Modulation of stimulatory and non-stimulatory myeloid cells

Abstract

To provide methods and compositions for the treatment of an immune-related condition in an individual, e.g., cancer.SOLUTION: The present invention relates to methods and compositions for enhancing an immune response and / or killing, disabling, or depleting non-stimulatory myeloid cells, using an antigen binding protein such as an antibody or antigen binding fragment thereof.SELECTED DRAWING: Figure 12A

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Application No. 62 / 056,569, filed September 28, 2014, and U.S. Provisional Application No. 62 / 129,883, filed March 8, 2015, each of which is incorporated by reference in its entirety and for all purposes.

[0002] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with Government support under grants U01 CA141451 and U54 CA163123 awarded by the National Institutes of Health. The Government has certain rights in this invention. [Background technology]

[0003] Immunity plays a role in preventing tumor growth. Within the lesion, a complex microenvironment can develop and, despite the recruitment of T cells, the development of tumor mass is often not effectively controlled. Understanding the balance between tumor elimination and tumor escape may depend on understanding the differential roles that myeloid cells play in the tumor microenvironment.

[0004] Myeloid populations in the tumor microenvironment prominently include monocytes and neutrophils (sometimes loosely grouped as immune suppressor cells of myeloid origin), macrophages, and dendritic cells. Although myeloid populations within tumors have long been thought to be, overall, non-stimulatory or suppressive, it has more recently been realized that not all tumor-infiltrating myeloid cells are created equal.

[0005] In normal tissues, many of these myeloid cells are essential for proper functioning of both innate and adaptive immunity, and in particular for proper wound repair, however, in the setting of cancer, there is generally a significant excess of macrophages and populations of these, and other, cell types are described as dysfunctional or distorted. When considered as a total population defined by a single marker such as CD68 or CD163, infiltration of "macrophages" has been associated with poor subject outcomes in multiple tumor types (de Visser, Cancer Immunol Immunother, 2008; 57: 1531-9 (Non-Patent Document 1)), (Hanada et al., Int J Urol 2000; 7: 263-9 (Non-Patent Document 2)), (Yao et al. Clin Cancer Res, 520, 2001; 7: 4021-6 (Non-Patent Document 3)), (Ruffell et al., PNAS, 523 2012; 109: 2796-801 (Non-Patent Document 4)). However, phenotypically and functionally fractionating macrophages from the tumor microenvironment is complicated by the similarities between macrophages and dendritic cells, which poses a challenge in tumor biology. Morphological criteria have often been applied to tissues to date, with one approach attempting to distinguish dendritic cells from macrophages on the basis that dendritic cells have a more spiky or dendritic morphology and macrophages have a more veiled or spherical morphology (Bell et al., J Exp Med 555, 1999;190:1417-26). Other groups are attempting to differentiate based on genetic and cell surface markers.

[0006] There is diversity in antigen-presenting compartments within tumors, and T cells can distinguish the characteristics of antigen-presenting cells (APCs). As T cells are the main drivers of tumor immunity, it will be important to understand the precise characteristics of their cognate APCs. Myeloid cells are prominent among the cells capable of presenting tumor-derived antigens to T cells, thereby maintaining them in an activated state. Antigen presentation occurs within the tumor itself and may affect the function of tumor cytotoxic T cells (CTLs). T cell activation by antigen-presenting cells (APCs) is a key component in antigen-specific immune responses and tumor cell killing. Understanding the characteristics of these myeloid populations may guide therapeutic avenues, as they represent the main T cell interactive partners and antigen-presenting cells for the influx of tumor-reactive cytotoxic T lymphocytes.

[0007] All patents, patent applications, publications, documents, and articles cited herein are hereby incorporated by reference in their entirety. [Prior art documents] [Non-patent literature]

[0008] [Non-Patent Document 1] de Visser,Cancer Immunol Immunother,2008;57:1531-9 [Non-Patent Document 2] Hanada et al.,Int J Urol 2000;7:263-9 [Non-Patent Document 3] Yao et al.Clin Cancer Res,520,2001;7:4021-6 [Non-Patent Document 4] Ruffell et al.,PNAS,523 2012;109:2796-801 [Non-Patent Document 5] Bell et al., J Exp Med 555, 1999;190:1417-26 Summary of the Invention

[0009] Described herein are methods for killing, disabling, or depleting non-stimulated myeloid cells present in cancer tissue of a subject, the methods comprising contacting the non-stimulated myeloid cells with an antibody or antigen-binding fragment thereof that binds to the non-stimulated myeloid cells and is present in an amount effective to kill, disable, or deplete the non-stimulated myeloid cells in the cancer tissue of the subject. In some aspects, the non-stimulated myeloid cells are present in an immune cell population that includes stimulatory myeloid cells and non-stimulated myeloid cells. In some aspects, killing, disabling, or depleting the non-stimulated myeloid cells reduces the amount or volume of cancer tissue, thereby treating the subject. In some aspects, the contacting increases the ratio of stimulatory myeloid cells to non-stimulated myeloid cells in the immune cell population. In some aspects, the contacting decreases the ratio of non-stimulated myeloid cells to stimulatory myeloid cells in the immune cell population. In some aspects, the contacting enhances an immune response in the subject. In some embodiments, the contact does not substantially kill, incapacitate, or deplete myeloid cells present outside the cancerous tissue and / or stimulatory myeloid cells present in the cancerous tissue.

[0010] Also described herein are methods of treating cancer in a subject, the methods comprising administering an antibody or antigen-binding fragment thereof that binds to unstimulated myeloid cells present in the cancer, the antibody or antigen-binding fragment thereof being present in an amount effective to kill, disable, or deplete the unstimulated myeloid cells. In some embodiments, the unstimulated myeloid cells are present in an immune cell population that includes stimulatory myeloid cells and unstimulated myeloid cells. In some embodiments, the killing, disabling, or depletion of the unstimulated myeloid cells reduces the amount or volume of cancer tissue, thereby treating the subject. In some embodiments, the contacting increases the ratio of stimulatory myeloid cells to unstimulated myeloid cells in the immune cell population. In some embodiments, the contacting decreases the ratio of unstimulated myeloid cells to stimulatory myeloid cells in the immune cell population. In some embodiments, the contacting does not substantially kill, disable, or deplete myeloid cells present outside the cancer and / or stimulatory myeloid cells present in the cancer. In some embodiments, the cancer in the subject is treated by generating or enhancing an immune response against the cancer.

[0011] In some aspects, the antibody or antigen-binding fragment thereof binds to an extracellular domain of a target protein expressed on unstimulated myeloid cells, the target protein being selected from the group consisting of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and the unstimulated myeloid cells are selected from the group consisting of CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - and wherein the antibody or antigen-binding fragment thereof kills, disables, or depletes the unstimulated myeloid cells by antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC) to a level that is less than the level of unstimulated myeloid cells present in the cancer tissue prior to contact of the unstimulated myeloid cells with the antibody or antigen-binding fragment thereof, and the unstimulated myeloid cells express CD45 + , HLA-DR + , CD14- , CD11c + , BDCA1 - , and BDCA3 + The cancer is treated by the treatment of cancer, wherein the immune response against the cancer tissue is enhanced by contacting or administering the stimulatory myeloid cells present in the cancer tissue without substantially killing, disabling, or depleting the myeloid cells present in a tissue other than the cancer tissue and / or the stimulatory myeloid cells present in the cancer tissue, and by killing, disabling, or depleting the non-stimulatory myeloid cells, the immune response against the cancer tissue is enhanced, and the cancer is treated.

[0012] In some embodiments, the unstimulated myeloid cells are selected from the group consisting of tumor associated macrophages; tumor associated dendritic cells; CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - ;CD45 + , HLA-DR + , and CD14 + ;CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + or BDCA3 +In some embodiments, the unstimulated myeloid cells are positive for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or negative for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, which may be determined, for example, by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis (RNAseq), or equivalent assay.

[0013] In some embodiments, the antibody or antigen-binding fragment thereof has at least one of antibody-dependent cell-mediated cytotoxicity (ADCC) activity, complement-dependent cytotoxicity (CDC) activity, and antibody-mediated phagocytosis activity. In some embodiments, the antibody is at least one of a monoclonal antibody, an antagonist antibody, a polyclonal antibody, an IgG1 antibody, an IgG3 antibody, an afucosylated antibody, a bispecific antibody, a human antibody, a humanized antibody, a chimeric antibody, a full-length antibody, and an antigen-binding fragment. In some embodiments, the antibody or antigen-binding fragment thereof is not an IgG2 antibody, or the antibody or antigen-binding fragment thereof is not an IgG4 antibody. In some embodiments, the antibody or antigen-binding fragment thereof is conjugated. In some embodiments, the antibody or antigen-binding fragment thereof is conjugated to at least one therapeutic agent selected from the group consisting of a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulator, an antiangiogenic agent, a proapoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment. In some embodiments, the antibody or antigen-binding fragment thereof selectively binds to at least one of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119. In some embodiments, the antibody or antigen-binding fragment thereof does not selectively bind to LILRB4.

[0014] In some aspects, the contacting or administering induces at least one of death of the unstimulated myeloid cells, apoptosis of the unstimulated myeloid cells, lysis of the unstimulated myeloid cells, phagocytosis of the unstimulated myeloid cells, and proliferation arrest of the unstimulated myeloid cells.

[0015] In some embodiments, the stimulatory myeloid cells are CD45 + , HLA-DR + , CD14 - , CD11c +, BDCA1 - , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + ;CD45 + , HLA-DR + , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , and BDCA3 + ; and CD45 + , HLA-DR + , CD11c + , and BDCA3 + , which may be determined, for example, by flow cytometry or an equivalent assay. In some embodiments, the stimulatory myeloid cells are negative for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or positive for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, which may be determined, for example, by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis, or an equivalent assay.

[0016] In some aspects, the unstimulated myeloid cells are present in an immune cell population that includes stimulated and unstimulated myeloid cells.

[0017] In some embodiments, the cancer tissue is a solid or liquid cancer. In some embodiments, the cancer is selected from the group consisting of melanoma, renal cancer, hepatobiliary cancer, head and neck squamous cell carcinoma (HNSC), pancreatic cancer, colon cancer, bladder cancer, glioblastoma, prostate cancer, lung cancer, and breast cancer.

[0018] In some embodiments, the subject is a human subject. In some embodiments, the subject has previously received, is currently receiving, or will receive immunotherapy. In some embodiments, the immunotherapy is at least one of immunotherapy that inhibits checkpoint inhibitors, immunotherapy that inhibits checkpoint inhibitors in T cells, anti-PD1, anti-PDL1, anti-CTLA4, adoptive T cell therapy, CAR-T cell therapy, dendritic cell vaccines, monocyte vaccines, antigen binding proteins that bind to both T cells and antigen presenting cells, BiTE antigen binding proteins, toll-like receipt ligands, and cytokines.

[0019] In some embodiments, the method enhances an immune response in the subject. In some embodiments, the immune response is an immunotherapy-based immune response. In some embodiments, the immunotherapy-based immune response targets cancerous tissue.

[0020] In some embodiments, the method further comprises administering an agent that enhances the activity or increases the number of stimulatory myeloid cells. In some embodiments, the agent is FLT3L.

[0021] In some embodiments, the methods treat cancer in a subject.

[0022] In some embodiments, the contacting or administering increases the ratio of stimulatory myeloid cells to non-stimulatory myeloid cells in the immune cell population. In some embodiments, the contacting or administering causes stimulatory myeloid cells present in the subject's tumor to represent greater than 1-4%, greater than 1-2%, greater than 1%, greater than 1.37%, greater than 1.6%, greater than 2%, greater than 3%, or greater than 4% of all CD45+, HLA-DR+ cells present in the tumor.

[0023] In some aspects, the method further comprises determining the number of stimulated myeloid cells and / or the number of unstimulated myeloid cells in a biological sample from the subject. In some embodiments, the determining step is used to determine whether the subject would benefit from administration of the antibody or antigen-binding fragment thereof. In some aspects, the determining step is used to monitor the effectiveness of administration of the antibody or antigen-binding fragment thereof.

[0024] In some embodiments, the method further comprises determining an expression level of at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4 in a biological sample from the subject. In some embodiments, the method further comprises determining an expression level of at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1 in a biological sample from the subject.

[0025] In some aspects, the antibody or antigen-binding fragment thereof is present in a pharmaceutical composition comprising the antibody or antigen-binding fragment thereof and a pharma- ceutical acceptable excipient. In some aspects, the composition is sterile.

[0026] In some aspects, the antibody or antigen-binding fragment thereof binds to an extracellular domain of a target protein expressed on unstimulated myeloid cells, the target protein being selected from the group consisting of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and the unstimulated myeloid cells are selected from the group consisting of CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 -and wherein the antibody or antigen-binding fragment thereof kills, disables, or depletes the unstimulated myeloid cells by antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC) to a level that is less than the level of unstimulated myeloid cells present in the cancer tissue prior to contact of the unstimulated myeloid cells with the antibody or antigen-binding fragment thereof, and the unstimulated myeloid cells express CD45 + , HLA-DR + , CD14 - , CD11c + , BDCA1 - , and BDCA3 + The immune cell population includes stimulated myeloid cells, which are stimulatory, as well as non-stimulatory myeloid cells, and by killing, disabling, or depleting the non-stimulatory myeloid cells, cancer is treated.

[0027] Also disclosed herein are methods of enhancing an immune response in a subject against a tumor, the methods comprising administering to the subject an effective amount of a treatment that enhances the abundance of stimulatory myeloid cells in the tumor or an effective amount of a treatment that reduces the abundance of non-stimulatory myeloid cells in the tumor, where the treatment enhances an immune response against the tumor, and optionally, the immune response reduces tumor volume.

[0028] Also disclosed herein is a method of improving the efficacy of a cancer immunotherapy treatment in a subject having a tumor, the method comprising administering to the subject an effective amount of a treatment that increases the abundance of stimulatory myeloid cells in the tumor, or an effective amount of a treatment that decreases the abundance of non-stimulatory myeloid cells in the tumor, where the subject has previously undergone, is currently undergoing, or will be undergoing cancer immunotherapy.

[0029] In some embodiments, the method comprises systemic administration or enhancement of FLT3L. In some embodiments, the method comprises systemic administration of one or more antibodies that selectively spare stimulated myeloid cells while eliminating or reducing non-stimulated myeloid cells. In some embodiments, the method comprises treatment of the subject's autologous bone marrow or blood cells with FLT3L while concurrently blocking the expression or action of CSF1. In some embodiments, the method comprises enhancing the expression of IRF8, Mycl1, or BATF3 or ZBTB46 in bone marrow or blood progenitor cell populations.

[0030] Also disclosed herein is a method for determining the presence or absence of unstimulated myeloid cells in a sample derived from a subject, the method comprising contacting a population of immune cells comprising unstimulated myeloid cells and stimulatory myeloid cells with an antibody or antigen-binding fragment thereof that binds to the unstimulated myeloid cells, determining the presence of a complex indicative of binding of the antibody to the unstimulated myeloid cells, optionally quantitating the number of unstimulated myeloid cells in the population, and optionally treating the subject with the antibody or antigen-binding fragment thereof that binds to the unstimulated myeloid cells.

[0031] Also disclosed herein is a method for determining the presence or absence of stimulatory myeloid cells in a sample derived from a subject, the method comprising contacting a population of immune cells comprising stimulatory and non-stimulatory myeloid cells with an antibody or antigen-binding fragment thereof that binds to the stimulatory myeloid cells, determining the presence of a complex indicative of binding of the antibody to the stimulatory myeloid cells, optionally quantitating the number of stimulatory myeloid cells in the population, and optionally treating the subject.

[0032] Also disclosed herein are methods for quantifying unstimulated myeloid cells in a tumor sample, the methods including: tumor associated macrophages; tumor associated dendritic cells; CD45 + , HLA-DR + , and CD14 + ;CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c+ ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + or BDCA3 + This involves measuring the number of cells that are not

[0033] Also disclosed herein is a method for quantifying stimulatory myeloid cells present in a tumor sample, the method comprising: + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + ;CD45 + , HLA-DR + , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , and BDCA3 + ; and CD45 + , HLA-DR + , CD11c + , and BDCA3 + The method includes measuring the number of cells that are at least one of:

[0034] In some embodiments, the cells are quantified by a cell sorting method, hi some embodiments, the cell sorting method is selected from the group consisting of fluorescence activated cell sorting, flow cytometry, magnetic activated cell sorting, microraft sorting, and affinity-based cell separation.

[0035] Also disclosed herein is a method for quantifying unstimulated myeloid cells in a tumor sample, the method comprising measuring the expression level of at least one of the following unstimulated myeloid cell markers: C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4.

[0036] Also disclosed herein is a method for quantifying stimulatory myeloid cells present in a tumor sample, the method comprising measuring the expression level of at least one of the following stimulatory myeloid cell markers: KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1.

[0037] In some embodiments, expression of the markers is measured by quantitative PCR. In some embodiments, quantification of marker gene expression is achieved using oligonucleotide arrays containing immobilized probes directed to sequences of the marker genes.

[0038] In some embodiments, a tumor sample is obtained from a tumor by needle biopsy, punch biopsy, or surgical resection of the tumor.

[0039] Also disclosed herein is a method for assessing the status of cancer in a patient, the method comprising obtaining a tumor sample from a subject and measuring the abundance of stimulatory myeloid cells in the tumor sample from the subject.

[0040] In some embodiments, the cancer status assessed is the likelihood of cancer recurrence, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates a decreased likelihood of cancer recurrence. In some embodiments, the cancer status assessed is the subject's amenability to immunotherapy treatment, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates an increased likelihood of the subject responding positively to the immunotherapy treatment. In some embodiments, the cancer status assessed is the efficacy of the immunotherapy treatment, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates that the immunotherapy treatment is effective. In some embodiments, the cancer status assessed is predicted cancer survival, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates an increased predicted cancer survival.

[0041] In some embodiments, the increased abundance of stimulatory myeloid cells is an abundance above the median or mean abundance of stimulatory myeloid cells observed in a pool of representative tumor samples. In some embodiments, the abundance of stimulatory myeloid cells is measured as a ratio of stimulatory myeloid cells to non-stimulated myeloid cells present in the sample. In some embodiments, the abundance of stimulatory myeloid cells is measured as a ratio of stimulatory myeloid cells to total myeloid cells present in the sample. In some embodiments, the abundance of stimulatory myeloid cells is measured as a ratio of total HLA-DR present in the sample. + In some embodiments, the increase in abundance of stimulatory myeloid cells is measured as a ratio of stimulatory myeloid cells to HLA-DR cells. + It is defined as more than 1.37 stimulatory myeloid cells per 100 cells. In some embodiments, the immunotherapy treatment is anti-PD1 treatment. In some embodiments, the anti-PD1 treatment is administration of nivolumab or pembrolizumab. In some embodiments, the subject has melanoma.

[0042] Also disclosed herein is a method for assessing the effectiveness of a treatment for increasing the abundance of stimulatory myeloid cells in a tumor, the method comprising administering the treatment to one or more subjects with cancer and measuring the abundance of stimulatory myeloid cells in one or more tumor samples from the one or more subjects, where an increase in the abundance of stimulatory myeloid cells in the one or more tumor samples indicates that the agent is effective.

[0043] In some embodiments, an increase in the abundance of stimulatory myeloid cells is defined as an increase in the abundance of stimulatory myeloid cells in one or more tumor samples compared to that observed in one or more tumor samples from one or more subjects prior to administration of treatment. In some embodiments, an increase in the abundance of stimulatory myeloid cells is defined as an increase in the abundance of stimulatory myeloid cells in one or more tumor samples from a treated subject compared to that observed in a pool of representative tumor samples from untreated subjects.

[0044] The anti-LILRB4 antibody or antigen-binding fragment thereof comprises one or more of the sequences shown in Table BB, or a variant thereof has at least 80%, 90%, or 95% sequence identity to a sequence shown in Table BB, optionally the antibody or antigen-binding fragment thereof comprises each of the CDRs having the CDR sequences shown in Table BB, optionally the antibody or antigen-binding fragment thereof comprises each of the variable domains shown in Table BB, and optionally the antibody or antigen-binding fragment thereof comprises the full-length sequence shown in Table BB.

[0045] Antibodies or antigen-binding fragments thereof that bind to the LILRB4 protein have the ability to specifically kill, deplete, or disable unstimulated myeloid cells.

[0046] In some embodiments, the antibody or antigen-binding fragment thereof binds to the extracellular domain of LILRB4, and the antibody or antigen-binding fragment thereof kills, disables, or depletes unstimulated myeloid cells by antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC).

[0047] In some embodiments, the antibody or antigen-binding fragment thereof has at least one of antibody-dependent cell-mediated cytotoxicity (ADCC) activity, complement-dependent cytotoxicity (CDC) activity, and antibody-mediated phagocytosis activity. In some embodiments, the antibody is at least one of a monoclonal antibody, an antagonist antibody, a polyclonal antibody, an IgG1 antibody, an IgG3 antibody, an afucosylated antibody, a bispecific antibody, a human antibody, a humanized antibody, a chimeric antibody, a full-length antibody, and an antigen-binding fragment. In some embodiments, the antibody or antigen-binding fragment thereof is not an IgG2 antibody, or the antibody or antigen-binding fragment thereof is not an IgG4 antibody. In some embodiments, the antibody or antigen-binding fragment thereof is conjugated. In some embodiments, the antibody or antigen-binding fragment thereof is conjugated to at least one therapeutic agent selected from the group consisting of a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulator, an antiangiogenic agent, a proapoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment. In some embodiments, the antibody or antigen-binding fragment thereof comprises a sequence having at least 95% identity to a sequence shown in Table BB.

[0048] One pharmaceutical composition includes an anti-LILBR4 antibody or antigen-binding fragment thereof disclosed herein, and a pharma- ceutical acceptable excipient.

[0049] In some embodiments, the composition is sterile.

