor cell marker phenotypic analysis. Monocytic antigens contained a mixture of monocytic and primary cells, occupying the middle range of the developmental spectrum (). Without being bound by theory, we hypothesized that heterogeneity within the LSC compartment contributes to the developmental heterogeneity observed in the above analysis. To begin characterizing potential LSC heterogeneity, we performed flow cytometric cell sorting to isolate primary (prim) and monocytic (mono) subpopulations from several MMP AMLs. Each subpopulation was independently transplanted into immunodeficient NSG-S mice, and leukemia engraftment was assessed by measuring the percentage of human CD45+ cells in the bone marrow of each experimental animal.These studies revealed two subgroups of MMP AML patients. In one subgroup, termed "Uni-MMP," LSC activity was detected in the primed subpopulation but not in the mono-subpopulation (Figure 1A). In contrast, in the second type of MMP AML, termed "Multi-MMP," LSC activity was readily detected in both the primed and mono-subpopulations (Figure 1B).

[0209] To assess the underlying mutational profiles of Uni-MMP and Multi-MMP types of AML, whole exome sequencing (WES) was performed on flow-sorted prime and mono subpopulations. WES analysis showed that prime and mono subpopulations from three independent Uni-MMP samples had comparable mutation profiles in 49 commonly mutated genes in AML, including ASXL1, CEBPA, GATA2, JAK3, MYD88, PTPN11, SRSF2, BCOR, CSF3R, GNAS, KDM6A, NOTCHI, RAD21, STAG2, BCOR1, DNMT3A, HRAS, KIT, NPM1, RUNX1, TET2, BRAF, ETV6, IDH1, KMT2A, NRAS, SETBP1, TP53, CALR, EZH2, IDH2, KRAS, PHF6, SF3B1, U2AF1, CBL, FLT3, JAK1, MEK1, PML, SMC1A, WT1, CBLB, GATA1, JAK2, MPL, PTEN, SMC3, and ZRSR2. Although some differences in variant allele frequencies were observed (FLT3 and SETBP1 mutations), overall, the analysis was consistent with a common genetic origin. WES of three multi-MMP samples showed two samples with similar profiles between the primed and mono-subpopulations, but the third sample showed clear differences, with distinct NRAS and SMC1A mutations in the two subpopulations. One sample also showed multiple mutations shared between the primed and mono-subpopulations, including IDH2 and SRSF2, suggesting divergence from a common ancestral clone at a relatively late stage in the disease course. Without being bound by theory, these data suggest that, at least in some instances, multi-MMP AML arises from underlying mutational variation, which is consistent with the understanding that phenotypically distinct subpopulations of LSCs can coexist in a given patient with AML.

[0210] To further characterize the leukemogenic properties of LSCs in Multi-MMP patients, we assessed the nature of disease that developed in transplanted NSG-S mice. Primed and mono-transplanted cells from two representative specimens (AML-07 and AML-13) consistently differed in their developmental spectrum. For both AML specimens, the primed subpopulation was able to recapitulate the entire disease developmental spectrum, with both primed and mono-transplanted cells present in the transplanted mice. In contrast, the mono-transplanted subpopulation caused only a monocytic disease, without the presence of more primary cells.

[0211] Notably, the observed distinct differences in the developmental spectrum of transplanted disease translated into distinct differences in treatment sensitivity. When primed versus mono-transplanted groups were treated in vivo with a venetoclax plus azacytidine (VEN+AZA) regimen, mono-derived disease was significantly more resistant to VEN+AZA than primed cells (Figure 2A-C). Thus, disease-initiating and evolving LSCs in the monocytic subpopulation exhibited a more restricted developmental hierarchy closer to the mature stage of the myeloid developmental spectrum, and distinct resistance to VEN+AZA therapy. This LSC subclass was termed mono-LSC (m-LSC), in contrast to the more conventional prim-LSC (p-LSC). Without being bound by theory, these findings indicate that heterogeneous LSC subpopulations with distinct developmental phenotypes coexist in the same patient. Furthermore, LSC heterogeneity gives rise to bulk tumor populations with distinct treatment responses in PDX models, demonstrating clinical significance.

[0212] Example 2 In the following non-limiting example, we conducted experiments to predict clinical outcomes depending on m-LSCs. Without being bound by theory, we hypothesized that the pathogenesis and clinical outcomes of de novo AML patients differ depending on the presence of m-LSCs. As shown schematically in Figure 3A, Uni-MMP patients initially exhibiting only p-LSCs were predicted to achieve longer remissions upon VEN+AZA therapy because p-LSCs are inherently dependent on the venetoclax-targeted BCL-2. In contrast, Multi-MMP patients with distinct m-LSC populations were predicted to relapse relatively quickly into monocytic disease. To test this concept, we evaluated three de novo AML patients treated with VEN+AZA therapy. As shown in Figures 3B-3D, patient Pt-20 had no detectable m-LSC activity at diagnosis, whereas patients Pt-12 and Pt-69 had readily detectable m-LSC activity in xenograft assays. The presence of functionally defined m-LSCs directly correlated with clinical outcome, with Uni-MMP patient Pt-20 experiencing long-term remission for over 3.5 years, and Multi-MMP patients Pt-12 and Pt-69 exhibiting a monocytic phenotype within 12 and 3 months, respectively, and experiencing relatively rapid disease relapse.

