Patient selection for immune cell therapy

Abstract

The present disclosure relates to methods for selecting patients affected with cancer for treatment with a modified immune cell by obtaining a sample and detecting if the cells express one or more diagnostic transcriptional programs. The disclosure also relates to kits for detecting if the cell expresses one or more diagnostic transcriptional programs.

Description

[0001] PATIENT SELECTION FOR IMMUNE CELL THERAPY

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of and priority to U.S. application number 63 / 582,711 filed on September 14, 2023, the entire contents of which are hereby incorporated by reference in their entireties for all purposes.

[0004] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0005] This invention was made with Government support under contract CA245468 awarded by the National Institutes of Health. The Government has certain rights in the invention.

[0006] BACKGROUND

[0007] Acute myeloid leukemia (AML) affects about 20,000 new patients annually in the United States. Adult AML and pediatric AML have only about 30% and about 70% overall survival (OS), respectively. Currently, the standard-of-care treatment for AML relies on aggressive chemotherapy and when feasible, allogeneic hematopoietic stem cell transplantation (allo-HSCT). Allo-HSCT is not tolerated by most older adults with AML, and often results in graft-versus-host disease (GvHD), which requires long-term immunosuppression. Recently, targeted therapies for pediatric AMI have been making progress, but AML heterogeneity complicates the development of targeted therapeutics. Hence, there is a strong unmet medical need for new curative therapies for AML.

[0008] CD8+ T cells have potent cytotoxic activity and are considered critical for tumor control, but AML can cause CD8+ T cell dysfunction. While CD8+ T cells recognize AML antigens via HLA Class I, relapse in up to 40% of AML patients is driven by the loss of HLA Class II expression on AML cells. Expression of HLA Class II is needed for the presentation of AML antigens to CD4+ T cells. Antigen-activated CD4+ T cells secrete interleukin-2 (IL- 2), interferon-gamma (IFN-y), and tumor necrosis factor-alpha (TNF-a) that can activate CD8+ T cells, helping them to kill tumor cells. Further, IFN-y secreted by CD4+ T cells can restore HLA class II expression on AML. Finally, CD4+ T cells can also acquire cytotoxic features themselves and kill the tumor cells directly. Thus, CD4+ T cells have an important role in the immune response to AML cells. Yet, the interaction between AML cells and CD4+ T cells, and its effect on AML patient survival, remains poorly understood. There therefore remains a need to understand these interactions and to identify patients with tumors that are more susceptible to immune cell therapies.

[0009] SUMMARY

[0010] In an aspect, provided herein is a method for selecting a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of a) obtaining a sample comprising diseased cells from a patient; b) detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4, wherein each of Pl, P2, P3, and P4 comprises differential overexpression of one or more associated genes listed in Table 2; c) by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient as suitable for treatment comprising administration of a modified immune cell; and d) administering a modified immune cell to said patient.

[0011] In another aspect, provided herein is a method for treating a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of 1) obtaining a sample comprising diseased cells from a patient; b) detecting if the diseased cells express one or more diagnostic transcription programs selected from the group consisting Pl, P2, P3, and P4; wherein each of Pl, P2, P3, and P4 comprises differential over-expression of one or more associated genes listed in Table 2; c) by the transcriptional programs found to be overexpressed in the diseased cells of the sample, selected a patient having a diseased cell overexpressing one or more of the genes in step b) as suitable for treatment comprising a modified immune cell; and d) administering a modified immune cell to said patient.

[0012] In some embodiments, the cells express Transcriptional Program Pl and wherein the patient is deemed suitable for treatment comprising administration of a modified immune cell.

[0013] In some embodiments, the cells do not express Transcriptional Program P3 and / or P4 and wherein the patient is deemed suitable for treatment comprising administration of a modified immune cell.

[0014] In some embodiments, Transcriptional Program Pl is assessed by overexpression of one or more genes selected from the group consisting of S100A9, LYZ, S100A8, CCL3, IL1B, S100A6, FCER1G, CTSS, IF130, and CXCL8.

[0015] In some embodiments, Transcriptional Program Pl is assessed by overexpression of one or more surface marker genes selected from the group consisting of CD68, TREM1, GPR183, PLAUR, EVI2B, FCGRT, EMP3, TNFRSF1B, ITGB2, MS4A6A, CYBB, CD83, CLEC7A, ITGAX, EMP1, CD44, IL10RA, MPEG1, APLP2, and CD14.

[0016] In some embodiments, Transcriptional Program P3 is assessed by differential expression of one or more genes selected from the group consisting of PRSS57, HSP90AB1, RAC2, NME2, CD52, CDK6, GATA2, EEF1B2, SERPINB1, and APRT.

[0017] In some embodiments, Transcriptional Program P3 is assessed by differential expression or one or more surface marker genes selected from the group consisting of CD52, SPN, CD69, GYPC, LY6E, CD63, CD34, RNF130, CD96, ITGA4, BST2, HLA-DRB1, TM7SF3, HLA-DMA, ITM2B, ATP6V0A2, CD47, IL2RG, CD82, and TMEM219.

[0018] In some embodiments, Transcriptional Program P4 is assessed by differential expression of one or more genes selected from the group consisting of CCL19, CXCL9, TNFAIP2, LAMP3, IDO1, CDKN1A, MARCKSL1, LSP1, EBB, and PPA1.

[0019] In some embodiments, Transcriptional Program P4 is assessed by differential expression of one or more cell surface marker genes selected from the group consisting of LAMP3, CCR7, CD40, HLA-DPA1, HLA-DPB1, HLA-DQB1, CD74, SLAMF7, HLA-DRA, HLA-DQA1 , VCAM1, IL2RA, ANTXR2, SLAMF1, HLA-DMB, ADAM28, AREG, PTGER4, LY75, and SLC38A1.

[0020] In some embodiments, the method is in vitro or ex vivo.

[0021] In some embodiments, the diseased cell is a cancer cell. In some embodiments, the cancer is a hematological cancer. In some embodiments, the hematological cancer is a lymphoma, myeloma, or leukemia.

[0022] In some embodiments, the hematological cancer is acute myeloid leukemia (AML), chronic myeloid leukemia (CML), acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), Hodgkin’s lymphoma, non-Hodgkin’s lymphoma, or multiple myeloma (MM).

[0023] In some embodiments, the hematological cancer is adult AML or pediatric AML.

[0024] In some embodiments, the diseased cells differentially express two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more of the genes of a selected transcriptional program, the cells are determined to express that transcriptional program.

[0025] In some embodiments, the gene expression is assayed using a polymerase chain reaction (PCR)-based assay. In some embodiments, the PCR-based assay is selected from PCR, real- time PCR, reverse-transcriptase PCR, single-cell PCR (scPCR), digital PCR, or multiplex PCR. In some embodiments, the modified immune cell is autologous. In some embodiments, the modified immune cell is allogeneic.

[0026] In an aspect, provided herein is a kit for detecting if a diseased cell expresses one or more diagnostic transcriptional programs selected from the group consisting of Transcriptional Program Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential expression of one or more associated genes listed in Table 2, comprising components for performing quantification of the selected genes from the selected Transcriptional Programs.

[0027] In some embodiments, the kit comprises primers for the amplification and quantification of expression products of the selected genes.

[0028] In some embodiments, the kit comprises primers targeting the genes, primers targeting the mRNA, primers targeting the cDNA, a probe targeting the cDNA, a probe targeting the mRNA, a probe targeting the DNA, an antibody specific to the protein products of the genes, or a combination thereof.

[0029] In some embodiments, the kit comprises two or more antigen binding compositions configured for quantification, wherein the antigen-binding compositions selectively bind to cell surface markers of a gene from a Transcriptions Program selected from Table 1.

[0030] In an aspect, provided herein is a method for selecting a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of: a. obtaining a sample comprising diseased cells from a patient; b. detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential overexpression of one or more associated genes listed in Table 1; and c. by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient as suitable for treatment comprising administration of a modified immune cell.

[0031] In some embodiments, the patient is administered the modified immune cell.

[0032] BRIEF DESCRIPTION OF THE DRAWINGS

[0033] FIG 1. is a graph depicting the elimination efficiency (%) of AML patient cells when co-cultured with CD4IL10cells. Samples PATISD and PAPZCL were resistant to killing by the CD4IL10cells.

[0034] FIG. 2A and FIG. 2B and 2C illustrate gene expression of surface proteins by CD4IL10cells. FIG. 3 depicts the single-cell RNA-seq assay experimental set up where samples are collected at 0 hr (before co-culture) and at 24 hr after co-culture of AML cells with CD4IL10cells.

[0035] FIG. 4A and FIG. 4B illustrate the differences in culturing of resistant AML patient cells or cell lines with or without CD4IL10cells or culturing with AML patient cells or cell lines that are sensitive to killing by CD4IL10cells after three days.

[0036] FIG. 5 illustrates the pre-sort and post-sort samples depicting one resistant or one sensitive AML cells co-cultured with CD4IL10cells after 24 hours.

[0037] FIG. 6 depicts single-cell RNA (scRNA)-seq data of AML cells and CD4IL10cells. The results show that the CD4IL10cells derived from healthy patients demonstrate less heterogeneity than those derived from AML patients.

[0038] FIG. 7 illustrates a two-tiered approach to the analysis to resolve the heterogeneity of AML samples.