[0050] In some embodiments, the anti-LILBR4 antibodies or antigen-binding fragments thereof disclosed herein are used in the methods disclosed herein. [The present invention 1001] 1. A method of killing, disabling or depleting unstimulated myeloid cells present in cancer tissue of a subject, comprising contacting unstimulated myeloid cells with an antibody or antigen-binding fragment thereof that binds to unstimulated myeloid cells and is present in an amount effective to kill, disable or deplete said unstimulated myeloid cells in cancer tissue of a subject, optionally wherein said unstimulated myeloid cells are present in an immune cell population that includes stimulatory myeloid cells and unstimulated myeloid cells, and optionally wherein killing, disabling or depleting said unstimulated myeloid cells reduces the amount or volume of cancer tissue. the subject is treated, and optionally, said contacting increases the ratio of stimulatory to non-stimulatory myeloid cells in said immune cell population, optionally, said contacting decreases the ratio of non-stimulatory to stimulatory myeloid cells in said immune cell population, optionally, said contacting enhances an immune response in said subject, and optionally, said contacting does not substantially kill, incapacitate or deplete myeloid cells present outside of the cancerous tissue and / or stimulatory myeloid cells present in the cancerous tissue. [The present invention 1002] the antibody or antigen-binding fragment thereof binds to an extracellular domain of a target protein expressed on the unstimulated myeloid cells, the target protein being selected from the group consisting of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and the unstimulated myeloid cells are selected from the group consisting of CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - wherein the antibody or antigen-binding fragment thereof kills, disables, or depletes the unstimulated myeloid cells by antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC) to a level that is less than the level of unstimulated myeloid cells present in the cancer tissue prior to contacting the unstimulated myeloid cells with the antibody or antigen-binding fragment thereof, and the unstimulated myeloid cells express CD45 + , HLA-DR +, CD14 - , CD11c + , BDCA1 - , and BDCA3 + The method of claim 1001, wherein said contact is present in an immune cell population comprising said stimulatory myeloid cells, said stimulatory myeloid cells being stimulatory, and said non-stimulatory myeloid cells, and said contact does not substantially kill, incapacitate, or deplete myeloid cells present outside said cancer tissue and / or said stimulatory myeloid cells present in said cancer tissue, and said cancer is treated by increasing the immune response against said cancer tissue due to the killing, incapacitation, or depletion of said non-stimulatory myeloid cells. [The present invention 1003] The unstimulated myeloid cells are selected from the group consisting of tumor-associated macrophages, tumor-associated dendritic cells, and CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - ;CD45 + , HLA-DR + , and CD14 + ;CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + or BDCA3 + The method of any of claims 1001 to 1002, wherein said antibody is not a marker for the inflammatory bowel disease, and ... [The present invention 1004] Any of the above methods of the invention, wherein the unstimulated myeloid cells are positive for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or negative for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, as measured by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis, or equivalent assay. [The present invention 1005] Any of the above-mentioned methods of the present invention, wherein the antibody or antigen-binding fragment thereof has at least one of antibody-dependent cell-mediated cytotoxicity (ADCC) activity, complement-dependent cytotoxicity (CDC) activity, and antibody-mediated phagocytosis activity. [The present invention 1006] Any of the methods of the invention described above, wherein the antibody is at least one of a monoclonal antibody, an antagonist antibody, a polyclonal antibody, an IgG1 antibody, an IgG3 antibody, an afucosylated antibody, a bispecific antibody, a human antibody, a humanized antibody, a chimeric antibody, a full-length antibody, and an antigen-binding fragment. [The present invention 1007] Any of the above methods of the present invention, wherein the antibody or antigen-binding fragment thereof is not an IgG2 antibody, or the antibody or antigen-binding fragment thereof is not an IgG4 antibody. [The present invention 1008] Any of the above methods of the invention, wherein the antibody or antigen-binding fragment thereof is conjugated. [The present invention 1009] The method of claim 1008, wherein the antibody or antigen-binding fragment thereof is conjugated to at least one therapeutic agent selected from the group consisting of a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulatory agent, an anti-angiogenic agent, a pro-apoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment. [The present invention 1010] Any of the above-mentioned methods of the present invention, wherein the antibody or antigen-binding fragment thereof selectively binds to at least one of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and optionally, the antibody or antigen-binding fragment thereof does not selectively bind to LILRB4. [The present invention 1011] Any of the methods of the present invention, wherein the contact induces at least one of death of the unstimulated myeloid cells, apoptosis of the unstimulated myeloid cells, lysis of the unstimulated myeloid cells, phagocytosis of the unstimulated myeloid cells, and proliferation inhibition of the unstimulated myeloid cells. [The present invention 1012] The stimulatory myeloid cells are + , HLA-DR + , CD14 - , CD11c + , BDCA1 - , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + ;CD45 + , HLA-DR + , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , and BDCA3 + ; and CD45 + , HLA-DR + , CD11c +, and BDCA3 + Any of the above methods of the present invention, comprising cells that are at least one of: [The present invention 1013] Any of the above methods of the invention, wherein the stimulatory myeloid cells are negative for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or positive for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, as measured by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis, or equivalent assay. [The present invention 1014] Any of the methods of the invention described above, wherein the unstimulated myeloid cells are present in an immune cell population that includes stimulatory and unstimulated myeloid cells. [The present invention 1015] Any of the above methods of the present invention, wherein the cancer tissue is a solid cancer or a liquid cancer. [The present invention 1016] The method of the present invention, wherein said cancer is selected from the group consisting of melanoma, renal cancer, hepatobiliary cancer, head and neck squamous cell carcinoma (HNSC), pancreatic cancer, colon cancer, bladder cancer, glioblastoma, prostate cancer, lung cancer, and breast cancer. [The present invention 1017] Any of the methods of the present invention described above, wherein the subject is a human subject. [The present invention 1018] Any of the above methods of the invention, wherein said subject has previously undergone, is currently undergoing, or will be undergoing immunotherapy. [The present invention 1019] The method of the present invention, wherein the immunotherapy is at least one of immunotherapy that inhibits checkpoint inhibitors, immunotherapy that inhibits checkpoint inhibitors in T cells, anti-PD1, anti-PDL1, anti-CTLA4, adoptive T cell therapy, CAR-T cell therapy, dendritic cell vaccines, monocyte vaccines, antigen binding proteins that bind to both T cells and antigen presenting cells, BiTE antigen binding proteins, Toll-like receptor ligands, and cytokines. [The present invention 1020] Any of the methods of the above invention, wherein the method enhances an immune response in the subject, optionally wherein the immune response is an immunotherapy-based immune response, and optionally wherein the immunotherapy-based immune response targets the cancer. [The present invention 1021] Any of the methods of the invention described above, wherein the method further comprises administration of an agent that enhances the activity or increases the number of stimulatory myeloid cells, optionally wherein the agent is FLT3L. [The present invention 1022] Any of the methods of the above invention, wherein the subject is treated for cancer. [The present invention 1023] Any of the methods of the invention described above, wherein said contacting increases the ratio of stimulatory to non-stimulatory myeloid cells in said immune cell population. [The present invention 1024] Any of the methods of the invention described above, wherein the contacting results in stimulatory myeloid cells present in the subject's tumor comprising greater than 1-4%, greater than 1-2%, greater than 1%, greater than 1.37%, greater than 1.6%, greater than 2%, greater than 3%, or greater than 4% of total CD45+, HLA-DR+ cells present in the tumor. [The present invention 1025] Any of the above methods of the present invention, further comprising determining the number of stimulated myeloid cells and / or the number of unstimulated myeloid cells in a biological sample from the subject, optionally wherein said determining step is used to determine whether the subject would benefit from administration of the antibody or antigen-binding fragment thereof, and optionally wherein said determining step is used to monitor the effectiveness of administration of the antibody or antigen-binding fragment thereof. [The present invention 1026] Any of the methods of the present invention described above, further comprising determining the expression level of at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, LILRB4, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1 in a biological sample from the subject. [The present invention 1027] Any of the methods of the invention described above, wherein the antibody or antigen-binding fragment thereof is present in a pharmaceutical composition comprising the antibody or antigen-binding fragment thereof and a pharma- ceutical acceptable excipient. [The present invention 1028] The method of claim 1027, wherein the composition is sterile. [The present invention 1029] 10. A method of treating cancer in a subject comprising administering an antibody or antigen-binding fragment thereof present in an amount effective to bind to and kill, incapacitate, or deplete unstimulated myeloid cells present in a cancer, wherein optionally, the unstimulated myeloid cells are present in an immune cell population comprising stimulatory myeloid cells and unstimulated myeloid cells, and optionally, the subject is treated by reducing the amount or volume of cancer tissue by killing, incapacitating, or depleting the unstimulated myeloid cells, and optionally, the contacting increases the ratio of stimulatory myeloid cells to unstimulated myeloid cells in the immune cell population, and optionally, the contacting decreases the ratio of unstimulated myeloid cells to stimulatory myeloid cells in the immune cell population, and optionally, the contacting does not substantially kill, incapacitate, or deplete myeloid cells present outside of the cancer and / or stimulatory myeloid cells present in the cancer, and optionally, the cancer in the subject is treated by generating or enhancing an immune response against the cancer. [The present invention 1030] the antibody or antigen-binding fragment thereof binds to an extracellular domain of a target protein expressed on the unstimulated myeloid cells, the target protein being selected from the group consisting of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and the unstimulated myeloid cells are selected from the group consisting of CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - wherein the antibody or antigen-binding fragment thereof kills, disables, or depletes the unstimulated myeloid cells by antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC) to a level that is less than the level of unstimulated myeloid cells present in the cancer tissue prior to contacting the unstimulated myeloid cells with the antibody or antigen-binding fragment thereof, and the unstimulated myeloid cells express CD45 + , HLA-DR + , CD14 - , CD11c + , BDCA1 - , and BDCA3 + The method of claim 1029, wherein an immune cell population comprises stimulatory myeloid cells, which are a stimulatory myeloid cell, and said non-stimulatory myeloid cells, and said cancer is treated by killing, disabling, or depleting said non-stimulatory myeloid cells. [The present invention 1031] The unstimulated myeloid cells are selected from the group consisting of tumor-associated macrophages, tumor-associated dendritic cells, and CD45 + , HLA-DR + , CD11c + , CD14 + , and BDCA3 - ;CD45 + , HLA-DR + , and CD14 + ;CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + ;CD45 +, HLA-DR + , CD14 - , CD11c + , and BDCA1 + or BDCA3 + Any of the methods of claims 1029 to 1030, wherein said method is not characterized by a specific function, and wherein said specific function is determined by flow cytometry or an equivalent assay. [The present invention 1032] Any of the above-mentioned methods of the invention for method of treatment, wherein the unstimulated myeloid cells are positive for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or negative for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, as measured by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis, or equivalent assay. [The present invention 1033] Any of the above invention methods of treatment, wherein the antibody or antigen-binding fragment thereof has at least one of antibody-dependent cell-mediated cytotoxicity (ADCC) activity, complement-dependent cytotoxicity (CDC) activity, and antibody-mediated phagocytosis activity. [The present invention 1034] Any of the above invention methods of treatment, wherein said antibody is at least one of a monoclonal antibody, an antagonist antibody, a polyclonal antibody, an IgG1 antibody, an IgG3 antibody, an afucosylated antibody, a bispecific antibody, a human antibody, a humanized antibody, a chimeric antibody, a full length antibody, and an antigen-binding fragment. [The present invention 1035] Any of the above methods of the invention for treating a disease, wherein said antibody or antigen-binding fragment thereof is not an IgG2 antibody, or said antibody or antigen-binding fragment thereof is not an IgG4 antibody. [The present invention 1036] Any of the above methods of the invention for treating a disease, wherein said antibody or antigen-binding fragment thereof is conjugated. [The present invention 1037] The method of claim 1036, wherein the antibody or antigen-binding fragment thereof is conjugated to at least one therapeutic agent selected from the group consisting of a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulatory agent, an anti-angiogenic agent, a pro-apoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment. [The present invention 1038] Any of the above methods of the invention for treating a disease, wherein the antibody or antigen-binding fragment thereof selectively binds to at least one of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119, and optionally, the antibody or antigen-binding fragment thereof does not selectively bind to LILRB4. [The present invention 1039] Any of the above methods of the invention for treating myeloid cell proliferation, wherein the contact induces at least one of death of the unstimulated myeloid cells, apoptosis of the unstimulated myeloid cells, lysis of the unstimulated myeloid cells, phagocytosis of the unstimulated myeloid cells, and proliferation arrest of the unstimulated myeloid cells. [The present invention 1040] The stimulatory myeloid cells are + , HLA-DR + , CD14 - , CD11c + , BDCA1 - , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + ;CD45 + , HLA-DR + , and BDCA3 + ;CD45 + , HLA-DR + , CD14- , and BDCA3 + ; and CD45 + , HLA-DR + , CD11c + , and BDCA3 + Any of the above inventive methods of treatment, wherein the cell comprises at least one of: [The present invention 1041] Any of the above-mentioned methods of the invention for method of treatment, wherein the stimulatory myeloid cells are negative for at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and / or positive for at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, as measured by polymerase chain reaction (PCR), gene array, flow cytometry, RNA sequence analysis, or equivalent assay. [The present invention 1042] Any of the above methods of the invention for methods of treatment, wherein said unstimulated myeloid cells are present in an immune cell population comprising stimulatory and unstimulated myeloid cells. [The present invention 1043] Any of the above methods of the invention for treating cancer, wherein said cancer is a solid cancer or a liquid cancer. [The present invention 1044] The method of claim 1043, wherein said cancer is selected from the group consisting of melanoma, renal cancer, hepatobiliary cancer, head and neck squamous cell carcinoma (HNSC), pancreatic cancer, colon cancer, bladder cancer, glioblastoma, prostate cancer, lung cancer, and breast cancer. [The present invention 1045] Any of the above methods of the invention for treating the disease, wherein said subject is a human subject. [The present invention 1046] Any of the above invention methods of treatment, wherein said subject has previously undergone, is currently undergoing, or will be undergoing immunotherapy. [The present invention 1047] 1046. The method of claim 1046, wherein said immunotherapy is at least one of immunotherapy that inhibits checkpoint inhibitors, immunotherapy that inhibits checkpoint inhibitors in T cells, anti-PD1, anti-PDL1, anti-CTLA4, adoptive T cell therapy, CAR-T cell therapy, dendritic cell vaccines, monocyte vaccines, antigen binding proteins that bind to both T cells and antigen presenting cells, BiTE antigen binding proteins, toll-like receptor ligands, and cytokines. [The present invention 1048] Any of the above methods of the present invention of methods of treatment, wherein said method enhances an immune response in said subject, optionally said immune response being an immunotherapy-based immune response, and optionally said immunotherapy-based immune response targets said cancer. [The present invention 1049] Any of the above methods of the invention for treating myeloid cell disease, wherein said method further comprises administration of an agent that enhances the activity or increases the number of stimulatory myeloid cells, optionally wherein said agent is FLT3L. [The present invention 1050] Any of the above invention methods of treatment, wherein said contacting increases the ratio of stimulatory to non-stimulatory myeloid cells in said immune cell population. [The present invention 1051] Any of the methods of the invention described above, wherein the administration results in stimulatory myeloid cells present in the subject's tumor accounting for more than 1-4%, more than 1-2%, more than 1%, more than 1.37%, more than 1.6%, more than 2%, more than 3%, or more than 4% of total CD45+, HLA-DR+ cells present in the tumor. [The present invention 1052] Any of the above-mentioned methods of the invention for treating a subject, further comprising determining the number of stimulated myeloid cells and / or the number of non-stimulated myeloid cells in a biological sample from the subject, optionally wherein said determining step is used to determine whether the subject will benefit from administration of the antibody or antigen-binding fragment thereof, and optionally wherein said determining step is used to monitor the effectiveness of administration of the antibody or antigen-binding fragment thereof. [The present invention 1053] Any of the above-mentioned methods of the invention for treating the disease further comprising determining the expression level of at least one of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, LILRB4, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1 in a biological sample from the subject. [The present invention 1054] Any of the above methods of the invention for treating a disease, wherein said antibody or antigen-binding fragment thereof is present in a pharmaceutical composition comprising said antibody or antigen-binding fragment thereof and a pharma- ceutical acceptable excipient. [The present invention 1055] The method of claim 1054, wherein the composition is sterile. [The present invention 1056] A method of enhancing an immune response in a subject against a tumor comprising administering to the subject an effective amount of a treatment that enhances the abundance of stimulatory myeloid cells in the tumor or an effective amount of a treatment that reduces the abundance of non-stimulatory myeloid cells in the tumor, wherein the treatment enhances an immune response against the tumor, and optionally, the immune response reduces the volume of the tumor. [The present invention 1057] A method of improving the efficacy of a cancer immunotherapy treatment in a subject having a tumor, comprising administering to the subject an effective amount of a treatment that increases the abundance of stimulatory myeloid cells in the tumor or an effective amount of a treatment that decreases the abundance of non-stimulatory myeloid cells in the tumor, wherein the subject has previously received, is currently receiving, or will receive the cancer immunotherapy. [The present invention 1058] The method of claim 1056 or 1057, comprising systemic administration or enhancement of FLT3L. [The present invention 1059] The method of invention 1056 or invention 1057 comprising systemic administration of one or more antibodies that result in the elimination or reduction of non-stimulated myeloid cells while selectively sparing stimulatory myeloid cells. [The present invention 1060] The method of invention 1056 or invention 1057, comprising treating the subject's autologous bone marrow or blood cells with FLT3L while concurrently blocking the expression or action of CSF1. [The present invention 1061] The method of claim 1056 or 1057, comprising increasing expression of IRF8, Mycl1, or BATF3 or ZBTB46 in bone marrow or blood progenitor cell populations. [The present invention 1062] 1. A method for determining the presence or absence of unstimulated myeloid cells in a sample derived from a subject, comprising: a. contacting a population of immune cells comprising said unstimulated myeloid cells and said stimulatory myeloid cells with an antibody or antigen-binding fragment thereof that binds to said unstimulated myeloid cells; b. determining the presence of a complex indicative of binding of the antibody to unstimulated myeloid cells; c. optionally, quantification of the number of unstimulated myeloid cells in the population; d. Optionally, treating the subject with an antibody or antigen-binding fragment thereof that binds to the unstimulated myeloid cells; and The method of determining the [The present invention 1063] 1. A method for determining the presence or absence of stimulatory myeloid cells in a sample derived from a subject, comprising: a. contacting a population of immune cells comprising said stimulatory myeloid cells and non-stimulatory myeloid cells with an antibody or antigen-binding fragment thereof that binds to said stimulatory myeloid cells; b. determining the presence of a complex indicative of binding of said antibody to stimulator myeloid cells; c. optionally, quantification of the number of stimulatory myeloid cells in the population; d. Optionally, treating the subject. The method of determining the [The present invention 1064] A method for quantifying unstimulated myeloid cells in a tumor sample, comprising: tumor associated macrophages; tumor associated dendritic cells; CD45 + , HLA-DR + , and CD14 + ;CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + ;CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + or BDCA3 + The method of quantification further comprises determining the number of cells that are not [The present invention 1065] A method for quantifying stimulatory myeloid cells present in a tumor sample, comprising: + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + ;CD45 + , HLA-DR + , and BDCA3 + ;CD45 + , HLA-DR + , CD14 - , and BDCA3 + ; and CD45 + , HLA-DR+ , CD11c + , and BDCA3 + The quantitative method includes measuring the number of cells that are at least one of the following: [The present invention 1066] The method of claim 1064 or 1065, wherein said cells are quantified by a cell sorting method. [The present invention 1067] 106. The method of claim 1066, wherein said cell sorting method is selected from the group consisting of fluorescence activated cell sorting, flow cytometry, magnetic activated cell sorting, microraft sorting, and affinity-based cell separation. [The present invention 1068] A method for quantifying unstimulated myeloid cells in a tumor sample, comprising measuring the expression level of at least one of the unstimulated myeloid cell markers: C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4. [The present invention 1069] A method for quantifying stimulatory myeloid cells present in a tumor sample, comprising measuring the expression level of at least one of the stimulatory myeloid cell markers: KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1. [The present invention 1070] The method of claim 1068 or 1069, wherein the expression level of said marker is measured by quantitative PCR. [The present invention 1071] The method of claim 1068 or 1069, wherein said quantification of the level of expression of the marker genes is achieved using an oligonucleotide array comprising immobilized probes directed to sequences of the marker genes. [The present invention 1072] The method of any of claims 1064 to 1071, wherein said tumor sample is obtained from said tumor by needle biopsy, punch biopsy, or surgical resection of the tumor. [The present invention 1073] A method for assessing a cancer state in a patient, comprising the steps of obtaining a tumor sample from the subject and measuring the abundance of stimulatory myeloid cells in the tumor sample from the subject. [The present invention 1074] The method of claim 1073, wherein the cancer status being assessed is the likelihood of cancer recurrence, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates a decreased likelihood of cancer recurrence. [The present invention 1075] The method of claim 1073, wherein the cancer status being evaluated is the subject's amenability to immunotherapy treatment, and an increased abundance of stimulatory myeloid cells in the tumor sample indicates an increased likelihood of the subject responding positively to immunotherapy treatment. [The present invention 1076] The method of claim 1073, wherein the cancer status that is assessed is the efficacy of an immunotherapeutic treatment, and an increase in the abundance of stimulatory myeloid cells in the tumor sample indicates that the immunotherapeutic treatment is effective. [The present invention 1077] The method of claim 1073, wherein the cancer status assessed is predicted cancer survival and an increased abundance of stimulatory myeloid cells in the tumor sample indicates increased predicted cancer survival. [The present invention 1078] Any of the methods of claims 1074 to 1077, wherein the increase in abundance of stimulatory myeloid cells is an abundance that exceeds the median or mean abundance of stimulatory myeloid cells observed in a pool of representative tumor samples. [The present invention 1079] The method of claim 1073, wherein said abundance of stimulatory myeloid cells is measured as a ratio of stimulatory myeloid cells to non-stimulated myeloid cells present in said sample. [The present invention 1080] The method of claim 1073, wherein said abundance of stimulatory myeloid cells is measured as a ratio of stimulatory myeloid cells to total myeloid cells present in said sample. [The present invention 1081] The abundance of stimulatory myeloid cells is determined by measuring the total HLA-DR1 stimulatory activity present in the sample.+ The method of the present invention 1073, wherein the percentage of stimulated myeloid cells is measured as the ratio of stimulated myeloid cells to cells. [The present invention 1082] Increased abundance of stimulatory myeloid cells is associated with HLA-DR + The method of claim 1081, wherein the stimulatory myeloid cell count is greater than 1.37 per 100 cells. [The present invention 1083] The method of claim 1075 or 1076, wherein said immunotherapy treatment is an anti-PD1 treatment. [The present invention 1084] The method of claim 1083, wherein the anti-PD1 treatment is administration of nivolumab or pembrolizumab. [The present invention 1085] The method of claim 1083, wherein the subject has melanoma. [The present invention 1086] 1. A method for assessing the effectiveness of a treatment for increasing the abundance of stimulatory myeloid cells in a tumor, comprising administering the treatment to one or more subjects with cancer and measuring the abundance of stimulatory myeloid cells in one or more tumor samples derived from the one or more subjects, wherein an increase in the abundance of stimulatory myeloid cells in the one or more tumor samples indicates that the substance is effective. [The present invention 1087] The method of claim 1086, wherein an increase in the abundance of stimulatory myeloid cells is defined as an abundance of stimulatory myeloid cells in said one or more tumor samples being greater than that observed in one or more tumor samples obtained from said one or more subjects prior to administration of said treatment. [The present invention 1088] The method of the present invention 1086, wherein an increase in the abundance of stimulatory myeloid cells is defined as an abundance of stimulatory myeloid cells in said one or more tumor samples from treated subjects being greater than that observed in a pool of representative tumor samples from untreated subjects. [Brief description of the drawings]

[0051] [Figure 1A] Rare DCs and abundant macrophages are shown in mouse and human tumors. Figure 1A shows flow cytometry and gating of tumor APC populations derived from digested and CD45-enriched PyMTchOVA tumors. AC is representative of ≥5 independent experiments. Figure 1B shows cytometry of APC populations in ectopic B78ChOVA tumors. Figure 1C shows histograms of tumor-derived mCherry fluorescence from tumor-infiltrating immune cells in B78chOVA. Histograms of each cell type, from front to back, show T cells, neutrophils (Nφ), DC2, DC1, monocytes, TAM2, TAM1, and tumor, respectively. FIG. 1D is a representative cytometry of digested human metastatic melanoma biopsies showing the identification of DC and TAM populations defined by CD45+Lin-(CD3e, CD56, CD19)HLA-DR+ and divided by CD14, BDCA1, and BDCA3. Double negative cells may reflect B cells that escaped the lineage gate, immature monocytes, or pDC. FIG. 1E is the relative proportion of tumor-infiltrating myeloid cells in PyMTchOVA and B78chOVA models, shown as % of total CD45+ cells. Data are shown as mean ± SEM from individual tumors and mice (n=5). FIG. 1F is the frequency of DC and TAM populations infiltrating human metastatic melanoma, shown as % of total CD45+. Data are shown as mean ± SEM from multiple patients and biopsies (n=4). [Figure 1B] See legend to Figure 1A. [Figure 1C] See legend to Figure 1A. [Figure 1D] See legend to Figure 1A. [Figure 1E] See legend to Figure 1A. [Figure 1F] See legend to Figure 1A. [Figure 2A]Surface and transcriptional profiling shows that distinct lineages of tumor DCs and tumor macrophages are highlighted. All data (Figures 2A-G) are derived from the ectopic B78chOVA tumor model. Cell lineages are as defined in Figure 1. Figure 2A shows expression of a panel of DC-specific markers compared to their respective isotypes (grey shading). The black outlines indicate CD103+DC2 populations, showing unique expression. Figure 2B shows differential expression of macrophage-specific markers (colored) with corresponding isotypes (grey shading). The black outlines indicate CD11b+DC1, TAM1, and TAM2 populations, showing unique expression. Figure 2C shows differential expression of DC-Th2 markers (colored) by the CD11b+DC1 population, compared to their respective isotypes (grey shading). The black outlines indicate CD11b+DC1, showing unique expression. Figure 2D shows global transcriptional profiles revealed by RNA sequencing of FACS-purified populations performed in biological triplicates. Data are shown as heatmaps of Log2 fold change relative to the global mean of the top 1000 most variable genes between DC1, DC2, TAM1, and TAM2. Figure 2E shows principal component analysis (PCA) of DC1, DC2, TAM1, and TAM2 populations based on global transcriptional profiles obtained by RNA sequencing. Figure 2F shows qRT-PCR analysis of Irf4, Irf8, Myb, and Zbtb46 (zDC) expression from sorted APC populations. Data are shown as mean ΔCt ± SEM, calculated in biological triplicates (n=3) (ND indicates not detected). Figure 2G shows intracellular staining for Irf4 and Irf8 in tumor APC populations compared to their respective isotypes (grey). In FIG. 2E, each cluster indicated by three dots represents, from left to right, CD103+DC2, CD11b+DC1, F4 / 80+TAM1, and F4 / 80+TAM2, respectively. [Figure 2B] See legend to Figure 2A. [Figure 2C]See legend to Figure 2A. [Figure 2D] See legend to Figure 2A. [Figure 2E] See legend to Figure 2A. [Figure 2F] See legend to Figure 2A. [Figure 2G] See legend to Figure 2A. [Figure 3A] Figure 3 shows the differential requirement of Irf4, Irf8, and Batf3 for tumor-infiltrating APC populations. All data are representative flow cytometry analyses of CD11b+DC1 and CD103+DC2 populations (gated on CD45+, Ly6C-, MHCII+, and CD24+). Data are presented as mean ± SEM. Statistical significance is indicated by *p<0.05, **p<0.01, ***p<0.001. ns=not statistically significant. Figure 3A shows ectopic PyMT-VO tumors derived from Irf8- / - (knockout (KO)) compared to controls (wild type (WT)). Relative cell percentages are presented as % of total MHCII+ cells. Data collected from individual mice (n=6) and from two independent experiments. FIG. 3B shows ectopic B78chOVA tumors in Irf4f / fxCD11c-CRE+ hosts compared to Cre-negative littermates. Relative cell percentages are shown as % of total MHCII+ cells. Data collected from individual mice (n=7) and from two independent experiments. FIG. 3C shows ectopic B78chOVA tumors in Batf3KO compared to wild type (WT). Relative cell percentages are shown as % of total MHCII+ cells. Data collected from individual mice (n=6). FIG. 3D shows ectopic B78chOVA tumors in Zbtb46-DTR mice that were acutely depleted with diphtheria toxin (DT) for 24 hours or given PBS. Relative cell percentages are shown as % of total MHCII+ cells. Data are collected from individual mice (n=6) and are from two independent experiments. [Figure 3B]See legend to Figure 3A. [Figure 3C] See legend to Figure 3A. [Figure 3D] See legend to Figure 3A. [Figure 4A]Tumor-infiltrating APC populations show differential dependency on M-CSF and GM-CSF cytokines. Figure 4A shows qPCR of CSF1R, CSF2Rb, and CSF3R expression from sorted APC. Data are shown as mean ΔCt±SEM, calculated for individual B78chOVA tumors in biological triplicates (n=3) (ND indicates non-detection). Figure 4B shows cytometry of tumor APCs after blocking (dotted) with anti-CSF-1 for 3 days compared to isotype (filled) treated tumor animals. Quantification was performed as % of total CD45+ cells in tumors, collected from individual mice (n=6) from two independent experiments, and shown as mean±SEM. Statistical significance is indicated by *p<0.05, **p<0.01, ***p<0.001. ns=not statistically significant. Figure 4C shows adoptive transfer of bone marrow (BM) progenitors and their contribution to BM, spleen, and tumor. Figure 4D shows representative cytometry of congenic cells reaching tumor. Gating was performed on CD45.2 and according to the gating strategy of Figure 1A. Figure 4E shows competitive BM adoptive transfer using wild type (WT) and GMCSFR KO GMP progenitors to recipients bearing B78chOVA tumors. Repopulation efficiency was plotted as % of total cells transferred. Representative gating of GMP cells reaching tumor, showing wild type (WT) (left bar for BM, spleen, and tumor, respectively) and knockout (KO) (right bar for BM, spleen, and tumor, respectively). DC reaching tumor were defined and quantified by CD24+CD11c+. Data were collected from two independent experiments and plotted as mean ± SEM from individual tumors (n=6). Figure 4F shows cytometry of CD11b+DC1 and CD103+DC2 populations (gated on CD45+, Ly6C-MHCII+, CD24+) among ectopic, cytokine-expressing tumors B16-F10, B16-GMCSF, and B16-FLT3L. Populations are shown as % of total MHCII+ cells for each tumor.Data were collected from three independent experiments and plotted as the mean ± SEM from individual tumors (n = 6). In each group of Fig. 4F (right panel), the bars represent DC2, DC1, TAM1, and TAM2, respectively, from left to right. [Figure 4B] See legend to Figure 4A. [Figure 4C] See legend to Figure 4A. [Figure 4D] See legend to Figure 4A. [Figure 4E] See legend to Figure 4A. [Figure 4F] See legend to Figure 4A. [Figure 5A]The antigen processing and presentation capabilities unique to CD103+DC2 are shown. All data (Figures 5A-G) are from the ectopic B78chOVA tumor model. Figure 5A shows a heatmap of log2 transformed expression levels of selected genes involved in cross-presentation, cytokine and chemokine production, and costimulation, obtained by RNA sequencing across the population. Color scale: light grey = bottom 20th percentile, dark grey = top 80th percentile, with a gradation of colors from the 20th to 80th percentiles around the center (50th percentile). Data were obtained from biological triplicates of sorted cells. Figure 5B shows cytometry analysis of surface protein levels of ligands for T cell regulatory molecules (dark lines) compared to their respective isotypes (grey shading). FIG. 5C shows cytometry analyzing expression of MCHI and MHCII (dark lines, front four lines) compared to their respective isotypes (shaded lines, back four lines). In FIG. 5C, the lines are, from front to back of the colored ones, CD103+DC2, CD11b+DC1, F4 / 80+TAM1, and F4 / 80+TAM2, respectively. In FIG. 5C, the lines are, from front to back of the shaded ones, CD103+DC2, CD11b+DC1, F4 / 80+TAM1, and F4 / 80+TAM2, respectively. FIG. 5D shows cytometry analyzing populations after dextran was uptaken ex vivo across the population. Grey=no dextran, light histogram=dextran binding performed at 4C, and dextran uptake performed at 37C=dark histogram, shown in triplicate. Delta geometric mean fluorescence intensity (gMFI) was plotted as mean ± SEM for each population. Data are representative of two independent experiments (n=6). Figure 5E shows cytometry analysis of relative pH of intracellular compartments across populations. B78 tumor cells were transfected with a ratiometric pH construct, N1-mCherry-pHlourin. pHluorin is a pH-sensitive GFP derivative that is quenched at acidic pH.Representative histograms show pHluorin fluorescence in mCherry+ cells, where lower pH-GFP intensity indicates a more acidic environment. Grey histograms are the respective populations from control tumors (B78 parent) that do not express pHluorin. Data are summarized as gMFI ratios of GFP fluorescence to mCherry fluorescence. Data are presented as mean ratios ± SEM and collected from three independent experiments. Figure 5F shows intracellular cytokine staining for IL12 in the populations. Percentage of IL12+ cells quantified across each population, data collected from two independent experiments (n=3) plotted as mean ± SEM. Statistical significance is indicated by *p<0.05. In Figure 5F, the lines are, from front to back, CD103+DC2, CD11b+DC1, F4 / 80+TAM1, and F4 / 80+TAM2, respectively. Figure 5G shows the transcript levels of cytokine Il12b and cytokine Il10 as measured by qPCR. Data are presented as mean ΔCt ± SEM and calculated from individual tumors in biological triplicates (n=3) (ND indicates not detected). [Figure 5B] See legend to Figure 5A. [Figure 5C] See legend to Figure 5A. [Figure 5D] See legend to Figure 5A. [Figure 5E] See legend to Figure 5A. [Figure 5F] See legend to Figure 5A. [Figure 6A]We show that CD103+DCs are excellent T cell stimulators for naive and activated CD8+T cells. All data are from the heterotopic B78chOVA tumor model. T cells+BMDCs (gray shading, backmost), T cells+BMDCs+SL8 (unshaded gray, second from backmost), T cells+tumor APCs (each colored histogram). A ratio of 20,000 T cells:4,000 APCs was seeded. Representative flow plots from 4 independent experiments are shown unless stated. Figure 6A shows flow cytometry analysis of early activation markers Nur77 and CD69 (12 hours) of naive or preactivated OT-I CD8+T cells cultured with sorted APC populations obtained directly from the tumor. In FIG. 6A, the lines are, from front to back, F4 / 80+TAM2, F4 / 80+TAM1, CD11b+DC1, and CD103+DC2, respectively. FIG. 6B shows representative flow cytometry analysis of naive OT-I CD8+ T cell proliferation measured by eFluor670 dye dilution and plotted against Nur77 (as a measure of TCR triggering) after 72 hours of co-culture with tumor APC populations. Total cell yield numbers are listed above the graph. FIG. 6C shows a histogram overlaid with naive T cell proliferation among tumor APCs. In FIG. 6C, the lines are, from front to back, F4 / 80+TAM1, F4 / 80+TAM2, CD11b+DC1, and CD103+DC2, respectively. FIG. 6D shows a representative cytometry analysis of T cell proliferation, measured by eFluor670 dye dilution and plotted against Nur77, after 72 hours of culturing preactivated OT-I CD8+ T cell blasts with a population of tumor APCs. Total cell yields are listed above the graph. FIG. 6E shows a histogram of preactivated OT-I CD8+ T cell proliferation overlaid among tumor APCs. In FIG. 6E, the lines are, from front to back, F4 / 80+TAM1, F4 / 80+TAM2, CD11b+DC1, and CD103+DC2, respectively.Figure 6F shows a representative cytometry analysis of T cell proliferation, measured by eFluor670 dye dilution at 72 hours after culturing naive OT-II CD4+ T cells with a population of tumor APCs. Representative flow plots are from two independent experiments. Figure 6G shows a histogram of naive OT-II CD4+ T cell proliferation overlaid among tumor APCs. The lines are, from front to back, F4 / 80+TAM1, F4 / 80+TAM2, CD11b+DC1, and CD103+DC2, respectively. [Figure 6B] See legend to Figure 6A. [Figure 6C] See legend to Figure 6A. [Figure 6D] See legend to Figure 6A. [Figure 6E] See legend to Figure 6A. [Figure 6F] See legend to Figure 6A. [Figure 6G] See legend to Figure 6A. [Figure 7A]In vivo and section imaging reveal that CD11b+DC1 and CD103+DC2 are sparsely present near the tumor margin, but can still interact with T cells when present in situ. Figure 7A shows the proximal / distal quantification of intratumoral APCs. Data are shown as mean ± SEM from four independent imaging runs. In Figure 7A, the bars in each group are TAM2, TAM1, and DC1 / 2, respectively, from left to right. Figure 7B shows in vivo contacts between APCs and T cells, shown as the percentage of total observed T cell couples. Two independent runs of in vivo two-photon imaging were performed, and the data were accumulated over 30 min at four different locations. Contacts were scored manually by counting the physical contacts that occurred between T cells and APCs, shown in red, yellow, and green. The arrangement of the bars indicates the contacted APCs (top: CD103+, CD11b+DC1, bottom: TAM1, center: TAM2). Figure 7C shows an ex vivo T cell pairing assay using digestive tumors positively selected for CD45+ cells and preactivated OT-I CD8+ T cells. Data were calculated as the % of T cell pairs (left) and the total % of T cell pairs (right) within each population. Data were collected from two independent experiments and plotted as the mean ± SEM. In Figure 7C, the bars in each group are DC2, DC1, TAM1, and TAM2, respectively, from left to right. [Figure 7B] See legend to Figure 7A. [Figure 7C] See legend to Figure 7A. [Figure 8A]We show that a rare CD103 DC2 population is required in tumors for efficient adoptive CTL therapy. Figure 8A shows tumor growth curves plotted as tumor area (mm2) over time for EG7.1 in zDC-DTR hosts. Arrows indicate the time of intraperitoneal administration of diphtheria toxin (DT) / PBS and intravenous transfer of 5x106 preactivated OT-I CD8+ T cells, days 4 and 5, respectively. Thereafter, diphtheria toxin (DT) / PBS was administered every 3 days, followed by FTY-720 / saline every 2 days throughout the course of time. The light grey dashed line (top) indicates the growth of EG7.1 in zDC-DTR hosts without T cell transfer. Transfer of activated CD8+ T cells and treatment with FTY-720 (black line, bottom) or additionally DT-mediated DC depletion (dark grey line, center) resulted in EG7.1 regression. Representative data are shown as mean tumor area ± SEM (n=4) from two independent experiments. Statistical significance is indicated by *p<0.05. Figure 8B shows a comparison of the prognostic value of CD103+ / CD103- gene signal ratios compared to individual genes (either CD103+ specific genes shown in green or TAM1 / TAM2 / Cd11b DC1 specific genes shown in red) in TCGA human samples in a multivariate COX proportional hazards survival analysis adjusted for cancer type as a covariate. Data are presented as hazard ratios (HR) with 95% confidence intervals, where for genes with BHp values ​​<0.05, values ​​<1 mean increased overall survival (OS) and values ​​>1 mean decreased OS. Figure 8C shows a comparison of the prognostic value of the CD103+ / CD103- gene signal ratio compared to several published prognostic gene signatures for TCGA human samples in a multivariate COX proportional hazards survival analysis adjusted for cancer type as a covariate. Data are presented as hazard ratios (HR) with 95% confidence intervals, where for genes with BHp values ​​<0.05, values ​​<1 mean increased overall survival (OS) and values ​​>1 mean decreased OS.FIG. 8D shows a KM plot across all 12 cancers in the human TCGA dataset, matched for cancer type. Data was analyzed for high CD103+ / CD103- gene expression ratio (black, n=1801) vs. low CD103+ / CD103- expression ratio (grey, n=1801), p-value=1.76e-07. FIG. 8E shows a KM plot for overall survival of breast cancer patients in the TCGA dataset. Data was analyzed for high CD103+ / CD103- gene expression ratio (black, n=422) vs. low CD103+ / CD103- expression ratio (grey, n=423), p-value=0.0255. FIG. 8F shows a KM plot for overall survival of head and neck squamous cell carcinoma patients in the TCGA dataset. Data were analyzed between high CD103+ / CD103- gene expression ratio (black, n=151) and low CD103+ / CD103- expression ratio (gray, n=152), p-value=0.000207. Figure 8G shows a KM plot of overall survival in lung adenocarcinoma patients in the TCGA dataset. Data were analyzed between high CD103+ / CD103- gene expression ratio (black, n=177) and low CD103+ / CD103- expression ratio (gray, n=178), p-value=0.000874. [Figure 8B] See legend to Figure 8A. [Figure 8C] See legend to Figure 8A. [Figure 8D] See legend to Figure 8A. [Figure 8E] See legend to Figure 8A. [Figure 8F] See legend to Figure 8A. [Figure 8G] See legend to Figure 8A. [Figure 9A]Figure 9A shows that the transcript levels of CD103+ and BDCA3+ genes are associated with increased post-relapse survival in metastatic melanoma. Figure 9A shows a comparison of the prognostic value of CD103+ genes, CD103+ / - ratios, and individual genes in a COX proportional hazards survival analysis performed using a metastatic melanoma dataset. Data are presented as hazard ratios (HRs) with 95% confidence intervals, with values ​​less than 1 indicating increased overall survival (OS) (post-relapse survival) after metastasis and values ​​greater than 1 indicating decreased OS after metastasis, with BH-fitted p-values ​​less than 0.05. Figure 9B shows a Kaplan-Meier plot of post-relapse survival in metastatic melanoma patients for expression of a list of genes of CD103+. Data were analyzed and categorized into "high" (light gray, lines above each plot) and "low" (black, lines below each plot) bins for CD103+ gene expression levels at stringency thresholds of 33%, 50%, and 66%. Figure 9C shows a Kaplan-Meier plot of post-relapse survival for metastatic melanoma patients for CD103+ / - gene expression ratios. Data were analyzed and categorized into "high" (light gray, lines above each plot) and "low" (black, lines below each plot) bins for CD103+ / - gene expression level ratios at stringency thresholds of 33%, 50%, and 66%. Figures 9D-E show a measure of class-based TIL categories, and Figures 9F-G show a histological measure of peritumoral CD3+ T cell numbers according to {Bogunovic et al., 2009} plotted against the SDC gene signature (Figures 9D, F) and the SDC / NSM ratio (Figures 9E, G). [Figure 9B] See legend to Figure 9A. [Figure 9C] See legend to Figure 9A. [Figure 9D] See legend to Figure 9A. [Figure 9E] See legend to Figure 9A. [Figure 9F] See legend to Figure 9A. [Figure 9G]See legend to Figure 9A. [Figure 10A] Flow cytometric quantification of tumor-infiltrating APC populations in human metastatic melanoma. Figure 10A shows a table of patients who underwent biopsy of human metastatic melanoma. Patient identification table includes age, sex, and tumor biopsy location for each patient, as well as treatment history (if known). All patients listed have received anti-PD-1 immunotherapy at UCSF. Prior history was coded as 0 for naive and 1 for previously treated. ** indicates rapid progression that did not allow further testing. Figure 10B shows a representative flow cytometric gating strategy for defining tumor-infiltrating myeloid subsets in human metastatic melanoma. Data are representative of patients with prominent BDCA3+ and BDCA1+ DC populations, gated on single and viable cells. (pDC, CD14+TAM, BDCA1+DC, BDCA3+, CD14-TAM). FIG. 10C shows a representative gating strategy for flow cytometry on human metastatic melanoma to define tumor-infiltrating myeloid subsets. Data are representative of a patient without a significant BDCA3+DC population and gated on single and viable cells (pDC, CD14+, BDCA1+DC, BDCA3+DC, CD14-TAM). FIG. 10D shows the frequency of CD45+ (black, left bar of each group) and HLA-DR+ (gray, right bar of each group) cells as a percentage of total viable cells across patient biopsies. FIG. 10E shows the frequency of tumor-infiltrating immune populations across patient biopsies as defined by the gating strategy. Data are the frequency of total CD45+ across patients and are shown as mean ± standard error (SEM). pDC, CD14+, TAM, BDCA1++DC, BDCA3+DC, CD14-TAM, lineage markers (CD3e, CD56, CD19). [Figure 10B] See legend to Figure 10A. [Figure 10C] See legend to Figure 10A. [Figure 10D]See legend to Figure 10A. [Figure 10E] See legend to Figure 10A. [Figure 11A] Figure 11 shows that cellular abundance of BDCA3+DC in human melanoma predicts anti-PD1 responsiveness. Patients were classified as either responders (grey, including partial or complete response) or non-responders (black, including stable and progressive disease). Figure 11A shows waterfall plots of CD45+ cells as percentage of total viable cells in individual patient tumors, split into responders and non-responders. Figure 11B shows quantification of frequency of responders (grey) and non-responders (black) as percentage of total viable CD45+ cells in tumors. Data are collected across patients and shown as mean ± SEM. ns = not significant. Figure 11C shows waterfall plots of BDCA3+DC as percentage of total CD45+ cells in individual patient tumors, split into responders and non-responders. Figure 11D shows quantification of the frequency of responders (grey) and non-responders (black) of BDCA3+DC as a percentage of total CD45+ cells in the tumor. Data was collected across patients and is shown as mean±SEM. **p=0.0056. Figure 11E shows a scatter plot of the frequency of BDCA3+DC and CD14+TAM as a percentage of total HLA-DR+ cells in the tumor, with responders shown as open circles and non-responders shown as closed circles. Figure 11F shows a scatter plot of the frequency of BDCA3+DC and BDCA1+DC as a percentage of total HLA-DR+ cells in the tumor, with responders shown as open circles and non-responders shown as closed circles. FIG. 11G is a scatter plot showing the frequency of BDCA3+DCs and CD14-TAMs as a percentage of total HLA-DR+ cells in the tumor, with responders shown as open circles and non-responders shown as closed circles. [Figure 11B] See legend to Figure 11A. [Figure 11C] See legend to Figure 11A. [Figure 11D] See legend to Figure 11A. [Figure 11E] See legend to Figure 11A. [Figure 11F] See legend to Figure 11A. [Figure 11G] See legend to Figure 11A. [Figure 12A] We show that CD103+DCs are required for anti-PD1 efficacy in a mouse model of melanoma. Figure 12A shows mouse and tumor models combined with immunotherapy treatment regimens. Figure 12B shows tumor area (mm2) of individual B78chOVA tumors in B6 control mice (leftmost graph), which were intraperitoneally administered 100ug of control Armenian hamster IgG and 100ug of control rat IgG2a on days 5, 8, and 11 of tumor growth. Data collected from two independent experiments with n=8. FIG. 12C shows the tumor area (mm2) of individual B78chOVA tumors in Zbtb46-DTR BM chimeric mice (middle graph), which were administered 100ug of anti-CTLA-4 and 100ug of anti-PD-1 on days 5, 8, and 11 of tumor growth, and injected with PBS on days 4, 7, and 10. Data was collected from two independent experiments, n=8. FIG. 12D shows the tumor area (mm2) of individual B78chOVA tumors in Zbtb46-DTR BM chimeric mice (rightmost graph), which were administered 100ug of anti-CTLA-4 and 100ug of anti-PD-1 on days 5, 8, and 11 of tumor growth, and injected with DT on days 4, 7, and 10. Data was collected from two independent experiments, n=8. [Figure 12B] See legend to Figure 12A. [Figure 12C] See legend to Figure 12A. [Figure 12D] See legend to Figure 12A. [Figure 13-1]By progressive gating, we show that both NSM and SDC populations were identified in all of the described human tumor types that were analyzed by flow cytometry (metastatic melanoma, head and neck squamous cell carcinoma (HNSC), and colon carcinoma). [Figure 13-2] See description of Figure 13-1. [Figure 13-3] See description of Figure 13-1. [Figure 14-1] Labeling of the indicated cell subsets in the tumor microenvironment was performed across B16-F10 and MC38 heterotopic mouse tumor models using various NSM markers including TREM2, as well as staining for MS467, LILRB4, and CD88, analyzed by flow cytometry. The staining patterns of all NSM markers reveal a high specificity for NSM populations (TAMs, Ly6C+ monocytes, CD11b+ DCs) with no staining of SDCs (CD103+ DCs). Populations were pre-gated similar to the gating strategy in Figure 1A and Figure 1B. Secondary controls for each population are shaded grey, with NSM marker staining for each population overlaid as a solid black histogram. [Figure 14-2] See description of Figure 14-1. [Figure 14-3] See description of Figure 14-1. [Figure 15] Expression of CCR7 on human SDCs. Populations were pre-gated similar to the gating strategy in FIG. [Figure 16] We show that the SDC gene products, CCR7 and XCR1, are specifically expressed in SDCs (CD103+DCs) and that NSMs (TAMs, Ly6C+monocytes, CD11b+DCs) do not express SDC proteins in the tumor microenvironment of mouse ectopic B16-F10 tumors. Populations were pre-gated using the same gating strategy as in Figure 1A and Figure 1B. Respective secondary controls are shaded in grey, with SDC marker staining for each population overlaid as a solid black histogram. [Figure 17-1] Healthy BM and spleen tissues from wild-type C57BL / 6 male mice show no staining for the NSM markers MS4A7 and TREM2, which are not detectable by flow cytometry analysis. Populations were pre-gated using the same gating strategy as in Figure 1A and Figure 1B. Secondary controls for each population are shaded grey, with MS4A7 and TREM2 staining for each population overlaid as solid black histograms (top panel). The bottom panel shows that there is no staining when TREM2 antibodies clone 2, clone 5, and clone 7 are used to stain healthy BM and spleen tissues from mice across immune populations at titer-adjusted concentrations (0 nM, 2 nM, 20 nM, and 200 nM), and that this lack of staining is specific. [Figure 17-2] See description of Figure 17-1. [Figure 17-3] See description of Figure 17-1. [Figure 18-1] We show that anti-TREM2 and LILRB4 antibodies specifically deplete TREM2 and LILRB4 bearing cells in vivo, respectively. Control and EL4 transfected cells expressing TREM2 or LILRB4 were mixed at a 1:1 ratio and injected intraperitoneally into WT B6 male mice. After 3 hours, animals were injected with (anti-TREM2 or anti-LILRB4) antibodies, or control human IgG1 or PBS. After 36 hours, mice were sacrificed and collected by peritoneal lavage, and cells recovered from the peritoneum were counted by flow cytometry. [Figure 18-2] See description of Figure 18-1. [Figure 18-3] See description of Figure 18-1. [Figure 19]Figure 1 shows that anti-NSM antibodies reduce tumor growth to the same extent as anti-PD-1 treatment compared to controls. MC38 colon carcinoma was injected into 6 week old male B6 mice. Mice randomized into treatment groups were treated by intraperitoneal injection with the indicated antibodies on days 5, 7, 11, and 15. 75% rank (top outliers excluded, bottom 3 / 4 plotted) shown. Dosing: 200ug / day for PD-1 and Fc control, 40ug, 20ug, 20ug, and 40ug for anti-Pi1.2 (anti-TREM2) antibody injected on days 5, 7, 11, and 15. Tumors were measured with calipers and tumor volumes are shown. [Figure 20A] Receiver operating characteristic (ROC) analysis of BDCA3+ in human melanoma. Figure 20A shows ROC analysis of BDCA3+ vs. CD45+ vs. prognosis using %BDCA3 staining data and anti-PD1 prognostic data. Figure 20B shows ROC analysis of BDCA3+ vs. HLA-DR+ vs. prognosis using %BDCA3 staining data and anti-PD1 prognostic data. [Figure 20B] See legend to Figure 20A. [Figure 21] We show that in primary human HNSC tumor tissue, TREM2 protein is expressed exclusively in the NSM population (CD14+TAM) with little or no expression in CD14-negative CD11c-positive cells, including SDC (BDCA3+DC). Staining with a commercial antibody specific for TREM2 (RnD, clone 237920) was performed on digested human HNSC tumor tissue, compared to a secondary control stain (anti-rat IgG, Jackson Immunoresearch), and analyzed by flow cytometry. This figure shows that in human tumor tissue, NSM gene products are specifically expressed in NSM cells, but not in SDC cells. Populations were gated for viable, CD45+, lineage negative, HLA-DR+, CD11c+, and divided by CD14 expression. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0052] These and other aspects and advantages of the present invention will become apparent from the detailed description and claims that follow. It will be understood that one, some, or all of the features of the various embodiments described herein may be combined to form other embodiments of the present invention.