[0213] To evaluate possible mutational changes during pathogenesis, we performed WES analysis on the sorted prime and mono subpopulations of patients Pt-20, Pt-12, and Pt-69. As expected for Pt-20, a patient with Uni-MMP AML, the prime and mono subpopulations showed highly similar mutational profiles. In contrast, both patients 12 and 69 displayed distinct mutations. More specifically, Pt-12 had an NRAS mutation specific to the mono subpopulation at diagnosis that persisted at relapse. On the other hand, Pt-12 had an SMCA1 mutation in the prime subpopulation at diagnosis that disappeared at relapse. The data clearly suggest the expansion of a genetically defined monocytic subclone. Similarly, Pt-69 had a duplication event of chromosomes 11 and 16 in the prime compartment at diagnosis that disappeared at relapse, which is also consistent with the expansion of a genetically distinct monocytic subclone. Finally, for comparison, data from Pt-65 also demonstrate the expansion of genetically distinct monocytic clones at relapse, marked by two KRAS mutations. Notably, both KRAS mutations that dominated at relapse were not readily detected at 400x sequencing depth in diagnostic specimens and were only seen using high-resolution methods (droplet digital PCR). Without being bound by theory, these data suggest that even minor monocytic subclones can be selected by the strong selective pressure of VEN+AZA in vivo.

[0214] Additionally, a cohort of 25 AML patients who relapsed after VEN+AZA therapy was subsequently analyzed (Tables 2A and 2B). Nine patients, including five with a monocytic phenotype at diagnosis and four with a primary phenotype, relapsed with monocytic features, accounting for 36% of all cases (Figure 3E).

[0215] Notably, patients who relapsed with monocytic features also had significantly shorter remission durations compared with patients who relapsed with a primary immunophenotype (Figures 3F and 3G), suggesting that patients who already possess m-LSCs may represent a subgroup with a particularly poor prognosis when treated with VEN+AZA therapy. Without being bound by theory, these findings indicate that the presence of m-LSCs in newly diagnosed AML patients represents a distinct disease entity that has not been previously identified, and that these m-LSCs can be used to predict disease pathology that responds to VEN+AZA therapy.

[0216] Example 3 In the following non-limiting example, m-LSC immunophenotypes were identified and characterized in primary AML specimens. Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) analysis was performed, enabling simultaneous protein-based surface antigen measurement and RNA-based transcriptomics analysis at the single-cell level. CITE-seq analysis was performed on a cohort of 27 primary AML specimens, including immunophenotypically defined prime, MMP, and mono AML (listed in Table 3). CITE-seq data were first analyzed using Clustifyr, an application that assigns phenotypes based on comparison with normal human hematopoietic transcriptomics (see Fu et al. F1000Res. 2020;9:223). In this analysis, bone marrow cells were sorted into HSPCs, MPPs, early promyelocytic subclusters, late promyelocytic subclusters, myeloid subclusters, classical monocytic subclusters, and non-classical monocytic subclusters to reveal the spectrum of myeloid development within primary AML specimens. Lineage assignment was strongly supported by the expression patterns of classical lineage-specific markers, such as CD7, CD56, CD19, CD33, CD34, CD11b, and CD123, at both the protein and RNA levels, as well as lineage-specific transcription factors, such as GATA2, CEBPA, SP11 / PU.1, AZU1, TCF7, and PAX5.

[0217] Next, we performed scArches analysis on myeloid subpopulations to identify cell types that represent a myeloid developmental hierarchy (see Zeng et al. Nat Med 2022;28:1212-23 and Lotfollahi et al. Nat Biotechnol 2022;40:121-30). This analysis revealed a diverse mixture of cell types, including leukemia stem and progenitor cells (LSPCs) quiescent, primed, cycling, granulocyte-macrophage progenitor (GMP), promonocyte (ProMono), mono, and conventional dendritic cell (cDC)-like leukemia cells, displaying a clear developmental hierarchy from top left to bottom right in the myeloid subpopulations of the primary AML cohort.

[0218] Next, the entire CITE-seq data was sorted into Prime, MMP, and Mono groups according to immunophenotype. The MMP group was also sorted into Uni-MMP and Multi-MMP subgroups based on their respective functional LSC activity, as measured in xenograft assays (Figure 4A). The relative proportions of each myeloid subcluster within the Prime, Uni-MMP, Multi-MMP, and Mono groups were highly consistent with their predicted identities. The majority of the Prime group exclusively contained the three types of LPSC cells (quiescent, primed, and cycling) that occupy the apex of the myeloid developmental hierarchy. In contrast, the Mono group exhibited a developmental hierarchy in which LSPC cell types were largely absent, but a ProMono-like cell type was predominant, suggesting that the latter may be enriched for m-LSCs. Consistent with this hypothesis, both LSPC and ProMono-like cell types were present in the Multi-MMP group, whereas only the former were present in the Uni-MMP group (Figure 4A).

[0219] To further validate which cell types are enriched for LSC activity, we screened several known LSC signatures using the CITE-seq dataset. The KMT2A-rearranged leukemia-specific LSC signature (KMT2A-r_LSC_signature, Table 4; see Somervailee et al. Cancer Cell 2006;10:257-68; Somervaille et al. Cell Stem Cell 2009;4:129-40; Hess et al. Blood 2006;108:297-304) closely matches the ProMono-like cell type and is specifically present in the Mono- and Multi-MMP groups. Previous studies have shown that KMT2A-rearranged leukemias, unlike other AMLs, are often associated with a monocytic immunophenotype and possess LSC characteristics distinct from conventional CD34+ primary LSCs. Consistently, the CD34+ primary LSC signature (CD34+_LSC_signature, Table 4; Ng et al., Nature 2016;23(540):433-7; Eppert et al. Nat Med 2011;17:1086-93) closely matched the LSPC-primed cluster, but not the ProMono-like cluster, in the CITE-seq dataset, further supporting the notion that ProMono-like cell types are enriched for m-LSC activity. GSEA was also performed to identify genes significantly upregulated in m-LSCs (Table 5). Finally, surface antigen expression analysis revealed that ProMono-like cells were predominantly CD4+, CD14-, CD11b-, and CD36- compared with other myeloid leukemia cells, providing a candidate immunophenotype for m-LSCs (Figure 4B).