[0039] FIG. 8A-FIG. 8D illustrate the analysis and clustering of AML single cells within each patient at each timepoint (FIG. 8A). The calculated average transcriptomes per cluster were averaged, revealing five different transcriptional programs shared across all patients and timepoints (FIG. 8B and FIG. 8C). One of the programs was low quality (FIG. 8D) and was removed from further analysis.

[0040] FIG. 9A and FIG. 9B illustrate the remaining four programs, revealing transcriptional heterogeneity among AML samples.

[0041] FIG. 10 depicts the top genes encoding surface proteins found in each transcriptional program.

[0042] FIG. 11 depicts the relative differentiation stage of AML cells in transcriptional programs P1-P4. Cells that survived 24 hours in co-culture, irrespective of the program, displayed a less differentiated transcriptional signature.

[0043] FIG. 12 is a graph illustrating representation of AML programs over a 24 hour period, with time points at time 0 hr and at 24 hr. Program P 1 was present in sensitive AML samples initially, but disappeared after 24 hours of co-culture with CD4IL10cells, while the majority of cells were in program P3 and remained so throughout. AML cells expressing program P4 increased after co-culture.

[0044] FIG. 13 demonstrates elimination efficiency within each transcriptional program. The abundance of the AML program P 1 positively correlated with killing, while the abundance of programs P3 and P4 showed a significant negative correlation with killing. FIG. 14A-FIG. 14C illustrates scoring of the abundance of AML programs P1-P4 in cell lines derived from patients with leukemias and lymphomas, using the Cancer Cell Line Encyclopedia RNA-seq dataset.

[0045] FIG. 15A and FIG. 15B depicts the evaluation of the association of AML transcriptional programs with the FAB classification, the WHO classification, and risk groups in a large cohort of pediatric AML samples from the National Cancer Institute (NCI) TARGET RNA-seq dataset.

[0046] FIG. 16A and FIG. 16B illustrates the association of AML transcriptional programs with patient survival.

[0047] FIG. 17 depicts analysis of differential expression of various genes in CD4IL10cells that were co-cultured with sensitive or resistant AML cells. CD4IL10cells co-cultured with resistant AML upregulated few T cell activation-related genes whereas co-culture with sensitive AML upregulated more genes related to T cell activation and anti-tumor response.

[0048] FIG. 18A and FIG. 18B illustrates gene set enrichment analysis and demonstrates that CD4IL10cells co-cultured with sensitive AML cells have a transcriptional signature of activated memory CD+ T cells, while CD4IL10cells co-cultured with resistant AML cells have a signature of resting memory CD4+ T cells.

[0049] FIG. 19 illustrates the top interacting pairs in the sensitivity-associated transcriptional program Pl and CD4IL10cells cultured with sensitive AML cells.

[0050] FIG. 20A and FIG. 20B demonstrate the top interacting pairs on AML cells and CD4IL10associated with programs P3 and P4.

[0051] FIG. 21A and FIG. 21B illustrates elimination efficiency of sensitive AML cell line U937 after knocking out top surface genes associated with Pl that have binding partners on the CD4IL10cells (FIG. 21A). Only the knockout of ICAM1 in U937 causes a resistance to killing, comparable to that of resistant cell line K562. FIG. 2 IB demonstrates the efficiency of knock out of TNFRSF1B, CD18, IFNGR1, and ICAM1 in U937 cells.

[0052] FIG. 22A and FIG. 22B demonstrates that CD4IL10cells constitutively express high levels of CD 18 and CD1 la, and therefore were not further upregulated in CD4IIJ 0cells interacting with killing-sensitive AML cells.

[0053] FIG. 23A and FIG. 23B illustrates that CD8+ T cell degranulation against ICAM1 knockout U937 and elimination of U937-ICAMl-kncokout cells by CD8+ T cells is significantly decreased compared to WT U937.

[0054] FIG. 24 demonstrates that CD8+ T cells did not degranulate and kill resistant K562 cells and degranulated upon stimulation with PMA and ionomycin (used as positive control). FIG. 25A and FIG. 25B illustrates elimination efficiency of AML cells by CD4IL10cells in the presence of inhibitors of LFA-1 or ICAM1 / LFA-1 interaction.

[0055] FIG. 26A and FIG. 26B demonstrates that only killing-sensitive AML cells potently induce primary CD 8+ T cell activation when compared to resistant AML cells.

[0056] FIG. 27 demonstrates the positive correlation between the degree of CD8+ T cell activation and AML cell killing.

[0057] DETAILED DESCRIPTION

[0058] Since primary human cytotoxic CD4+ T cells are rare, comprising on average 2.2% of the CD4+ T cell compartment in healthy donors, the AML-CD4+ T cell interaction using engineered human cytotoxic CD4+ T cells called CD4IL10was studied. CD4IL10cells are generated by lentiviral overexpression of the human IL 10 gene in healthy donor CD4+ T cells (Jacobsohn et al. 2018. Biol Blood Marrow Transplant 24, 2040-2046. 10.1016 / j.bbmt.2018.06.010). Constitutive expression of IL-10 in CD4+ T cells has dual benefits: it can re-invigorate exhausted T cells, and induces cytotoxic phenotype and functions. Indeed, CD4IL10cells kill AML cell lines and primary AML patient samples in vitro via perforin and granzyme B and inhibit leukemia progression in vivo. Notably, CD4IL10cells kill AML cells in an antigen-independent manner, likely due to tonically active T cell receptor (TCR) after in vitro expansion, bypassing the dependence on the very rare AML antigen-specific T cells to study their interaction with AML cells.

[0059] While most primary adult and pediatric AML cells are killed by CD4IL10cells, some are resistant to killing. CD200 glycoprotein on resistant AML impairs the release cytotoxic granules from CD4IL10cells, and others have described the same effect on CD8+ T cells (Coles et al. 2012. Leukemia 26, 2148-2151. 10.1038 / leu.2012.77) and NK cells. However, the inhibitory effect of CD200 on T cells was only partial, and not sufficient to completely explain the AML resistance to T cell killing. To better understand the determinants of AML sensitivity or resistance to T cell killing, killing-sensitive and -resistant primary AML samples before and after co-culture with CD4IL10cells was analyzed using single-cell RNA sequencing (scRNA- seq). AML transcriptional programs associated with sensitivity or resistance to CD4IL10killing were identified, showing that resistance-related programs are found in less differentiated, stem cell-like AML cells, and in patients with poor survival rates. It was also revealed that killing- sensitive, but not killing-resistant AML, successfully activate CD4IL10cells. AML expression of ICAM1, which is required for the immune synapse formation with T cells, is necessary for AML killing by both CD4IL10cells and primary, ex vivo-isolated CD8+ T cells. These results emphasize the role of T cell response to AML in AML patient survival and identify ICAM1 as one of the immune triggers necessary for AML killing by T cells.

[0060] Accordingly, this disclosure provides methods and kits for selecting a patient affected with a hematological disease or disorder with a modified immune cell comprising obtaining a sample comprising diseased cells from a patient and detecting if said diseased cells express one or more diagnostic transcriptional program as described herein.

[0061] It is to be understood that the methods described in this disclosure are not limited to particular methods and experimental conditions disclosed herein as such methods and conditions may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0062] Furthermore, the experiments described herein, unless otherwise indicated, use conventional molecular and cellular biological and immunological techniques within the skill of the art. Such techniques are well known to the skilled worker and are explained fully in the literature. See, e.g., Ausubel, et al., ed., Current Protocols in Molecular Biology, John Wiley & Sons, Inc., NY, N.Y. (1987-2008), including all supplements, Molecular Cloning: A Laboratory Manual (Fourth Edition) by MR Green and J. Sambrook and Harlow et al., Antibodies: A Laboratory Manual, Chapter 14, Cold Spring Harbor Laboratory, Cold Spring Harbor (2013, 2nd edition).

[0063] Unless otherwise defined, scientific and technical terms used herein have the meanings that are commonly understood by those of ordinary skill in the art. In the event of any latent ambiguity, definitions provided herein take precedent over any dictionary or extrinsic definition. Unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. The use of “or” means “and / or” unless stated otherwise. The use of the term “including,” as well as other forms, such as “includes” and “included,” is not limiting.

[0064] Generally, nomenclature used in connection with cell and tissue culture, molecular biology, immunology, microbiology, genetics and protein and nucleic acid chemistry and hybridization described herein is well-known and commonly used in the art. The methods and techniques provided herein are generally performed according to conventional methods well known in the art and as described in various general and more specific references that are cited and discussed throughout the present specification unless otherwise indicated. Enzymatic reactions and purification techniques are performed according to manufacturer’s specifications, as commonly accomplished in the art or as described herein. The nomenclatures used in connection with, and the laboratory procedures and techniques of, analytical chemistry, synthetic organic chemistry, and medicinal and pharmaceutical chemistry described herein are those well-known and commonly used in the art. Standard techniques are used for chemical syntheses, chemical analyses, pharmaceutical preparation, formulation, and delivery, and treatment of patients. Although any methods and materials similar or equivalent to those described herein can be used in the practice of the present disclosure, exemplary methods and materials are now described. All publications mentioned herein are incorporated herein by reference to describe in their entirety.

[0065] Definitions

[0066] The articles “a” and “an” are used herein to refer to one or to more than one (i. e. , to at least one) of the grammatical object of the article. By way of example, “a gene” means one gene or more than one gene.