[0053] Detailed Description For purposes of interpreting this specification, the following definitions shall apply and, whenever appropriate, terms used in the singular shall include the plural and vice versa. In the event that any definition set forth below conflicts with any document incorporated herein by reference, the definition set forth shall control.

[0054] Aspects and embodiments of the invention described herein are understood to include "comprising," "consisting," and "consisting essentially of" aspects and embodiments.

[0055] For all compositions described herein and all methods of using the compositions described herein, the composition may either comprise the recited components or steps or "consist essentially of" the recited components or steps. When a composition is described as "consisting essentially of" the recited components, the composition may include the recited components and may include other components that do not substantially affect the condition being treated, but does not include any other components other than those explicitly recited components that substantially affect the condition being treated, or if the composition includes an extra component other than those recited that substantially affects the condition being treated, the composition does not include the extra component in a concentration or amount sufficient to substantially affect the condition being treated. When a method is described as "consisting essentially of" the recited steps, the method may include the recited steps and may include other steps that do not substantially affect the condition being treated, but the method does not include any other steps other than those explicitly recited that substantially affect the condition being treated. As a non-limiting specific example, when a composition is described as "consisting essentially of" the components, the composition may additionally include any amount of a pharma- ceutically acceptable carrier, vehicle, or diluent, and such components that do not substantially affect the condition being treated.

[0056] The term "optionally," when used sequentially, is intended to include one to all of the listed combinations, and contemplates all subcombinations.

[0057] As used herein, an "effective amount" or "therapeutically effective amount" refers to an amount of a therapeutic compound, such as an anti-NSM antigen binding agent or an anti-NSM antibody, administered to an individual, either alone or in combination with other therapeutic modalities, either as a single dose or as part of a series of doses, that is effective to produce or contribute to a desired therapeutic effect. Examples of desired therapeutic effects are enhancing immune response, slowing or delaying tumor development, stabilizing disease, and ameliorating one or more symptoms. An effective amount may be given in one or more doses.

[0058] As used herein, the term "treating" refers to slowing or reversing the progression of a condition, such as cancer. As used herein, the term "treatment" refers to the act of treating a condition, such as cancer.

[0059] As used herein, "individual" or "subject" refers to any animal classified as a mammal, including humans, domestic and farm animals, as well as zoo, sport, or pet animals, such as dogs, horses, rabbits, cows, pigs, hamsters, gerbils, mice, polecats, rats, cats, and the like. In some embodiments, the individual is a human. In some embodiments, the individual is a mouse.

[0060] As used herein, the term "about" refers to a normal range of error for each value, which is readily understood by one of ordinary skill in the art. Reference to a value or parameter described herein with "about" includes (and describes) embodiments that are directed to the value or parameter itself.

[0061] It must be noted that, in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise.

[0062] For any of the structural and functional properties described herein, methods for determining such properties are known in the art.

[0063] Non-stimulatory myeloid cells (NSM) Provided herein are methods and compositions for disabling and / or detecting unstimulated myeloid cells (NSM), including the use of anti-NSM antibodies. Also provided herein are methods and compositions for targeting and / or detecting unstimulated myeloid cells that express NSM proteins.

[0064] Also provided herein are methods and compositions for disabling and / or detecting unstimulated myeloid cells, including the use of antibodies targeted to non-human homologs of human NSM proteins in non-human individuals.

[0065] As used herein, non-stimulatory myeloid cells are myeloid cells that are not sufficiently effective at stimulating an immune response (e.g., not as effective at stimulating an anti-tumor response in a tumor microenvironment as compared to stimulatory myeloid cells). In some embodiments, non-stimulatory myeloid cells are not as effective at presenting antigens (e.g., tumor antigens) to T cells or are not as effective at stimulating tumor-specific T cell responses as compared to stimulatory myeloid cells. In some embodiments, non-stimulatory myeloid cells may exhibit a reduced ability to uptake, process, and / or present tumor-associated antigens to T cells as compared to stimulatory myeloid cells. Non-stimulatory myeloid cells may contain reduced or no cytotoxic T lymphocyte restimulation capacity, or in some cases may not be able to stimulate effective tumor cell killing. Unstimulated myeloid cells may exhibit lower expression of genes and cell surface markers involved in antigen processing, antigen presentation, and / or antigen costimulation compared to stimulated myeloid cells, including, but not limited to, CD80, CD86, MHC1, and MHCII.

[0066] Unstimulated myeloid cells may exhibit lower expression of genes associated with cross-presentation, costimulation, and / or stimulatory cytokines and higher expression of the anti-inflammatory cytokine IL-10 compared to stimulated myeloid cells, including, but not limited to, any one or more of TAP1, TAP2, PSMB8, PSMB9, TAPBP, PSME2, ​​CD24a, CD274, BTLA, CD40, CD244, ICOSL, ICAM1, TIM3, PDL2, RANK, FLT3, CSF2RB, CSF2RB2, CSF2RA, IL12b, XCR1, CCR7, CCR2, CCL22, CXCL9, and CCL5. In some embodiments, unstimulated myeloid cells are dependent on the transcription factor IRF4 and the cytokines GM-CSF or CSF-1 for differentiation and survival. In some embodiments, unstimulated myeloid cells can contribute to tumor angiogenesis by secreting vascular endothelial growth factor (VEGF) and nitric oxide synthase (NOS), and can support tumor growth by secreting epidermal growth factor (EGF).

[0067] In some embodiments, the unstimulated myeloid cells are tumor-associated macrophages (TAMs) or dendritic cells (DCs). In some embodiments, the unstimulated myeloid cells are not dendritic cells (DCs).

[0068] In some embodiments, the unstimulated myeloid cells are tumor-associated macrophages (TAMs). TAMs are macrophages that reside near or within cancerous tumors and are derived from circulating monocytes or tissue-resident macrophages.

[0069] In some embodiments, unstimulated and stimulated myeloid cells are differentiated based on the markers they express or that they selectively express. The expression level of a cell surface marker may be described as "+" or "positive". The absence of a cell surface marker may be described as "-" or "negative". The expression level of a cell surface marker may be further described as "high" (cells expressing high levels of the marker) or "low" (cells expressing low levels of the marker), which indicates the relative expression level of each marker on the cell surface. The level of the marker may be determined by various methods known in the art, such as immunostaining and FACS analysis, or gel electrophoresis and Western blotting.

[0070] In some embodiments, the non-stimulatory myeloid cells are dendritic cells (DCs). In some embodiments, dendritic cells can be distinguished by spike-like or dendritic morphology. In one embodiment, the non-stimulatory dendritic cells are at least CD45+, HLA-DR+, CD14-, CD11c+, and BDCA1+ (also referred to as DC1 cells). In one embodiment, the non-stimulatory dendritic cells are not CD45+, HLA-DR+, CD14-, CD11c+, and BDCA3+ (also referred to as DC2 cells). In one embodiment, dendritic cells that are CD45+, HLA-DR+, CD14-, CD11c+, and BDCA3+ are stimulatory myeloid cells.

[0071] In some embodiments, the unstimulated myeloid cells are tumor associated macrophages. In some embodiments, for example in humans, the unstimulated tumor associated macrophages are at least CD45+, HLA-DR+, CD14+. In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , CD11b + In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR +, CD14 + , CD11c + In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , BDCA3 - In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11c + In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , CD11b + , and CD11c + In some embodiments, the unstimulated tumor associated macrophages are at least CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + It is.

[0072] In some embodiments, the methods and compositions of the invention are useful for targeting TAMs and DCs in other animals, such as mice. In such embodiments, contacting of mouse TAMs and DCs with NSM antibodies is performed. In one embodiment, for example in mice, tumor associated macrophages are at least CD45+, HLA-DR+, CD14+, CD11b 高 , and CD11c 低(also referred to as TAM1). In one embodiment, for example in mice, tumor-associated macrophages are at least CD45+, HLA-DR+, CD14+, CD11b 低 , and CD11c 高 (also referred to as TAM2). 高 The term "macrophage" refers to a macrophage that expresses high levels of CD11b. 低 The term "macrophage" refers to CD11b 高 The term "CD11c" refers to a macrophage that expresses a level of CD11b on its surface that is substantially lower than that of macrophages. 高 The term "CD11c" refers to macrophages that express high levels of CD11c. 低 The term "macrophage" refers to Cd11c 高 It concerns macrophages that express substantially lower levels of CD11c on their surface than that of macrophages.

[0073] In some embodiments, the unstimulated myeloid cells of the invention comprise one or more of TAM cells and DC1 cells.

[0074] In some embodiments, for example in a mouse, the unstimulated myeloid cells of the invention comprise one or more of TAM1, TAM2, and DC1 cells, In such embodiments, contacting of the unstimulated myeloid cells of the invention with an NSM antibody is performed.

[0075] In some embodiments, the unstimulated myeloid cells are localized within the periphery of a neoplastic lesion or in the ducts of a cancerous tumor, where they come into contact with allogeneic T cells, hi one embodiment, the localization of the unstimulated myeloid cells is modified, such that they no longer localize to the periphery of the tumor or no longer come into contact with T cells.

[0076] In some embodiments, the unstimulated myeloid cells are present in an immune cell population that includes stimulated and unstimulated myeloid cells. In some embodiments, the unstimulated myeloid cells are present in an immune cell population that includes only unstimulated myeloid cells. The immune cell populations of the present invention may be pure, allogeneic, xenogeneic, derived from a variety of sources (e.g., diseased tissue, tumor tissue, healthy tissue, cell banks), maintained in primary cell culture, maintained in immortalized culture, and / or maintained in ex vivo culture.

[0077] In some embodiments, the unstimulated myeloid cells are tumor-associated macrophages.

[0078] In some embodiments, the unstimulated myeloid cells are dendritic cells.

[0079] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA1 + The present invention consists essentially of cells which are

[0080] In some embodiments, the unstimulated myeloid cells are CD45 +, HLA-DR + , CD14 + , BDCA3 - In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , BDCA3 - The present invention consists essentially of cells which are

[0081] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + In some embodiments, the unstimulated myeloid cells comprise cells that are CD45 + , HLA-DR + , CD14 + , CD11b + The present invention consists essentially of cells which are

[0082] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11c +In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11c + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , CD11c + The present invention consists essentially of cells which are

[0083] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , and CD11c + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , BDCA3 - , and CD11c + The present invention consists essentially of cells which are

[0084] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3- , CD11b + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + The present invention consists essentially of cells which are

[0085] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , CD11b + , and CD11c + The present invention consists essentially of cells which are

[0086] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + In some embodiments, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , BDCA3 - , CD11b + , and CD11c + The present invention consists essentially of cells which are

[0087] In some embodiments, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + In some embodiments, the unstimulated myeloid cells are not CD45 + , HLA-DR + , CD14 - , CD11c + , and BDCA3 + Includes cells that are not

[0088] In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 +, CD11b 高 , and CD11c 低 In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b 高 , and CD11c 低 In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b 高 , and CD11c 低 In some embodiments, for example in mice, the unstimulated myeloid cells are comprised of cells that are CD45 + , HLA-DR + , CD14 + , CD11b 高 , and CD11c 低 In such embodiments, contacting of unstimulated mouse myeloid cells with the NSM antibody is performed.

[0089] In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b 低 , and CD11c 高 In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b 低 , and CD11c 高 In some embodiments, for example in mice, the unstimulated myeloid cells are CD45 + , HLA-DR + , CD14 + , CD11b 低 , and CD11c 高 In some embodiments, for example in mice, the unstimulated myeloid cells are comprised of cells that are CD45 +, HLA-DR + , CD14 + , CD11b 低 , and CD11c 高 In such embodiments, contacting of unstimulated mouse myeloid cells with the NSM antibody is performed.

[0090] In some embodiments, the unstimulated myeloid cells are present in cancer tissue.

[0091] In some embodiments, the immune cell population is present in cancer tissue.

[0092] In some embodiments, the non-stimulatory cells and the stimulatory myeloid cells are present in cancer tissue.

[0093] In some embodiments, the biological sample comprises an immune cell population that includes unstimulated myeloid cells and stimulated myeloid cells.

[0094] NSM cells may collectively refer to DC1 cells, TAM1 cells, and TAM2 cells present in tumor tissues, and may be distinguished from other cell types by expressing NSM cell markers. For example, genes and associated proteins that are more abundantly expressed or transcribed in NSM cells compared to those in SDCs may serve as NSM markers. An exemplary NSM marker is CD11b. Additional examples of NSM markers are listed in Table A. NSM cells may express TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119 on their cell surface. In some embodiments, NSM cells do not express at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1.

[0095] In one embodiment, the NSM cells are tumor-infiltrating myeloid cells that express one or more of the NSM marker genes set forth in Table A. In another embodiment, the NSM cells are tumor myeloid cells that express three or more of the NSM markers set forth in Table A. In another embodiment, the NSM cells are tumor myeloid cells that express most or all of the NSM markers set forth in Table A. In another embodiment, the NSM cells are identified as tumor myeloid cells that express MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1. (Table A) TIFF2025027013000002.tif86128

[0096] Stimulatory Myeloid Cell As used herein, stimulatory myeloid cells (also referred to in certain aspects as SDCs) are myeloid cells that are effective at stimulating an immune response (e.g., more effective at stimulating an anti-tumor response in a tumor microenvironment compared to non-stimulatory myeloid cells). In some embodiments, stimulatory myeloid cells are more effective at presenting antigens (e.g., tumor antigens) to T cells or are useful for stimulating tumor-specific T cell responses compared to non-stimulatory myeloid cells. In some embodiments, stimulatory myeloid cells may exhibit a higher capacity for uptake, processing, and / or presentation of tumor-associated antigens to T cells compared to non-stimulatory myeloid cells. Stimulatory myeloid cells may have a higher capacity for restimulation of cytotoxic T lymphocytes or, in some cases, may be able to stimulate effective tumor cell killing compared to non-stimulatory myeloid cells. Stimulated myeloid cells may exhibit increased expression of genes and cell surface markers involved in antigen processing, antigen presentation, and / or antigen costimulation, including, but not limited to, CD80, CD86, MHC1, and MHCII, compared to non-stimulated myeloid cells.

[0097] Exemplary stimulatory myeloid cell markers are listed in Table A. For example, in human SDC, expression of Xcr1, Clec9a, and BDCA3 (CD141) are markers of SDC identity. It will be noted that, although CD103 is not expressed in human SDC, in mice, CD103 can also be used as a strong marker of SDC identity.

[0098] In one embodiment, SDCs are tumor-infiltrating myeloid cells that have a dendritic cell identity and also express one or more of the SDC markers listed in Table A. In another embodiment, SDCs are tumor-infiltrating myeloid cells that have a dendritic cell identity and also express two, three, four, five, six, seven, eight, nine, or all of the SDC markers listed in Table A. In another embodiment, SDCs are identified as tumor-infiltrating myeloid dendritic cells that express BDCA3, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, XCR1, and CLEC9A. SDC cells may express at least one of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1. In some embodiments, SDCs do not substantially express TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and / or TMEM119 on their cell surface. In some embodiments, SDCs do not substantially express C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and / or LILRB4. Flow cytometry and PCR, among other art-recognized assays, can be used to assess the expression levels of the markers disclosed herein.

[0099] Stimulatory myeloid cells express CD45 + , HLA-DR + , CD14 - , CD11c+ , and BDCA3 + The stimulatory myeloid cells may be CD45 + , HLA-DR + , and BDCA3 + The stimulatory myeloid cells may be CD45 + , HLA-DR + , CD14 - , and BDCA3 + The stimulatory myeloid cells may be CD45 + , HLA-DR + , CD11c + , and BDCA3 + It could be.

[0100] antibody The present application provides antibodies and compositions, including antibodies that bind to NSM proteins, including antibodies that disable unstimulated myeloid cells.

[0101] The present application provides antibodies and compositions, including antibodies that bind to NSM proteins, including antibodies that disable unstimulated myeloid cells.

[0102] As used herein, an "antibody" or "immunoglobulin" refers to a polypeptide substantially encoded by an immunoglobulin gene or set of immunoglobulin genes, or an analyte-binding fragment thereof, which specifically binds to and specifically recognizes an analyte (e.g., an antigen). Recognized immunoglobulin genes include the kappa, lambda, alpha, gamma, delta, epsilon, and mu constant region genes, as well as a myriad of immunoglobulin variable region genes. Light chains are classified as either kappa or lambda. The "class" of an antibody or immunoglobulin refers to the type of constant domain or constant region possessed by its heavy chain. There are five major classes of antibodies: IgA, IgD, IgE, IgG, and IgM. Some of these may be further divided into subclasses (isotypes), such as IgG1, IgG2, IgG3, IgG4, IgG5, IgG6, IgG7, IgG8, IgG9, IgG10, IgG11, IgG12, IgG13, IgG14, IgG15, IgG16, IgG17, IgG18, IgG19 ...9, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19, IgG19 2 , IgG 3 , IgG 4 , IgA1, and IgA 2 The heavy-chain constant domains that correspond to the different classes of immunoglobulins are called α, δ, ε, γ, and μ, respectively.

[0103] An exemplary immunoglobulin (antibody) structural unit consists of two pairs of polypeptide chains, each pair having one "light" chain (about 25 kD) and one "heavy" chain (about 50-70 kD). The N-terminal domain of each chain defines a variable region having about 100-110 or more amino acids, primarily responsible for antigen recognition. The terms variable light chain (VL) and variable heavy chain (VH) refer to these light and heavy chain domains, respectively. The IgG1 heavy chain consists of, from N- to C-terminus, a VH domain, a CH1 domain, a CH2 domain, and a CH3 domain, respectively. The light chain consists of, from N- to C-terminus, a VL domain and a CL domain. The IgG1 heavy chain contains a hinge between the CH1 and CH2 domains. In certain embodiments, the immunoglobulin construct comprises at least one immunoglobulin domain derived from IgG, IgM, IgA, IgD, or IgE linked to a therapeutic polypeptide. In some embodiments, the immunoglobulin domains found in the antibodies provided herein are derived or obtained from immunoglobulin-based constructs, such as diabodies or nanobodies. In certain embodiments, the immunoglobulin constructs described herein comprise at least one immunoglobulin domain derived from a heavy chain antibody, such as a camelid antibody. In certain embodiments, the immunoglobulin constructs provided herein comprise at least one immunoglobulin domain derived from a mammalian antibody, such as a bovine antibody, a human antibody, a camelid antibody, a murine antibody, or any chimeric antibody.

[0104] As used herein, the term "hypervariable region" or "HVR" refers to each of the regions of an antibody variable domain that are sequence hypervariable and / or form structurally defined loops ("hypervariable loops"). Generally, a natural antibody with four chains contains six HVRs, three in the VH (H1, H2, H3) and three in the VL (L1, L2, L3). HVRs generally contain amino acid residues from the hypervariable loops and / or from the complementarity determining regions (CDRs), which have the highest sequence variability and / or are involved in antigen recognition. With the exception of CDR1 in VH, CDRs generally contain the amino acid residues that form the hypervariable loops. Hypervariable regions (HVRs) are also referred to as "complementarity determining regions" (CDRs), and these terms are used interchangeably herein in reference to the portions of the variable regions that form the antigen binding region. This particular region is described by Kabat et al., USDept. of Health and Human Services, Sequences of Proteins of Immunological Interest (1983), and Chothia et al., J Mol Biol 196:901-917 (1987), in which the definitions include overlapping or subsets of amino acid residues when compared to each other. Nevertheless, it is intended that application of either definition to refer to the CDR of an antibody or variant thereof is within the scope of the term as defined and used herein. The exact number of residues that encompass a particular CDR will vary depending on the sequence and size of the CDR. One of ordinary skill in the art can routinely determine which residues comprise a particular CDR by considering the variable region amino acid sequence of the antibody.