[0220] Example 4 In the following non-limiting example, we performed an experiment to functionally validate m-LSCs. This involves a series of flow sorting and transplantation studies to functionally validate the m-LSC immunophenotypes from the CITE-seq analysis. Two monoclonal samples, AML-16 and AML-20, were used. From these samples, various subpopulations of cells were isolated using CD45, CD34, CD4, CD14, CD11b, and CD36 expression (Figures 5A-5B and 8A-8B). To avoid contamination with conventional CD34+ p-LSCs, we gated on the CD34- fraction when validating m-LSCs. As shown in Figures 5D-5E and 8D-8E, functional analysis of each subpopulation demonstrated that the majority of m-LSCs were enriched for the CD34-, CD4+, CD14-, CD11b-, and CD36- immunophenotypes. Furthermore, secondary transplants of animals initially transplanted with m-LSCs (designated population D) also demonstrated robust engraftment, indicative of strong self-renewal capacity.

[0221] Notably, in AML-20, some engraftment potential was detected in the CD14-, CD11b+, and CD36+ control group (Figure 5E), suggesting that the developmental hierarchy of m-LSC-derived AML in certain patients is shallower than in other patients (e.g., AML-16). We also applied a similar approach to verify m-LSCs in multi-MMP patients. AML-07 was functionally defined as a multi-MMP specimen. As shown in Figures 5C, 5F, 8C, and 8F, serial transplantation experiments demonstrated that m-LSCs in this multi-MMP AML were also enriched for CD34-, CD14-, CD11b-, and CD36- immunophenotypes. Note that CD4+ cells were not included in this sorting due to their limited cell numbers. Together, these data reveal an m-LSC immunophenotype applicable to both mono- and multi-MMP AML, which is distinct from the profile previously described for conventional primary LSCs (i.e., CD34+ and CD38-).

[0222] To further investigate the immunophenotype of m-LSCs, analytical flow cytometry was used to assess the expression of several additional cell surface antigens associated with stem cell activity. Both CD117 and CD244 have been shown to be frequently expressed specifically in CD34- AML specimens. However, CD117 expression was not detected in any of the seven specimens that underwent functional evaluation for the presence of m-LSCs. Similarly, CD244 was detected at low levels in only two of the seven specimens. The expression of the monocytic marker CD64 was also investigated, as this antigen has been shown to be commonly found in monocytic relapses. In contrast, CD64 was strongly expressed in six of the seven specimens. Without wishing to be bound by theory, these results indicate that m-LSCs can be further identified using immunophenotypic markers, CD117-, CD244-, and CD64+, in addition to those discussed above.

[0223] Finally, we also assessed the expression of another LSC marker, GPR56. GPR56 mRNA expression was nearly absent in monocytic AML at both bulk and single-cell resolution. Furthermore, flow analysis of GPR56 also showed that its protein expression was high in primary AML cells but completely absent in m-LSC-enriched populations. Without wishing to be bound by theory, these results suggest that m-LSCs can be further identified by their CD117-, CD244-, GPR56-, and CD64+ immunophenotype.

[0224] Example 5 In the following non-limiting example, we conducted an experiment targeting purine metabolism in m-LSCs. m-LSCs promote refractory / relapse responses to venetoclax-based regimens, and to address this, we developed a therapy that selectively targets m-LSCs. Using the above CITE-seq data, several gene expression signatures encompassing pyrimidine and purine metabolism were revealed in the m-LSC compartment. These results were supported by the expression patterns of key enzymes known to regulate one-carbon metabolism (e.g., TYMS and DHFR) that feed into the purine (e.g., HPRT1) and pyrimidine synthesis (e.g., DHODH) pathways. Consistent with the gene expression analysis, metabolic analysis revealed enhanced purine metabolism in flow-sorted m-LSCs compared to non-m-LSCs.

[0225] Next, functional studies were performed to evaluate agents known to affect these pathways.

[0226] Methotrexate (MTX), brequinar (BRQ), and cladribine (CdA) were selected based on their inhibitory activities on the one-carbon metabolic enzymes DHFR and TYMS, the pyrimidine synthetase DHODH, and purine DNA / RNA synthesis, respectively. Colony-forming unit assays were performed on m-LSCs and p-LSCs isolated from mono-, multi-MMP, and primed specimens, as well as on normal CD34+ hematopoietic stem and progenitor cells (HSPCs) from two healthy donors. As shown in Figures 6A and 6B, CdA demonstrated remarkable specificity for m-LSCs while leaving p-LSCs and normal HSPC controls unaffected. This selectivity was not observed with other chemotherapeutic agents, cytarabine and daunorubicin (Figure 6C), suggesting the specific sensitivity of m-LSCs to CdA. Furthermore, CdA also outperformed BRQ and MTX in efficacy against m-LSCs (Figure 6D). Therefore, given its excellent selectivity and widespread clinical use, CdA was selected for in vivo concept studies in combination with VEN+AZA in two functionally validated MMP AMLs. As shown in Figure 6E, multi-MMP AML-13 and AML-07 were transplanted into NSG-S mice and treated in vivo with VEN+AZA alone, CdA alone, or the triple combination therapy. Analysis of AML cells in both bone marrow and spleen demonstrated that the addition of CdA clearly improved the disappearance of tumors that were resistant to VEN+AZA in two PDX models (Figures 6F-H). Notably, flow analysis of remaining transplanted human cells after treatment revealed that the VEN+AZA regimen selectively eliminated the primary subpopulation, whereas the CdA regimen targeted the monocytic subpopulation, and the triple combination regimen eradicated both.