[0067] “About” as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20% or ± 10%, more preferably ±5%, even more preferably ±1 %, and still more preferably ±0.1 % from the specified value, as such variations are appropriate to perform the disclosed methods.

[0068] As used herein, the terms “administer” or “administration” or “administering” refer to the act of injecting or otherwise physically delivering a substance as it exists outside the body (e.g., an isolated binding polypeptide provided herein) into a patient, such as by, but not limited to, pulmonary (e.g., inhalation), mucosal (e.g., intranasal), intradermal, intravenous, intramuscular, subcutaneous delivery and / or any other method of physical delivery described herein or known in the art. When a disease, or a symptom thereof, is being managed or treated, administration of the substance typically occurs after the onset of the disease or symptoms thereof. When a disease, or symptom thereof, is being prevented, administration of the substance typically occurs before the onset of the disease or symptoms thereof and may be continued chronically to defer or reduce the appearance or magnitude of disease-associated symptoms.

[0069] The term “antibody” as used herein, refers to an immunoglobulin molecule which specifically binds with an antigen. Antibodies can be intact immunoglobulins derived from natural sources or from recombinant sources and can be immunoreactive portions of intact immunoglobulins. Antibodies are typically tetramers of immunoglobulin molecules. The antibodies in the present invention may exist in a variety of forms including, for example, polyclonal antibodies, monoclonal antibodies, Fv, Fab and F(ab)2, as well as single chain antibodies and humanized antibodies (Harlow et al, 1999, In: Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, NY; Harlow et al., 1989, in: Antibodies: A Laboratory Manual, Cold Spring Harbor, New York; Houston et al., 1988, Proc. Natl. Acad. Sci. USA 85:5879-5883; Bird et al., 1988, Science 242:423-426).

[0070] As used herein, the term “autologous” is meant to refer to any material derived from the same individual to which it is later to be re-introduced into the individual.

[0071] As used herein, the term “allogeneic” refers to a graft derived from a different animal of the same species.

[0072] As used herein, the term “CD4IIJ 0”or“LV-10 cells” refers to a modified CD4+ T cell that expresses interleukin- 10 (IL- 10). The expression of IL- 10 converts CD4+ T cells into a T regulatory type 1 -like cell that suppresses effector T cells in vitro and xenoGvHD in humanized mouse models. These cells have demonstrated anti-leukemic effects in vitro and in vivo in a human leukocyte antigen (HLA) class Ldependent but antigen-independent manner. These cells have been described previously in Locafaro, et al. (2017. Molecular Therapy, vol. 25(10): 2254-2269), Cieniewicz et al. (Haematologica. 2021 Oct 1 ; 106(10):2588-2597. doi: 10.3324 / haematol.2020.263129.) and Liu et al. (Cytotherapy. 2021 Nov;23(l 1): 1017-1028. doi: 10.1016 / j.jcyt.2021.05.010.).

[0073] As used herein, the term “disease” is a state of health of an animal wherein the animal cannot maintain homeostasis, and wherein if the disease is not ameliorated then the animal’s health continues to deteriorate. The term “disorder” as used herein refers to a state of health in an animal in which the animal is able to maintain homeostasis, but in which the animal’s state of health is less favorable than it would be in the absence of the disorder. Left untreated, a disorder does not necessarily cause a further decrease in the animal’s state of health.

[0074] As used herein, the term “expression” is defined as the transcription and / or translation of a particular nucleotide sequence driven by its promoter.

[0075] As used herein, the term “modified immune cell” refers to an immune cell or a plurality of immune cells which have been modified. In some embodiments, the immune cell is a T cell. In some embodiments, the T cell is a CD8+ T cell or a CD4+ T cell. In some embodiments, the modification can be genetic. In some embodiments, the modification can promote the reduced expression of a gene (e.g., a “knock-down”). In some embodiments, knock-down of a gene can be achieved using techniques known in the art. These include, but are not limited to, CRISPR / Cas9, TALENs, RNAi, zinc-finger nucleases, and morpholines.

[0076] In some embodiments, the modification can promote the increased expression of a gene. In some embodiments, the increased expression of a gene can be of a gene that is normally expressed in a particular cell type. In some embodiments, the increased expression of a gene can be of a gene that is not typically expressed in a particular cell type (e.g., a “knock-in”). In some embodiments, the immune cell is modified to express an exogenous cytokine or receptor. In some embodiments, the exogenous cytokine is interleukin- 10 (IL- 10). In some embodiments, the modified immune cell is a CD4IL10cell.

[0077] The terms “patient,” “subject,” “individual,” and the like are used interchangeably herein, and refer to any animal, or cells thereof whether in vitro or in situ, amenable to the methods described herein. In certain non-limiting embodiments, the patient, subject or individual is a human.

[0078] As used herein, the term “polymerase chain reaction” or “PCR” refers to multiple repeated cycles of synthesis of a specific DNA fragment (amplification) caused by cyclic changes of the temperature of the reaction mixture and resulting in exponential increase in the quantities of the DNA fragment limited by two oligonucleotide primers. The cyclic change of the temperature of the reaction mixture known to specialists in the field as thermocycling undergoes through the following consecutive stages: denaturation of the double stranded target DNA molecule (melting), attachment of oligonucleotide primers to complementary sites of the formed single stranded target DNA molecules (annealing) and elongation of the primers with the participation of the thermostable polymerase until elongated fragments of complementary DNA molecules are formed (elongation).

[0079] The PCR is used for amplification of nucleic acids and allows detection and identification of the presence and quantity of nucleic acid with the target nucleotide sequence in the DNA / RNA sample.

[0080] The PCR experiment involves preparation of a reaction mixture in a buffer solution which generally contains thermostable polymerase, deoxyonucleoside triphosphates, oligonucleotide primers, and magnesium ions. The sample of DNA under investigation is added to the mixture for further amplification with subsequent registration of the amplified nucleotide sequences (amplicons).

[0081] In some embodiments, the PCR assay is selected from conventional PCR, real-time PCR, reverse-transcriptase PCR, single-cell PCR (scPCR), digital PCR, or multiplex PCR.

[0082] The term “polynucleotide” or “nucleic acid” as used herein refers to a polymeric form of nucleotides of any length, either ribonucleotides or deoxyribonucleotides. Thus, this term includes, but is not limited to, single-, double- or multi-stranded DNA or RNA, genomic DNA, cDNA, DNA-RNA hybrids, or a polymer comprising purine and pyrimidine bases, or other natural, chemically or biochemically modified, non-natural, or derivatized nucleotide bases. The backbone of the polynucleotide can comprise sugars and phosphate groups (as may typically be found in RNA or DNA), or modified or substituted sugar or phosphate groups. Alternatively, the backbone of the polynucleotide can comprise a polymer of synthetic subunits such as phosphoramidates and thus can be an oligodeoxynucleoside phosphoramidate (P-NH2) or a mixed phosphoramidate- phosphodiester oligomer. In addition, a double- stranded polynucleotide can be obtained from the single stranded polynucleotide product of chemical synthesis either by synthesizing the complementary strand and annealing the strands under appropriate conditions, or by synthesizing the complementary strand de novo using a DNA polymerase with an appropriate primer.

[0083] The term “primer” as used herein may refer to a polynucleotide which is i) capable of hybridizing to an original nucleic acid strand and ii) acting as a point of initiation for the synthesis of a new nucleic acid strand, wherein the new nucleic acid strand is an extension product of the primer and is complementary to the original strand. A primer may have a free — OH group at its 3' terminus, which may serve as the origin of synthesis for the extension product.

[0084] A primer may contain standard nucleotides [e.g. standard DNA deoxyribonucleotides (deoxyadenosine monophosphate, deoxyguanosine monophosphate, thymidine monophosphate, deoxycytidine monophosphate) or standard RNA ribonucleotides (adenosine monophosphate, guanosine monophosphate, uridine monophosphate, cytidine monophosphate)], alternative nucleotides (e.g. inosine), modified nucleotides, nucleotide analogs, or a combination thereof. For example, an oligonucleotide primer may include peptide nucleic acids, morpholines (e.g. phosphorodiamidate morpholino oligos), locked nucleic acids [see, for example, Kaur, H, et. al, Biochemistry 45 (23), 7347-55 (2006)], glycol nucleic acids, or threose nucleic acids. A primer may have a backbone, including, for example, phosphodiester linkages, phosphorothioate linkages (a non-bridging O is replaced with sulfur), or peptide linkages (as part of a peptide nucleic acid). Alternative nucleotides, modified nucleotides, and nucleotide analogs may be referred to collectively herein as “non-standard nucleotides.”

[0085] In some embodiments, a primer may be of any length and contain any nucleotide sequence which permits sufficiently stable and specific annealing of the primer to its complement at the temperature being used for a method or step thereof involving the primer. The exact length desired of a primer may depend on a variety of factors, including the temperature of a reaction, the chemical composition of the primer, and the reaction involving the primer. In some embodiments, the template-binding region of a primer may be of any length and contain any nucleotide sequence which permits sufficiently stable and specific annealing of the template-binding region of the primer to its complement at the temperature being used for a method or step thereof involving the primer. The exact length desired of the template- binding region of a primer may depend on a variety of factors, including the temperature of a reaction, the chemical composition of the template-binding region of the primer, and the reaction involving the primer. The inclusion of one or more non-standard nucleotides in the primer may change the desired length of the primer for use in a method provided herein, as compared to the length of a corresponding primer lacking a non-standard nucleotide. For example, if with a method provided herein it is desired to have a primer with a certain Tm, in some embodiments, a primer with the selected Tm may be of a shorter length if the primer contains at least some non-standard nucleotides, as compared to if the primer contains only standard nucleotides.