[0105] As used herein, the term "single chain" refers to a molecule comprising amino acid monomers linearly linked by peptide bonds. In certain such embodiments, in a single chain Fab molecule, the C-terminus of the Fab light chain is linked to the N-terminus of the Fab heavy chain. As described in more detail herein, in an scFv, the C-terminus of the variable domain of the light chain (VL) is linked by a polypeptide chain to the N-terminus of the variable domain of the heavy chain (VH). Alternatively, an scFv comprises a polypeptide chain in which the C-terminus of the VH is linked by a polypeptide chain to the N-terminus of the VL.

[0106] The "Fab fragment" (also called antigen-binding fragment) contains the constant domain of the light chain (CL) and the first constant domain of the heavy chain (CH1) in addition to the variable domains VL and VH present in the light and heavy chains, respectively. The variable domain contains the complementarity determining loops (CDRs, also called hypervariable regions) involved in antigen binding. The variable domain contains the complementarity determining loops (CDRs, also called hypervariable regions) involved in antigen binding. Fab' fragments differ from Fab fragments by the addition of a few residues at the carboxy terminus of the heavy chain CH1 domain including one or more cysteines from the antibody hinge region.

[0107] A "single-chain Fv" or "scFv" comprises the VH and VL domains of an antibody, wherein these domains are present in a single polypeptide chain. In one embodiment, the Fv polypeptide further comprises a polypeptide linker between the VH and VL domains which enables the scFv to form the desired structure for antigen binding. For a review of scFvs, see Pluckthun in The Pharmacology of Monoclonal Antibodies, vol. 113, Rosenburg and Moore eds., Springer-Verlag, New York, pp. 269-315 (1994). HER2 antibody scFv fragments are described in WO93 / 16185, U.S. Patent No. 5,571,894, and U.S. Patent No. 5,587,458.

[0108] The "single domain antibody" or "sdAb" format is an individual immunoglobulin domain. Sdabs are extremely stable and easy to express as fusion partners with the Fc chain of an antibody (Harmsen MM, De Haard HJ (2007). "Properties, production, and applications of camelid single-domain antibody fragments". Appl. Microbiol Biotechnol. 77(1):13-22).

[0109] The term "Fc domain" or "Fc region" as used herein is used to define a C-terminal region of an immunoglobulin heavy chain that contains at least a portion of the constant region. The term includes native sequence Fc regions and variant Fc regions. Unless otherwise specified, the numbering of amino acid residues in an Fc region or constant region is according to the EU numbering system. The EU numbering system, also known as the EU index, is as described in Kabat et al, Sequences of Proteins of Immunological Interest, 5th Ed. Public Health Service, National Institutes of Health, Bethesda, MD, 1991. As used herein, the "Fc polypeptide" of a dimeric Fc refers to one of the two polypeptides that form the dimeric Fc domain, i.e., a polypeptide that contains the C-terminal constant region of an immunoglobulin heavy chain and has the ability to achieve stable self-association. For example, the Fc polypeptide of a dimeric IgGFc contains the CH2 constant domain sequence of an IgG and the CH3 constant domain sequence of an IgG. The classes of Fc can be IgA, IgD, IgE, IgG, and IgM, and some of these classes can be further divided into subclasses (isotypes). 1 , IgG 2 , IgG 3 , IgG 4 , IgA 1 , and IgA 2 It is.

[0110] The terms "Fc receptor" and "FcR" are used to describe receptors that bind to the Fc region of an antibody. For example, an FcR may be a native-sequence human FcR. In general, FcRs are those that bind IgG antibodies (gamma receptors) and include receptors of the FcγRI, FcγRII, and FcγRIII subclasses, including allelic variants or spliced ​​forms of such receptors. FcγRII receptors include FcγRIIA ("activating receptors") and FcγRIIB (inhibitory receptors), which have similar amino acid sequences that differ primarily in their cytoplasmic domains. Immunoglobulins of other isotypes may also bind to certain FcRs (see, e.g., Janeway et al., Immuno Biology: the immune system in health and disease, (Elsevier Science Ltd., NY) (4th ed., 1999)). FcγRIIA, an activating receptor, contains an immunoreceptor tyrosine-based activation motif (ITAM) in its cytoplasmic domain. The inhibitory receptor FcγRIIB contains an immunoreceptor tyrosine-based inhibitory motif (ITIM) in its cytoplasmic domain (reviewed in Daeron, Annu. Rev. Immunol. 15:203-234 (1997)). FcRs are reviewed in Ravetch and Kinet, Annu. Rev. Immunol 9:457-92 (1991); Capel et al., Immunomethods 4:25-34 (1994); and de Haas et al., J. Lab. Clin. Med. 126:330-41 (1995). Other FcRs, including those to be identified in the future, are encompassed by the term "FcR" as used herein. The term also includes the neonatal receptor, FcRn, which is responsible for the transfer of maternal IgG to the fetus (Guyer et al., J. Immunol. 117:587 (1976), and Kim et al., J. Immunol. 24:249 (1994)).

[0111] Modification of CH2 domain can affect FcR binding to Fc. Many amino acid modifications in Fc region are known in the art, which selectively change the affinity of Fc for different Fc gamma receptors. In some embodiments, Fc contains one or more modifications that promote selective binding of Fc-gamma receptors.

[0112] Examples of mutations that alter the binding of FcR to Fc are described below.

[0113] S298A / E333A / K334A, S298A / E333A / K334A / K326A (Lu Y, Vernes JM, Chiang N, et al. J Immunol Methods.2011 Feb 28;365(1-2):132-41),

[0114] F243L / R292P / Y300L / V305I / P396L, F243L / R292P / Y300L / L235V / P396L (Stavenhagen JB, Gorlatov S, Tuaillon N, et al. Cancer Res. 2007 Sep 15;67(18):8882-90, Nordstrom JL, Gorlatov S, Zhang W, et al.Breast Cancer Res.2011 Nov 30;13(6):R123),

[0115] F243L(Stewart R,Thom G,Levens M,et al.Protein Eng Des Sel.2011 Sep;24(9):671-8.), S298A / E333A / K334A(Shields RL,Namenuk AK,Hong K,et al.J Biol Chem.2001 Mar 2;276(9):6591-604),

[0116] S239D / I332E / A330L, S239D / I332E (Lazar GA, Dang W, Karki S, et al. Proc Natl Acad Sci US A.2006 Mar 14;103(11):4005-10),

[0117] S239D / S267E, S267E / L328F (Chu SY, Vostiar I, Karki S, et al.Mol Immunol.2008 Sep;45(15):3926-33),

[0118] S239D / D265S / S298A / I332E, S239E / S298A / K326A / A327H, G237F / S298A / A330L / I332E, S239D / I332E / S298A, S239D / K326E / A330L / I332E / S298A, G236A / S239D / D270L / I332E, S239E / S267E / H268D, L234F / S267E / N325L, G237F / V266L / S267D, and other mutations described in WO2011 / 120134 and WO2011 / 120135, which are incorporated herein by reference. Mutations described on page 283 of Therapeutic Antibody Engineering (by William R. Strohl and Lila M. Strohl, Woodhead Publishing series in Biomedicine No 11, ISBN 1 907568 37 9, Oct 2012).

[0119] In some embodiments, the antibodies described herein contain modifications to improve their ability to mediate effector functions. Such modifications are known in the art and include afucosylation, or affinity engineering of Fc to activating receptors, and affinity engineering of Fc to C1q to target CDC, the latter being primarily affinity engineering of Fc to FCGR3a to target ADCC. Table B below summarizes various designs reported in the literature for engineering effector functions.

[0120] Methods for producing antibodies with little or no fucose at the Fc glycosylation site (Asn297 in EU numbering) without altering the amino acid sequence are well known in the art. GlymaX® technology (ProBioGen AG) is based on introducing a gene for an enzyme that alters the cellular pathway of fucose biosynthesis into cells used for antibody production. This prevents the antibody-producing cells from adding the sugar "fucose" to the N-linked antibody carbohydrate moiety. (von Horsten et al. (2010) Glycobiology. 2010 Dec;20(12):1607-18. Another approach to obtaining antibodies with reduced levels of fucosylation can be found in U.S. Pat. No. 8,409,572, which teaches selecting cell lines for antibody production for the ability of the cells to produce antibodies with reduced levels of fucosylation. Antibodies can be fully afucosylated, meaning that the antibody has no detectable fucose, or partially afucosylated, where partial afucosylation means that the isolated antibody has less than 95%, 85%, 75%, 65%, 55%, 45%, 35%, 25%, 15%, or 5% of the amount of fucose typically found in a similar antibody produced by a mammalian expression system.

[0121] Thus, in one embodiment, the antibodies described herein may comprise a dimeric Fc that contains one or more of the amino acid modifications that improve effector function, as shown in Table B. In another embodiment, the antibodies may be afucosylated to improve effector function. (Table B) Engineering of CH2 domains and effector functions TIFF2025027013000003.tif128149

[0122] Fc modifications that reduce FcγR and / or complement binding and / or effector function are known in the art. Recent publications have described strategies that have been used to engineer antibodies to reduce or silence their effector function (see Strohl, WR (2009), Curr Opin Biotech 20:685-691, and Strohl, WR and Strohl LM, "Antibody Fc engineering for optimal antibody performance" In Therapeutic Antibody Engineering, Cambridge: Woodhead Publishing (2012), pp225-249). These strategies include reducing effector function through glycosylation modifications, using IgG2 / IgG4 scaffolds, or introducing mutations into the hinge or CH2 regions of Fc. For example, U.S. Patent Publication No. 2011 / 0212087 (Strohl), International Patent Publication No. WO2006 / 105338 (Xencor), U.S. Patent Publication No. 2012 / 0225058 (Xencor), U.S. Patent Publication No. 2012 / 0251531 (Genentech), and Strop et al ((2012) J. Mol. Biol. 420:204-219) describe modifications that specifically reduce binding of FcγR or complement to Fc.

[0123] Specific non-limiting examples of known amino acid modifications that decrease binding of FcγR or complement to Fc include those set forth in the table below. (Table C) Modifications that reduce FcγR or complement binding to Fc TIFF2025027013000004.tif109128

[0124] In some embodiments, the antibody has antibody-dependent cellular cytotoxicity (ADCC) activity. ADCC can occur when an antibody binds to a surface antigen of a pathogenic or tumorigenic target cell. An effector cell that has an Fc gamma receptor (FcγR or FCGR) on its cell surface recognizes and binds to the Fc region of the antibody bound to the target cell. Such effector cells include cytotoxic T cells, natural killer (NK) cells, macrophages, neutrophils, eosinophils, dendritic cells, or monocytes. Such binding can cause activation of intracellular signaling pathways that lead to cell death. In certain embodiments, the immunoglobulin Fc region subtype (isotype) of the antibody includes human IgG1 and IgG3. As used herein, ADCC refers to a cell-mediated reaction in which non-specific cytotoxic cells expressing Fc receptors (FcR), such as natural killer (NK) cells, neutrophils, and macrophages, recognize antibodies bound to target cells and subsequently cause lysis of the target cells. NK cells, the primary cells intended to mediate ADCC, express only FcγRIII, whereas monocytes express FcγRI, FcγRII, and FcγRIII. Expression of FcR on hematopoietic cells is summarized in Table 3 on page 464 of Ravetch and Kinet, Annu. Rev. Immunol 9:457-92 (1991). To assess the ADCC activity of a molecule of interest, an in vitro ADCC assay, such as that described in U.S. Pat. No. 5,500,362 or 5,821,337, may be performed. Useful effector cells for such assays include peripheral blood mononuclear cells (PBMC) and natural killer (NK) cells. Alternatively, or additionally, ADCC activity of the molecule of interest may be assessed in vivo, e.g., in an animal model such as that disclosed in Clynes et al., Proc. Natl. Acad. Sci. (USA) 95:652-656 (1998).

[0125] In some embodiments, the antibody has complement-dependent cytotoxicity (CDC) activity. Antibody-induced CDC is mediated through proteins of the classical complement cascade and is triggered by the binding of the complement protein C1q to the antibody. Binding of the antibody Fc region to C1q induces activation of the complement cascade. In certain embodiments, the immunoglobulin Fc region subtype (isotype) of the antibody includes human IgG1 and IgG3. As used herein, CDC refers to the ability of a molecule to lyse a target in the presence of complement. The complement activation pathway is initiated by the binding of the first component of the complement system (C1q) to a molecule (e.g., a polypeptide (e.g., an antibody)) complexed with a cognate antigen. To assess complement activation, a CDC assay may be performed, e.g., as described in Gazzano-Santoro et al., J. Immunol. Methods 202:163 (1996).

[0126] The anti-NSM antibody may target at least one, two, three, four or more of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119. The anti-NSM antibody may target TREM2. The anti-NSM antibody may target MS4A7. In some embodiments, the anti-NSM antibody does not target one or more of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and / or TMEM119. In some embodiments, the anti-NSM antibody does not target LILRB4. In some embodiments, the anti-NSM antibody does not bind to TREM2. In some embodiments, the anti-NSM antibody does not bind to MS4A7. In some embodiments, the anti-NSM antibody does not bind to C5AR1. In some embodiments, the anti-NSM antibody does not bind to LYVE1. In some embodiments, the anti-NSM antibody does not bind to ABCC3. In some embodiments, the anti-NSM antibody does not bind to LILRB4. In some embodiments, the anti-NSM antibody does not bind to MRC1 / CD206. In some embodiments, the anti-NSM antibody does not bind to SIGLEC1. In some embodiments, the anti-NSM antibody does not bind to STAB1. In some embodiments, the anti-NSM antibody does not bind to TMEM37. In some embodiments, the anti-NSM antibody does not bind to MERTK. In some embodiments, the anti-NSM antibody does not bind to TMEM119. In some embodiments, the anti-NSM antibody does not bind to TLR7.

[0127] In some embodiments, the antibody has antibody-dependent cellular phagocytosis (ADCP) activity. ADCP can occur when an antibody binds to a surface antigen of a pathogenic or tumorigenic target cell. Phagocytic cells, including monocytes and macrophages, that have Fc receptors on their cell surface recognize and bind to the Fc region of an antibody bound to a target cell. Binding of the Fc receptor to an antibody bound to a target cell can initiate phagocytosis of the target cell. ADCP can be considered a form of ADCC.

[0128] In some embodiments, the antibody has the ability to form an immune complex, for example, an immune complex may be a tumor cell coated with the antibody.

[0129] In some embodiments, the anti-NSM antibodies do not substantially bind to myeloid cells present outside of the cancer tissue, hi some embodiments, the anti-NSM antibodies do not substantially bind to stimulatory myeloid cells present in the cancer tissue.

[0130] In some embodiments, the antibody is a monoclonal antibody.

[0131] In some embodiments, the antibody is a polyclonal antibody.

[0132] In some embodiments, the antibody is produced by a hybridoma, hi other embodiments, the antibody is produced by a recombinant cell that has been engineered to express the desired variable and constant domains.

[0133] In some embodiments, the antibody may be a single chain antibody or other antibody derivative or variant thereof that retains the antigen specificity and lower hinge region.

[0134] In some embodiments, the antibody may be a polyfunctional antibody, a recombinant antibody, a human antibody, a humanized antibody, a fragment thereof, or a variant thereof. In certain embodiments, the antibody fragment or derivative thereof is selected from a Fab fragment, a Fab'2 fragment, a CDR, and an ScFv.

[0135] Human antibodies include all antibodies having variable and constant regions derived from human immunoglobulin sequences. In one embodiment, all of the variable and constant domains are derived from human immunoglobulin sequences (fully human antibodies). Such antibodies may be prepared in a variety of ways, including immunizing mice with an antigen of interest that have been genetically modified to express antibodies derived from genes encoding human heavy and / or light chains.

[0136] A humanized antibody has a sequence that differs from that of an antibody derived from a non-human species by the presence of one or more amino acid substitutions, deletions, and / or additions such that the humanized antibody is less likely to induce and / or induces a lesser degree of immune response when administered to a human subject compared to a non-human species antibody. In one embodiment, certain amino acids in the framework and constant domains of the heavy and / or light chains of a non-human species antibody are modified to produce a humanized antibody. In another embodiment, the constant domain(s) from a human antibody are fused to the variable domain(s) of a non-human species. In another embodiment, one or more amino acid residues in one or more CDR sequences of a non-human antibody are altered to reduce the immunogenic potential of the non-human antibody when administered to a human subject, and none of the altered amino acid residues are critical for the antibody to immunospecifically bind to its antigen, or the changes made to the amino acid sequence are conservative changes, such that the binding of the humanized antibody to the antigen is not significantly impaired compared to the binding of the non-human antibody to the antigen. Examples of methods for preparing humanized antibodies can be found in US Pat. Nos. 6,054,297, 5,886,152, and 5,877,293.

[0137] A chimeric antibody refers to an antibody that contains one or more regions derived from one antibody and one or more regions derived from one or more other, different antibodies.

[0138] In some embodiments, the antibody is specific for a surface antigen, such as an NSM protein. In some embodiments, the therapeutic antibody is specific for a tumor antigen (e.g., a molecule specifically expressed by tumor cells). In certain embodiments, the therapeutic antibody may have a human or non-human primate IgG1 or IgG3 Fc portion.

[0139] In some embodiments, the antibody is linked or conjugated to an effector molecule, hi certain embodiments, the antibody is conjugated to at least one therapeutic agent selected from the group consisting of a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulator, an antiangiogenic agent, a proapoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment.

[0140] In some embodiments, the antibody is an agonist antibody. An agonist antibody can induce (e.g., enhance) one or more activities or functions of an NSM after the antibody binds to an NSM protein expressed in a cell. An agonist antibody can bind to and activate an NSM, causing changes in cell proliferation or altering antigen-presenting ability. An agonist antibody can bind to and activate an NSM, triggering intracellular signaling pathways that lead to alterations in cell proliferation or apoptosis.

[0141] In some embodiments, the antibody is an antagonist antibody. An antagonist antibody can block (e.g., reduce) one or more activities or functions of NSM after the antibody binds to an NSM protein expressed in a cell. For example, an antagonist antibody can bind to one or more NSM proteins and block the binding of a ligand to the NSM protein, thereby preventing cell differentiation and proliferation or altering antigen-presenting ability. An antagonist antibody can bind to an NSM protein and prevent activation of the NSM protein by its ligand, thereby altering intracellular signaling pathways that contribute to cell proliferation and survival.

[0142] In some embodiments, the antibody is a depleting antibody. A depleting antibody is one that will kill unstimulated myeloid cells when the molecule comes into contact through the interaction of the antibody with other immune cells. For example, when the antibody binds to a cell bearing an NSM protein, the antibody can bind complement proteins and induce complement-dependent cell lysis. When the antibody binds to a cell bearing an NSM protein, the antibody can also trigger nearby cells with Fc receptors to kill the cell bearing the NSM protein by antibody-dependent cell-mediated cytotoxicity (ADCC).

[0143] In some embodiments, the antibody is a neutralizing antibody, and the antibody neutralizes one or more biological activities of NSM. In some embodiments, the NSM protein is expressed on the surface of unstimulated myeloid cells and the antibody recognizes the extracellular domain of the NSM protein.

[0144] In some embodiments, the antibody is selective for (binds preferentially to) NSM. In certain embodiments, antibodies that selectively bind to NSM have a dissociation constant (Kd) in the range of 0.0001 nM to 1 μM. In certain embodiments, the antibody specifically binds to an epitope of an NSM protein that is conserved among proteins from different species. In other embodiments, selective binding includes, but is not necessarily exclusive binding.

[0145] In one embodiment, an anti-NSM antibody bound to its target is responsible for inducing in vivo depletion of the unstimulated myeloid cells to which it has bound. In some embodiments, the effector proteins induced by the clustered antibodies can induce a variety of responses, including release of inflammatory cytokines, control of antigen production, endocytosis, or cell death. In one embodiment, the antibody has the ability to recruit and activate complement, or to mediate antibody-dependent cell-mediated cytotoxicity (ADCC) in vivo, or to mediate phagocytosis in vivo by binding to Fc receptors. Upon binding, the antibody may deplete unstimulated myeloid cells by inducing apoptosis or necrosis of the unstimulated myeloid cells.

[0146] In some embodiments, the antibody is an IgG1 antibody.

[0147] In some embodiments, the antibody is an IgG3 antibody.

[0148] In some embodiments, the antibody is not an IgG2 antibody.

[0149] In some embodiments, the antibody is not an IgG4 antibody.

[0150] In some embodiments, disabling of unstimulated myeloid cells is performed in vitro and is achieved by a) killing of unstimulated myeloid cells, b) depletion of unstimulated myeloid cells with magnetic beads, or c) sorting of unstimulated myeloid cells by fluorescence activated cell sorting (FACS).

[0151] In certain embodiments, the antibodies provided herein have a dissociation constant (Kd) in the range of 0.0001 nM to 1 μM. For example, the Kd of an antibody can be in the range of about 1 μM, about 100 nM, about 50 nM, about 10 nM, about 1 nM, about 500 pM, about 100 pM, or about 50 pM to any of about 2 pM, about 5 pM, about 10 pM, about 15 pM, about 20 pM, or about 40 pM.

[0152] In some embodiments, for in vivo administration of anti-NSM antibodies described herein, typical dosages may vary from about 10 ng / kg to up to about 100 mg / kg or more of individual body weight per day, preferably from about 1 mg / kg / day to 10 mg / kg / day, depending on the route of administration. For repeated administration over a period of several days or longer, treatment is maintained until a desired suppression of symptoms is achieved, depending on the severity of the disease or disorder being treated. An exemplary dosing regimen includes administration of an initial dose of anti-NSM antibody that is about 2 mg / kg, followed by a maintenance dose of about 1 mg / kg administered once a week for every two weeks. Other dosing regimens may be used depending on the pharmacokinetic decay pattern the physician wishes to achieve. For example, dosing of an individual 1 to 21 times per week is contemplated herein. In certain embodiments, a dosage range of about 3 μg / kg to about 2 mg / kg (such as about 3 μg / kg, about 10 μg / kg, about 30 μg / kg, about 100 μg / kg, about 300 μg / kg, about 1 mg / kg, and about 2 mg / kg) may be used. In certain embodiments, the dosing frequency is three times a day, twice a day, once a day, every other day, once a week, once every two weeks, once every four weeks, once every five weeks, once every six weeks, once every seven weeks, once every eight weeks, once every nine weeks, once every ten weeks, or once a month, once every two months, once every three months, or longer. Progress of treatment is easily monitored by conventional techniques and assays. Dosing regimens involving administration of anti-NSM antibodies can be varied over time, regardless of the dose used.

[0153] In certain embodiments, the antibody is conjugated to a drug, and the drug is, for example, a toxin, a chemotherapeutic agent, an immunomodulator, or a radioisotope. Several methods for preparing ADCs (antibody drug conjugates) are known in the art, and are described, for example, in U.S. Patent No. 8,624,003 (Pott method), No. 8,163,888 (one-step method), and No. 5,208,020 (two-step method). The antibody or antigen-binding fragment thereof can be conjugated to at least one drug, including a radionuclide, a cytotoxin, a chemotherapeutic agent, a drug, a prodrug, a toxin, an enzyme, an immunomodulator, an antiangiogenic agent, an apoptotic agent, a cytokine, a hormone, an oligonucleotide, an antisense molecule, an siRNA, a second antibody, and a second antibody fragment that binds to an antigen.

[0154] Proteins, nucleotides, and homologs Methods and compositions are provided herein for disabling and / or detecting unstimulated human myeloid cells expressing NSM proteins. In some embodiments, the invention relates to disabling and / or detecting unstimulated myeloid cells derived from non-human mammalian cells expressing a homologue of an NSM protein. For example, the expression pattern of an NSM protein in a mouse may be as restricted as its human homologue. Thus, in one embodiment, methods and compositions are provided herein for disabling and / or detecting unstimulated mouse myeloid cells expressing an NSM protein. Similar methods and compositions are also provided herein for disabling and / or detecting unstimulated cells derived from any individual expressing a homologue of an NSM protein in a similar expression pattern, which cells exhibit an expression pattern equivalent to that of the NSM protein.

[0155] The NSM proteins or nucleotides may include at least one or more of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, TLR7, and LILRB4, and homologs thereof. The SDC proteins or nucleotides may include at least one or more of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, BDCA3, and XCR1, and homologs thereof. Cell surface NSM proteins may include at least one or more of TREM2, MS4A7, C5AR1, LYVE1, ABCC3, LILRB4, MRC1 / CD206, SIGLEC1, STAB1, TMEM37, MERTK, and TMEM119. Cell surface NSM proteins may be targeted by one or more anti-NSM antibodies, alone or in combination. NSMs are generally positive for NSM proteins or nucleotides and negative for SDC proteins or nucleotides, and conversely, SDCs are generally positive for SDC proteins or nucleotides and negative for NSM proteins or nucleotides.

[0156] The antigen-binding constructs described herein comprise at least one polypeptide. Polynucleotides encoding the polypeptides described herein are also described. The antigen-binding constructs are typically isolated.

[0157] As used herein, "isolated" refers to a material (e.g., a polypeptide or polynucleotide) that has been identified, separated and / or recovered from components of its natural cell culture environment. Contaminant components of its natural environment are materials that would interfere with diagnostic or therapeutic uses of the antigen-binding construct, and may include enzymes, hormones, and other proteinaceous or non-proteinaceous solutes. Isolated also refers to a material that has been produced synthetically, e.g., by human intervention.

[0158] The terms "polypeptide," "peptide," and "protein" are used interchangeably herein to refer to a polymer of amino acid residues. That is, a description directed to a polypeptide applies equally to a description of a peptide and to a description of a protein, and vice versa. The terms apply to naturally occurring amino acid polymers as well as to amino acid polymers in which one or more amino acid residues are not naturally encoded amino acids. As used herein, the terms encompass amino acid chains of any length, including full-length proteins, in which the amino acid residues are linked by covalent peptide bonds.

[0159] The term "amino acid" refers to naturally occurring and non-naturally occurring amino acids, as well as amino acid analogs and amino acid mimetics that function in a manner similar to naturally occurring amino acids. Naturally encoded amino acids are the 20 common amino acids (alanine, arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, praline, serine, threonine, tryptophan, tyrosine, and valine), as well as pyrrolidine and selenocysteine. Amino acid analogs refer to compounds that have the same basic chemical structure as a naturally occurring amino acid, i.e., a carbon bonded to a hydrogen, a carboxyl group, an amino group, and an R group, such as homoserine, norleucine, methionine sulfoxide, and methionine methyl sulfonium. Such analogs have modified R groups (such as norleucine) or modified peptide backbones, but retain the same basic chemical structure as a naturally occurring amino acid. Reference to an amino acid includes, for example, naturally occurring proteinogenic L-amino acids, D-amino acids that are chemically modified amino acids such as amino acid variants and derivatives, naturally occurring non-proteinogenic amino acids such as β-alanine, ornithine, etc., as well as chemically synthesized compounds that have properties known in the art to be characteristic of amino acids. Examples of non-naturally occurring amino acids include, but are not limited to, α-methyl amino acids (e.g., α-methylalanine), D-amino acids, histidine-like amino acids (e.g., 2-aminohistidine, β-hydroxy-histidine, homohistidine), amino acids with an additional methylene in the side chain ("homo" amino acids), and amino acids in which the carboxylic acid functionality of the side chain is replaced with a sulfonic acid group (e.g., cysteic acid). The incorporation of synthetic unnatural amino acids, substituted amino acids, or unnatural amino acids, including one or more D-amino acids, into the proteins of the invention can be advantageous in many different ways: D-amino acid-containing peptides and the like have increased stability in vitro or in vivo compared to their L-amino acid-containing counterparts.Thus, constructing peptides and the like incorporating D-amino acids can be particularly useful when increased intracellular stability is desired or required. More specifically, D-peptides and the like are resistant to endogenous peptidases and proteases, thereby improving the bioavailability of the molecule and extending its in vivo duration when such properties are desirable. Furthermore, D-peptides and the like cannot be efficiently processed to perform major histocompatibility complex class II-restricted presentation to T helper cells, and therefore are unlikely to induce humoral immune responses in the whole organism.

[0160] Amino acids may be referred to herein by either their commonly known three letter symbols or by the one-letter symbols recommended by the IUPAC-IUB Biochemical Nomenclature Commission. Similarly, nucleotides may be referred to herein by their commonly accepted single-letter codes.

[0161] Polynucleotides encoding the polypeptides of antigen-binding constructs are also included in the present invention. The term "polynucleotide" or "nucleotide sequence" is intended to indicate a contiguous stretch of two or more nucleotide molecules. The nucleotide sequence may be of genomic, cDNA, RNA, semisynthetic or synthetic origin, or any combination thereof.

[0162] The term "nucleic acid" refers to deoxyribonucleotides, deoxyribonucleosides, ribonucleosides, or ribonucleotides, and polymers thereof that exist in either single-stranded or double-stranded form. Unless otherwise limited, the term encompasses nucleic acids that contain known analogs of natural nucleotides that have similar binding properties as the reference nucleic acid and are metabolized in a manner similar to naturally occurring nucleotides. Unless otherwise limited, the term also refers to oligonucleotide analogs, including PNA (peptide nucleic acid), DNA analogs used in antisense technology (phosphorothioates, phosphoroamidates, and the like). Unless otherwise stated, a particular nucleic acid sequence implicitly encompasses its conservatively modified variants (including but not limited to substitutions with degenerate codons) and complementary sequences in addition to the sequence explicitly indicated. Specifically, substitution with degenerate codons may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and / or deoxyinosine residues (Batzer et al., Nucleic Acid Res. 19:5081 (1991); Ohtsuka et al., J. Biol. Chem. 260:2605-2608 (1985); Rossolini et al., Mol. Cell. Probes 8:91-98 (1994)).

[0163] "Conservatively modified variants" applies to both amino acid and nucleic acid sequences. With respect to a particular nucleic acid sequence, "conservatively modified variants" refers to nucleic acids that code for the same or essentially identical amino acid sequences, or to nucleic acids that do not code for an amino acid sequence, but that have been modified to an essentially identical sequence. Because the genetic code is degenerate, a large number of functionally identical nucleic acids code for any given protein. For example, the codons GCA, GCC, GCG, and GCU all code for the amino acid alanine. Thus, at any position where alanine is specified by a codon, the codon can be changed to any of the corresponding codons described without changing the encoded polypeptide. Such nucleic acid variations are "silent variations," which are a type of conservatively modified variation. Every nucleic acid described herein that codes for a polypeptide also describes every possible silent variation of that nucleic acid. One of skill in the art will recognize that each codon in a nucleic acid (with the exception of AUG and TGG, which are normally the only codons for methionine and TGG, which are normally the only codons for tryptophan) can be altered to yield a functionally identical molecule. Accordingly, each silent variation of a nucleic acid that encodes a polypeptide is implicit in each of the described sequences.

[0164] With respect to amino acid sequences, one of skill in the art will recognize that individual substitutions, deletions, or additions to a nucleic acid, peptide, polypeptide, or protein sequence that alter, add, or delete a single amino acid or a small percentage of amino acids in the coding sequence are "conservatively modified variants" in which the alteration results in the deletion of one amino acid, the addition of one amino acid, or the substitution of one amino acid with a chemically similar amino acid. Tables showing conservative substitutions that provide functionally similar amino acids are known to those of skill in the art. Such conservatively modified variants are in addition to, and do not exclude, polymorphic variants, interspecies homologs, and alleles described herein.