[0227] Summary of Examples 1 to 5 Examples 1-5 describe the identification and characterization of a previously unrecognized type of human acute myeloid leukemia (AML) stem cell, defined as "m-LSC." This particular subclass of LSC is distinguished from more primary subtypes by its unique immunophenotype (CD34-, CD4+, CD14-, CD11b-, and CD36-), a relatively narrow developmental profile restricted to the formation of monocytic progeny cells, and a gene expression profile largely similar to that of normal human promyelocytes. In particular, m-LSC differ from the previously described CD34- LSC population, which predominantly expressed both CD177 and CD244. The molecular biology of m-LSCs differs from more primary LSCs in that they appear to be largely dispensable for BCL-2 dependency, thereby rendering this type of LSC resistant to treatment with venetoclax and azacitidine. Furthermore, m-LSCs demonstrate a selective dependency on one-carbon metabolism and purine / pyrimidine metabolism, further highlighting the importance of cellular metabolism in the pathophysiology and therapeutic resistance of AML.

[0228] In particular, the dependency of m-LSCs on purine metabolism enhances their sensitivity to drugs such as cladribine, a well-known purine analog. As demonstrated herein, the addition of cladribine to the VENCLAX+AZA regimen enhances the eradication of primary AML containing m-LSC activity in both in vitro and in vivo preclinical models. These findings provide important mechanistic insights that may explain the results from several recent clinical trials that reported excellent CR / CRi and MRD-negativity rates when combining venetoclax with chemotherapy regimens, particularly those containing cladribine or its close relative fludarabine, termed FLAG-Ida, CLIA, or Clad-LDAC / AZA. Notably, the inclusion of cladribine in these three trials was primarily based on empirical clinical experience and a long history of using cladribine-containing chemotherapy regimens in the relapsed / refractory stage of AML. As demonstrated herein, the discovery of m-LSCs, their inherent resistance to venetoclax, and their sensitivity to cladribine may explain the efficacy of cladribine / venetoclax-based regimens in eradicating the entire LSC population.

[0229] The results provided herein demonstrate the stratification of primary AML patients based on the properties of underlying LSC subpopulations. Figures 7A-7C show a tree diagram as an analogy to explain the developmental hierarchy of AML, with the underground roots representing LSCs and the aboveground branches symbolizing more differentiated blasts. Figure 7A shows that a single class of more primary LSCs (p-LSCs) may exist in newly diagnosed AML patients with varying degrees of monocytic differentiation potential. In this scenario, m-LSCs are absent, and venetoclax-based therapy is predicted to result in relatively high CR rates and longer remission durations. In contrast, as shown in Figure 7B, some newly diagnosed multi-MMP AML patients have at least two distinct subtypes of LSCs (p-LSCs and m-LSCs) with primary and monocytic characteristics. Depending on the size of the m-LSC population, these patients are clinically predicted to respond, subsequently relapse, or become refractory to venetoclax-based therapy. Finally, in more severe cases, only m-LSCs are present, which are likely to result in disease refractory to venetoclax (Figure 7C). As shown in Figures 9A-9B, patients with the most differentiated monocytic phenotype (i.e., FAB-M5), rather than those with a myelomonocytic phenotype (i.e., FAB-M4), exhibit the highest frequency of refractory disease. Furthermore, patients with relapsed monocytic disease experience significantly shorter remission periods compared to patients who experienced a primary relapse.

[0230] The new model shown in Figures 7A-7C can be used to design future therapies. Detection of any m-LSC population at diagnosis in patients for whom venetoclax-based therapy is being considered may warrant consideration of additional therapeutics designed to selectively target monocyte populations in the hope of avoiding relapse, which has a very poor prognosis in this setting.

[0231] Beyond cladribine (and methotrexate), such potential agents include immunotherapies targeting monocyte antigens such as CD64 and LILRB4, or small molecules that selectively disrupt the unique biological characteristics of phenotypically monocytic AML. For example, MCLI inhibitors appear to be more effective in the context of monocytic AML. The results provided herein demonstrate that m-LSCs depend on MCL1 for energy metabolism. Alternatively, for patients with pure p-LSC disease at diagnosis, no additional treatment other than venetoclax and azacitidine may be appropriate to enable long-term remission. For patients with pure m-LSC disease, other more effective treatment strategies can be considered instead of venetoclax. Future clinical trials designed in this way may help optimize treatment outcomes and prevent overtreatment.

[0232] Disease progression and / or relapse due to m-LSCs is observed in only approximately 30% of AML patients. However, the emergence of drug-resistant disease eventually occurs in the majority of newly diagnosed patients treated with VEN+AZA regimens. This finding strongly suggests that other subclasses of LSCs exist (or can evolve) in patients treated with venetoclax-based regimens. Therefore, additional phenotypes associated with venetoclax-resistant LSCs may exist.