[0086] A primer provided herein may be prepared by any suitable method. For example, a primer may be chemically synthesized. In another example, a naturally occurring nucleic acid may be isolated, cleaved (e.g., with restriction enzymes), and / or modified to generate or to become part of a primer described herein.

[0087] In some embodiments, a label may be attached to a primer. Labels include, for example, binding ligands (e.g., digoxin or biotin), enzymes, fluorescent molecules / fluorophores, luminescent molecules, quencher molecules, or radioisotopes. In other embodiments, a base of an oligonucleotide may be replaced with a fluorescent analog, such as 2-aminopurine (see, for example, Proc. Acad. Sci. USA, 91, 6644-6648 (1994), which is herein incorporated by reference in its entirety).

[0088] The presence of a non-standard nucleotide in a primer may affect various properties of the primer. In some embodiments, inclusion of a non-standard nucleotide in a primer may increase or decrease the thermodynamic stability of a primer to a complementary sequence thereof. For example, a primer having increased thermodynamic stability may contain a locked nucleic acid. A primer having decreased thermodynamic stability may contain, for example, inosine (described by Auer et al., Nucl. Acids Res. 24; 5021-5025 (1996)) or a negatively charged chemical group, such as a carboxylic acid.

[0089] As used herein, the term “probe” may refer to a molecule used to target and detect another molecule. The probe may be used to quantify a particular molecule of interest. In some embodiments, the probe may be a probe targeting a nucleic acid, such as cDNA, mRNA, or other nucleic acids. The probe may contain a fluorescent reporter at its 5 ’ and / or 3 ’ terminus. The probe may also contain a quencher of the fluorescent reporter. The term “sample” as used herein, is used in its broadest sense. It may refer to a specimen or culture. The specimen may be a patient’s cells obtained for analysis by the methods as described herein. The specimen may be obtained from a biopsy, a drawing of fluid, resection of a tumor or other tissue. Biological samples may be animal, including human, fluid, solid (e.g., stool) or tissue, as well as liquid and solid food products.

[0090] As used herein, the term “Transcriptional Program” refers to an expression profile of a diseased cell. The transcriptional program of a patient’s diseased cell may predict success of a therapy comprising a modified immune cell.

[0091] As used herein, the phrase “treatment” is an approach for obtaining beneficial or desired clinical results. For purposes of this disclosure, beneficial or desired clinical results include, but are not limited to, alleviation of symptoms, diminishment of extent of disease, stabilized (e.g., not worsening) state of disease, preventing spread (e.g., metastasis) of disease, delay or slowing of disease progression, amelioration or palliation of the disease state, and remission (whether partial or total), whether detectable or undetectable. “Treatment” can also mean prolonging survival as compared to expected survival if not receiving treatment.

[0092] Methods

[0093] In one aspect, the disclosure provides methods for selecting a patient affected with a hematological disease or disorder for treatment with modified immune cell, the method comprising the steps of: a) obtaining a sample comprising diseased cells from a patient; b) detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4, wherein each of Pl, P2, P3 and P4 comprises differential overexpression of one or more associated genes listed in Table X; c) by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient as suitable for treatment comprising administration of a modified immune cell; and d) administering a modified immune cell to said patient.

[0094] In some embodiments, the hematological disease is a cancer. Some examples of examples of hematological cancers include leukemias, including acute leukemias (such as acute lymphocytic leukemia, acute myelocytic leukemia, acute myelogenous leukemia and myeloblasts, promyeiocytic, myelomonocytic, monocytic and erythroleukemia), chronic leukemias (such as chronic myelocytic (granulocytic) leukemia, chronic myelogenous leukemia, and chronic lymphocytic leukemia), polycythemia vera, lymphoma, Hodgkin's disease, non-Hodgkin's lymphoma (indolent and high grade forms), multiple myeloma, Waldenstrom's macroglobulinemia, heavy chain disease, myelodysplastic syndrome, hairy cell leukemia and myelodysplasia. In certain embodiments, the cancer is a lymphoma, myeloma, or leukemia.

[0095] In some embodiments, the lymphoma, myeloma, or leukemia is relapsed. “Relapsed” refers to a cancer which has been previously treated and which progresses and requires the initiation of additional treatment but does not meet the criteria for either primary, refractory, or relapsed and refractory. Clinical criteria for determining relapse are well known to those of skill in the art.

[0096] In some embodiments, the lymphoma, myeloma, or leukemia is refractory. “Refractory” refers to a cancer which is non-responsive (e.g., fails to achieve a minimal response or develops progressive disease while on therapy).

[0097] In some embodiments, the lymphoma, myeloma, or leukemia is both relapsed and refractory.

[0098] In some embodiments, the leukemia is acute myeloid leukemia (AML), chronic myeloid leukemia (CML), acute lymphocytic leukemia (ALL), or chronic lymphocytic leukemia (CLL). In some embodiments, the myeloma is multiple myeloma (also known as Kahler’s disease). In some embodiments, the lymphoma is a Hodgkin’s lymphoma or a non- Hodgkin’s lymphoma.

[0099] In some embodiments, the diseased cells are analyzed to determine the transcriptional program.

[0100] In some embodiments, the diseased cells express one or more diagnostic transcriptional programs. In some embodiments, the diagnostic transcriptional programs comprise cell surface markers. In some embodiments, the transcriptional program is categorized as “Pl”. Program Pl is associated with AML cells sensitive to killing by modified immune cells (e.g., CD4IL10cells). This transcriptional program is enriched for genes associated with mature monocytic cells, integrins, and adhesion proteins. Additionally, Pl contained S100A8 and S100A9, which are considered to contribute to myeloid differentiation of leukemic cells. Expression of Program P2 does not clearly correlate with sensitivity or resistance to killing. AML cells enriched in program P3 over-expressed CD34, which is ordinarily expressed on hematopoietic stem cells (HSCs) and leukemic stem cells (LSCs). Program P4 contains HLA class II genes, as well as CD200, which is a gene associated with AML LSCs. CD200 has been shown to impair the cytotoxic function of NK cells, CD8+ T cells, and CD4IL10cells. The genes associated with Programs P1-P4 can be found in Table 1. Table 1. Top 20 surface genes and top 10 genes associated with transcriptional programs PI-

[0101] PL

[0102] These cell surface markers can be detected and quantified using various detection methods known in the art. Typically, mRNA detecting the surface markers is detected, either direction or indirectly (e.g., by detection of cDNA prepared from the mRNA). Methods for detecting mRNAs or cDNAs are well established in the art, including by not limited to hybridization techniques, polymerase chain reaction (PCR), quantitative PCR, real-time quantitative PCR, RNA sequencing, northern blotting, and Southern blotting. Methods for detecting protein expression are also well-established in the art, including but not limited to western blotting, immunoprecipitation, immunohistochemistry (IHC), immunofluorescence (IF) and enzyme linked immunosorbent assay (ELISA). For surface proteins, expression can be detected by flow cytometry (FC), using fluorochrome-labeled antibodies specific for the given marker.

[0103] Suitable methods for determining the level of cell surface marker expression at the mRNA level include RNA sequencing, conventional microarray analysis, polymerase chain reaction (PCR), quantitative polymerase chain reaction and real-time quantitative PCR. In some embodiments, RNA is extracted for the cells using standard protocols. In some embodiments, RNA analysis is performed using techniques that do not require RNA isolation.

[0104] The mRNA expression level of cell surface markers can be measured using conventional DNA microarray expression profiling technology. A DNA microarray is a collection of specific DNA segments or probes affixed to a solid surface or substrate such as glass, plastic or silicon, with each specific DNA segment occupying a known location in the array. Hybridization with a sample of labeled RNA, usually under stringent hybridization conditions, allows detection and quantitation of RNA molecules corresponding to each probe in the array. After stringent washing to remove non-specifically bound sample material, the microarray is scanned by confocal laser microscopy or other suitable detection method. Modem commercial DNA microarrays, often known as DNA chips, typically contain tens of thousands of probes, and thus can measure expression of tens of thousands of genes simultaneously. Such microarrays can be used in practicing the present invention. Alternatively, custom chips containing as few probes as those needed to measure engraftment markers of interest, plus necessary controls or standards, e.g., for data normalization, can be used in practicing the disclosed methods.

[0105] Detection may include detecting the absence of a cell surface marker.

[0106] In some embodiments, the methods include an administration step. In some embodiments, a modified immune cell is administered to the patient after the patient was selected as suitable for treatment depending on the transcriptional program found to be expressed in the patient sample.

[0107] In some embodiments, the modified immune cell is a T cell. In some embodiments, the T cell is a CD8+ T cell. In some embodiments, the T cell is a CD4+ T cell. In some embodiments, the T cell is modified to express an exogenous protein. In some embodiments, the T cell is modified to overexpress an endogenous gene. In some embodiments, the T cell is modified to prevent expression of an endogenous gene. In some embodiments, the T cell is modified to overexpress a cytokine or an engineered receptor. In some embodiments, the cytokine is interleukin- 10 (IL- 10). In some embodiments, the modified immune cell is a CD4+ T cell expressing exogenous IL- 10.