[0165] Tables showing conservative substitutions resulting in functionally similar amino acids are known to those of skill in the art. Each of the following eight groups contains amino acids that are conservative substitutions for one another: 1) alanine (A), glycine (G), 2) aspartic acid (D), glutamic acid (E), 3) asparagine (N), glutamine (Q), 4) arginine (R), lysine (K), 5) isoleucine (I), leucine (L), methionine (M), valine (V), 6) phenylalanine (F), tyrosine (Y), tryptophan (W), 7) serine (S), threonine (T), and 8) cysteine ​​(C), methionine (M) (see, e.g., Creighton, Proteins: Structures and Molecular Properties (WH Freeman & Co.; 2nd edition (December 1993)).

[0166] The term "identical" or "percent identity" in the context of two or more nucleic acid or polypeptide sequences refers to two or more sequences or subsequences that are identical. Sequences are "substantially identical" if they have a percentage of amino acid residues or nucleotides that are identical (i.e., the percent identity over a specified region is about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, or about 95%) when compared and aligned for maximum correspondence over a comparison window or designated region, as measured using one of the sequence comparison algorithms described below (or other algorithms available to those of skill in the art). This definition also refers to the complementary sequence of a test sequence. Identity can exist over a region that is at least about 50 amino acids or nucleotides in length, or over a region that is 75-100 amino acids or nucleotides in length, or, if not specified, over the entire sequence of the polynucleotide or polypeptide. Polynucleotides encoding the polypeptides of the invention, including homologs from species other than human, may be obtained by a process that includes screening libraries under stringent hybridization conditions using labeled probes having the polynucleotide sequences described herein or fragments thereof, and isolating full-length cDNA and genomic clones containing the polynucleotide sequences. Such hybridization techniques are well known to those skilled in the art.

[0167] For sequence comparison, typically, one sequence is a reference sequence, and the sequence is compared with the test sequence.When using sequence comparison algorithm, the test sequence and the reference sequence are input into computer, and if necessary, subsequence coordinates are designated, and parameters of sequence algorithm program are designated.Default program parameters can be used, or alternative parameters can be designated.The sequence comparison algorithm then calculates the percent sequence identity of the test sequence compared with the reference sequence based on the program parameters.

[0168] As used herein, a "comparison window" includes a reference to a segment having any one of a number of contiguous positions selected from the group consisting of 20 to 600, usually about 50 to about 200, more usually about 100 to about 150, within which a sequence and a reference sequence having the same number of contiguous positions may be compared after the two sequences are optimally aligned. Methods of sequence alignment for comparison purposes are known to those of skill in the art. Optimal sequence alignment for purposes of comparison can be performed by, but is not limited to, the local homology algorithm of Smith and Waterman (1970) Adv. Appl. Math. 2:482c, by the homology alignment algorithm of Needleman and Wunsch (1970) J. Mol. Biol. 48:443, by the similarity search method of Pearson and Lipman (1988) Proc. Nat'l. Acad. Sci. USA 85:2444, by computer implementations of such algorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group, 575 Science Dr., Madison, Wis.), or by manual alignment and visual inspection (see, e.g., Ausubel et al., Current Protocols in Molecular Biology (1995 Supplement)).

[0169] One example of an algorithm suitable for determining percent sequence identity and sequence similarity is the BLAST and BLAST 2.0 algorithms, described in Altschul et al. (1997) Nuc. Acids Res. 25:3389-3402, and Altschul et al. (1990) J. Mol. Biol. 215:403-410, respectively. Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information, available on the World Wide Web at ncbi.nlm.nih.gov. The BLAST algorithm parameters W, T, and X determine the sensitivity and speed of the alignment. The BLASTN program (for nucleotide sequences) uses as defaults a word length (W) of 11, an expectation (E) of 10, M=5, N=-4, and a comparison of both strands. For amino acid sequences, the BLASTP program uses as default a string length of 3, and an expectation (E) of 10, and the BLOSUM62 scoring matrix (see Henikoff and Henikoff (1992) Proc. Natl. Acad. Sci. USA 89:10915), alignments (B) of 50, expectation (E) of 10, M=5, N=-4, and a comparison of both strands. The BLAST algorithm is typically run with the "low complexity" filter turned off.

[0170] The BLAST algorithm also performs a statistical analysis of the similarity between two sequences (see, e.g., Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90:5873-5787). One similarity measure provided by the BLAST algorithm is the smallest sum probability (P(N)), which provides an indication of the probability that a match between two nucleotide or amino acid sequences would occur by chance. For example, a nucleic acid is considered to be similar to a reference sequence if the smallest sum probability is less than about 0.2, or less than about 0.01, or less than about 0.001 in comparing the test nucleic acid with the reference nucleic acid.

[0171] The phrase "selectively (or specifically) hybridizes to" refers to molecular binding, duplexing, or hybridization that occurs only to a particular nucleotide sequence under stringent hybridization conditions when that sequence is present in a complex mixture (including, but not limited to, total cellular or library DNA or RNA).

[0172] The phrase "stringent hybridization conditions" refers to hybridization of DNA sequences, RNA sequences, or other nucleic acid sequences, or combinations thereof, under conditions of low ionic strength and high temperature as known in the art. Typically, under stringent conditions, a probe will hybridize to its target sequence in a complex mixture of nucleic acids (including, but not limited to, whole cell or library DNA or RNA), but will not hybridize to other sequences in the complex mixture. Stringent conditions are sequence-dependent and will be different in different circumstances. Longer sequences hybridize specifically at higher temperatures. Detailed guidance for nucleic acid hybridization can be found in Tijssen, Laboratory Techniques in Biochemistry and Molecular Biology--Hybridization with Nucleic Probes, "Overview of principles of hybridization and the strategy of nucleic acid assays" (1993).

[0173] As used herein, the terms "engineer, engineered, engineering" are intended to include any manipulation of the peptide backbone or post-translational modifications of a naturally occurring or recombinant polypeptide or fragment thereof. Engineering includes altering the amino acid sequence, altering the glycosylation pattern, or altering the side groups of individual amino acids, as well as combinations of such techniques. Engineered proteins are expressed and produced by standard molecular biology techniques.

[0174] By "isolated nucleic acid molecule or polynucleotide" is intended a nucleic acid molecule, DNA, or RNA, which has been removed from its natural environment. For example, a recombinant polynucleotide contained in a vector and encoding a polypeptide is considered isolated. Further examples of isolated polynucleotides include recombinant polynucleotides maintained in heterologous host cells, or polynucleotides that are purified (partially or substantially) in solution. Isolated polynucleotides include polynucleotide molecules contained in cells that normally contain the polynucleotide molecule, but where the polynucleotide molecule is present extrachromosomally or in a chromosomal location that differs from its natural chromosomal location. Isolated RNA molecules include in vivo or in vitro RNA transcripts, as well as positive and negative stranded forms, and double-stranded forms. The isolated polynucleotides or nucleic acids described herein further include such molecules that are synthetically produced, for example, via PCR or chemical synthesis. Additionally, in certain embodiments, the polynucleotide or nucleic acid includes a regulatory element, such as a promoter, a ribosome binding site, or a transcription terminator.

[0175] The term "polymerase chain reaction" or "PCR" generally refers to a method for amplifying a desired nucleotide sequence in vitro, for example, as described in U.S. Patent No. 4,683,195. In general, the PCR method involves repeated primer extension synthesis cycles using oligonucleotide primers capable of preferentially hybridizing to a template nucleic acid.

[0176] By a nucleic acid or polynucleotide having a nucleotide sequence that is at least, for example, 95% "identical" to a reference nucleotide sequence of the present invention, it is intended that the nucleotide sequence of the polynucleotide is identical to the reference sequence, except that the polynucleotide sequence may contain up to 5 point mutations per nucleotide of each 100 residues of the reference nucleotide sequence. In other words, to obtain a polynucleotide having a nucleotide sequence that is at least 95% identical to the reference nucleotide sequence, up to 5% of the nucleotides of the reference sequence may be deleted or substituted with another nucleotide, or a number of nucleotides corresponding to up to 5% of the total nucleotides of the reference sequence may be inserted into the reference sequence. Such modifications of the reference sequence may occur at the 5' or 3' terminal position of the reference nucleotide sequence, or at any position between these terminal positions, either interspersed individually between the residues of the reference sequence, or at any position in one or more adjacent groups within the reference sequence. As a practical matter, whether any particular polynucleotide sequence has at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, or 99% identity to a nucleotide sequence of the present invention can be conventionally determined using known computer programs, such as those discussed for polypeptides (e.g., ALIGN-2).

[0177] A derivative or variant of a polypeptide is said to share "homology" with or be "homologous" to a peptide if the amino acid sequence of the derivative or variant has at least 50% identity with the amino acid sequence of 100 residues derived from the original peptide. In certain embodiments, the derivative or variant is at least 75% identical to either the peptide or peptide fragment having the same number of amino acid residues as the derivative. In certain embodiments, the derivative or variant is at least 85% identical to either the peptide or peptide fragment having the same number of amino acid residues as the derivative. In certain embodiments, the amino acid sequence of the derivative is at least 90% identical to either the peptide or peptide fragment having the same number of amino acid residues as the derivative. In some embodiments, the amino acid sequence of the derivative is at least 95% identical to either the peptide or peptide fragment having the same number of amino acid residues as the derivative. In certain embodiments, the derivative or variant is at least 99% identical to either the peptide or peptide fragment having the same number of amino acid residues as the derivative.

[0178] As used herein, the term "modified" refers to any alteration made to a given polypeptide, such as a change to the length, amino acid sequence, chemical structure, co-translational modification, or post-translational modification of a polypeptide. The term "(modified)" refers to any alteration to the polypeptide under discussion, i.e., the polypeptide under discussion can be modified or unmodified.

[0179] In some embodiments, an antibody or protein disclosed herein comprises an amino acid sequence that is at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% identical to the relevant amino acid sequence, or a fragment thereof, set forth in the table(s) or accession number(s) disclosed herein. In some embodiments, an isolated antibody or protein disclosed herein comprises an amino acid sequence encoded by a polynucleotide that is at least 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% identical to the relevant nucleotide acid sequence, or a fragment thereof, set forth in the table(s) or accession number(s) disclosed herein.

[0180] Pharmaceutical Compositions The present application provides compositions comprising antibodies, including pharmaceutical compositions comprising any one or more of the antibodies described herein, together with one or more pharma- ceutically acceptable excipients. In some embodiments, the compositions are sterile. Pharmaceutical compositions generally comprise an effective amount of an antibody.

[0181] In addition to one or more of the antibodies disclosed herein, such compositions may contain pharma- ceutically acceptable additives, carriers, buffers, stabilizers, or other materials well known to those skilled in the art.Such materials should be non-toxic and should not interfere with the efficacy of the active ingredient.The exact nature of the carrier or other materials may depend on the route of administration, which may be, for example, oral, intravenous, cutaneous or subcutaneous, intranasal, intramuscular, or intraperitoneal.

[0182] The pharmaceutical composition for oral administration can be in the form of tablet, capsule, powder, or liquid. Tablets can contain solid carriers such as gelatin or adjuvants. Liquid pharmaceutical compositions generally contain liquid carriers such as water, petroleum, animal or vegetable oils, mineral oil, or synthetic oil. Can contain saline solution, dextrose or other sugar solution, or glycols such as ethylene glycol, propylene glycol, or polyethylene glycol.

[0183] For intravenous, cutaneous or subcutaneous injection, or injection into the site of pain, the active ingredient will be in the form of a parenterally acceptable aqueous solution that is pyrogen-free and has suitable pH, isotonicity and stability.Those skilled in the art are well able to prepare suitable solutions using isotonic vehicles such as, for example, sodium chloride injection, Ringer's injection, lactated Ringer's injection, etc.Preservatives, stabilizers, buffers, antioxidants, and / or other additives may be included as necessary.

[0184] Whatever polypeptide, antibody, nucleic acid, small molecule, or other medicamentously useful compound is to be administered to an individual, the administration is preferably carried out in a "therapeutically effective amount" that is sufficient to provide a benefit to the individual, or in a "prophylactically effective amount" (although in some cases, prophylaxis can be considered to be treatment). The actual amount administered, as well as the rate and course of administration, will depend on the nature and severity of the protein aggregation disorder being treated. Prescription of treatment, e.g., determining dosage, etc., is within the responsibility of general practitioners and other physicians, and typically takes into account the disorder to be treated, the symptoms of the individual subject, the site of delivery, the method of administration, and other factors known to physicians. Examples of the above-mentioned techniques and protocols can be found in Remington's Pharmaceutical Sciences, 16th edition, Osol, A. (ed), 1980.

[0185] The compositions may be administered alone or in combination with other treatments, either simultaneously or sequentially depending on the condition to be treated.

[0186] method How to use In one aspect, the application provides a method of contacting unstimulated myeloid cells with an anti-NSM antibody, such as a human antibody, which results in disabling of the unstimulated myeloid cells.

[0187] In another aspect, the application provides a method of contacting unstimulated myeloid cells with an anti-NSM mouse antibody, which results in disabling of the unstimulated myeloid cells.

[0188] In some embodiments, the non-stimulatory cells are one or more of DC1 cells and TAM cells.

[0189] In some embodiments, the application provides a method of disabling non-stimulated myeloid cells, the method comprising contacting non-stimulated myeloid cells with an NSM antibody, thereby killing the non-stimulated myeloid cells. Disabling refers to partially or completely eliminating the function of a cell. In some embodiments, disabling non-stimulated myeloid cells leads to induction of proliferation arrest of the cell. In some embodiments, disabling non-stimulated myeloid cells leads to apoptosis of the cell. In some embodiments, disabling non-stimulated cells leads to lysis of the cell, for example, by complement-dependent cytotoxicity (CDC) or antibody-dependent cell-mediated cytotoxicity (ADCC). In some embodiments, disabling non-stimulated myeloid cells leads to necrosis of the cell. In some embodiments, disabling non-stimulated myeloid cells leads to induction of proliferation arrest of the cell. In some embodiments, disabling non-stimulated myeloid cells leads to inactivation of the cell. In some embodiments, disabling non-stimulated myeloid cells leads to neutralization of activity of an NSM protein in the cell. In some embodiments, disabling non-stimulated myeloid cells leads to reduced proliferation of the cell. In some embodiments, disabling of non-stimulatory myeloid cells leads to differentiation of the cells. In some embodiments, disabling of non-stimulatory myeloid cells leads to a decrease in the ability of the cells to act as suppressive antigen-presenting cells or to activate antigen-presenting cells. In some embodiments, disabling of non-stimulatory myeloid cells leads to mislocalization of the cells in tumor tissue or in the tumor microenvironment (TME). In some embodiments, disabling of non-stimulatory myeloid cells leads to changes in the spatial organization of the cells in tumor tissue or in the tumor microenvironment. In some embodiments, disabling of non-stimulatory myeloid cells leads to changes in the temporal expression of the cells in tumor tissue or in the TME. In some embodiments, the method further comprises removing non-stimulatory myeloid cells.

[0190] In any or all of the aspects of disabling unstimulated myeloid cells described herein, any improvement or decrease or change in aspect of property(ies) or function(ies) is compared to cells not contacted with an anti-NSM antibody.

[0191] In another aspect, the application provides a method of contacting an unstimulated myeloid cell with an anti-NSM antibody, which results in functional modulation of the unstimulated myeloid cell. The modulation can be any one or more of the following. In some embodiments, the unstimulated cell is one or more of DC1 cells, TAM1 cells, and TAM2 cells. In some embodiments, the functional modulation leads to disabling of the unstimulated myeloid cell. In some embodiments, the functional modulation leads to an improved ability of the cell to stimulate both naive and activated CD8+ T cells, for example, by improving the ability of the unstimulated cell to cross-present tumor antigens on MHCI molecules to naive CD8+ T cells. In some embodiments, the modulation improves the T cell stimulatory function of the unstimulated myeloid cell, including, for example, the ability of the cell to induce T cell receptor (TCR) signaling, T cell proliferation, or T cell cytokine production. In one embodiment, the viability of the unstimulated cell is decreased or the proliferation of the unstimulated cell is decreased. In one embodiment, the ratio of stimulated to unstimulated myeloid cells is increased.

[0192] In any or all of the embodiments of reducing the function of unstimulated myeloid cells described herein, any improvement or reduction or change in the property(ies) or function(ies) aspect is compared to cells not contacted with an anti-NSM antibody.

[0193] In some embodiments, the application provides a method of killing (also referred to as inducing cell death) of unstimulated myeloid cells, the method comprising contacting unstimulated myeloid cells with an anti-NSM antibody, thereby killing the unstimulated myeloid cells. In some embodiments, killing is increased compared to unstimulated myeloid cells not contacted with the anti-NSM antibody. In some embodiments, the contacting induces apoptosis of the unstimulated myeloid cells. In some embodiments, the contacting induces apoptosis of the unstimulated myeloid cells. In some embodiments, the unstimulated myeloid cells are present in an immune cell population that includes unstimulated myeloid cells and stimulated myeloid cells. In some embodiments, the method further comprises removing the unstimulated myeloid cells. In some embodiments, 10%-80% of the cells are killed. In some embodiments, at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the cells are killed.

[0194] In some embodiments, the application provides a method of increasing the ratio of stimulatory myeloid cells to non-stimulatory myeloid cells in an immune cell population comprising stimulatory myeloid cells and non-stimulatory myeloid cells, the method comprising contacting the immune cell population with an anti-NSM antibody. In some embodiments, the ratio is increased compared to a cell population not contacted with the anti-NSM antibody. In some embodiments, the ratio of DC2 cells to DC1 cells is increased. In some embodiments, the ratio of DC2 cells to TAM1 cells is increased. In some embodiments, the ratio of DC2 cells to TAM2 cells is increased. In some embodiments, the ratio of DC2 cells to TAM1 cells+TAM2 cells is increased. In some embodiments, the ratio of DC2 cells to TAM1 cells+DC1 cells is increased. In some embodiments, the ratio of DC2 cells to DC1 cells+TAM2 cells is increased. In some embodiments, the ratio of DC2 cells to DC1 cells+TAM2 cells is increased. In some embodiments, the percentage is increased by at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100%.

[0195] In some embodiments, the pre-contact ratio of stimulatory myeloid cells:non-stimulatory myeloid cells ranges from 0.001:1 to 0.1:1. In some embodiments, the post-contact ratio of stimulatory myeloid cells:non-stimulatory myeloid cells is 0.1:1 to 100:1.

[0196] In some embodiments, the number of unstimulated myeloid cells is decreased. In some embodiments, the stimulatory myeloid cells are DC2 cells. In some embodiments, the unstimulated myeloid cells die, for example, by necrosis or apoptosis. In some embodiments, the unstimulated myeloid cells are induced into growth arrest. In some embodiments, the unstimulated myeloid cells no longer proliferate. In some embodiments, the spatial localization of unstimulated myeloid cells is altered and the proportion is increased in specific regions of the TME. In some embodiments, the temporal expression of unstimulated myeloid cells is altered and the proportion is increased during specific periods during tumor development.

[0197] In some embodiments, the contacting is performed in vitro. In some embodiments, the contacting is performed in vivo. In some particular embodiments, the contacting is performed in vivo in a human. In some embodiments, the contacting is caused by administration of an anti-NSM antibody. In some embodiments, the individual (such as a human) to whom the antibody is administered has cancer.

[0198] In another aspect, the invention provides a method of treating an immune-related condition (e.g., cancer) in an individual, the method comprising administering to the individual an effective amount of a composition comprising an anti-NSM antibody. In another aspect, the invention provides a method of enhancing an immune response in an individual, the method comprising administering to the individual an effective amount of a composition comprising an anti-NSM antibody. In some embodiments, such methods are further provided in combination with other concomitant treatments, such as PDL blockade therapy, CTLA4 blockade therapy, systemic checkpoint blockade therapy that blocks inhibitory molecules on T cells, adoptive T cell therapy, CAR T cell therapy, dendritic cell therapy, or other cellular therapies, as well as conventional chemotherapy.

[0199] In some embodiments, the method further comprises determining the expression level of the NSM protein in a biological sample from the individual. In some embodiments, the biological sample includes, but is not limited to, bodily fluids, tissue samples, organ samples, urine, feces, blood, saliva, CSF, and any combination thereof. In some embodiments, the biological sample is from a tumor tissue. In some embodiments, the expression level comprises an mRNA expression level of an mRNA encoding the NSM protein. In some embodiments, the expression level of the NSM protein comprises a protein expression level of the NSM. In some embodiments, the expression level of the NSM protein in the sample is detected using a method selected from the group consisting of FACS, Western blot, ELISA, immunoprecipitation, immunohistochemistry, immunofluorescence, radioimmunoassay, dot blot, immunodetection, HPLC, surface plasmon resonance, optical spectroscopy, mass spectrometery, HPLC, qPCR, RT-qPCR, multiplex qPCR or RT-qPCR, RNA sequence analysis, microarray analysis, SAGE, MassARRAY techniques, and FISH, and combinations thereof.

[0200] In another aspect, the application provides a method for determining the presence or absence of unstimulated myeloid cells in general, or the presence or absence of specific unstimulated myeloid cells (e.g., DC1 cells, TAM1 cells, and / or TAM2 cells), comprising contacting a cell population comprising unstimulated myeloid cells with an anti-NSM antibody and quantifying the number of unstimulated myeloid cells. In another aspect, the application provides a method for determining the presence or absence of unstimulated myeloid cells, comprising contacting a population of immune cells comprising unstimulated myeloid cells and stimulatory myeloid cells with an anti-NSM antibody, detecting complexes or moieties indicative of binding of the antibody to the cells, and optionally quantifying the number of unstimulated myeloid cells in the population. In another aspect, a method for determining the relative proportion of non-stimulated to stimulatory myeloid cells is provided, the method comprising contacting an immune cell population comprising non-stimulated and stimulatory myeloid cells with an anti-NSM antibody, quantifying the number of stimulatory and non-stimulated myeloid cells, and determining the relative proportion of non-stimulated to stimulatory myeloid cells.

[0201] In the embodiments described herein for detection and / or quantification, anti-NSM antibodies bind to NSM proteins but do not necessarily affect a biological response, such as ADCC, although they may have an effect on a biological response.

[0202] In another aspect, the invention provides a method for identifying an individual who may respond to immunotherapy (e.g., using anti-NSM antibodies) for the treatment of an immune-related condition (e.g., cancer), comprising detecting an expression level of an NSM protein in a biological sample from the individual, and determining whether the individual may respond to immunotherapy based on the expression level of the NSM protein, where an elevated level of the NSM protein in the individual compared to the level of the NSM protein in a healthy individual indicates that the individual may respond to immunotherapy. In some embodiments, such methods may be used for the purpose of diagnosing an immune-related condition (e.g., cancer) in an individual, where such methods are based on the expression level of the NSM protein, where an elevated level of the NSM protein in the individual compared to the level of the NSM protein in a healthy individual indicates that the individual suffers from cancer. In some embodiments, the expression level comprises an mRNA expression level of an mRNA encoding the NSM protein. In other embodiments, the expression level of the NSM protein comprises a protein expression level of the NSM protein. In some embodiments, the expression level of the NSM protein is detected in the sample using a method selected from the group consisting of FACS, Western blot, ELISA, immunoprecipitation, immunohistochemistry, immunofluorescence, radioimmunoassay, dot blot, immunodetection, HPLC, surface plasmon resonance, optical spectroscopy, mass spectrometry, HPLC, qPCR, RT-qPCR, multiplex qPCR or RT-qPCR, RNA sequence analysis, microarray analysis, SAGE, MassARRAY techniques, and FISH, and combinations thereof. In such embodiments, the anti-NSM antibody binds to the NSM protein but does not necessarily induce a biological response such as ADCC. In some embodiments, the biological sample is derived from tumor tissue. In some embodiments, the biological sample includes, but is not limited to, bodily fluids, tissue samples, organ samples, urine, feces, blood, saliva, CSF, and any combination thereof.

[0203] Also disclosed herein is a method for enhancing the immune response of a subject against tumor or enhancing the efficacy of immunotherapy treatment.Generally, treatment that increases the abundance of SDC will improve the subject's prognosis, such as recurrence-free survival, and will enhance the efficacy of cancer immunotherapy treatment.Treatment can increase the relative or absolute abundance of SDC cells in the subject's tumor.Treatment can decrease the relative or absolute abundance of NSM cells in the subject's tumor.

[0204] An exemplary method of general therapeutic strategy includes increasing the number of SDCs by systemic introduction of Flt3L. Another method is treatment of the subject's autologous bone marrow or blood cells with FLT3L while blocking CSF1 in parallel. Expression of SDC transcription factors such as IRF8, Mycl1, or BATF3 or ZBTB46, for example, by retrovirus, in bone marrow or blood progenitor cell populations may be used to promote SDC development. Another strategy of treatment includes systemic elimination of NSM cells while selectively sparing SDCs. This may result in favorable overall changes in the proportion of these populations. Elimination of NSM cells may be achieved by any means, including administration of antibodies against NSM surface proteins (systemic or tumor-localized).

[0205] In some embodiments, SDC-enhancing therapies are applied as therapeutic treatments to better enable the subject's natural immune system to control or eradicate the cancer. In another embodiment, an SDC-enhancing therapy of the invention is applied in combination with a therapeutic treatment, such as an immunotherapeutic treatment (such application being performed before, simultaneously with, or after the immunotherapeutic treatment), and the SDC-enhancing therapy serves as an adjunctive or supplemental therapy to increase the efficacy of the therapeutic treatment.

[0206] Method of administration In some embodiments, the methods provided herein are useful for treating an immune-related condition in an individual. In one embodiment, the individual is a human and the antibody is an NSM antibody. In another embodiment, the individual is a mouse and the antibody is an NSM antibody.

[0207] In some embodiments, the methods described herein (such as methods of enhancing an immune response or inducing disabling of unstimulated myeloid cells) are useful in the treatment of cancer, such that the anti-NSM antibody or the individual to whom the anti-NSM antibody is administered has cancer. In some embodiments, the cancer is a solid cancer. In some embodiments, the cancer is a liquid cancer. In some embodiments, the cancer is immune evasive. In some embodiments, the cancer is immune responsive. In certain embodiments, the cancer is selected from the group consisting of melanoma, renal cancer, hepatobiliary cancer, head and neck squamous cell carcinoma (HNSC), pancreatic cancer, colon cancer, bladder cancer, prostate cancer, lung cancer, glioblastoma, and breast cancer.

[0208] In some embodiments, the immune-related condition is an immune-related condition associated with expression of the NSM protein in unstimulated myeloid cells (in humans) or an immune-related condition associated with expression of a homologue of the NSM protein in a non-human species. In some embodiments, the immune-related condition is an immune-related condition associated with overexpression of the NSM protein in unstimulated myeloid cells compared to stimulated myeloid cells. In some embodiments, the overexpression of NSM mRNA or NSM protein is at least about 2-fold, about 5-fold, about 10-fold, about 25-fold, about 50-fold, or about 100-fold higher compared to stimulated myeloid cells.

[0209] In some embodiments, the antibody is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by injection, by inhalation, intrathecally, intracerebroventricularly, or intranasally. An effective amount of an anti-NSM antibody may be administered for the treatment of cancer. The appropriate dosage of an anti-NSM antibody may be determined based on the type of cancer to be treated, the type of anti-NSM antibody, the severity and course of the cancer, the individual's clinical symptoms, the individual's medical history and response to treatment, and the discretion of the attending physician.

[0210] Detection and quantification of SDC and NSM cells The present invention encompasses any methodology aimed at quantifying SDC and / or NSM cells. Various embodiments relate to the identification and quantification of SDC and / or NSM cells, for example, in tumor samples. A tumor sample can be any tissue containing tumor cells obtained from a patient as known in the art, for example, a portion of a tumor removed by biopsy (e.g., needle biopsy or punch biopsy, e.g., 4 mm punch biopsy), or substantially the entire tumor surgically removed, including primary or metastatic cells. It will be noted that the abundance of SDC is greater in distal regions of the tumor compared to the marginal regions. In a typical sample, this difference will be averaged out and will not affect the results. However, if an excessive amount of marginal material is included in the sample, this may affect the results and result in an undercount of the abundance of SDC.

[0211] In one embodiment, the number of SDC and NSM cells in a sample is directly quantified by fluorescence-activated cell sorting (FACS), similar flow cytometry methodologies, magnetic-activated cell sorting, microraft sorting, affinity-based cell separation methods, and other means of isolating specific cell types from a mixed population of cells. For example, tumor samples may be enzymatically digested to prepare single cell suspensions, as known in the art. Cells can then be labeled with antibodies specific for protein or carbohydrate markers unique to each cell type. Cell fractions can then be separated by FACS or similar methodologies using a variety of gating protocols based on different labels, as known in the art. For example, as described in the Examples, single cell suspensions from digested tumors were labeled with antibodies bearing fluorescent tags, allowing the dendritic cell fraction to be isolated by FACS from other cell types in the sample, separating pools of SDC and NSM cells. Labeling of either extracellular or intracellular marker proteins, as known in the art, may be used in such methodologies.

[0212] For example, in one FACS protocol, the various cell types of the tumor myeloid compartment may be sorted as follows: Cells expressing CD11b and Ly6C represent monocytes and neutrophils and can be removed by such expression. High expression of CD24 and low expression of F4 / 80 may be used to distinguish tumor macrophage cells (TAM1 and TAM2) from dendritic cells (SDC and DC1 cells). The two tumor macrophage populations can be separated from each other by their differential expression of CD11b and CD11c, since TAM1 cells are "CD11b high", "MHC class II low" and "CD11c low", while TAM2 cells are "CD11b low", "MHC class II high" and "CD11c high". Human tumor macrophages characteristically express CD14, whereas DCs typically do not express CD14. Examples of distinguishing surface markers that help distinguish the two dendritic populations from each other and from macrophages include CD103, XCR1, Clec9a, and CD11b in mice, or CD14, BDCA3, XCR1, and Clec9a in humans. For example, the two dendritic cell populations may be separated in mouse tumors by their differential expression of CD11b (absent in SDCs and present in NSM cells) and CD103 (absent in NSM cells and present in SDCs). Similarly, in humans, SDCs express BDCA3, XCR1, and Clec9, while non-stimulatory DCs express BDCA1 and macrophages express CD14.

[0213] In another embodiment, direct histological analysis of tissue samples is used to determine the presence, frequency, and relative abundance of SDC compared to other cell types. For example, tissue sections may be stained with labeled antibodies targeting SDC markers to compare antigens, and tissue sections may be stained with labeled antibodies targeting NSM markers to compare antigens. Labeled tissue sections may then be analyzed by quantitative fluorescence microscopy, which may be applied to quantify SDC and NSM cells in the sample, as well as to visualize the relative physical distribution and physical localization of such cells in the sample.

[0214] In another embodiment, the abundance of SDC and / or NSM cells in a sample is determined indirectly by observing gene expression patterns in a bulk tumor sample, making separation of the sample into cellular fractions unnecessary. Quantitative analysis of SDC and NSM gene markers in a bulk tumor sample is used as a surrogate measure of the proportion of SDC to NSM cells present in the tumor. For example, in one embodiment, the entire transcriptome of cells in a tumor sample is assayed to determine the ratio of SDC marker gene expression to NSM marker gene expression. It will be understood that such quantification of marker gene expression can be achieved using any number of tools known in the art directed to the analysis of gene expression.