[0233] Without being bound by theory, the results presented herein demonstrate a correlation between disease-inducing mutations, LSC heterogeneity, AML developmental stage, and diverse therapeutic responses in clinical settings. Novel types of venetoclax-resistant m-LSCs can also be found in RAS-mutant monoclonal antibodies (AML-20), KMT2A-rearranged monoclonal antibodies (AML-16), and multi-MMP-containing monoclonal antibodies (AML-07). Taken together, these findings suggest that complex oncogenic mutations likely converge to limited LSC subtypes that can shape the developmental hierarchy of bulk disease and ultimately influence clinical treatment response. This model suggests that understanding LSC heterogeneity is central to improving therapeutic interventions for AML. In addition to AML, malignant stem cell heterogeneity may also influence myeloid pathology. Therefore, the successful development of next-generation precision medicine for AML requires careful analysis of human LSC heterogeneity and the discovery of targeted therapies tailored to each LSC subtype.

[0234] Materials and Methods for Examples 1-5 Primary AML and normal mobilized peripheral blood samples Primary human AML specimens were collected from leukapheresis products, peripheral blood, or bone marrow of AML patients who provided informed consent for sample collection according to the University of Colorado tissue collection protocol (Colorado Multicenter Review Board Protocols #12-0173 and #06-0720). Normal mobilized peripheral blood (MPB) specimens were collected from volunteer donors at the University of Colorado. The age, sex, cytogenetic, and mutation information of the primary AML specimens used in this study are detailed in Table 1C.

[0235] Patients, Treatment and Response This study included 25 newly diagnosed AML patients who received venetoclax plus azacitidine therapy and experienced a relapse response. Patients were diagnosed, treated, and monitored for relapse response between January 2015 and February 2020. The University of Colorado Institutional Review Board approved a request (#19-0115) to retrospectively analyze these patients. Diagnosis and relapse phenotype were determined by morphological review by a hematologist and review of clinical flow records, when available. Remission duration was calculated as the number of days between the date of best response and the date of relapse. Cytogenetic and mutational information for diagnosis and relapse stage, as well as remission duration, are detailed in Table 2.

[0236] Treatment and culture of primary AML and normal CD34+ HSPCs Primary human AML specimens and normal MPB samples were resuspended at approximately 100–200 e6 cells / ml in freezing medium consisting of 50% FBS (GE Healthcare), 10% DMSO (Sigma), and 40% IMDM medium (GIBCO) and then cryopreserved in liquid nitrogen. Cells were thawed in a 37°C water bath and washed twice with thawing medium consisting of IMDM (GIBCO), 2.5% FBS (GE Healthcare), and 10 μg / ml DNase (Sigma). Normal CD34+ HSPCs were enriched from thawed MPB samples using a CD34 MicroBead kit (Miltenyi Biotec). Cells were cultured in complete serum-free medium (SFM) at 37°C in a 5% CO2 incubator. SFM consisted of IMDM (GIBCO), 20% BIT 9500 (STEMCELL Technologies), 10 μg / ml LDL (low-density lipoprotein, Millipore), 55 μM 2-mercaptoethanol (GIBCO), and 1% Pen / Strep (GIBCO). Complete SFM was generated by supplementing SFM with FLT-3, IL-3, and SCF cytokines (PeproTech) at 10 ng / ml each.

[0237] Colony formation assay Freshly sorted m-LSCs from primary AMI or CD34+ HSPCs isolated from normal mobilized peripheral blood samples were seeded onto human methylcellulose (R&D Systems) at approximately 100K / ml and 2K / ml, respectively. Small molecule inhibitors were added directly to the methylcellulose at the desired final concentration at the time of seeding. Colonies were counted 2–3 weeks after initial seeding.

[0238] Immunophenotypic analysis of primary AML Approximately 0.5–1e6 freshly thawed primary AML cells were stained with an immunophenotyping panel including antibodies against human CD45, CD34, CD117, CD11b, CD64, CD14, CD244, LILRRB4, CD36, or CD68 for 15 min at 4°C, washed with ice-cold FACS buffer, then resuspended in FACS buffer and analyzed on a BD FACS Celesta flow cytometer (BD). FACS files were analyzed with Flowjo 10.5.3 (Flowjo).

[0239] Flow sorting of primed and mono-subpopulations for xenotransplantation studies Freshly thawed primary AML cells were stained with a viability dye and antibodies against human CD45 or CD34 and CD11b. For all specimens except Pt-69, the prime subpopulation was sorted as CD45-intermediate and SSC-intermediate, while the mono subpopulation was sorted as CD45-bright and SSC-intermediate / high. For Pt-69, the prime and mono subpopulations could not be easily separated using a CD45 / SSC gating strategy. An alternative CD34 / CD11b gating strategy was used. From the CD34 / CD11b gate, two prime subpopulations were revealed from the diagnostic (Dx) specimen: one showing a CD34+ / CD11b- phenotype (Dx-plasm-A) and the other showing a CD34+ / CD11b+ phenotype (Dx-plasm-B). One mono subpopulation, designated Dx-mono, exhibiting a CD34- / CD11b- partially positive (PP) phenotype was also identified from the diagnostic (Dx) specimen. In contrast, at relapse (RI), a single mono subpopulation, designated R1-mono, exhibiting a CD34- / CD11b-PP phenotype was identified. All subpopulations were sorted and used in xenotransplantation studies.