[0108] The modified immune cell and pharmaceutical composition comprising the same may be administered in a manner appropriate to the disease to be treated (or prevented). The quantity and frequency of administration will be determined by such factors as the condition of the patient, and the type and severity of the patient’s disease, although appropriate dosages may be determined by clinical trials.

[0109] In some embodiments the modified immune cell and pharmaceutical compositions comprising the same maybe administered through intraarterial, intraperitoneal, intramuscular, subcutaneous, rectal, or vaginal administration.

[0110] Kits

[0111] Components for performing quantification of the selected genes from the selected Transcriptional Programs as described herein may be contained within a kit or article of manufacture, e.g., designed for use in one of the methods of the invention as described herein.

[0112] In some embodiments, the kit comprises a single fluid. In some embodiments, the kit comprises 2 fluids. In some embodiments, the kit comprises 3 fluids. In some embodiments, the kit comprises 4 or more fluids. A fluid may include a diluent, a buffer, or any other described herein or known in the art suitable for diluting, stabilizing, buffering, or otherwise transporting or storing components for performing quantification.

[0113] In some embodiments, the kit comprises primers for the amplification and quantification of expression products of the selected genes. In some embodiments, the kit may comprise all the components needed for a PCR reaction, including, but not limited to target- specific primers, dNTPs, polymerase enzymes, and buffers.

[0114] In some embodiments, the kit comprises primers targeting the genes, primers targeting the mRNA, primers targeting the cDNA, a probe targeting the cDNA, a probe targeting the mRNA, a probe targeting the DNA, an antibody specific to the protein products of the genes, and a combination thereof.

[0115] In some embodiments, the probe may be a polynucleotide, similar to a primer. In some embodiments, the probe may be a protein or a polypeptide. In some embodiments, the probe comprises a fluorescent tag. In some embodiments, the probe comprises a radionuclide. In some embodiments, the probe comprises a tag that may be detected using fluorescent microscopy. In some embodiments, the probe comprises a tag that may be detected using a blotting technique (e.g., Western blotting, Northern blotting, Southern blotting). In some embodiments, the probe may comprise a quenching molecule. In some embodiments, the probe comprises a tag that may be detected using electron microscopy. In some embodiments, the probe may be an antibody or a fragment thereof. In some embodiments, the kit comprises two or more antigen binding compositions configured for quantification, wherein the antigen- binding compositions selectively bind to cell surface markers of a gene from a Transcriptional Program selected from Table 1. In some embodiments, the antigen-biding compositions comprise fluorescently labeled antibodies or antibodies comprising a binding site for detection elements. In some embodiments, the primer or probe or antibody allows for the quantification of the target molecule.

[0116] EXAMPLES

[0117] Example 1. Methods and Materials

[0118] Cell Culture

[0119] De-identified pediatric AML bone marrow aspirates were obtained from the Children’s Oncology Group (COG; CA, USA). Each AML sample contained a minimum of 80% blasts, as reported by COG. Primary adult AML samples SU540 and SU555 were obtained with the help of Dr. Ravindra Majeti and Dr. Yusuke Nakauchi (Stanford University Medical Center Institutional Review Board protocol # 6453). Human blood leukocytes were obtained from de- identified healthy donors (Stanford Blood Center, CA, USA), from which the CD4IL10cells were generated, cultured, and functionally tested as described (Cieniewicz, et al. 2020. Haematologica Online. 10.3324 / haematol.2020.263129; Liu et al. 2021. Cytotherapy 23, 1017-1028. 10.1016 / j.jcyt.2O21.05.010). Human CD8+ T cells were isolated from healthy donors via magnetic bead labeling (CD8+ T cell isolation kit, Miltenyi Biotec, Germany). U937 (ATCC, VA, USA), K562 (ATCC, VA, USA) and primary AML cells were cultured as before.

[0120] Killing and Degranulation Assays

[0121] CD4IL10cells were co-cultured with target cells at a 1: 1 effector: target (E : T) ratio for 3 days as described (Cieniewicz, et al. 2020. Haematologica Online. 10.3324 / haematol.2020.263129.), unless otherwise specified. When indicated, LLA-1 inhibitors (BIRT377, BMS688571 and A286982 from Tocris Bioscience, UK; BMS587101 from MedChemExpress, NJ, USA) were added into the killing assay at 0.1, 1 and 10 pM, and elimination efficiency was calculated 24 hr after co-culture. Lor killing assay with ex vivo- isolated primary CD8+ T cells, target U937 cells (killing-sensitive) and control K562 cells (killing-resistant) were pre-treated with soluble anti-CD3 monoclonal antibody (mAb; OKT3, Miltenyi Biotec, at 200 ng / ml) for 15 min at 37°C prior to co-culture with primary human CD8+ T cells, to allow the CD3 mAb to bind to Lc-receptors on U937 cells (control K652 cells do not express Pc receptors). Next, freshly isolated human CD8+ T cells were co-cultured with pre-treated target cells at a 1:1 E:T ratio in the presence of IL -2 (50 U / ml) for 3 days. After culture, remaining cells in each condition were quantified via CountBeads using flow cytometry as in the CD4IL10cell killing assay 16. Killing was calculated as elimination efficiency (%): [1 - (AML cell number cultured with T cells) / (AML cell number cultured alone)] x 10016. For CD8+ T cell degranulation assay, target cells were pre-treated with anti- CD3 mAb as above, and co-cultured with human CD8+ T cells at 1 : 1 E:T ratio in the presence of anti-CD107a-APC mAb (BD Biosciences, CA, USA). After 1 hour, brefeldin A and monensin (BioLegend, CA, USA; used as per manufacturer’s instructions) were added to each well, cells were cultured for 4 more hours, stained with a viability dye and anti-CD3 and anti- CD 8 mAb and fixed with 4% formaldehyde until acquisition by flow cytometry. Flow cytometry data was acquired on a BD LSR Fortessa and BD FACS Aria II, and analyzed using FlowJo 10.8.

[0122] CRISPR / Cas9-Mediated Genome Editing and Optimization

[0123] CRISPR / Cas9 knock-outs of IFNGR1, TNFRSFIB, ITGB2 were performed as previously described (Uyeda et al. 2021. Front Immunol 12, 683680. 10.3389 / fimmu.202L 683680.), with minor optimizations in sgRNA concentration and electroporation. ICAM1 knockout was made by first cloning an ICAM 1 -targeting sgRNA into a modified lentiCRISPRv2 plasmid with an RFP reporter instead of puromycin. Third generation lentivirus was produced. RFP+ICAM1- cells were FACS-sorted one week post transduction. Knockout was confirmed by flow cytometry or Sanger sequencing > 5 days after editing.

[0124] Kits (Synthego, CA, USA) that contained 3 individual single-guide RNAs per target to knock out individual IFNGR1, TNFRSFIB, and ITGB2 were used. Ribonucleoprotein (RNP) complexes were generated by mixing sgRNAs (30 pmol each) with 62 pmol of HiFi Cas9 (Integrated DNA Technologies, IA, USA). The published protocol was optimized by adding of 4 pM electroporation enhancer (Integrated DNA Technologies, IA, USA) and using the SF Cell Line nucleofection solution (Lonza, Switzerland) for the sensitive AML cell line U937.

[0125] Bulk RNA data preprocessing

[0126] NCI TARGET bulk- RNA-seq dataset and the dataset used in FIG. 13 were processed using STAR. For each dataset, the transcript-per-million (TPM) values were used. TPM profiles of cell-lines from Cancer Cell Line Encyclopedia (CCLE) were downloaded from the Broad Institute’s website

[0127] (https: / / data.broadinstitute.org / ccle / CCLE_RNAseq_rsem_genes_tpm_20180929.txt). Gene IDs were mapped to gene symbols using EnsDb.Hsapiens.v8634 package. The expression matrix was filtered for protein-coding genes and hematopoietic cell-lines. The resulting expression values were re-converted to TPM. scRNA-seq

[0128] Four cryopreserved primary AML samples with pre-determined susceptibility to CD4IL10killing, rested them for 2 hours at 37°C, then FACS-sorted an aliquot of live cells for scRNA-seq samples on day 0. CD4II J 0cells at the end of their expansion cycle (resting state) were also sorted for live cells prior to scRNA-seq on day 0. Harvested T cells and remaining AML cells and were co-cultured for 24 hours at a 1 : 1 (E:T) ratio, then stained with anti-NGFR and anti-CD33 mAb to sort CD4IIJ 0cells and AML cells, respectively (CD4IL10cells are engineered to overexpress truncated NGFR as a marker gene, besides IL 10). After sorting, cells were adjusted to a 1: 1 ratio to allow equal representation of AML and CD4IL10cells in scRNA-seq data. This was repeated twice, so that each AML sample was co-cultured with T cells from two different donors. scRNA-seq was completed at Stanford Functional Genomics Facility (SFGF) using the Chromium Single Cell Gene Expression kit (10X Genomics, CA, USA) and Illumina Novaseq (Illumina Inc, CA, USA) sequencer according to manufacturer’s protocols.

[0129] Single-cell Analysis

[0130] Raw counts output by CellRanger were loaded into Seurat v4.0.5 according to the accompanying vignette.