[0215] In one embodiment, the expression evaluation of marker genes in tumor samples is performed using quantitative PCR methodology, as known in the art. Such methodology can be performed using a whole tumor transcriptome protocol and a primer pair capable of specifically amplifying the sequence of the marker gene, as known in the art. Given that the sequence of the marker gene is known, the generation of primers therefor is easy for those skilled in the art. Reference to the "gene sequence" of a particular gene in the context of quantifying expression level is understood to refer to the entire or partial nucleic acid sequence that corresponds to or is complementary to the mRNA (or the cDNA generated therefrom) produced by that gene when expressed, as known in the art.

[0216] In another embodiment, the expression level of the marker gene can be measured using DNA array techniques, as known in the art. Probes that bind to the transcripts of the marker gene can be easily generated by those skilled in the art using the known sequences of the marker genes, and can be used in any number of gene expression chips and analysis platforms.

[0217] In another embodiment, quantification of SDC and NSM cells is achieved by monitoring the presence or activity of downstream genes and proteins, defined as genes and proteins regulated by marker genes or their translation products, and whose activities change predictably in response to the expression of marker genes. In another embodiment, functional assays are used to identify or quantify SDC and NSM cells, for example, by differences in immunological activity. For example, SDCs have the ability to cross-present tumor antigens and are potent activators of CD8 T cells, whereas NSM cells do not. Similarly, NSM cells behave in a highly phagocytic manner, whereas SDCs are less robust phagocytes.

[0218] Abundance and exploration Various embodiments of the present invention relate to determining the abundance of SDC in tumors. The abundance of such cells may be assessed by various measures. Such measurements may include relative or absolute measurements, and may include direct or indirect measurements. For example, relative abundance may be the ratio of SDC to NSM cells in a sample, the ratio of SDC to the number of DC1 cells in a sample, or the ratio of SDC to all cell types in a sample, the ratio of SDC to all myeloid cells in a sample, or the ratio of HLA-DR to ... + In some embodiments, the absolute abundance of SDC is determined, for example, as a measure of the total number of SDC per ml of tumor tissue, or a measure of the total number of SDC per microgram of tumor tissue. Indirect measures include the evaluation of gene expression levels of SDC marker genes alone, or the evaluation of marker expression levels in comparison with other cell types, such as NSM cells.

[0219] In various embodiments, the abundance of SDC in a subject's tumor comprises a prognostic, diagnostic, or therapeutic selection indicator.

[0220] Various embodiments relate to comparative measures such as "elevation" or "increase" in the abundance of SDC. Such comparative measures may be performed by comparing representative samples with samples from subjects. Representative samples may include, for example, samples from the same subject at an earlier time point, samples from similar subjects (e.g., matched for age, sex, health indicators, cancer progression, cancer type, etc.), or samples from similar tumors (e.g., tumor type, tumor stage, and other measures of tumor progression). In some embodiments, for example, efficacy of a treatment is measured, and elevated abundance is defined as an increase in abundance compared to that observed in a representative sample from a subject not treated. In some embodiments, a typical or average measure of SDC abundance is used as a baseline to determine what constitutes elevated or increased abundance, and may use, for example, the mean, median, or similar statistical measure of SDC in representative samples. Various statistical methodologies known in the art may be used to define a significantly elevated or increased amount.

[0221] In one embodiment, the abundance of SDC in a subject's tumor comprises a prognostic indicator, and the subject's prognosis is predicted based on the abundance of SDC in the subject's tumor, with increased abundance indicating a higher probability of a favorable prognosis. Exemplary measures of prognosis include the likelihood of recurrence-free survival, predicted time period of recurrence-free survival, predicted time period of overall survival, risk of recurrence, quality of life indicators, and the like. For example, in one embodiment, the ratio of SDC to NSM cells in a tumor sample is measured, either directly or indirectly, and used as a measure of the abundance of SDC, and the predicted time period of recurrence-free survival is a measure of the subject's prognosis. For example, the mean or median ratio of expression of SDC marker genes to expression of NSM marker genes observed in a pool of similar tumor samples can serve as a threshold value, and if the ratio measured in an individual subject exceeds that threshold, the subject is likely to survive without recurrence.

[0222] In another embodiment, the abundance of SDC in a subject's tumor is an indication of the likelihood that the subject will respond positively to immunotherapy treatment, and an increase in the abundance of SDC in a tumor sample from a subject is an indication of a high likelihood of responding positively to immunotherapy.For example, in one embodiment, the ratio of SDC to NSM cells in a tumor sample is measured directly or indirectly and used as a measure of the abundance of SDC.For example, the mean or median ratio of the expression level of SDC marker genes to the expression level of NSM marker genes observed in a pool of similar tumor samples can serve as a threshold value, and if the ratio measured in an individual subject is below this threshold value, the subject is considered to be unlikely to respond positively to immunotherapy.

[0223] A method for predicting which subjects are likely to be suitable for immunotherapy treatment would advantageously allow for the selection of appropriate therapeutic intervention. Subjects deemed unlikely to respond to immunotherapy treatment may be administered other treatment modalities, while subjects likely to respond to immunotherapy can be treated accordingly. The therapeutic selection index of the present invention is applicable to predicting responsiveness or non-responsiveness to any cancer immunotherapy known in the art. For example, one class of cancer immunotherapy is known as "checkpoint blockade" therapy. The mammalian immune system contains a variety of "checkpoints," which are self-limiting inhibitory pathways that normally act to attenuate immune responses and prevent autoimmune reactions. Tumors have been shown to hijack these pathways, resulting in suppression of anti-tumor immune responses. Various therapeutic strategies are known as checkpoint blockade, which involve the use of ligands, such as antibodies, to block these control points and suppress tumor-induced suppression of immune responses to regain anti-tumor immunity. Another class of immunotherapy involves cell-based strategies in which cells, such as dendritic cells, are removed from a subject, expanded and activated ex vivo to target tumor antigens, and then the activated cells are reintroduced into the body to mount an immune response against the tumor in the subject.

[0224] The disclosure contained herein provides a technical field that includes a novel association between the abundance of SDC and the subject's prognosis and / or the subject's suitability for immunotherapy treatment. The present invention broadly encompasses any application of such concepts. It is within the skill of the art to implement the concepts of the present invention by establishing a predictive association between a specific measure of the abundance of SDC and a characteristic measure of the subject's prognosis or suitability for a specific immunotherapy for any specific type or subtype of cancer. Such predictive associations can encompass any statistical regimen that embodies the phenomenon that an increase in the abundance of SDC indicates an improved prognosis or improved suitability of a subject for immunotherapy treatment.

[0225] In one embodiment, the present invention includes predictive associations, where the ratio of expression of SDC marker genes to expression of NSM marker genes is used as a measure of SDC abundance relative to NSM immune cell abundance, and an increase in the SDC population predicts an increased likelihood of subject survival. For example, as described in the Examples, a large pool of gene expression data from 3602 tumor samples representing 12 different cancer types (data from the TCGA pan-cancer project) was analyzed, where relevant subject survival data was available for each tumor sample. For each sample, the observed mean expression level (measured in relative intensity units in the normalized dataset) of all SDC marker genes in Table A was calculated as a measure of SDC dendritic immune cell abundance. Similarly, for each sample, the observed mean expression level of all NSM marker genes in Table A was calculated as a measure of NSM immune cell abundance. Then, for each sample, the ratio of SDC to NSM cell abundance signal was calculated and log-transformed, and the Z-score was normalized to a median of 0 and a standard deviation of 1 across the entire dataset. For each cancer type, the median gene expression ratio of SDC to NSM gene markers was calculated. For each cancer type, the pool of samples was divided into "high" SDC to NSM ratio or "low" SDC to NSM ratio, with the high pool containing all samples with standardized ratios above the median for the entire population of similar samples (matched based on cancer type) and the low pool containing all samples with standardized ratios below the median. The Kaplan-Meier method was used to evaluate the association between overall survival and the SDC / NSM characteristic ratio as a binary variable (per cancer, split across the median). As shown in the figure, the data clearly show a substantial increase in overall survival in the high pool compared to the low pool.

[0226] Thus, the ratio of SDC marker gene expression to NSM gene expression in a sample is predictive of the overall survival of the subject from which the sample was obtained, with an increase in the ratio indicating increased overall survival. In this case, an "elevated" ratio is defined as a ratio exceeding the median ratio for that cancer type. Thus, in one embodiment, the present invention includes a method for predicting increased overall survival of a subject (compared to subjects with low SDC / NSM characteristic ratios), which comprises (1) calculating a logarithmic z-score of the ratio of the mean expression of SDC marker genes to the mean expression of NSM genes in tumor samples from the subject, followed by a comparison of the observed ratio in the subject to a threshold value corresponding to the median ratio of the expression of SDC marker genes to the expression of NSM genes for the cancer type of the tumor sample, where a ratio value in the sample above the threshold indicates a longer overall survival compared to the mean overall survival.

[0227] It will be understood that the example of the method of calculating SDC abundance shown herein is illustrative and may be modified in various ways. For example, the gene subset of Table A may be used. For example, in one embodiment, SDC markers BDCA3, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, and CLEC9A, and NSM markers MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1 are used. Similarly, the specific mathematical operations used to calculate gene expression ratios may be modified, for example, log-transformed values ​​may be summed and then averaged, rather than log-transforming average values. The exact nature and order of the mathematical operations used to calculate the ratios is not essential, so long as the specific methodology is representative of the ratio of the expression levels of SDC marker genes to the expression levels of NSM marker genes in a sample.

[0228] In alternative embodiments, the abundance of NSM may be measured as the number of NSM cells per total viable tumor cells, the number of NSM cells per total tumor immune cells, the number of NSM cells per unit volume of tumor sample, or the number of NSM cells per unit mass (e.g., mg) of tumor sample. Similarly, the abundance of SDC may be measured as the number of SDC cells per total viable tumor cells, the number of SDC cells per total tumor immune cells, the number of SDC cells per unit volume of tumor sample, or the number of SDC cells per unit mass (e.g., mg) of tumor sample.

[0229] Total myeloid cells in a sample may be assessed as the total CD11b+ cells in a sample. Total myeloid cells in a sample may be defined as the total cells expressing CD14 plus the total cells expressing CD16 plus the total cells expressing HLA.

[0230] In one embodiment, the abundance of SDC cells is assessed by flow cytometry as the percentage of HLA-DR positive myeloid cells in a sample that express an SDC marker, which may be, for example, BDCA3 or XCR1 or Clec9a.

[0231] The inventors of the present disclosure have advantageously discovered that the abundance of CD14 expressing (CD14+) macrophages and monocytes can be used as a measure of the abundance of non-stimulatory cells or can be used to classify subject pools for more accurate prediction of cancer prognosis or more accurate evaluation of therapeutic efficacy. CD14+ macrophages can compete with stimulatory dendritic cells, and thus the balance of CD14+ cells to SDC cells in myeloid pools can be important in determining cancer prognosis. The proportion of CD14+ cells can modulate the effect of SDC abundance. In one embodiment, a surrogate measure of NSM abundance is defined as the abundance of CD14+ myeloid cells in a sample. In one embodiment, the abundance of CD14+ myeloid cells is measured as the percentage of CD14 expression among all CD11b+ myeloid cells. In another embodiment, the proportion of HLA-DR positive cells expressing CD14 is used as a measure of the abundance of CD14+ cells. In another embodiment, the abundance of CD14+ myeloid cells is measured as a percentage of total immune cells expressing CD45. In another embodiment, the abundance of CD14+ myeloid cells is measured as the number of CD14+ cells per gram of sample tissue or a similar measure.

[0232] In one embodiment of the invention, SDC abundance is measured as the percentage of myeloid cells that express HLA-DR+ and also express SDC markers, e.g., BDCA3 or XCR1. In one embodiment, SDC abundance is used as a prognostic indicator, an indicator of therapeutic efficacy, or an indicator of a subject's suitability for a particular treatment, with increased SDC abundance indicating a favorable prognosis, favorable response to a treatment, or increased likelihood of suitability for a particular treatment, and decreased SDC abundance indicating a poor prognosis, ineffectiveness of a treatment, or decreased likelihood of suitability for a particular treatment. For example, an abundance of SDC (e.g., BDCA3+ cells) of 1-4%, 1-2%, 1%, 2%, 3%, 4%, 5%, or 1.37% or more of HLA-DR+ cells may be considered to be an increased abundance of SDC. For example, a subject having a tumor with an SDC cell content of 1-5%, 1-4%, 1-2%, 1%, 2%, 3%, 4%, 5%, or 1.37% or greater of HLA-DR+ cells has a greater than 50% chance of responding positively to an immunotherapy treatment such as anti-PD1, e.g., a greater than 85% chance of responding positively.

[0233] In one embodiment, the treatment evaluated is an immunostimulatory or immunotherapeutic treatment. For example, the treatment may include treatment targeting programmed cell death protein 1 (PD1) or programmed cell death ligand 1 (PD-L1). For example, anti-PD1 treatments include nivolumab (Opdivo™), pembrolizumab (Keytruda™). Another similar treatment is targeting CTLA-4, for example, with ipilimumab (Yervoy™). In one embodiment, the likelihood that a subject will respond to anti-PD1 treatment is evaluated by measuring the abundance of SDC cells in the subject's tumor, for example, the abundance of SDC cells is evaluated as the percentage of HLA-DR+ myeloid cells expressing SDC markers (e.g., BDCA3) in the tumor, and an increase in the abundance of SDC cells indicates that the subject will respond well to anti-PD1 treatment, and a decrease in the abundance of SDC cells indicates that the subject will respond poorly to anti-PD1 treatment. In one example, an increased abundance of SDC cells is defined as 4% or more of HLA-DR+ myeloid cells in a tumor sample, and a decreased abundance of SDC cells is defined as less than 4% of HLA-DR+ myeloid cells. In one embodiment, the subject is a subject with melanoma. The above methodology may be similarly utilized to evaluate the efficacy of anti-PD1 therapy, where an increase in the abundance of SDC cells observed after treatment indicates that the therapy is effective. Similarly, a putative inhibitor of PD1 may be identified as one that increases the abundance of SDC cells, where the abundance of SDC cells is measured, for example, as the percentage of HLA-DR+ cells that are BDCA3+ cells.

[0234] In one embodiment, the invention includes screening methods aimed at identifying compositions (or other types of treatment modalities) that enhance the abundance of SDC. For example, tumor-bearing animals may be exposed to a putative enhancer that enhances the abundance of SDC, and the tools and methods of the invention may then be used to assess the abundance of SDC, e.g., compared to an untreated control or a sample from the same subject prior to treatment, whereby an increase in the abundance of SDC indicates that the treatment effectively enhances the abundance of SDC. Such SDC abundance may include any measure of SDC abundance, including relative and absolute measures of SDC, e.g., the ratio of SDC to NSM cells, or indirect measurements thereof.

[0235] Kits and Articles of Manufacture The present application provides a kit comprising any one or more of the antibody compositions described herein. In some embodiments, the kit further comprises a component selected from any of a secondary antibody, a reagent for immunohistochemistry analysis, a pharma- ceutically acceptable additive, and instructions, and any combination thereof. In one particular embodiment, the kit comprises a pharmaceutical composition comprising any one or more of the antibody compositions described herein, together with one or more pharma-ceutically acceptable additives.

[0236] In one aspect, the kit can be comprised of reagents, biomaterials, and other components to facilitate the measurement of SDC and NSM cells. For example, in one embodiment, the kit can include antibodies, including fluorescently labeled antibodies targeting myeloid cells, general dendritic cell markers, SDC cell markers, and NSM cell markers to facilitate FACS or other cell sorting or flow cytometry methodologies to quantify SDC and / or NSM cells in a sample. For example, to facilitate FACS isolation of SDC and NSM fractions, a kit containing antibodies with different labels targeting mouse CD45, CD11c, Ly6C, MHCII, CD24, F4 / 80, CD11b, and CD103 may be used, while a kit containing antibodies with different labels targeting human CD45, CD11c, CD14, HLA-DR, BDCA1, and BDCA3 may be used.

[0237] In another embodiment, the kit can include a set of PCR primers for amplifying one or more SDC genetic markers or one or more NSM genetic markers. In one embodiment, the kit of PCR primers includes a set of primers capable of specifically amplifying one, two, three, four, five, six, seven, eight, nine, or all of the SDC markers listed in Table A, and one, two, three, four, five, six, seven, eight, nine, or ten or more of the NSM markers listed in Table A. In another embodiment, the kit of PCR primers includes a set of primers capable of specifically amplifying BDCA3, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1.

[0238] The kit can include two or more probes containing subsequences of SDC or NSM genetic markers for binding to and / or labeling SDC or NSM transcripts or cDNA. In another embodiment, the kit includes a microarray or other solid substrate having immobilized probes thereon, the immobilized probes containing one or more SDC or NSM marker gene sequences for binding to and quantification of tumor-infiltrating SDC or NSM transcripts or cDNA derived therefrom. In one embodiment, the array includes a set of probes corresponding to one, two, three, four, five, six, seven, eight, nine, or all of the SDC markers listed in Table A, and / or one, two, three, four, five, six, seven, eight, nine, or ten or more of the NSM markers listed in Table A. In another embodiment, the array comprises a set of probes corresponding to BDCA3, KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, CLEC9A, MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1.

[0239] The kit can include a set of PCR primers capable of specifically amplifying the gene sequences of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, and CLEC9A in a sample. The kit can include a set of PCR primers capable of specifically amplifying the gene sequences of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, and TLR7 in a sample. The kit can include a set of PCR primers capable of specifically amplifying the gene sequences of MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1 in a sample. The oligonucleotide array can include immobilized probes capable of binding to the gene sequences of KIT, CCR7, BATF3, FLT3, ZBTB46, IRF8, BTLA, MYCL1, BDC3A, XRC1, and CLEC9A. The oligonucleotide array can include immobilized probes capable of binding to the gene sequences of C5AR1, LYVE1, ABCC3, MRC1, SIGLEC1, STAB1, C1QB, C1QA, TMEM37, MERTK, C1QC, TMEM119, MS4A7, APOE, CYP4F18, TREM2, and TLR7. The oligonucleotide array can include immobilized probes capable of binding to the gene sequences of MRC1, MS4A7, C1QC, APOE, C1QB, C1QA, and C5AR1.

[0240] The present application also provides an article of manufacture comprising any one of the antibody compositions or kits described herein. Examples of articles of manufacture include vials (including sealed vials). EXAMPLES

[0241] Below are examples of specific embodiments for carrying out the present invention. The examples are provided for illustrative purposes only and are not intended to limit the scope of the present invention in any manner. Efforts have been made to ensure accuracy with respect to the numbers used (e.g., amounts, temperatures, etc.), but it is understood that some experimental error and deviation should be allowed for.

[0242] The practice of the present invention will employ, unless otherwise indicated, conventional methods of protein chemistry, biochemistry, recombinant DNA techniques, and pharmacology, which are within the skill of the art. Such techniques are explained fully in the literature, see, for example, TECreighton, Proteins: Structures and Molecular Properties (WH Freeman and Company, 1993); A. L. Lehninger, Biochemistry (Worth Publishers, Inc., current addition); Sambrook, et al., Molecular Cloning: A Laboratory Manual (2nd Edition, 1989); Methods In Enzymology (S. Colowick and N. Kaplan eds., Academic Press, Inc.); Remington's Pharmaceutical Sciences, 18th Edition (Easton, Pennsylvania: Mack Publishing Company, 1990); Carey and Sundberg Advanced Organic Chemistry 3rd Edition (East, Pennsylvania: Mack Publishing Company, 1992); rd Ed. (Plenum Press) Vols A and B (1992).

[0243] Example 1: Materials and Methods for Examples 1-9 Mouse tumors

[0244] PyMT-ChOVA transgenic C57BL / 6 founder mice were as described (Engelhardt et al., 2012) and offspring were screened by PCR for the PyMT-ChOVA transgene, monitored for cancer, and used at 20-30 weeks of age. B78ChOVA is a mutant of B78 (Graf et al., 1984) and was generated and used as described in Supplementary Methods. All additional strain information can be found in Supplementary Methods. All mice were maintained under SPF conditions and treated in accordance with NIH and American Association of Laboratory Animal Care standards and in accordance with UCSF care regulations.

[0245] Flow cytometry

[0246] All antibodies were purchased from BD Pharmingen, eBioscience, Invitrogen, Biolegend, UCSF hybridoma core, or produced in the Krummel Lab. For surface staining, cells were incubated with anti-Fc receptor antibody (clone 2.4G2) and the antibody was used to stain cells on ice for 30 minutes in PBS supplemented with 2% FCS. Viability was assessed by staining with fixable Live / Dead Zombie (Biolegend) or DAPI. For intracellular staining, cells were harvested 6 hours after injection of mice with BrefeldinA (Cayman) at 10ug / g body weight and stained with antibodies against surface markers, then fixed with 2% PFA for 10 minutes at 25°C, permeabilized with 0.2% saponin, and stained with target antibodies. All flow cytometry was performed on a BD Fortessa flow cytometer. Flow cytometry data analysis was performed using Flowjo (Treestar). Cell sorting was performed using a BD FACS Aria II.

[0247] TCGA bioinformatics analysis

[0248] Clinical expression analysis used genome-wide mRNA levels (Illumina mRNA sequencing) from 3602 patient tumor samples representing 12 cancer types (845 breast, 265 ovarian, 303 head and neck squamous cell carcinoma, 122 bladder, 168 glioblastoma, 190 colon, 173 AML, 72 rectal, 355 lung adenocarcinoma, 259 lung squamous, 480 renal, and 370 uterine), normalized and pooled into a single dataset by the TCGA PanCancer working group and as published (Cancer Genome Atlas Research et al., 2013; Hoadley et al., 2014) (data available from TCGA Data Base). Portal at https: / / tcga-data.nci.nih.gov / tcga / and available at https: / / www.synapse.org / as syn1715755). + / CD103 - The characteristic ratio of CD103 + The average expression level of DC genes was calculated by CD103 -The mean expression of DC genes was calculated as the logarithm of the mean expression and then normalized (mean = 0, standard deviation = 1, list of genes in Figure 8C) to obtain z-scores. Applicants also evaluated published characteristics of T cells (Palmer et al., 2006), proliferation (Wolf et al., 2014), CSR / injury (Chang et al., 2005), and gamma interferon (Viigimaa et al., 2010) as published, along with CD8 / CD68 expression ratio (DeNardo et al., 2011). Overall survival data were obtained from the TCGA portal (downloaded in June 2013) (Cancer Genome Atlas Research et al., 2013), and survival analyses were performed in multivariate models using Cox proportional hazards modeling, adjusting for cancer type. Significance was assessed using log-rank p-values ​​after fitting multiple comparisons using the Benjamini-Hochberg method (Bejamini and Hochberg, 1995). Kaplan-Meier survival plots were generated using the Survival package in R. For all data in the KM plot (Figure 8E), Applicants found that the tumor types had CD103 + / CD103 - The median characteristic ratio of was used to "match" the cancer types by classifying each sample as "high" or "low."

[0249] Mouse strain information

[0250] OT-I mice are specific for SIINFEKL (SL8), an ovalbumin peptide related to H-2Kb (Hoquist et al., 1994), and have been crossed with CD45.1, Nur77-eGFP (Moran et al., 2011), and Cd2-RFP (Veiga-Fernandes et al., 2007) or actin-CFP (Hadjantonakis et al., 2002) mice to generate genomically encoded, fluorescently or congenically labeled T cells for adoptive transfer, imaging, and activation experiments.

[0251] For regulation of myeloid cell populations in tumors, the following mouse strains were used: C57BL / 6 was purchased from Simonsen; Irf4 f / f xCD11c-Cre (Klein et al., 2006), (Williams et al., 2013) were kindly provided to the applicant by Anne Sperling of the University of Chicago. - / - FVBN (Ouyang et al., 2011) was kindly provided to the applicant by Scott Kogan of UCSF. Zbtb46-DTR (Meredith et al., 2012), Csf2rb - / - (Robb et al., 1995), and Csf3r - / - (Liu et al., 1996).

[0252] For visualization of APCs in tumors, PyMT-ChOVA transgenic mice were cultured using Cx 3 F1 progeny carrying both transgenes, obtained by crossing with cr1-eGFP ( Jung et al., 2000 ) and Cd11c-mCherry mice ( Khanna et al., 2010 ), were used for imaging experiments.

[0253] Cell lines, cell culture, plasmids, gene transfer

[0254] The following tumor cell lines were cultured under standard conditions and then injected into mice: B16-F10 (Fidler, 1975), B16-GMCSF (Dranoff et al., 1993), B16-FLT3L (Curran and Allison, 2009) were kindly provided by Larry Fong; B78-parental (Graf et al., 1984). B78chOVA was parental B78 transfected with the same Ch-OVA fusion construct used in PyMTChOVA (Engelhardt et al.) using standard methods. EL4 (Hyman et al., 1972), EG7 (Moore et al., 1988), EG7-chOVA, and Vo-PyMT-luciferase-FVB were kindly provided to the applicant by Zena Werb at UCSF (Halpern et al., 2006), and LLC was kindly provided to the applicant by Lewis Lanier at UCSF (Bertram and Janik, 1980). B78p-mCherry-pHlourin was generated by transfecting B78-parental cells with the N1-mCherry-pHlourin construct using Lipofectamine according to the manufacturer's instructions (Koivusalo et al., 2010, Webb et al., 2011, Choi et al., 2013).

[0255] Briefly, adherent cells were grown in DMEM supplemented with penicillin / streptomycin / glutamine and 10% FCS at 37°C / 5% CO2 on tissue culture treated plastic plates and split every 2 days, whereas suspension cells were grown in flasks in RPMI-1640 supplemented with 10% FCS and penicillin / streptomycin / glutamine and split every 2 days.

[0256] Ectopic tumor injection

[0257] Tumor cell lines were harvested and washed three times with PBS before being mixed 1:1 with growth factor reduced Matrigel Matrix (BD Biosciences) for a final injection volume of 50ul. 100,000 tumor cells (unless otherwise stated) were injected subcutaneously into the right flank of shaved mice and allowed to grow for 14–21 days before use.

[0258] Tumor digestion

[0259] PyMT-chOVA and ectopic B78chOVA tumors were excised from mice and the total weight of tumor tissue removed was determined. The tumors were then minced using a scalpel before being placed in a 25 ml Erlenmeyer flask containing a stir bar and digested three times with 500 U / ml collagenase IV (Sigma), 100 U / ml collagenase I (Worthington), and 200 mg / ml DNAse I (Roche) per 0.3 grams of tumor weight with the Erlenmeyer flask placed on a stir plate in a 37°C incubator with a 5% CO2 atmosphere, with 30 min intervals between each digestion. After each 30 min interval, the tumor was passed through a 70 um cell strainer to remove large pieces of undigested tumor, and the remaining chunks were then subjected to digestion again while the isolated single cells were kept on ice. Total tumor immune infiltrates were then enriched by CD45-biotin magnetic positive selection (StemSep) at 4°C.

[0260] Human samples

[0261] Tissues were minced firmly with surgical scissors and transferred to a 25mL Erlenmeyer flask containing a magnetic stir bar and treated with 3mg / ml collagenase A (Roche) and 50U / ml DNase I (Roche) per 0.3g tissue for 1 hour at 37°C / 5% CO2 with constant stirring. Samples were then filtered through a 70um filter, spun down, and resuspended for staining (Ruffell et al., 2012). For all human samples, informed consent was obtained from all subjects and the study was conducted in accordance with IRB approval (IRB number 13-12246, 12 / 06 / 2013 to 12 / 05 / 2014).

[0262] Cell isolation

[0263] OT-I naive CD8 + T cells were isolated from lymph nodes and spleens of 6-12 week old mice. Selection was performed using a negative CD8 isolation kit (Stemcell Technologies) according to the manufacturer's instructions. BMDCs were generated by plating bone marrow cells at 1-2x10^6 cells / ml and culturing them with GM-CSF (granulocyte macrophage colony stimulating factor) in IMDM containing 10% FCS for 8-11 days. BMDCs were fully matured by adding IL-4 for the last 2 days of culture and LPS 12 hours before use.

[0264] Labeling of T cells with eFlour670

[0265] OT-I CD8 + T cells were incubated with 2 uM efluor670 (eBioscience) in RPMI without FCS for 15 min at 37° C. Afterwards, eFluor670 labeling was stopped using 2 ml of FCS and cells were washed three times with RPMI containing 10% FCS before use.

[0266] Bulk activation of T cells (generation of CTLs)

[0267] OT-I TCR transduced lymph node cells were stimulated with B6 splenocytes pulsed with 100 ng / ml SL8 peptide for 30 min and then washed three times. Cells were grown in the presence of 2 U / ml recombinant human IL-2 for 2 days after stimulation and again 4 days after stimulation and used for experiments 2–3 days later.

[0268] T cell proliferation assay

[0269] Lymph node cells were isolated from OT-I TCR transgenic mice and naive CD8 + T cells were enriched and / or bulk activated cultures of CTLs were used. Lymph node cells were isolated from OT-II TCR transgenic mice and naive CD4 + T cells were enriched and 20,000 enriched naive CD8 cells or 5-day pre-activated OT-I T cells or naive CD4 cells labeled with 2 uM eFluor670 were mixed with either 4,000 BMDCs pulsed with or without 25 ng / ml SL8 peptide (OT-I) or 1 ug / ml pOVA323-339 peptide (OT-II) or 4,000 unpulsed tumor APCs (unless otherwise stated) in 96-well V-bottom plates and incubated at 37°C / 5% CO2 for 12, 48, or 72 hours, at which time activation was measured by flow cytometry as CD69 / Nur77 increase and efluor670 dilution.

[0270] Pair formation assay

[0271] Pairing assays were performed as described (Friedman et al., 2006). Briefly, labeled T cells were mixed with stained single cell suspensions from tumor digests digested for 30 min to 1 h and then fixed with 2% PFA for flow cytometry. Percentage of pairing was calculated as the number of T cell pairs relative to the total number of T cells.

[0272] In vivo multiphoton microscopy imaging and surgery

[0273] Animals were kept under anesthesia using isofluorane on a heated microscope stage, and the depth of anesthesia was monitored at regular intervals according to institutional guidelines. Prior to surgery, animals were injected intravenously with 100ug Evans Blue in PBS and intraperitoneally with 1ml of lactated Ringer's solution. Mammary glands were surgically exposed and tumors were imaged through a modified version of a suction window previously described by applicant (Thornton et al.). Intravital imaging was performed using a custom-built two-photon device (MaiTai: Spectra Physics, Chameleon: Coherent) equipped with two infrared lasers. The MaiTai lasers were tuned to 870nm or 910nm for simultaneous excitation of CFP and GFP, or for excitation of GFP alone, respectively. The Chameleon laser was tuned to 1030nm for excitation of mCherry. Emission was detected using a 25x1.2NA water lens (Zeiss) coupled to a 6-color detector array (custom-made utilizing a Hamamatsu H9433MOD detector), and alternating laser excitation was used to obtain 12 detection channels. Excitation filters used were violet 417 / 50, blue 475 / 23, green 510 / 42, yellow 542 / 27, red 607 / 70, and far-red 675 / 67. The microscope was controlled by the MicroManager software suite, and z-stack images were acquired with 4x averaging and a z-depth of 3 uM. Data analysis was performed using the Imaris software suite (Bitplane).