[0240] xenograft research In this study, NSG-S (NOD.Cg-Prkdcscid I12rgtmlWjlTg(CMV-IL3, CSF2, KITLG)1Eav / MloySzJ) mice (The Jackson Laboratory) were used for xenotransplantation studies. Experiments were initiated using male or female mice ranging from 6 to 8 weeks of age. Littermates of the same sex were randomly assigned to experimental groups. NSG-S mice were pretreated with 30 mg / kg busulfan (Alfa Aesar) via intraperitoneal (IP) injection 24 h before transplantation. Busulfan stock was freshly prepared at 25 mg / ml in 100% DMSO. The stock was then diluted 1:10 with prewarmed saline (0.9% NaCl) to 2.5 mg / ml immediately before use. To prevent busulfan precipitation due to its low solubility, the diluted busulfan solution was stored in a 37°C water bath before IP injection. To compare the engraftment potential of different subpopulations of primary AML, each subpopulation was sorted according to the percentage of total viable cells (detailed in Table 6). When the cell dose was less than 0.5e6 / mouse, mononuclear cells isolated from the bone marrow and spleen of untreated NSG-S mice were used as carrier cells. Sorted cells, with or without carrier cells, were then washed, pelleted, and resuspended in saline buffer, allowing for tail vein injection into NSG-S mice at 0.1 ml per mouse. To prevent the development of graft-versus-host disease, in vivo anti-human CD3 antibody (BioCell) was added at a final concentration of 1 μg / e6 cells 15 minutes before injection. During all experiments, mice weighed approximately 20–30 grams, and no animals lost more than 10% of their body weight. Mice were housed in ventilated cages, and in vivo treatments were performed, if necessary, in the University of Colorado animal care room. The majority of experiments lasted 6–12 weeks. At the end of the experiment, mice were euthanized using carbon dioxide. Bone marrow and spleens were harvested and subjected to red blood cell lysis, and mononuclear cells were stained with human CD45, mouse CD45 antibody, and DAPI to determine engraftment rates within surviving cells. All animal experiments were performed in accordance with Institutional Animal Care and Use Committee protocol number 00308.

[0241] In vivo treatment Approximately 2–4 weeks after the initial transplant, tumor burden in the bone marrow was determined to be greater than 5% in the sentinel mice. The mice were then treated with various in vivo regimens: venetoclax (100 mg / kg, orally administered 5 days a week for 2 weeks); azacitidine (3 mg / kg, intraperitoneally administered 3 days a week for 2 weeks); and cladribine (10 mg / kg, intraperitoneally administered 3 days a week for 2 weeks). All treatments were administered simultaneously within the same 2-week time window.

[0242] CITE-seq sample preparation and library construction Mononuclear cell suspensions were prepared from freshly thawed primary AML specimens cryopreserved in liquid nitrogen. For each specimen, approximately 1–2e6 mononuclear cell suspensions were stained with total seq B antibody (1 μg / cell, Biolegend) and fluorescently labeled flow antibodies against CD45 (BD Biosciences), CD235a (BD Biosciences), and DAPI. Cells were stained in staining buffer (PBS + 2% FBS) for 20 minutes at 4°C. Viable cells and red blood cell-free cells were obtained by sorting DAPI- / CD235a- cells on a BD Biosciences ARIA II cell sorter. After sorting, cells were washed twice with staining buffer, resuspended at 1000 cells / μl in PBS with 2% FBS, and immediately used for capture. After cell collection and counting, cells were processed using the 10x Genomics 3' Dual Index v3.1 Library Kit with cell surface protein feature barcoding technology. Briefly, 10,000 cells were targeted from a stock suspension of 1,000 cells / μl. Cells were processed according to the protocol to generate a 3' gene expression library and a Feature Barcode cell surface library. Both libraries were double-indexed, and samples were quantified using Qubit (Life Technologies) and assessed for size and quality using Tapestation (Agilent). Libraries were normalized and pooled for sequencing on a Novaseq 6000 (Illumina) for paired-end 2x150bp sequencing. The target read depth for the gene expression library was 100,000 reads / cell, or approximately 500 million paired-end reads / library. The target read depth for the cell surface library was 40,000 reads / cell, or 200 million paired-end reads / library.

[0243] CITE-seq data preprocessing Raw sequencing data for gene expression, antibody-derived tags (ADTs, surface proteins), and hashed libraries were processed using STARsolo 2.7.8a with the 10X Genomics GRCh38 / GENCODE v32 genome and transcriptome reference (version GRCh38_2020A) or TotalSeq barcode reference, as appropriate. Hashed samples were demultiplexed using GMM-Demux. Cell-containing droplets were then identified using dropkick 1.2.6 (using manual thresholding if automatic thresholding failed), ambient RNA was removed using DecontX 1.12 (www.github.com / campbio / celda), cells estimated to contain >50% ambient RNA were removed, and doublets were identified and removed using DoubletFinder 2.0.3. The remaining cells were then filtered to retain only cells with >200 genes, 500–80,000 UMIs, less than 10–20% UMIs from genes encoded by the mitochondrial genome (sample-dependent based on UMI distribution), less than 5% UMIs from HBB, less than 20,000 UMIs from antibody-derived tags (ADTs), and >100–2,750 UMIs from antibody-derived tags (sample-dependent based on UMI distribution). The filtered cells were modeled in a latent space using TotalVI 0.18.0 to create a joint embedding derived from both RNA and ADT expression data, correcting for batch effects, mitochondrial fraction, and cell cycle. Scanpy 1.8.2 was used to cluster the data in the latent space using the Leiden algorithm, and marker genes were identified in the latent space using TotalVI.