[0131] After loading the 10X Genomics CellRanger output into Seurat 4.0.5, genes expressed in less than 3 cells and ribosomal genes were filtered out, and 28,570 genes remained. Cells expressing less than 500 reads and / or 500 features, and more than 50% mitochondrial reads were also filtered out. The mitochondrial cut-off was higher than suggested in Seurat vignette describing ex-vivo isolated peripheral blood mononuclear cell (PBMC) analysis, because cultured AML cells and CD4IL10cells are expected to be more metabolically active than resting PBMC. Notably, both AML and CD4IL10cells at each time point were FACS-sorted for live cells, and 10X capture and processing for scRNA-seq started within Ih post-sort.

[0132] Raw counts were scaled to 10,000 reads per cell, and log-normalized. The top 2000 genes were selected using the vst method implemented in function FindVariableFeatures, run with the default parameters. Clusters of cells were identified by FindNeighbors, using the top 30 PCA components and otherwise default parameters, and FindClusters, with the resolution parameter set to 0.8 and otherwise default parameters. UMAP plots were generated using the top 30 PCA components with the RunUMAP function.

[0133] Differential Gene Expression Analysis

[0134] Unless otherwise specified, DGE analysis was performed using the function FindMarkers, run with parameters: mean.fxn = rowMeans, min.cells. group = 0, min. cells. feature = 0, min.pct = 0, logfc.threshold = 0, only.pos = FALSE, max.cells.per.ident = 500, retum.thresh = 1.

[0135] Gene-set Enrichment Analysis

[0136] Full transcriptomes of T cells were leveraged: CD4 naive, T cells: CD4 memory resting, and T cells: CD4 memory activated from Newman et al35. For each cell population, each gene in the transcriptome was ordered by calculating the average log2 fold change of each population relative to the others. From the gene lists identified as described in section AML-induced CD4IL10cells transcriptional changes, top 50 with the highest average log2 fold change across CD4IL10cells cultured with sensitive and resistant samples were evaluated in mean log2 fold change-ordered transcriptomes using pre-ranked Gene Set Enrichment Analysis (GSEA) (fgsea R package) with 1,000 permutations.

[0137] Cell Type Annotation

[0138] Cells were assigned to cell types using marker genes ANPEP (CD 13), CD33, CD3D and CD3E. The Wilcoxon test was used to assess differential gene expression between clusters, and p-values were adjusted for multiple hypothesis testing using the Benjamini-Hochberg method. Clusters with a q-value < 0.05 for ANPEP or CD33 were considered AML, and those with q-value < 0.05 for CD3D or CD3E were considered CD4IL10cells. Clusters over- expressing both AML and CD4IL10markers, or none of the two, were filtered out.

[0139] Identification of AML Transcriptional Programs

[0140] AML cells form each patient / timepoint pair were clustered, the expression of each gene was averaged across cells from each patient / timepoint pair within each cluster and merged the resulting average transcriptomes into a single matrix, T*. Clusters (columns) with <25 cells and genes (rows) with no expression were filtered out, resulting in matrix T. AML cell programs were identified by applying non-negative matrix factorization (NMF) on matrix T using 25 NMF restarts as detailed in Luca et al (2021. Cell 5482-5496 e5428. 10.1016 / j.cell.2021.09.014).

[0141] The number of programs at which the Cophenetic coefficient fell below 0.99 were selected and programs with less than 200 marker genes in the downstream analysis were ignored. To assign single cells and external expression data to the programs, the recovery procedure described in Luca et al (2021. Cell 5482-5496 e5428. 10.1016 / j.cell.2021.09.014) was used. The single cells and bulk samples for which the abundance of the filtered programs was highest were considered unassigned. A recovery procedure to assign external expression data to programs was used, considering the single cells and bulk samples with the highest abundance of the filtered program as unassigned. AML-Induced CD4IL10Cell Transcriptional Changes

[0142] DGE analysis was performed between CD4IL10cells before and after co-culture with each AML sample. The Wilcoxon test z-scores of CD4IL10cells co-cultured with sensitive and resistant AML cells were separately combined into meta-z scores, with the natural logarithm of the number of cells as weights and converted to two-sided p-values. Genes with a q-value < 0.05 (Benjamini-Hochberg procedure) in only one of the two conditions were analyzed further.

[0143] Ligand-Receptor Analysis

[0144] Potential ligand-receptor interactions between AML and CD4IL10were identified using the CellChat database, focusing on overexpressed genes in AML programs and in CD4IL10cells after co-culture with sensitive or resistant AML, and interactions for which all ligand genes were overexpressed in an AML program and all receptor genes in the CD4IL10cells, or vice versa.

[0145] Example 2. Single-cell interaction analysis of primary AML and cytotoxic CD4IL10cells.

[0146] To identify CD4IL10killing-sensitive and -resistant primary AML samples, primary AML cells were co-cultured with CD4IL10cells to determine that AML cells from patients PARCEV and PARCHW were sensitive, while AML cells from patients PATISD and PAPZCL were resistant to CD4IL10mediated killing (FIG. 1). As previously shown, CD4IL10cells expressed the expected phenotype, including CD2, CD 18, CD226, and other surface proteins (FIG. 2A-2C).

[0147] To understand how sensitive and resistant AML cells change transcriptionally after their interaction with CD4IL10cells, and how the contact with either type of AML affects CD4IL10cells, scRNA-seq before (Oh) and 24 hours after (24h) AML-CD4IL10cell co-culture were performed (FIG. 3). To obtain high-quality samples, live AML cells and CD4IL10cells were sorted immediately prior to single-cell capture for scRNA-seq. Unlike in the 3-day killing assay (FIG. 4A-4B), 24-hour co-culture did not result in complete elimination of sensitive AML cells by CD4IL10cells (FIG. 5).

[0148] Following pre-processing and quality control, 72,095 single cells were considered for downstream analysis. Of those, 47,521 cells were annotated to AML and 24,574 to CD4IL10cells. AML cells showed heterogeneity between patients, but not between replicates (i.e., two aliquots of the same AML patient sample thawed and analyzed at different time points; FIG. 6), suggesting that the variability introduced by sample processing was minimal. CD4IL10cells derived from healthy donors showed less heterogeneity than AML (FIG. 6). Within the co- cultures, the transcriptome of both AML and CD4IL10cells separated by timepoint, suggesting that in vitro incubation by itself induced transcriptional changes.

[0149] Example 2. AML samples contain cells expressing four different transcriptional programs.

[0150] To resolve the heterogeneity of AML samples while mitigating patient- and in vitro- induced differences, a two-tiered approach was employed (FIG. 7). First, AML single cells within each patient were clustered at each timepoint (FIG. 8A), then calculated the average transcriptome per cluster. The averages were then clustered, revealing five AML cell transcriptional programs shared across all patients and timepoints (FIG. 8B-8C). One of the programs was low quality (< 200 overexpressed markers features and > 20% of mitochondrial reads; FIG. 8D) and was removed from further analysis.

[0151] The remaining four programs revealed major AML transcriptional heterogeneity (FIG. 9A-9B). Program Pl was enriched mostly in cells from killing-sensitive AML samples at Oh. Programs P2 and P3 were enriched in all samples and conditions, while program P4 was found in cells mostly after 24 hours of co-culture (FIG. 9A). Top 5 genes encoding surface proteins found in each program are depicted in FIG. 10. Cells enriched in program Pl overexpressed genes associated with mature monocytes or other myeloid cells, such as S100A8 / S100A9, CD68, CD14, integrin- and adhesion protein-encoding genes ITGAX and ITGB2, ICAM1 (encoding CD54), and cytokine or cytokine receptor-encoding genes such as IL 1 ORA, TNFRSF1B, and IFNGR1. No notable immune-related genes in program P2 were identified. Cells enriched in program P3 overexpressed CD34, which is expressed by hematopoietic stem cells (HSC) and leukemic stem cells (LSC). AML cells enriched in program P4 overexpressed genes encoding HLA class II proteins, as well as CD200, found on AML and LSC39, which had previously been found to have a role in AML resistance to CD4IU 0(FIG. 10).

[0152] Because the AML programs P1-P4 contained genes associated with different maturation levels of hematopoietic cells, the comparative differentiation stage of AML cells in programs P1-P4 was further assessed. AML cells in program Pl had highest estimated differentiation, whereas AML cells in programs P2-P4 had a lower estimated differentiation (FIG. 11). Cells that survived 24h culture, irrespective of the program, displayed a less differentiated transcriptional signature (p < 10-16, Wilcoxon test; FIG. 11). These differentiation levels were in accordance with the French-American-British (FAB) AML classification, which is based on morphology and differentiation stage. FAB classification was reported for two out of four AML patient samples used in the analysis: sensitive PARCEV sample was FAB M4 (myelomonocytic AML), while resistant PAPZCL sample was MO (undifferentiated AML).

[0153] Next, the representation of AML programs across time was examined. Program P 1 was present in sensitive AML samples initially, but disappeared after 24-hour co-culture (FIG. 12), suggesting an association of program P 1 with sensitivity to killing. Representation of AML cells expressing program P2 was overall low, and decreased in some, but not all samples after co-culture. On the other hand, majority of AML cells expressed program P3, and this remained largely unchanged after co-culture. AML cells expressing program P4 increased after co- culture (FIG. 12). These data suggest an association of programs P3 and P4 with resistance to CD4IL10cell-mediated killing.

[0154] Example 3. AML transcriptional programs correlate with AML susceptibility to T cell killing and patient survival.