[0274] Staining and multiphoton imaging of ex vivo tumor sections

[0275] Animals were euthanized and tumors were harvested. Interfering fat was removed and tumors were embedded in 2% low melting point agarose in PBS (SeaPlaque, Lonza). 300 μM thick sections were prepared using a Compresstome VF-200, Precision Instruments Inc. tissue slicer. Sections were attached to plastic coverslips using Vetbond (3M) and stained with Alexa647-labeled rat anti-CD11b antibody for 2 h in RPMI supplemented with 5% rat serum at 37°C / 5% CO2. Sections were washed in RPMI and imaged using a Nikon A1R confocal microscope.

[0276] RNA extraction, Fluidigm, and RNA-seq analysis

[0277] 4,000–20,000 cells were sorted and added directly to 300 ul Trizol LS, flash frozen, and quickly stored at -80°C until extraction. RNA was extracted by phenol-chloroform method and ethanol precipitated. Samples were then treated with DNaseI and cDNA was synthesized using SuperscriptIII (Invitrogen). For nanoliter qPCR Fluidigm analysis, cDNA was preamplified (12 cycles) via target-specific amplification using 2x Taqman PreAmp Master Mix (Applied Biosystems) and then treated with Exonuclease I to remove unincorporated primers. Samples and primers (target primers were designed using the Harvard Primer Bank: http: / / pga.mgh.harvard.edu / primerbank / ) were then loaded onto a 48.48 Dynamic Array with 2x SsoFast EvaGreen Super Mix (Bio-Rad) and run on a BioMark HD. For RNA sequencing, samples were extracted using the Arcturus Picopure RNA isolation kit (Life Technologies), biologically analyzed, and submitted to the UCSF Genomics Core. Libraries were prepared using the Nugen Ovation kit and subsequently sequenced on an Illumina HiSeq 2500 instrument. Single-end, 50-base pair reads were generated, yielding approximately 405 million reads with an average depth of 33.7 million reads / sample. Reads were aligned to the mouse genome (USCS mm10) and specifically mapped to known mRNAs for differential expression assessment. For analysis and assessment of differential expression, alignments were performed using Tophat (Trapnell et al., 2009) and differential expression analysis was performed using DESeq (Anders and Huber, 2010).

[0278] Tumor growth

[0279] Tumor growth curves were calculated over the indicated time periods by measuring tumor area (mm2) using a caliper as tumor width x tumor height. 2 ) was measured.

[0280] Treatment with diphtheria toxin, FTY-720, and anti-CSF-1

[0281] Diphtheria toxin (DT) was purchased from Sigma-Aldrich. For transient DT ablation, DTR mice were injected intraperitoneally with 20 ng DT per gram body weight, and mice were euthanized for analysis 24 hours after DT injection. For long-term ablation, mice were initially injected intraperitoneally with 20 ng / gram DT, followed by a maintenance dose of 4 ng / gram every 3 days.

[0282] FTY720 was purchased from Cayman and reconstituted in saline to aliquots of 1 mg / ml and stored at -20 C. 200 ul of FTY at a final concentration of 100 ug / ml in saline was injected intraperitoneally once every two days for the indicated time periods.

[0283] Neutralizing anti-CSF-1 antibody, clone 5A1, and isotype rat IgG2a, was purchased and purified from the UCSF Antibody Core. Animals were initially treated with 1 mg of antibody by intraperitoneal injection and analyzed 3 days later. Mice were subsequently injected intraperitoneally with 0.5 mg doses once every 5 days to maintain depletion over time.

[0284] Preparation and adoptive transfer of GMP progenitor cells

[0285] All bones (including femur, tibia, humerus, ulna, radius, and pelvis) were collected, transferred to sorting buffer (PBS supplemented with 2% FCS), ground in a mortar and pestle, washed repeatedly with HBSS, and then passed through a 70um filter. Cells were then lysed with 175mM ammonium chloride for 5 minutes at 37°C, washed, and density gradient centrifugation was performed using an underlay of 3ml Histopaque-1110 (Sigma) to select viable cells and remove remaining bone debris. Bone marrow cells were enriched for CD117 positive cells using CD117 Microbeads (Miltenyi Biotec) and positive selection was performed using AutoMACS. Cells were then stained with a lineage mix of unconjugated rat antibodies (CD4, CD8, Mac1, Gr-1, CD5, Ter119, and CD3) for 30 min on ice, washed, and stained with a fluorescently conjugated anti-rat secondary antibody for 30 min on ice. Cells were then washed and stained with a progenitor master mix (Ckit-APC-cy7, Sca1-PB, CD34-FITC, and FcgR-PerCPCy5.5) for 30 min on ice, washed, and sorted for viable, cKit+Sca1-, CD34+FcgR+ cells using BD FACs AriaII for GMP.

[0286] Dextran uptake assay

[0287] After tumor digestion and CD45 selection as described above, cells were cultured at 1x10 6Cells were seeded in 96-well round-bottom plates at 1000 x 1000 nm and incubated in triplicate for 30 min at either 4°C or 37°C in the presence or absence of 1 mg / ml Dextran-Pacific Blue (10,000 MW). Plates were gently tapped once every 5 min. Plates were then washed three times before staining with surface antibodies and immediately analyzed by flow cytometry. Dextran uptake was measured as the geometric mean fluorescence intensity of dextran uptake at 37°C minus the geometric mean fluorescence intensity of dextran binding at 4°C.

[0288] Cell tracking and imaging analysis

[0289] Data were visualized and analyzed using Imaris Software (Bitplane). Individual T cells were identified and tracked by Imaris. CD11c mcherry DCs were calculated using an iso-surface of masked DCs from segmentation in MATLAB. Contact duration was determined by the calculated tracking duration of masked T cell-DC pairs tracked using Imaris.

[0290] Antibody clones

[0291] Mouse Ab clones: CD45 clone 30-F11, CD45.1 clone A20, CD45.2 clone 104, CD11b clone M1 / 70, CD11c clone N418, CD103 clone 2E7, CD24 clone M1 / 69, CD90.2 clone 30-H12, Ly6C clone HK1.4, MHCII clone N22, F4 / 80 clone BM8, CD69 clone H1.2F3, CD135 clone A2F10, CD117 clone 2B8, CD26 clone H194-112, CD206 clone C068C2, CD64 clone X54-5 / 7.1, MerTK clone Y323, and CD301b clone 11A10-B7-2 were kindly provided by Akiko Iwasaki from Yale. PDL2 clone TY25, IRF4 clone M17, and IRF8 clone T14 were kindly provided to applicant by Roger Sciammas from the University of Chicago, IL12 clone C17.8, CD80 clone 16-10A1, CD86 clone GL1, 2B4 clone m2B4, and PDL1 clone 10F.9G2.

[0292] Human Ab clones: CD45 clone Hl30, CD3e clone OKT3, HLADR clone L243, CD56 clone CMSSB, CD19 clone H1B19, CD14 clone 61D3, CD16 clone CB16, CD11c clone 3.9, BDCA1 clone L161, and BDCA3 clone AD5-14H12.

[0293] statistical analysis

[0294] Statistical analysis was performed using GraphPad Prism software. All data are representative of at least four separate experiments unless otherwise specified. Error bars indicate SEM calculated using Prism and are from triplicate experimental conditions. Specific statistical tests used included paired and independent T-tests, and all p-values ​​less than 0.05 were considered statistically significant.

[0295] Example 2: Surface markers delineate rare neoplastic DC subsets from abundant macrophages. To interrogate tumor-infiltrating myeloid populations, we devised an 11-color flow cytometry panel and used a stepwise gating strategy using PyMTChOVA, an oncogene-driven engineered autologous mammary tumor model that independently co-expresses the fluorescent mCherry protein and ovalbumin (Engelhardt et al., 2012). Applicants used a stepwise gating strategy to interrogate tumor-infiltrating myeloid populations using PyMTChOVA, an oncogene-driven engineered autologous mammary tumor model that independently co-expresses the fluorescent mCherry protein and ovalbumin ( + Compartments were characterized, many of which contained phagocytosed tumor antigens and thus displayed mCherry fluorescence (Figure 1A). By partially gating on all hematopoietic cells with the myeloid-specific marker CD11b and the monocyte marker Ly6C, it was possible to exclude neutrophils and monocytes (data not shown). MHCII + Intracellularly, DCs express CD24 高 and F4 / 80 低 DCs are distinguished from macrophages based on the expression of CD11b and CD103, either alone or together, which is typically sufficient to make this distinction. As observed in healthy peripheral tissues, DCs were subsequently found to be analytically classified into two populations based on differential expression of CD11b and CD103 (Hashimoto et al., 2011). Applicants found such populations in two melanoma mouse models (B78ChOVA (a mutant of B16 expressing mCherry and OVA), Figure 1B and BRAF V600E, data not shown), across mouse species (e.g., FVB PyMT, data not shown), and ectopic tumors (Lewis lung carcinoma, data not shown). For ease of identification and discussion, Applicants will henceforth refer to these DC populations as "CD11b + DC1 and CD103 + It is called "DC2".

[0296] F4 / 80 高 CD24 低Analysis of the compartments also revealed the presence of two types of macrophages, which were identified by differential expression of CD11c and CD11b. 低 CD11b 高 Cells (up to this point, "TAM1") and CD11c 高 CD11b 低 The cells ("TAM2") were similarly depicted with MHCII 高 Populations and MHCII 低 The populations appear to be broadly consistent with those of the DCs (Movahedi et al., 2010) (see also Fig. 5c). CD11c, an otherwise "highly protoypical" DC marker, was most abundant in DCs, while it was highly expressed in TAM2 and to a lesser extent in TAM1 (data not shown). These populations were present across all models examined, although their prevalence and the capabilities they possessed were unclear and differed only to a small extent (Fig. 1A-B and data not shown). Applicants therefore applied their lineage and functional studies to one example autologous (PyMTChOVA) and ectopic (B78ChOVA) tumor models. These specific models are not covered where otherwise noted.

[0297] Tumor-derived mCherry loading and retention was assessed in each of these populations. 高 We found the presence of cells, previously reported by applicant to be localized to the tumor periphery and subsequently identified exclusively by CD11c (Engelhardt et al., 2012), that were most abundant in the TAM1 and TAM2 gates (Figure 1c and data not shown). + DC1 and CD103 + DC2 showed poor uptake or retention of mCherry, while some monocytes, but little if any neutrophils, showed evidence of moderate antigen loading.

[0298] CD11b + and CD103 + DC subsets have been found in many peripheral mouse tissues and their counterparts have been identified in peripheral human tissues, defined by their expression of BDCA1 and BDCA3, respectively (Dzionek et al., 2000; Haniffa et al., 2012). Applicants have found that these markers can also be used to equally differentiate TAM / DC in human metastatic melanoma samples (Figure 1D). CD16, which represents all TAMs, - HLADR + CD11c + CD14 + Cells are CD16 - HLADR + CD11c + CD14 - The DC populations were distinct from those analyzed and classified by differential expression of BDCA1 ("DC1") and BDCA3 ("DC2"). Consistent across mouse models (Figure 1E) and human melanoma biopsies (Figure 1F), CD11b + / BDCA1 DC1 population, and CD103 + While / BDCA3 DC2 populations are present, they are rare, especially with respect to DC2.

[0299] Example 3: Protein and transcriptional imaging of tumor DCs and macrophages. To validate our gating strategy, we applied an antibody panel defined by the ImmGen consortium (Gautier et al., 2012; Miller et al., 2012). Consistent with our "DC" assignment, CD103 was identified in the B78chOVA and PyMTchOVA models. + DC2 expressed CD135 (Flt3), CD117 (cKit), and CD26, whereas both populations of TAMs did not (Fig. 2A and data not shown). +DC1 did not express detectable levels of DC markers and was in fact further separated from TAM1 and TAM2 by expressing several "macrophage" markers, including CD206, CD64, and MerTK (Fig. 2B and data not shown). + DC1 expressed low levels of CD301b and PDL2, both of which are IRF4-dependent "DCs" found in the skin. Th 2" population (Figure 2C and data not shown) (Gao et al., 2013; Kumamoto et al., 2013).

[0300] To further delineate these APCs, Applicants analyzed the gene expression profile of cells sorted from B78chOVA tumors using RNA-seq analysis. As shown in Figure 2D, gene blocks clearly separated four distinct populations, and PCA analysis (Figure 2E) revealed that TAM1, TAM2, and CD11b + DC1 is the most similar, and CD103 + Among the most differentially expressed genes, Irf8 (Tamura et al., 2005) and Zbtb46 (zDC) (Meredith et al., 2012), transcription factors that define the DC lineage, were expressed in CD103 and DC2, respectively. + Irf4 was specific for either only DC2 or both DCs, whereas Irf4 was specific for CD11b + All of the subpopulations were moderately enriched in DC1, all of which were verified by RT-qPCR (Figure 2F). This was also confirmed at the protein level by intracellular flow cytometry targeting IRF4 / 8 (Figure 2G and data not shown). All populations expressed Myb, indicating their origin from hematopoietic stem cells as opposed to being derived from tissue progenitors arising from the yolk sac (Schulz et al., 2012). The distinct surface phenotype and expression of key transcription factors was reaffirmed in the PyMTchOVA model (data not shown).

[0301] Because these intratumoral populations may be mediated through distinct tumor-specific mechanisms and not dependent on transcription factors as they are in some normal tissues, Applicants used knockout or transcription factor-driven diphtheria toxin receptor (DTR) mice to investigate dependency on Irf8, Irf4, Batf3, and zDC. Applicants utilized a variety of ectopic tumors due to the unpredictable variability and time required to integrate and breed these alleles into spontaneous models. Applicants used an ectopic PyMT mammary tumor model to demonstrate that loss of Irf8 results in the downregulation of CD103. + Specifically depletes DC2 but has no effect on TAM1 or TAM2, whereas CD11b + We found that the proportion of DC1 was slightly enriched, whereas CD11b + The enrichment of DC1 is likely a result of compensation (Figure 3A). In contrast, conditional deletion of Irf4 driven by CD11c-Cre in the B78chOVA model (Williams et al., 2013) resulted in the downregulation of CD11b + DC1 was specifically decreased, whereas the others were largely unchanged (Fig. 3B). Consistent with the RNA-seq data, Batf3-deficient animals also downregulated tumor CD103 in the B78chOVA model. + The DC2 population is deficient, whereas the CD11b + There was no effect on DC1, TAM1, or TAM2 populations (Figure 3C). Finally, when the zDC-driven DTR allele was used, CD103 + DC2 was specifically and significantly decreased, whereas CD11b + Applicants found that the DC1 or TAM1 / TAM2 populations changed little or not at all (Figure 3D), which was somewhat unexpected. This could indicate unpredictable variation in the DTR allele or subtle but significant variation in zDC expression. In summary, CD11b +Compared with TAM1 / TAM2, which is highly abundant in DC1 and tumors, CD103 + Applicants conclude that DC2 represents an APC of a distinct lineage.

[0302] Example 4: CD103 + DC2 are programmed by different cytokines. APCs originate from bone marrow (BM) progenitors and their differentiation into DC / macrophage subsets is dependent on specific cytokines. To determine the cytokines driving differentiation into these populations, applicants examined the expression of colony-stimulating factor (CSF) receptors across models by qPCR. TAM1, TAM2, and CD11b + Csf1r (M-CSFR) was found exclusively in DC1, whereas Csf2rb (GM-CSFR) was specifically expressed in DC1 and DC2 subsets, and Csf3r (G-CSF) was absent in all (Figure 4A).Using either neutralizing antibody treatment or cytokine receptor-deficient mice bearing ectopic tumors, applicants functionally tested the dependence of APCs in tumors on CSF cytokines.

[0303] TAM1 and TAM2 cells are critically dependent on CSF-1 for their maintenance, as previously shown (Wyckoff et al., 2004), whereas CD11b + DC1 population and CD103 + The DC2 population was uniquely independent of CSF1 (Figure 4B). Using cytokine receptor-deficient mice, applicants developed a congenic adoptive transfer model in which granulocyte-macrophage progenitor cells (GMPs) were transferred into hosts bearing ectopic tumors and followed repopulation in the BM, spleen, and tumors (Figure 4C). In tumors, cells derived from GMPs populated all myeloid compartments, indicating that CD11b + DC1, CD103 +This confirms that DC2, TAM1, and TAM2 are of GMP origin (Figure 4D). By using the GMP adoptive system in conjunction with competitive transfer, Applicants were able to identify Csf2rb - / - They found that the cells selectively lacked the ability to reconstitute DCs, where the DCs were CD24 + CD11c + The total number of APCs was defined as the sum of DC1 / DC2 using a gating of 1. Applicants found no effect on TAM1 and TAM2 repopulation, suggesting that CSF2 (GM-CSF) is a unique requirement for the development of neoplastic DCs (Figure 4E), whereas none of the four APCs required CSF-3 (data not shown).

[0304] Because DCs are prototypically driven by GM-CSF or FLT3-ligand (FLT3L), Applicants used a B16 melanoma tumor model engineered to express GMCSF or FLT3L to assess whether cytokines are sufficient to drive DC populations in tumors. + The proportion of DC1 was significantly skewed, whereas FLT3L-expressing tumors expressed rare CD103 + It specifically promoted the proliferation of DC2 ( Fig. 4F ).

[0305] Example 5: CD103 + DC2-specific antigen processing and presentation abilities. Having established the lineage requirements of the different APCs, Applicants next assessed their ability to initiate, commit, and sustain T cell responses. To analyze the cells for antigen processing, presentation, and costimulation, Applicants analyzed the transcript and protein levels of genes involved in these pathways using the RNA-seq data in Figure 2. The differences were substantial and spanned a broad range of potential APC functions (Figure 5A). Notably, surface levels of molecules involved in regulating T cell responses, including CD80, CD86, and 2B4, were comparable between populations, while CD103 +DC2 displayed distinct transcriptional profiles consistent with enhanced cross-presentation, enhanced costimulation, and increased chemokine expression that would be predicted to enhance T cell interactions (Fig. 5A, Fig. 5B, and data not shown). There were no significant differences in the expression of MHC1 and MHCII between APCs, with the exception of CD103. + MHCI was slightly reduced in DC2 (Figure 5C). However, phagocytic capacity, measured exogenously by uptake of dextran derived from ectopic tumors ex vivo, was significantly higher than that of CD103 compared with TAM1 / TAM2. + A significant difference was observed in DC2 (Fig. 5D).

[0306] Since DC maturation and phagocytic capacity are often inversely correlated, Applicant has determined that CD103 + We hypothesized that the decrease in DC2 phagocytic capacity would correspond to increased cross-presentation of antigens and more mature DCs (Guermonprez et al., 2002). Efficient cross-presentation of antigens in DCs relies on Nox2, which controls the pH of the phagosome, thereby preventing destruction of T cell peptides. Prior to this study, this was previously determined using a ratiometric assay to compare the intracellular fluorescence intensity of pH-sensitive and pH-insensitive fluorophores after phagocytosis (Savina et al., 2006). Therefore, applicants generated a B78 (melanoma) tumor line expressing a fusion of a pH-sensitive GFP (pHluorin, quenched below pH 6.5) and a pH-insensitive fluorophore (mCherry). The mCherry in each population was expressed in 10% of the ... + By analyzing pHluorin intensity within the compartment alone, Applicants found that only the "DC" population maintained pHluorin in an alkaline (fluorescent) environment, and by comparing the pHluorin and mCherry signal ratios, they found that CD103 + While DC2 maintained the most basic intracellular compartment, TAM1 and TAM2 populations were highly acidic, thus indicating a degradative phagocytic pathway (Figure 5E). +In addition to increased alkalinity in the phagosome lumen of DC2, these cells showed differential expression of the proinflammatory cytokine IL-12 and the absence of the anti-inflammatory cytokine IL-10 (Fig. 5F, G, and data not shown). Taken together, all these features suggest that CD8 + CD103 for efficient antigen cross-presentation to T cells + This suggests that DC2 is highly prepared.

[0307] Example 6: CD103 + DC2 are naïve CD8 + T cells and activated CD8 + It is a potent stimulator of T cells. Applicants have previously demonstrated that when obtained directly from tumors, the totality of the myeloid compartment that is loaded with antigen is composed of naive CD8 + It is possible to stimulate T cells, but not pre-activated CD8 + They found that it was not possible to stimulate T cells with CD103 + Based on the unique cross-presenting phenotype of DC2, Applicants sought to test the T cell stimulatory capacity of each population freshly isolated from tumors. + After 12 hours of co-culture with T cells, CD103 was able to robustly induce TCR signaling. + DC2 population, which indicates that naive OT-I CD8 + T cells and preactivated OT-I CD8 + This was evidenced by an increase in the early T cell activation markers Nur77 and CD69 in both OT-I and T cells. Importantly, this was consistent in both ectopic and autologous mouse models (Fig. 6A and data not shown). Dye-labeled OT-I CD8 + Extended co-culture with T cells increased the expression of CD11b + DC1 population and CD103 + The DC2 population is composed of naive CD8 +CD103 was found to be the most robust stimulator of T cell proliferation, demonstrating that almost the entirety of the stimulatory capacity previously identified in phagocytic tumor myeloid cells is present specifically within these DCs (Fig. 6B-6C and data not shown). + DC2 had the ability to specifically induce potent proliferation of established CTLs, which were not stimulated by other populations, suggesting that CD103 + It was suggested that DC2 is an excellent cross-presenting stimulator of CTLs in tumors (FIGS. 6D to 6E, respectively, and data not shown).

[0308] Finally, CD103 + DC2 is usually present at low frequency in all tumor isolates, and at this frequency, it expresses CD103 + DC2s remain unable to drive CTL proliferation (data not shown (Engelhardt et al., 2012)). Moreover, neither of the APC subsets were able to drive CTL proliferation using CD4 + The exogenous peptide did not induce T cell proliferation (Fig. 6F-6G, data not shown). However, exogenous peptide did in fact restore the proliferation-stimulating capacity of DC1 and DC2, suggesting that such DCs may not be essentially incapable of stimulating CD4 T cells (data not shown). Crucially, this was due to the fact that intratumoral CD103 + We demonstrate that DC2 are uniquely capable of uptake, processing, and presentation of tumor antigens to robustly stimulate CTLs, challenging the simple notion that tumors contain only weak or suppressive myeloid populations.

[0309] Example 7: CD103 by in vivo imaging + Elucidation of DC2 localization and T cell interactions. Rare CD103 +Given the unique T cell stimulatory capacity of DC2, Applicant sought to understand the spatial organization of these cells within tumors and their interaction dynamics with T cells both in vivo and in vitro. To differentiate these populations in vivo in viable autochthonous tumors, Applicant transfected the PyMTchOVA allele with Cx 3 Crossing to the cr1-eGFP allele and the Cd11c-mCherry allele generated three specific fluorescent populations in the myeloid compartment (data not shown). Both DC subsets (DC1 / DC2) were specifically labeled in red (CD11c-mCherry only), whereas the TAM1 and TAM2 populations were specifically labeled in green (Cx 3 cr1-eGFP) and yellow (CD11c-mCherry and Cx 3 The red DC subsets were labeled with GFP (cr1-eGFP). Using this fluorescence technique in conjunction with two-photon intravital imaging, we observed that TAM1 and TAM2 populations were closely adjacent to the tumor lesion and preferentially migrated to the margin, a zone where we previously found T cells to be preferentially recruited (Engelhardt et al., 2012). In contrast, red DC subsets were typically found in a separate collagen-rich zone distal to the tumor lesion, constituting nearly 70% of all distally localized APCs (Figure 7A and data not shown).

[0310] This method detects CD11b + DC1 cells and CD103 + Because they were not completely distinct from DC2 cells, Applicants attempted to determine whether the scarce red DCs might represent exclusively one or the other subset. To delineate subsets in situ, Applicants utilized imaging of live tumor sections using staining with anti-CD11b antibodies. Using this, Applicants were able to identify CD11b DCs in the presence of a red / green fluorescent reporter. + DC1 subset and CD103 +It was possible to distinguish in situ from the DC11b DC2 subset, as well as from the CD11b + DC and CD11b - We found that both TAMs and DCs were present at these locations (data not shown). Applicants conclude that while TAMs are generally the predominant cell type at the tumor margin, CTL-stimulating APCs can nevertheless be found there, albeit in very low numbers.

[0311] Applicant's previous data showed that inflowing CTLs behaved as trapped at the tumor margin, and Applicant sought to determine whether this could occur in DCs or TAMs or both. For either in vivo or live section imaging, we used actin-CFP-labeled OT-I CD8 + We analyzed T cell dynamics in vivo in a red / green reporter system by adoptively transferring T cells into mice bearing spontaneous mammary tumors. We observed that stable T cell interactions were largely localized to the tumor periphery (Figure 7B and data not shown), as previously described (Boissonnas et al., 2013; Engelhardt et al., 2012). Although TAM1 interactions dominated all scored interactions, DC and TAM2 were also clearly involved in T cell capture. This indicates that DC1 / 2 are neither incapacitated nor physically excluded from T cells active within the tumor in tumor-proximal regions, but raises the fundamental question of which has the greater intrinsic ability to engage T cells.

[0312] To answer this question, applicants decoupled APC selection from the physical constraints of the tissue, prepared single cell suspensions by digesting tumors, introduced in vitro activated OT-I CTLs, and allowed them to form antigen-specific pairs with the OT-I CTLs. Applicants then quantified the proportion of each APC population that paired with T cells by flow cytometry. This revealed that OT-I T cells express CD103 +It was found that DC2 and TAM1 / 2 subsets were preferentially paired (left panel of FIG. 7C). However, because TAM1 / 2 was present at a high frequency, most T cell-APC pairs were formed with TAM1 / 2 cells (right panel of FIG. 7C). Applicant concludes that in tumors, DC2 contributes to T cell interactions when present near the periphery and has the ability to compete for T cell occupancy.

[0313] Example 8: Rare Tumor CD103 + DC2 allows for efficient adoptive T cell therapy. Applicants have demonstrated that the spontaneously regressing EG7 tumor cell line expresses CD11b β- + DC1 and CD103 + We were surprised to find that the ratio of DC to DC2 was almost reversed. The spontaneously regressing EG7 tumor cell line is henceforth referred to as EG7.2. While this aggressive growing line maintained the relative proportion of DCs that we observed in all other aggressive tumors (data not shown), this spontaneously regressing model showed unusually high numbers of CD103 + DC2 (data not shown). + We also observed increased tumor growth in Irf8KO tumor models lacking DC2, but not in Irf4 conditional KO models (data not shown). Taken together, these findings suggest that the tumor abundance of DC2 may play an important role in tumor control, but the difference in growth may represent a magnitude of variation in these lines beyond their myeloid populations and their CTL stimulatory capacity. Therefore, CD103 + To formally test whether DC2 is required for efficient CTL-mediated tumor regression, applicants analyzed regression in a proliferating EG7.1 tumor model following adoptive T cell therapy with activated tumor-specific T cells (Helmich and Dutton, 2001). Applicants performed these experiments in zDC-DTR mice, in which tumors express CD103 +It is possible to specifically deplete DC2 (Figure 3D). + To isolate the effect of DC2 and exclude any effect of LN priming, we (1) isolated activated OT-I CD8 cells that do not require LN priming and typically do not pass through LNs. + (2) the use of CTL blasts and SIP to prevent rare transferred CTL T cells from leaving the LNs 1 Applicants specifically designed an experiment that included two strategies: treatment of animals with the R antagonist FTY-720. FTY-720 alone had minimal effect on the ability of transferred CTL to mediate tumor regression (data not shown). However, Applicants found that CD103 expression in association with FTY-720 was significantly increased in the IL-16 / IL-2 / IL-3 ... + We found that depletion of DC2 had a profound effect on the ability of CTLs to efficiently mediate tumor regression, thereby significantly delaying T cell-mediated tumor regression ( Fig. 8A ).

[0314] Example 9: Intratumoral CD103 + The profile of DC2 abundance predicts prognosis across human cancers. For human tumors, CD103 + To determine whether DC2 abundance plays an important role, Applicants utilized TCGA array data (Cancer Genome Atlas Research et al., 2013; Hoadley et al., 2014) that quantifies relative gene expression levels from multiple human cancer types with matched prognostic data. + Applicant's RNA sequencing data was used to select high level transcripts that characterize DC2, along with TAM1 / TAM2 / CD11b. + To characterize DC1 cells, CD103 +We also selected a subset of genes that were downregulated in DC2 (genes in the top and bottom of Figure 8B, respectively). We identified the human homologs of these mouse genes and assayed the expression of these "signatures" in TCGA data from patients from all cancer types to assess their association with prognosis. In proportional hazards survival analysis, fitting the model with cancer type as a covariate, we observed that individual genes from these populations conferred only modest benefits on prognosis (expressed as hazard ratios (HRs)). However, we found that CD103 + and CD103 - When we defined the ratio of gene expression data to and used this as a continuous variable within a Cox analysis, we observed that there was a highly significant association (BH p=0.00019) with increased survival (Figure 8B).

[0315] This analysis shows that the ratio of the cell types we identified to their functional opposites produces very strong prognostic value across human cancer outcomes. Comparison of this "signature" with other previously described "immune scores" shows that CD103 is significantly more potent than other current TCGA data analyses, including those based on total T cell abundance (Palmer et al., 2006) and those performed by the bulk ratio of CD8 T cells to macrophages (CD8 / CD68 DeNardo et al., 2011). + / CD103 - It was shown that the CD103 / BDCA3 gene ratio provided the strongest immune-promoting survival signal (Figure 8C). Although with opposite prognosis, Applicant's score also compares favorably with immune scores associated with poor prognosis. It should be noted that expression of CSF-1 in tumors of these patients also inversely correlated with measures of the CD103 / BDCA3 gene ratio, but similarly with total tumor Flt3L levels (data not shown).

[0316] Finally, applicants attempted to analyze the TCGA data within individual cancer types. Matching for cancer type, Kaplan-Meier (KM) across all 12 cancers in this dataset showed that high CD103 + / CD103 - This demonstrates an overall benefit in tumors with gene expression signatures (Fig. 8D and data not shown). The magnitude of this association is particularly striking in breast cancer, head and neck squamous cell carcinoma, and lung adenocarcinoma (Fig. 8E-8G). Overall, the strong immune signature exhibited was unexpected, all the more so since it was derived entirely from experimental immune profiling in mouse tumor models.

[0317] Example 10: Materials and Methods for Example 11 Melanoma bioinformatics analysis

[0318] The melanoma dataset GSE19234 (n=44) was preprocessed with quantile normalization in the R environment before characterization and association with survival (Cox proportional hazards). Bogunovic, D., et al. Immune profile and mitotic index of metastatic melanoma lesions enhance clinical staging in predicting patient survival. Proc Natl Acad Sci USA 106, 20429-20434 (2009). SDC / NSM characterization ratios were calculated as the logarithm of the mean expression of SDC genes divided by the mean expression of NSM genes, and then standardized (mean=0, standard deviation=1, list of genes in Figure 1A) to obtain z scores. Survival analyses were performed using Cox proportional hazards modeling. After fitting multiple comparisons using the Benjamini-Hochberg method, significance was assessed using log-rank p-values. The survival package in R was used to perform the following analyses: 20Kaplan-Meier survival plots were generated and Applicant classified each sample as "high" or "low" using the 33% value, 50% value (median value), or 66% value of the SDC or SDC / NSM characteristic ratio.