[0244] CITE-seq data analysis Clusters were annotated using clustifyr 1.9.1 and the leukemia / normal bone marrow reference dataset (see Triana et al. Nat Immunol 2021;22:1577-89). Scanpy and Seurat 4.1.1 (ref. 58; RRID: SCR_007322) were then used to generate uniform manifold approximations and projections from the TotalVI embeddings and perform exploratory analysis, data visualization, etc. Myeloid subpopulations in the CITE-seq data were re-annotated using scArches 0.5.7 and the leukemia reference dataset (see Zeng et al. Nat Med 2022;28:1212-23). ​​The reference model was trained for 400 epochs based on the 3,000 most variable genes determined by scanpy's pp.highly_variable_genes() function. The model was then updated using the transfer learning of the scArches algorithm to annotate the query myeloid subpopulations. CD34+_LSCs and KMT2A-r_LSCs were identified by scoring each individual cell using the AddModuleScore() function in Seurat software and custom-generated candidate CD34+ LSC and KMT2A-r_LSC gene expression signatures, as described in the text.

[0245] WES analysis WES libraries were generated using the Agilent SureSelect XT Exome Preparation Kit (Agilent) with 200 ng input, following the protocol. The probes used were SureSelect XT Human All Exon V7 (Agilent). Libraries were normalized using Qubit (Invitrogen) and Tapestation (Agilent), and 2 × 150 bp reads were sequenced on a Novaseq 6000 (Illumina) to obtain 400x coverage. Overall sequencing quality was assessed using Fastqc v0.11.9, and reads were trimmed using cutadapt (cutadapt, RRID:SCR_011841) v2.9 to remove Illumina universal adapters, low-quality bases (phred < 30), and any reads with a minimum read length of less than 10 base pairs. The trimmed fastq files were then aligned to the GRCh38 p.13 genome using BWA v0.7.17 (BWA, RRID: SCR_010910). Strict quality control of the alignment and removal of duplicate reads were performed using Picard suite of tools v2.21.1 (Picard, RRID: SCR_006525) and samtools v1.8 (samtools, RRID: SCR_002105). Variants in the alignment were called using DeepVariant v1.0.0, followed by filtering of low-quality variants using BCFtools (BCFtools, RRID: SCR_005227) v1.11. SNPs were removed if the unfiltered raw read depth was less than 20 reads and the mapping quality was less than 30. All remaining variants were then annotated using Annovar v2020-06-07 (Annovar, RRID:SCR_012821).Of all the databases used for annotation, the most notable databases used for data interpretation were COSMIC database v92 (COSMIC, RRID: SCR_002260), Clinvar v2020031 (Clinvar, RRID: SCR_006169), SIFT (SIFT, RRID: SCR_012813), PolyPhen (PolyPhen, RRID: SCR_013189), and nci60. To compare the mutational profiles between primed and mono-cells, we focused on nonsynonymous exonic mutations that occurred in 49 commonly mutated genes in AML.

[0246] Metabolomic analysis For each mono-AML specimen, five replicates of 500,000 cells were freshly sorted from the m-LSC-enriched D subpopulation (CD34-, CD4+, CD14-, CD11b-, CD36-m-LSC) and non-m-LSC subpopulation (CD34-, CD4+, CD'4-, CD11b+, CD36+ non-m-LSC). Sorted cells were washed with ice-cold PBS, and cell pellets were snap-frozen for ultra-performance liquid chromatography-mass spectrometry analysis as previously described (32). Results were normalized by cell number. Pathway enrichment analysis was performed for metabolites that were ≥1.2-fold higher in population D compared to population E with a P value <0.1. All analyses were performed using MetaboAnalyst 5.0 software (MetaboAnalyst, RRID:SCR_015539).

[0247] statistical analysis Statistical analyses were performed in GraphPad Prism 9.3.1 (GraphPadPrism, RRID:SCR_002798). Median ± interquartile range was used to describe summary statistics. When applicable, a one- or two-sided Mann-Whitney test was used to compare two groups. The Kruskal-Wallis test with correction for multiple comparisons using the original FDR method of Benjamini and Hochberg was used to compare three or more groups. The exact statistical analysis method is described in the figure legends.

[0248] Example 6 In the following non-limiting example, CD70 expression in m-LSCs was analyzed by flow cytometry and correlated with resistance to treatment with a combination of venetoclax and azacitidine.

[0249] Briefly, cells from 14 AML samples were analyzed by flow cytometry to identify m-LSCs based on their CD34-, CD4+, CD11b-, CD14-, and CD36 immunophenotypes, as well as for expression of CD70. Figure 10A shows the percentage of total blast cells in each AML sample that were CD70+ (left side of graph), as well as the percentage of m-LSCs in each AML sample that were CD70+ (right side of graph). The results shown in Figure 10A demonstrate that CD70 is expressed on m-LSCs, with some samples showing more than 50% of m-LSCs being CD70-positive.

[0250] Next, the results of the analysis shown in Figure 10A were further analyzed based on whether the AML samples were obtained from patients who were sensitive to treatment with the combination of venetoclax and azacitidine or from patients who were resistant to treatment with the combination of venetoclax and azacitidine. Figure 10B shows the percentage of total blast cells and m-LSCs that were CD70+ in AML samples from Ven+Aza-resistant and Ven+Aza-sensitive samples. As shown in Figure 10B, patients who were sensitive to Ven+Aza treatment had a lower percentage of m-LSCs that were CD70+ compared to patients who were resistant to Ven+Aza. That is, the m-LSC population of Ven+Aza-resistant patients had a higher percentage of cells that were CD70+. Without being bound by theory, these results indicate that patients with higher levels of CD70+ m-LSCs may be more resistant to treatment with Ven+Aza and, therefore, may benefit from alternative therapies, including those incorporating the use of CD70-targeting agents. Furthermore, these results indicate that determining the number of CD70+ m-LSCs (i.e., CD34-, CD4+, CD11b-, CD14-, CD36-, and CD70+ cells) in biological samples collected from patients can predict their response to treatment with the combination of venetoclax and azacitidine. [Table 1C-1] [Table 1C-2] [Table 2A] [Table 2B-1] [Table 2B-2] [Table 2B-3] Table 3 Table 4-1 Table 4-2 Table 4-3 Table 5-1 Table 5-2 Table 5-3 Table 6-1 Table 6-2