[0155] Our scRNA-seq analysis suggested that AML transcriptional programs are linked to AML differentiation stage and sensitivity to CD4IL10killing. Next, it was asked whether they associate with: 1) sensitivity to killing in a larger, independent cohort of AML samples; 2) AML FAB subtypes, risk group, or World Health Organization (WHO) classification; and 3) AML patient survival. First, the abundance of each AML transcriptional program in bulk RNA- seq samples from a AML cohort was correlated (n = 14), which had known sensitivity to CD4IL10killing (measured by elimination efficiency; see Methods). In line with previous observations in single-cell data, the abundance of the AML program Pl positively correlated with killing (r = 0.48, p = 0.086), while the abundance of programs P3 and P4 showed a significant negative correlation with killing (r = -0.6, p = 0.022, and r = -0.6, p = 0.023, respectively; FIG. 13).

[0156] As tumor biology studies often utilize model cell lines, the abundance of AML programs P1-P4 in cell lines derived from patients with leukemias and lymphomas was scored, using the Cancer Cell Line Encyclopedia (CCLE) RNA-seq dataset (FIG. 14A-14C). The cell lines with high abundance of AML program P 1 were derived from mature monocytic tumors, including THP-1 and U937, which were used as killing-sensitive controls in CD4IL10killing assays (FIG. 14B-14C). Other cell lines, such as the killing-resistant K562 cells with undifferentiated / erythroleukemic phenotype were used as a negative control for CD4IL10killing, exhibited low Pl but high P3 and P4 scores (FIG. 14B-14C). Thus, the relative AML program abundance in RNA-seq data of tumor cell lines can be an indicator of their sensitivity to CD4IL10cell killing. The association of AML transcriptional programs with the FAB classification, the WHO classification, and risk groups in a large cohort of pediatric AML samples from the National Cancer Institute (NCI) TARGET RNA-seq dataset was evaluated (FIG. 15A-15B). The AML program P 1 , associated with sensitivity to killing, was significantly depleted from FAB subtypes Ml and M2 (acute myeloblastic leukemia with minimal maturation or with maturation, respectively), and was significantly enriched (q < 0.05) in AML subtypes M4 (acute myelomonocytic leukemia) and M5 (acute monocytic leukemia) (FIG. 15A). Pl was also significantly enriched in WHO subtype AML with KMT2A rearrangement (q < 0.05), acute monocytic leukemia, and AML with CBFB::MYH11 fusion (FIG. 15A). No association between Pl program abundance and risk groups was observed, but Pl was depleted from samples with RUNX1::RUNX1T1 fusion (FIG. 15A), which is associated with worse prognosis in pediatric AML43.

[0157] The AML program P2, with undefined association to killing (FIG. 13), was significantly enriched in FAB subtype M5 (q < 0.05), enriched in FAB subtype M6 (acute erythroid leukemia) and WHO subtype AML with KMT2A, as well as in AML with NUP98 rearrangement, which has poor prognosis. Program P2 was significantly depleted from WHO subtype AML with CBFB::MYH11 fusion (FIG. 15A), which is mainly associated with good survival, significantly depleted from low-risk AML, and significantly enriched in AML with standard risk (q < 0.05). Program P3, associated with resistance to killing, was found enriched in AML without maturation and high-risk AML, while being significantly depleted from low- risk AML. Program P4, also associated with resistance to killing, was enriched in AML subtype M0 (undifferentiated acute myeloblastic leukemia) and M7 (acute megakaryoblastic leukemia; FIG. 13). Altogether, AML cells expressing the T cell killing sensitivity-associated program Pl had mature myeloid-like features and mutations linked to better survival, while AML cells expressing program P2 and killing resistance-associated programs P3 and P4 had less differentiated features, and were linked to higher risk AML.

[0158] Finally, the association of AML transcriptional programs with patient survival was examined, using the TARGET RNA-seq dataset previously analyzed (n=187). Patient samples with enrichment of program P 1 , associated with sensitivity to T cell killing, showed a trend towards better survival outcomes, but it was not statistically significant (FIG. 16A). In contrast, AML patients with enrichment of program P3 and P4, associated with resistance to killing, had significantly reduced overall survival (P3; log-rank p = 0.04, HR = 1.5, 95% CI = [0.99 - 2.3]; FIG. 16A upper panel) and relapse-free survival (P4; log-rank p = 0.016, HR = 1.6, 95% CI = [1 - 2.5]; FIG. 16A lower panel). These enrichments were also consistent when considering the abundance of programs as continuous variables in univariate Cox models, where program P2 was also found in patients with worse outcomes (FIG. 16B).

[0159] Altogether, these AML programs, identified by studying the AML / T cell interaction, reinforce the importance of T cell response in AML elimination, and suggest that the expression of T cell killing-resistance associated programs P3 and P4 in patient AML cells could indicate a risk of poor outcome.

[0160] Example 4. Killing-sensitive AML cells activate CD4IL10cells.

[0161] After mitigating the effect of in vztro-induced transcriptional changes, the transcriptional changes occurring in CD4IU 0cells after interaction with sensitive or resistant AML cells were also analyzed. The transcriptome of CD4IL10cells co-cultured with sensitive AML was markedly more perturbed than those co-cultured with resistant AML (1,646 vs. 343 differentially expressed genes). This suggests that CD4IL10cells make more interactions (or higher affinity interactions) with sensitive AML compared to the resistant ones. CD4IIJ 0cells co-cultured with sensitive AML upregulated many genes associated with T cell activation, such as genes encoding for activation-induced proteins IL2RA (CD25) and TNFRSF4 (0X40), cytokines CSF1 (M-CSF), CSF2 (GM-CSF), IFNG, and LTA, metabolism related genes such as FABP5 and PKM, and co-inhibitory molecules such as HAVCR2 (TIM3) and CTLA4 (FIG. 17). CD4IU 0cells co-cultured with resistant AML upregulated few T cell activation-related genes. Accordingly, gene set enrichment analysis revealed that CD4IL10cells co-cultured with sensitive AML cells have a transcriptional signature of activated memory CD4+ T cells, while CD4IL10cells co-cultured with resistant AML cells have a signature of resting memory CD4+ T cells (FIG. 18A-18B). Collectively, these data suggest that sensitive AML cells can engage and activate T cells, which facilitates their killing, whereas the resistant AML cells do not activate T cells and survive the interaction.

[0162] To identify potential receptor-ligand interactions between AML cells and CD4IU 0cells, known receptor-ligand pairs from the CellChat database were leveraged, focusing on the genes upregulated in both AML and CD4IL10cells after their interaction. For AML cells expressing the sensitivity-associated transcriptional program P 1 , some of the top interacting pairs were the genes encoding for: a) receptors for IFN-y, TNF-a and lymphotoxin A cytokines (encoded by IFNGR1 and TNFRSF1B) on AML, and cytokines IFNG, TNF, and LTA on CD4IL10cells; and b) integrins ITGB2 (encoding CD18), ITGAL (CDl la), ITGAM (CDl lb) and ITGAX (CD 11c) on AML cells, and adhesion proteins ICAM1 (encoding ICAM1, also known as CD54) and ICAM2 (CD 102) on CD411 10cells (FIG. 19). AML cells enriched in resistance-associated programs P3 and P4 displayed a different, less abundant interaction profile with CD4IL10cells. For AML program P3, top interacting pair was between LGALS9 (encoding galectin-9) on AML cells and CD44 on CD4IU 0cells (FIG. 20A). For AML program P4, top interacting pair was between ICAM1 , here expressed on AML cells, and ITGAL (CD1 la) on CD4IL10cells (FIG. 20B).

[0163] Overall, sensitive AML were successful in activating the T cells, likely by making more cell-cell interactions, and are subsequently killed by T cells, whereas resistant AML fail to activate the T cells and evade T cell killing.

[0164] To validate these predicted interactions, several highly expressed genes found in program P2 from the otherwise killing-sensitive AML cell line U937 were knocked out. The effect of the knock-out on CD4IL10cell-mediated killing U937 cells was quantified. Knockout of TNF-a receptor (encoded by TNFRSF1B) and IFN-y receptor (IFNGR1) from U937 cells did not alter their sensitivity to killing. Similarly, knockout of CD 18 integrin (ITGB2) from U937 cells did not have an effect (FIG. 21A-21B).

[0165] Notably, CD 18 and CD1 la are subunits of the LFA-1 (lymphocyte function-associated antigen 1) protein. LFA-1, when expressed on T cells, binds to ICAM1 on target cells, enabling immune synapse formation and T cell-mediated killing of target cells. CD4IL10cells constitutively express high levels of LFA-1 subunits CD18 (ITGB2; FIG. 2A-2C) and CD1 la (ITGAL, FIG. 22A-22B), which were not further upregulated in CD4IU 0cells interacting with killing-sensitive AML cells and thus not identified by CellChat (FIG. 19). However, ICAM1 is one of the top upregulated genes in AML cells expressing sensitivity-associated program P 1. Therefore, ICAM1 was knocked out on U937 cells (U937-ICAM1-KO), which significantly decreased their sensitivity to CD4IL10killing (FIG. 21A). Thus, ICAM1 expression on AML is one of the key mechanisms that enables AML killing by CD4IL10cells.

[0166] ICAM1 / LFA-1 interaction is critical for the immune synapse formation between endogenous cytotoxic cells, such as CD8+ T cells, and tumor cells in vivo (Reina et al. 2017. Cancers 9. 10.3390 / cancers9110153; Schmits et al. 1996. J Exp Med 183, 1415-1426). This could explain why patients with abundant AML programs P3 and P4, associated with low ICAM1 expression and resistance to CD4IIJ 0killing, have poor survival. To test whether ICAM1 / LFA-1 interaction governs AML killing by ex vivo-isolated, primary CD8+ T cells, human CD8+ T cells were co-cultured with killing-sensitive, wild-type U937 cells or U937 lacking ICAM1 (U937-ICAM1-KO), in conditions with sub-optimal TCR stimulation akin to the stimulation provided by tumor neoantigens. Primary human CD8+ T cells released cytotoxic granules and killed almost all wild-type U937 cells, whereas their degranulation and killing of U937-ICAM1-KO cells was significantly impaired (FIG. 23A and 23B). Similar to CD4IL10cells, CD8+ T cells did not degranulate and kill resistant K562 cells (FIG. 24). Thus, ICAM1 expression on AML also enables AML killing by primary CD8+ T cells.

[0167] To understand whether LFA-1, the ICAM1 binding partner expressed on T cells, is equally important as ICAM1 for AML sensitivity to killing, small molecule inhibitors of LFA- 1 or ICAM1 / LFA-1 interaction (BMS587101, BIRT377, BMS688521, A286982) were added to the AML / CD4IL10 cell co-culture (killing assay; Methods). All four agents increased the resistance of wild-type U937 cells to CD4IU 0killing in a dose-dependent manner (FIG. 25A- 25B), further confirming the role of ICAM1 / LFA-1 interaction for effective AML killing by T cells.

[0168] Next, it was demonstrated that only the killing-sensitive, wild-type U937, but not resistant U937-ICAM1-KO cells, potently induce primary CD8+ T cell activation, as measured by frequency of CD69+CD25+ / - CD8+ T cells after 24h co-culture (FIG. 26A and FIG. 26B). Primary CD8+ T cell activation in response to U937 cells (a killing-sensitive AML cell line) was in line with CD4IL10cell activation in response to killing-sensitive primary AML cells (FIG. 17, FIG. 18A). CD8+ T cells were also co-cultured with primary adult (SU540, SU555) and pediatric (PAPVET, PATLIG) AML samples, which were previously determined to be sensitive to CD4IU 0. Two out of four primary AML samples induced potent CD8+ T cell activation after 24 hours of interaction, and three out of four primary AML samples were also killed by CD8+ T cells (FIG. 26A-26B). Notably, killing of primary AML by was significantly impaired by an LFA-1 antagonist, showing that LFA-1 signaling is critical for AML killing also when CD8+ T cells are allogeneic to primary AML cells (FIG. 26A-26B). It was also observed that there was a positive correlation between the degree of CD8+ T cell activation and AML cell killing (FIG. 27).

[0169] Collectively, the data suggest that ICAM1 / LFA-1 interaction is one of the key mechanisms that governs AML elimination by cytotoxic CD4+ and CD8+ T cells, which could influence AML control in patients.

Claims

CLAIMS1. A method for selecting a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of: a. obtaining a sample comprising diseased cells from a patient; b. detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential overexpression of one or more associated genes listed in Table 1; c. by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient as suitable for treatment comprising administration of a modified immune cell; and d. administering a modified immune cell to said patient.

2. A method for treating a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of: a. obtaining a sample comprising diseased cells from a patient; b. detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential overexpression of one or more associated genes listed in Table 1; c. by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient having a diseased cell overexpressing one or more of the genes in step (b) as suitable for treatment comprising a modified immune cell; and d. administering a modified immune cell to said patient.

3. The method of claim 1 or 2, wherein the cells express Transcriptional Program Pl and wherein the patient is deemed suitable for treatment comprising administration of a modified immune cell.

4. The method of claim 1 or 2, wherein the cells do not express Transcriptional Program P3 and / or P4 and wherein the patient is deemed suitable for treatment comprising administration of a modified immune cell.

5. The method of claim 1 or 2, wherein Transcriptional Program Pl is assessed by overexpression of one or more genes selected from the group consisting of S100A9, LYZ, S100A8, CCL3, IL1B, S100A6, FCER1G, CTSS, IF130, and CXCL8.

6. The method of claim 1 or 2, wherein Transcriptional Program Pl is assessed by overexpression of one or more surface marker genes selected from the group consisting of TREM1, GPR183, PLAUR, EVI2B, FCGRT, EMP3, TNFRSF1B, ITGB2, MS4A6A, CYBB, CD83, CLEC7A, ITGAX, EMP1, CD44, IL10RA, MPEG1, APLP2, CD14, CD68.

7. The method of claim 1 or 2, wherein Transcriptional Program P3 is assessed by differential expression of one or more genes selected from the group consisting of PRSS57, HSP90AB1, RAC2, NME2, CD52, CDK6, GATA2, EEF1B2, SERPINB1, and APRT.

8. The method of claim 1 or 2, wherein Transcriptional Program P3 is assessed by differential expression of one or more surface marker genes selected from the group consisting of CD52, SPN, CD69, GYPC, LY6E, CD63, CD34, RNF130, CD96, ITGA4, BST2, HLA-DRB1, TM7SF3, HLA-DMA, ITM2B, ATP6V0A2, CD47, IL2RG, CD82, and TMEM219.

9. The method of claim 1 or 2, wherein Transcriptional Program P4 is assessed by differential expression of one or more genes selected from the group consisting of CCL19, CXCL9, TNFAIP2, LAMP3, IDO1, CDKN1A, MARCKSL1, LSP1, EPI3, and PPA1.

10. The method of claim 1 or 2, wherein Transcriptional Program P4 is assessed by differential expression of one or more cell surface marker genes selected from the group consisting of LAMP3, CCR7, CD40, HLA-DPA1, HLA-DPB1, HLA-DQB1, CD74, SLAMF7, HLA-DRA, HLA-DQA1, VCAM1, IL2RA, ANTXR2, SLAMF1, HLA-DMB, ADAM28, AREG, PTGER4, LY75, and SLC38A1.

11. The method of any of claims 1-10, wherein the method is in vitro or ex vivo.

12. The method of any one of claims 1-10, wherein the diseased cell is a cancer cell.

13. The method of claim 12, wherein the cancer is a hematological cancer.

14. The method of claim 13, wherein the hematological cancer is a lymphoma, myeloma, or leukemia.

15. The method of claim 13 or 14, wherein the hematological cancer is acute myeloid leukemia (AML), chronic myeloid leukemia (CML), acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), Hodgkin’s lymphoma, non-Hodgkin lymphoma, or multiple myeloma.

16. The method of claim 15, wherein the hematological cancer is adult acute myeloid leukemia or pediatric acute myeloid leukemia.

17. The method of any one of claims 1-16, wherein if the diseased cells differentially express: two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more of the genes of a selected Transcriptional Program, the cells are determined to express that Transcriptional Program.

18. The method of any one of claims 1-15, wherein gene expression is assayed using a polymerase chain reaction (PCR)-based assay.

19. The method of claim 16, wherein the PCR-based assay is selected from PCR, real- time PCR, reverse-transcriptase PCR, single-cell PCR (scPCR), digital PCR, or multiplex PCR.

20. The method of any one of claims 1-19, wherein the modified immune cell is a T cell.

21. The method of claim 20, wherein the T cell is a CD8+ T cell or a CD4+ T cell.

22. The method of claim 20, wherein the T cell is a Tri cell or cell having a Tri phenotype.

23. The method of any one of claims 1-19, wherein the modified immune cell is a polyclonal Tri cell.

24. The method of any one of claims 1-19, wherein the modified immune cell is a cell having a Tri phenotype comprising a CD4+ cell modified to express IL- 10.

25. The method of claim 24, wherein the modified immune cell is an LV-10 cell.

26. The method of any one of claims 1-25, wherein the modified immune cell is allogeneic.

27. The method of any one of claims 1-25, wherein the modified immune cell is autologous.

28. A kit for detecting if a diseased cell expresses one or more diagnostic transcriptional programs selected from the group consisting of Transcriptional Program Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential expression of one or more associated genes listed in Table 1, comprising components for performing quantification of the selected genes from the selected Transcriptional Programs.

29. The kit of claim 28, comprising primers for the amplification and quantification of expression products of the selected genes.

30. The kit of claim 29, comprising primers targeting the genes, primers targeting the mRNA, primers targeting the cDNA, a probe targeting the cDNA, a probe targeting the mRNA, a probe targeting the DNA, an antibody specific to the protein products of the genes, and a combination thereof.

31. The kit of any one of claims 28-30, comprising two or more antigen binding compositions configured for quantification, wherein the antigen-binding compositions selectively bind to cell surface markers of a gene from a Transcriptional Program selected from T able 1.

32. The kit of claim 31 , wherein the antigen-binding compositions comprise fluorescently labeled antibodies or antibodies comprising a binding site for detection elements.

33. A method for selecting a patient affected with a hematological disease or disorder for treatment with a modified immune cell, the method comprising the steps of: a. obtaining a sample comprising diseased cells from a patient; b. detecting if the diseased cells express one or more diagnostic transcriptional programs selected from the group consisting of Pl, P2, P3, and P4; wherein, each of Pl, P2, P3, and P4 comprises differential overexpression of one or more associated genes listed in Table 1; and c. by the transcriptional programs found to be expressed in the diseased cells of the sample, selecting a patient as suitable for treatment comprising administration of a modified immune cell.

34. The method of claim 33, wherein the patient is administered the modified immune cell.

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