Claims

1. 1. A method of treating acute myeloid leukemia (AML) in a subject, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 on a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step a), wherein a cell is identified as m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) if at least one m-LSC is identified, administering to said subject a combination of at least one BCL-2 inhibitor, at least one hypomethylating agent, and at least one m-LSC targeting agent; or If no m-LSC is identified, administering to said subject a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

2. 1. A method for identifying whether a subject having AML will respond to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, and CD36 on a plurality of cells in a sample from the subject; b) identifying the presence of at least one monocytic leukemia stem cell (m-LSC) based on the expression measured in step a), wherein a cell is identified as m-LSC if it is at least CD34-, CD4+, CD11b-, CD14-, and CD36-; c) identifying the subject as non-responsive to the treatment if the presence of at least one m-LSC is identified; or and if no m-LSC is identified, identifying the subject as responsive to the treatment.

3. step (a) further comprises measuring the expression of at least CD117, CD244, CD64, and GPR56; 3. The method of claim 1 or claim 2, wherein the cells are identified as m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+ and GPR56-.

4. 1. A method of treating acute myeloid leukemia (AML) in a subject, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 on a plurality of cells in a sample from the subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34−, CD4+, CD11b−, CD14−, CD36−, and CD70+; and c) if at least one CD70+ m-LSC is identified, administering to the subject a treatment comprising at least one CD70 targeting agent, preferably wherein the treatment further comprises at least one BCL-2 inhibitor and at least one hypomethylating agent.

5. 1. A method for identifying whether a subject with AML will respond to treatment with a CD70-targeting agent, comprising: a) measuring the expression of at least CD34, CD4, CD11b, CD14, CD36, and CD70 on a plurality of cells in a sample from the subject; b) identifying the presence of at least one CD70+ monocytic leukemia stem cell (m-LSC) based on the expression measured in step (a), wherein a cell is identified as a CD70+ m-LSC if it is at least CD34−, CD4+, CD11b−, CD14−, CD36−, and CD70+; c) identifying the subject as responding to the treatment if the presence of at least one CD70+ m-LSC is identified.

6. step (a) further comprises measuring the expression of at least CD117, CD244, CD64 and GPR56; 6. The method of claim 4 or claim 5, wherein the cells are identified as CD70+ m-LSCs if they are at least CD34-, CD4+, CD11b-, CD14-, CD36-, CD117-, CD244-, CD64+, GPR56-, and CD70+.

7. the at least one CD70 targeting agent i) an anti-CD70 antibody, preferably wherein said anti-CD70 antibody is cusatuzumab; ii) anti-CD70 immunotherapy, preferably comprising CAR-T cells and / or NK cells that specifically target CD70; or iii) A method according to any one of claims 1 to 6, wherein the agent inhibits CD70 signaling, preferably the agent inhibiting CD70 signaling prevents binding of CD27 to CD70.

8. 8. The method of any one of claims 1 to 7, wherein the at least one m-LSC targeting agent is an agent that modulates one-carbon metabolism, an agent that modulates purine synthesis, an agent that modulates pyrimidine synthesis, or any combination thereof.

9. The method of any one of claims 1 to 8, wherein the at least one m-LSC targeting agent is selected from methotrexate, brequinar, and cladribine.

10. The method according to any one of claims 1 to 9, wherein the at least one hypomethylating agent is selected from azacitidine and decitabine.

11. 11. The method of any one of claims 1 to 10, wherein the at least one BCL-2 inhibitor is selected from venetoclax and navitoclax.

12. 12. The method of any one of claims 1 to 11, wherein step (a) comprises performing PCR, high-throughput sequencing, next-generation sequencing, Northern blot, reverse transcription PCR (RT-PCR), real-time PCR (qPCR), quantitative PCR, qRT-PCR, flow cytometry, mass spectrometry, microarray analysis, digital droplet PCR, Western blot, transcriptomics and cellular indexing of epitopes by sequencing (CITE-SEQ), or any combination thereof.

13. The method of any one of claims 1 to 12, wherein the subject has AML and has not received any treatment for AML.

14. The method of any one of claims 1 to 13, wherein the subject has AML and has previously received at least one AML treatment.

15. 11. The method of claim 10, wherein the at least one AML treatment comprises a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

16. 16. The method of any one of claims 1 to 15, wherein identifying the subject as responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as having a long-term remission after receiving said treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

17. 17. The method of any one of claims 1 to 16, wherein identifying the subject as non-responsive to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent comprises identifying the subject as refractory to treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent and / or the subject as relapsing after treatment with a combination of at least one BCL-2 inhibitor and at least one hypomethylating agent.

18. 18. The method of any one of claims 1 to 17, wherein the biological sample comprises blood, a bone marrow biopsy, a bone marrow aspirate, a chloroma biopsy, a tissue biopsy, cerebrospinal fluid, or any combination thereof.

19. 19. The method of claim 18, wherein the sample is a bone marrow biopsy.

20. 19. The method of claim 18, wherein the sample is a bone marrow aspirate.

21. 19. The method of claim 18, wherein the sample is a chloroma biopsy.

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