[0319] Patients and samples

[0320] Patients were enrolled in this study if they had histologically confirmed stage IV or stage III unresectable metastatic melanoma. Patients consented to tissue collection under a UCSF IRB approved protocol (UCSF CHR number 13-12246). The enrollment period for the study began in December 2012 and ended in February 2015. Patients were treated with monoclonal antibodies blocking the PD-1 / PDL-1 axis: pembrolizumab (Keynote 001, Keynote 002, Keynote 006 or expanded access program or commercially available) or nivolumab (commercially available). Cutaneous / subcutaneous tumors were biopsied either by punch (4 mm or 6 mm), surgical excision (sample K10), and all other tumor biopsies were performed exclusively by core biopsy (16 g or 18 g). Additional samples were sent for pathology evaluation. Biopsies (n=21) were collected before anti-PD1 infusion. Fresh biopsy samples were rapidly placed in a sterile container on saline-soaked gauze and placed in a container with wet ice and transported to the laboratory for evaluation. All response assessments were performed with radiological imaging using the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST). A complete response was defined as complete regression of all target and non-target lesions, and a partial response was defined as regression of more than 30% of target lesions without the appearance of new lesions. Stable disease was defined as a 30% or less decrease in size of target lesions or a 20% or less increase. Progressive disease was defined as a 20% or greater increase in target lesions or the appearance of new lesions greater than 1 cm in size. Patients with a complete or partial response were classified as "responders" and patients with stable or progressive disease were classified as "non-responders." If progression was defined clinically without benefit of follow-up testing (eg, new lesions), patients were classified as responders and RECIST was designated as "x."

[0321] Digestion of human tissue

[0322] The tissue was minced firmly with surgical scissors, transferred to a 25 mL Erlenmeyer flask containing a magnetic stir bar, and incubated at 4°C for 3 h in 5% CO using 3 mg / ml collagenase A (Roche) and 50 U / ml DNase I (Roche) per 0.3 g tissue. 2 The cells were incubated at 37°C for 1 hour under constant agitation in a 70um filter. Samples were then filtered through a 70um filter, spun down, and resuspended for staining. Ruffell, B., et al. Leukocyte composition of human breast canser. Proc Natl Acad Sci USA 109, 2796-2801 (2012).

[0323] Flow cytometry and Ab clones

[0324] All antibodies were purchased from BD Pharmingen, eBioscience, Invitrogen, BioLegend, UCSF hybridoma core, or produced in the Krummel Lab. For surface staining, cells were incubated with a mixture of human anti-Fc receptor antibodies (clone 3G8, clone FUN-2, and clone 10.1, BioLegend) and stained with antibodies in PBS supplemented with 2% FCS and 2 mM EDTA for 30 min on ice. Viability was assessed by staining with fixable Live / Dead Zombie NIR or Aqua (BioLegend). All flow cytometry was performed on a BD Fortessa flow cytometer. Flow cytometry data analysis was performed using FlowJo (Treestar) software. Cell sorting was performed using a BD FACS Aria II.

[0325] Mouse antibodies against human antigens: CD45 clone H130, CD3e clone OKT3, HLA-DR clone L243, CD56 clone CMSSB, CD19 clone H1B19, CD14 clone 61D3, CD16 clone CB16, CD11c clone 3.9, BDCA1 clone L161, and BDCA3 clone AD5-14H12.

[0326] Cell lines and cell culture

[0327] B78ChOVA is a mutant of B78 and was generated by standard transfection procedures using the same Ch-OVA fusion construct used to generate the PyMTchOVA cell line. Graf, LH, Jr., Kaplan, P. & Silagi, S. Efficient DNA-mediated transfer of selectable genes and unselected sequences into differentiated and undifferentiated mouse melanoma clones. Somatic cell and molecular genetics 10, 139-151 (1984), and Engelhardt, JJ, et al. Marginating dendritic cells of the tumor microenvironment cross-present tumor antigens and stably engage tumor-specific T cells. Cancer Cell 21, 402-417 (2012). Briefly, adherent cells were cultured in DMEM containing penicillin, streptomycin, and glutamine, supplemented with 10% FCS, at 5% CO2. 2 Cells were grown in tissue culture treated plastic plates at 37°C in an ambient atmosphere and split every 2 days. Suspension cells were grown in tissue culture T25 and T75 flasks in RPMI-1640 supplemented with 10% FCS and penicillin / streptomycin / glutamine and split every 2 days.

[0328] Mouse tumors

[0329] All mice were maintained under SPF conditions and treated in accordance with NIH and American Association of Laboratory Animal Care standards and in accordance with UCSF IACUC protocols.

[0330] Tumor cell lines were harvested, washed three times with PBS, and then mixed 1:1 with growth factor-reduced Matrigel Matrix (BD Biosciences) in a final injection volume of 50 ul. 150,000 tumor cells were injected subcutaneously into the shaved right flank and allowed to grow for 14–21 days.

[0331] Mouse species

[0332] For regulation of myeloid cell populations in tumors, wild-type C57BL / 6 were purchased from Simonsen, and Zbtb46-DTR C57BL / 6 mice were obtained from Simonsen. Meredith, MM, et al. Expression of the zinc finger transcription factor zDC (Zbtb46, Btbd4) defines the classical dendritic cell lineage. J Exp Med 209, 1153-1165 (2012). Zbtb46-DTR BM chimeras were generated from lethally irradiated (two doses of 5.5 Gy) 8-week-old C57BL / 6 male recipients and 2–5X10 6 Zbtb46-DTR BM cells were used and generated according to standard procedures. Mice were kept in antibacterial water for 4 weeks and used for experiments 8 weeks after reconstitution.

[0333] Tumor growth

[0334] For tumor growth curves, tumor area (mm2) was measured over the indicated time periods as tumor width x tumor height using electronic calipers. 2 ) was measured.

[0335] Treatment with diphtheria toxin, anti-PD-1, and anti-CTLA-4

[0336] DT was purchased from Sigma-Aldrich. For transient DT clearance in DTR mice, DTR mice were injected intraperitoneally with 20 ng DT per gram body weight and euthanized for analysis 24 hours after DT injection. For long-term clearance, mice were initially injected intraperitoneally with 20 ng / gram DT, followed by 4 ng / gram once every 3 days for up to 15 days.

[0337] Purified anti-PD-1 (clone RMPI-14) and anti-CTLA-4 (clone 9H10) were purchased from BioXcell, and 100ug of each antibody was injected intraperitoneally on days 5, 8, and 11 of tumor growth as triple-treatment combination therapy.

[0338] statistical analysis

[0339] Statistical analysis was performed using GraphPad Prism software. All data are representative of at least four independent experiments unless otherwise specified. Error bars indicate SEM calculated using Prism and are from triplicate experimental conditions. Specific statistical tests used included paired and independent T-tests, and all p-values ​​less than 0.05 were considered statistically significant.

[0340] Example 11: Intratumoral BDCA3+ DC predict prognosis to anti-PD1 checkpoint therapy in human melanoma. Intratumoral APCs are highly phenotypically diverse, with myeloid lineages contributing to multiple populations that resemble both macrophages and dendritic cells. However, it has long been believed that "macrophages" are suppressive to tumor progression (DeNardo et al., and Hanada et al.), whereas intratumoral dendritic cells are probably stimulatory (Sandel et al.). Efforts to gain a clear and detailed understanding of this have been largely hampered by the lack of a clear way to distinguish between these cell types. Recently, applicants have attempted high-dimensional flow cytometry together with RNA-seq analysis to distinguish intratumoral myeloid cells. Applicants have found that, indeed, a small population of cross-presenting dendritic cells is highly stimulatory to CTLs, whereas other true "dendritic cell" subsets, as well as the highly abundant macrophage population, fail to stimulate tumor antigen-reactive CD8 T cells. Rare stimulatory dendritic cells (SDCs) are defined in mice by expression of the integrin CD103 and in humans by expression of CD141 / BDCA3 (Broz et al.).

[0341] To specifically pinpoint the role of these rare immunostimulatory DC populations in human melanoma, Applicants first exploited either two "signature" gene sets whose RNAs are highly enriched in mouse SDCs compared to all remaining non-stimulatory myeloid (NSM, which includes macrophages and non-stimulatory DC) antigen-presenting cell subsets, or, conversely, one gene set that is preferentially expressed in NSMs (Figure 9A). Applicants then searched for a well-annotated dataset from 44 metastatic melanoma patients that includes both RNA expression analysis, tumor mitotic index, clinical disease staging, and metastatic melanoma patient survival (Bogunovic et al.). Applicants attempted to analyze RNA abundance by analyzing either individual SDC genes, the average of all SDC genes, or the ratio of SDC / NSM genes. These latter two can be considered measures of overall SDC abundance and relative SDC / NSM cell abundance, respectively (Broz et al.).

[0342] Seven of the nine SDC signature genes conferred significant prognostic benefit, expressed as hazard ratios (HRs) (Table 1 below), with both the SDC signature and the SDC / NSM signature ratio having highly significant predictive value. TIFF2025027013000005.tif72170

[0343] To better visualize these prognostic associations, Kaplan-Meier (KM) plots were generated for either the SDC gene or the SDC / NSM ratio, where patients were binned into "high" or "low" trait expression, with increasing stringency cut-points for binning expression at thresholds of either 33%, 50%, or 66% (Figure 9B, C). These analyses showed that selecting for the highest levels of expression increased survival prospects, with tumors in the top 33% for SDC or SDC / NSM showing the most statistically significant increase in survival from the time of metastasis. This was consistent with the expression of stimulatory BDCA3 in tumors. +This supports the hypothesis that increased DC abundance supports better survival, even in the absence of treatment.

[0344] Given the relevance of this association to T cell immunity, Applicants further utilized curated information on TIL abundance in characterized tumors to correlate SDC and SDC / NSM signatures with analytical classification data on TIL infiltration. This analysis revealed that both class-based measures of TIL categories and measures of peritumoral CD3+ T cell numbers were highly associated with the SDC gene signature and, to a lesser, but still highly significant extent, with the SDC / NSM ratio (Figures 9D-9G).

[0345] These associations suggested a correlation between SDC abundance, T cell function, and overall survival. We attempted to explore this association as it may relate to checkpoint blockade. However, since the SDC and SDC / NSM signatures are only surrogates for the populations themselves, applicants explored how they might relate by attempting to directly measure these populations from melanoma biopsies in the context of clinical trials of checkpoint therapy.

[0346] To test this goal, applicants used flow cytometry to analyze tumor biopsies from 21 biopsy specimens obtained from patients with metastatic melanoma to track their progression in response to anti-PD-1 treatment. Of the 21 patients, 5 were female and 16 were male, with a mean age of 61.6 years, and biopsies were taken from a variety of locations and tissues (Figure 10A). For each of these patients, biopsies were enzymatically digested and analyzed by flow cytometry to quantify the proportion of immune cell infiltrates in the tumor. Applicants designed a comprehensive flow panel to probe the human myeloid infiltrate using the markers CD45, HLA-DR, CD3, CD19, CD56, CD11c, CD11b, CD85g, CD14, BDCA1, and BDCA3. Using these markers, applicants were able to sequentially gate the immune compartment of these tumors and to identify the BDCA3 + DC subset, BDCA1 + DC subset, CD14 + TAM subsets and CD14 - It was possible to identify TAM subsets (Figure 10B, Figure 10C). Applicants found that some patients had a predominantly BDCA3+SDC population (Figure 10B) and others had a significantly reduced BDCA3+SDC population (Figure 10C). + The overall amount of cellular infiltration and the proportion of cells expressing HLA-DR also varied significantly between tumors (Fig. S10D). In most melanomas, the overall abundance of lymphocytes ("lineage") was highly enriched (Fig. S10E). And, classification of HLA-DR+ cells into myeloid subpopulations, as shown in Fig. S10C / D, also showed highly significant heterogeneity across patient biopsies (Fig. S10E).

[0347] To examine the association between these immune myeloid infiltrates and patient response, applicants analyzed and stratified patients into either "non-responders," defined as either stable or progressive disease, or "responders," defined as partial or complete responses to anti-PD-1 treatment (see FIG. 10A and Methods). This approach revealed no significant differences in the percentage of total CD45+ immune cell infiltrates between responder and non-responder patients; in fact, both groups had similar mean percentages of CD45+ cells with similar variability around the mean (FIGS. 11A, 11B, and data not shown). Similarly, there was no clear association between the overall frequency of lymphoid cells and prognosis (data not shown). In contrast, the percentage of total tumor cells (CD45 + Gating on cells (Figures 11C-11D) or as a percentage of total APCs (HLA-DR + Gating on cells with BDCA3 + DCs were quantified across response groups, and patients who were responders to anti-PD-1 had BDCA3 in their tumors. + The frequency of DCs was statistically significantly higher. Collectively, these findings suggest that the total immune cell infiltrate in tumors is not predictive of responsiveness to immunotherapy, possibly due to the presence of total CD45 + This is because the TME contains both tumor-promoting and tumor-antitumor subpopulations, whereas stimulatory BDCA3 + These results suggest that the proportion of DCs is indeed predictive of anti-PD-1 immunotherapy efficacy. Although there were clear instances where responders had relatively low numbers of BDCA3, using this sample size and with an absolute exclusion of the top 2% of HLA-DR+, a 95% confidence interval for responder status was obtained.

[0348] Applicants sought to further explore this data to see if this positive association could be further improved by considering the precise identification of the remaining myeloid populations, specifically the abundance of either CD14+TAMs or alternative DC populations characterized by BDCA1 or CD14-TAMs. Applicants plotted individual patients by the percentage of BDCA3+ cells they had versus the respective percentages of such, and coded each according to responder status. While responders still fell into the BDCA3+ high region of the plot, Applicants found that no clear trends existed for other populations (Figures 11E-11G). Again, these findings indicate that the presence of BDCA3 is a strong indicator that a robust antitumor response can be elicited, but that other factors may play a role in enabling a response in a minority of patients, despite having lower levels. Future studies should focus on the intratumoral localization of BDCA3+ cells as a possible explanation. Applicants currently have insufficient antibody capacity against these and therefore future tests will need to be developed.

[0349] BDCA3 + Having established a strong association between DC abundance and responsiveness to immunotherapy, Applicants investigated whether this association represents a functional requirement for this stimulatory DC population, or simply a "trait" of responsiveness, to checkpoint blockade therapy. To test this, Applicants used an easy-to-use mouse melanoma model, the B78chOVA cell line. 7 The B78chOVA cell line is a modified variant of B16 melanoma that expresses mCherry fluorescent protein and ovalbumin. In conjunction with this tumor model, the applicant used Zbtb46-DTR BM chimeric mice, in which (CD103 +Applicants have previously shown that CD103+SDCs are preferentially ablated in melanoma (Broz et al.). In our mouse model, anti-PD1 monotherapy had no effect on melanoma. Applicants therefore used the ablation model to investigate whether depletion of CD103+SDCs interferes with the efficacy of a combined anti-PD-1 and anti-CTLA-4 immunotherapy regimen (Figure 12A). We treated Zbtb46-DTR BM chimeric mice with either anti-PD-1 and anti-CTLA-4, or an isotype-matched control antibody, using a treatment regimen of three doses administered on days 5, 8, and 11, with either DT or PBS injections starting on day 1, and we confirmed that DT treatment alone had no effect on tumor growth in this model (data not shown). Applicants found that while untreated melanoma tumors grew progressively, melanoma tumors treated with the combination immunotherapy rapidly regressed after 7-8 days and were almost completely eradicated by day 15 (Figures 12B, 12C). In contrast, in association with this potent immunotherapy, CD103 in mice was downregulated. + Depletion of DCs abolished the rapid tumor regression and abrogated the efficacy of the dual therapy. + These results suggest that DCs are a functional requirement for the efficacy of immunotherapy (FIG. 12D).

[0350] Thus, the applicants have demonstrated that specific SDC (CD103 + or BDCA3 +) populations. In general, these findings further emphasize the importance of fully understanding the immune landscape of tumor tissues, as revealed in previous studies (DeNardo et al., and Fridman et al.). Beyond the scope of "Immuno-scoring" (Ascierto et al.), which is gaining acceptance as a new diagnostic marker for some cancers, the applicant's work shows the increasing need to perform detailed immune profiling of human tumors to identify rare populations of immune cells that can regulate T cells in the microenvironment. Stratification will require the development of biopsy-compatible tests, after continuous refinement of the characteristics revealed in the initial studies, and the applicant's work highlights that high-dimensional imaging, for example by mass ion beam technology, could be one such method in the future (Angelo et al.).

[0351] Example 12: Materials and Methods for the Examples Below Tumor digestion

[0352] Tumors were excised from the mice and the total weight of the tumor tissue removed was determined. The tumors were then minced using a scalpel and incubated in a 50 ml conical beaker with 20 ul / ml Liberase TL (Roche) from a 5 mg / ml stock solution and 200 mg / ml DNAse I (Roche) per 0.3 grams of tumor weight in a 37°C shaker with 5% CO. 2 The cells were digested at room temperature for 30 minutes. After 30 minutes, the tumor was passed through a 70um cell strainer and viable cells were enriched by a density gradient of Ficoll Paque Plus (GE). Viable cells were collected from the interface and washed into staining buffer (PBS supplemented with 2% FCS and 2mM EDTA).

[0353] Isolation of mouse bone marrow and spleen

[0354] Femurs and tibias were removed and bone marrow was extruded using PBS / 2% FCS / 2mM EDTA and a 25G needle / syringe. Spleens were excised from mice and minced using a scalpel. Tissue fragments were digested in a 50ml conical beaker using 500U / ml collagenase IV (Worthington), 100U / ml collagenase I (Worthington), and 200mg / ml DNAse I (Roche) in a 37°C shaker. The digested tissue was then filtered through a 70um cell strainer. Both bone marrow and spleen were lysed in 0.8% NHCl. 4 Red blood cells were lysed using for 5 min and then washed into staining buffer (PBS supplemented with 2% FCS and 2 mM EDTA).

[0355] Human tumor samples

[0356] The tissue was minced firmly with surgical scissors, then transferred to a 50 ml conical beaker and incubated at 37°C / 5% CO with 20 ul / ml Liberase TL (Roche) from a 5 mg / ml stock solution and 200 mg / ml DNAse I (Roche) per 0.3 grams of tumor weight. 2 The samples were treated for 30 minutes under constant agitation at 0.05°C for 30 minutes. Samples were then filtered through a 70um filter, spun down, and resuspended for staining (Ruffell et al., 2012). Informed consent was obtained from all subjects for all human samples, and the study was conducted in accordance with IRB approval (IRB number 13-12246, 12 / 06 / 2013-12 / 05 / 2014).

[0357] Flow cytometry and Ab clones

[0358] All antibodies were purchased from BD Pharmingen, eBioscience, Invitrogen, BioLegend, Human Protein Atlas or produced at Krummel Lab or Precision Immune Inc. For surface staining, cells were incubated with anti-Fc receptor antibody (clone 2.4G2) and 500 nm human IgG1Fc and stained with primary antibodies in PBS supplemented with 2% FCS and 2 nM EDTA for 30 min on ice. Cells were then washed twice with PBS supplemented with 2% FCS and 2 mM EDTA and stained with the appropriate secondary antibodies for 30 min on ice. Viability was assessed by staining with fixable Live / Dead Zombie Aqua (BioLegend) or Zombie NIR or DAPI. All flow cytometry was performed on a BD Fortessa flow cytometer. Flow cytometry data analysis was performed using FlowJo (Treestar) software.

[0359] Anti-mouse Ab clones: CD45 clone 30-F11, CD11b clone M1 / 70, CD11c clone N418, CD103 clone 2E7, CD24 clone M1 / 69, CD90.2 clone 30-H12, Ly6C clone HK1.4, MHCII clone M5 / 114.15.2, F4 / 80 clone BM8, CD64 clone X54-5 / 7.1.

[0360] NSM markers: MS4A7 (polyclonal, obtained from Human Protein Atlas, product number: HPA017418), MS4A6A (polyclonal, obtained from Human Protein Atlas, product number HPA011391). Rat anti-mouse CD88 (C5aR) clone 20 / 70, anti-LILRB4 clone (Pi1.5 clone 1), anti-Trem2 (Pi1.2 clone 2, clone 5, or clone 7), CD206 clone C068C2, MerTK clone Y323.

[0361] SDC: anti-CCR7 clone 4B12 (mouse), anti-CCR7 clone 3D12 (human), anti-XCR1 clone ZET (mouse), CD135 clone A2F10 (mouse), CD117 clone 2B8 (mouse).

[0362] Anti-human Ab clones: CD45 clone H130, CD3e clone OKT3, HLADR clone L243, CD56 clone CMSSB, CD19 clone H1B19, CD14 clone 61D3, CD16 clone CB16, CD11c clone 3.9, BDCA1 clone L161, and BDCA3 clone AD5-14H12. TREM2 (clone 237920).

[0363] Secondary antibodies: anti-human Fab-A488, anti-rat-A488, and anti-goat-A488 were used, all purchased from Jackson Immunoresearch.

[0364] To generate anti-TREM2 antibodies, purified protein antigens corresponding to the extracellular domains of human and mouse TREM2 were produced as Fc fusions and purchased from R&D Systems (Minneapolis, MN). These antigens were diluted in phosphate-buffered saline (PBS), pH 7.4, and immobilized by adsorption on 96-well immunoplates overnight at 4C. The immunoplates were then blocked with bovine serum albumin (BSA) and incubated with the naive synthetic Fab-phagemid library for at least 2 h at room temperature. Unbound phages were removed by extensive washing with PBS supplemented with 0.05% Tween-20. Bound phages were eluted with 0.1 N HCl. Eluted phages were neutralized with 1 M Tris-Cl, pH 8.0, and amplified by passaging through bacterial hosts with transient complementation by helper phage M13KO7. Amplified phages were separated from bacterial supernatant and concentrated by adding 1 / 5 volume PEG-8000, 2.5M NaCl, incubating on ice for 20 min, and then sedimenting by centrifugation at >17,600xg for 20 min. Sedimented phages were resuspended in PBS containing 0.5% BSA and 0.05% Tween-20 and used for subsequent rounds of selection performed by adsorption to mouse, human, or both antigens. After 3–5 rounds of selection, phages were produced from individual clones grown in a 96-well format, and culture supernatants were used in phage ELISA to detect specifically binding clones. Clones that bound to antigen but not to bovine serum albumin or human Fc control were subjected to DNA sequence analysis. Pi1.2 clone 2, clone 5, and clone 7 were selected and tested. These clones were found to bind mouse and human extracellular TREM2 but not mouse or human extracellular TREM1 (data not shown). The accession number for TREM1 (triggering receptor expressed on myeloid cells 1) is NM_018643.3 and is available through the NCBI website as of September 25, 2015.

[0365] Antibody libraries were obtained from the University of Toronto. See Persson et al. CDR-H3 Diversity is Not Required for Antigen Recognition by Synthetic Antibodies. J Mol Biol. 2013 February 22; 425(4): 803-811, which is incorporated by reference herein for the purposes of this disclosure and for all purposes. Various synthetic antibody libraries are also described in USPN7985840B2, which is incorporated by reference herein. Various synthetic antibody libraries are also described in various book chapters (Fellouse and Sidhu, "Making antibodies in bacteria," in: Making and Using Antibodies, Howard and Kaser, eds. Taylor and Francis, 2007, which is incorporated by reference herein.

[0366] LILRB4 antibodies were produced using methods similar to those described above or in WO2013080055, which is incorporated herein by reference. The sequence of Clone 1 is shown in Table BB.

[0367] Cell lines and cell culture

[0368] MC38 cells were cultured by standard cell culture practices. Briefly, adherent cells were cultured in DMEM supplemented with penicillin, streptomycin, and glutamine and 10% FCS at 37 °C for 24 h at 5% CO. 2 EL4 suspension cells were grown in RPMI-1640 supplemented with penicillin, streptomycin, and glutamine, 10% FCS, and 5% CO at 37°C in a 37°C, 5% CO atmosphere, and split every 2 days. 2 The cells were grown in tissue culture flasks at 37° C. under atmospheric conditions and split every 2 days.

[0369] Mouse tumors

[0370] All mice were maintained under SPF conditions and treated in accordance with NIH and American Association of Laboratory Animal Care standards and in accordance with UCSF IACUC protocols.

[0371] Tumor cell lines were harvested and washed three times with PBS before injection in a final injection volume of 50 ul. 150,000 tumor cells were injected subcutaneously into the shaved right flank and allowed to grow for 14-21 days in 6-8 week old C57BL / 6 male mice.

[0372] Tumor growth

[0373] For tumor growth curves, tumors were measured with electronic calipers as tumor width x tumor height over the indicated time periods, and tumor volumes (mm 3 ) was calculated as V = (L x W x W) / 2.

[0374] Antibody treatment

[0375] Purified anti-PD-1 (clone RMPI-14) purchased from BioXcell, human IgG1Fc (purchased from BioXcell), or in-house produced antibody clones were treated with 200ug intraperitoneal injections on four occasions on days 5, 8, and 11, and 14 of tumor growth, with the exception of anti-TREM2 (Pi1.2) (clone 2), which was injected at 40ug, 20ug, 20ug, and 40ug on the respective days.

[0376] Generation of transductants

[0377] Cell lines were generated by lentiviral transduction using GeneCopoeia lentiviral vectors and the LentiPack HIV Packaging System. Infected cell lines were cultured in selective antibiotic (puromycin) and selected for target protein expression by FACS according to the manufacturer's instructions.

[0378] Dye labeling of cells

[0379] Cells were incubated in FCS-free RPMI containing 0.5uM eFluor670 (eBioscience) or 0.5uM CMTMR (Thermo) for 15 minutes at 37°C, after which the dye labeling process was stopped using 2ml of FCS and washed three times with RPMI containing 10% FCS before use.

[0380] Intraperitoneal depletion assay

[0381] 2x10^6 dye-labeled cells of parental and target-expressing transduced cell lines were injected intraperitoneally into wild-type (WT) B6 male mice. Four hours later, animals were injected with 500ug of depleting or control antibodies. After 24-36 hours, migrated cells were harvested by peritoneal lavage and enumerated by flow cytometry.

[0382] statistical analysis

[0383] Statistical analysis was performed using GraphPad Prism software. All data are representative of at least four independent experiments unless otherwise specified. Error bars indicate SEM calculated using Prism and are from triplicate experimental conditions. Specific statistical tests used included paired and independent T-tests, and all p-values ​​less than 0.05 were considered statistically significant.

[0384] Example 13: Presence of NSM and SDC in multiple human tumors. Next, we determined whether NSM and SDC exist across multiple different human tumor types. Human tumor tissue biopsies from metastatic melanoma, head and neck squamous cell carcinoma (HNSC), and colon cancer were analyzed by flow cytometry for the presence of SDC and NSM populations. Representative flow cytometry shows that stepwise gating identified both NSM and SDC populations in all of the described human tumor types (metastatic melanoma, head and neck squamous cell carcinoma (HNSC), and colon cancer). See Figure 13.

[0385] Example 14: Expression and binding of NSM proteins in mouse tumors. We next determined whether certain NSM proteins are expressed on the cell surface of NSM and whether anti-NSM antibodies can bind to such NSM proteins. We also determined whether certain NSM proteins are expressed on SDCs.

[0386] Staining of mouse tumors with NSM markers demonstrated that these markers are specific for NSM and not for SDC or other cell types or subsets. Figure 14 shows labeling of the indicated cell subsets with various NSM markers and gating performed within the indicated cell subsets. Staining of the indicated markers is shown in black histograms, and staining control isotypes are shown by grey-shaded histograms. Top row: B16 melanoma stained with anti-TREM2 (Pi1.2 clone 2); second row: MC38 stained with anti-TREM2 (Pi1.2 clone 2); third row: MC38 stained with anti-MS4A7 (commercial polyclonal antibody purchased from Human Protein Atlas, product code: HPA017418); fourth row: B16 stained with anti-LILRB4 (Pi1.5 clone 1); fifth row: MC38 stained with anti-C5AR1. The data show strong binding to inflammatory DCs, Ly6c+ monocytes, and TAMs, and prominent binding to CD11b+ DCs. Little or no staining was observed on CD103+ DCs, T cells, B cells, and tumor cells.

[0387] The binding of an anti-NSM antibody targeted to a given NSM protein indicates that the NSM may be depleted or killed via known antibody-based depletion mechanisms, for example, by selecting an appropriate Fc domain that enables ADCC.

[0388] Example 15: Expression of CCR7 in human SDC and NSM cells. The specific expression of CCR7 in the SDC and NSM populations in digested tumor tissues was analyzed by flow cytometry. All data are from human metastatic melanoma cells. Figure 15 shows that CCR7 is specifically expressed on human SDCs compared to NSMs and other immune cells.

[0389] Example 16: SDC protein expression and binding in tumors. We next determined whether certain SDC proteins are expressed on the cell surface of SDC and whether anti-SDC antibodies can bind to such SDC proteins, and whether certain SDC proteins are expressed on NSM.

[0390] The specific expression of SDC and NSM gene products in the SDC and NSM populations, respectively, in digested tumor tissue was analyzed by flow cytometry. All data are from the ectopic B78chOVA tumor model. Expression of SDC markers (CCR7 and XCR1, black lines) was compared with their respective isotypes (gray shading) across cell populations in the tumor. Figure 16 shows that SDC gene products are specifically expressed in SDC, and that SDC proteins are not expressed in NSM.

[0391] Example 17: No binding to NSM occurs outside of tumors. Bone marrow (BM) and spleen of healthy wild-type B6 mice were analyzed by flow cytometry for expression of TREM2 (clone 237920, RnD) and MS4A7 (commercially available polyclonal, Human Protein Atlas).

[0392] Representative histograms show the staining levels of TREM2 and MS4A7 across several healthy tissue populations. Secondary controls for each population (anti-rat-A488 and anti-rabbit-A488, respectively, obtained from Jackson Immunoresearch) are shaded grey and target protein staining for each population is overlaid as a solid black histogram.

[0393] Bone marrow (BM) and spleen of healthy wild-type B6 mice were analyzed by flow cytometry for expression of TREM2 (Pi1.2 clone 2, clone 5, and clone 7) by antibody staining across a range of staining concentrations (2, 20, 200 nM) and compared to controls (human IgG1Fc, labeled as 0 nM) across immune populations.

[0394] Figure 17 shows that healthy BM and spleen tissues show virtually no staining for multiple NSM markers, indicating that the use of anti-NSM antibodies during, for example, tumor therapy is unlikely to result in significant non-specific effects.

[0395] Example 18: Depletion of NSM in tumors using anti-TREM2 or anti-LILRB4 antibodies. Next, it was determined whether anti-NSM antibodies could specifically deplete NSM-bearing cells in vivo.

[0396] TREM2: Control and EL4 transfected cells expressing TREM2 (TREM2 can also be called Pi1.2) were dye-labeled with CMTMR and Elfour670, respectively, and mixed at a 1:1 ratio. 4x10^6 of the total cell mixture was injected intraperitoneally into wild-type (WT) B6 male mice. Four hours later, the animals were injected with 500ug of anti-Pi1.2 (anti-TREM2) antibody or control human IgG1. Thirty-six hours later, the mice were sacrificed and collected by peritoneal lavage, and the cells recovered from the peritoneum were counted by flow cytometry. Figure 18 shows that anti-TREM2 antibody specifically depletes TREM2-bearing cells in vivo, while the control antibody does not cause depletion.

[0397] LILRB4 (ILT3): Control expressing TdTomato and GFP, respectively, and EL4 transfected cells expressing LILRB4 were mixed at 1:1 ratio at 5x10^5 of each cell type and injected into the peritoneal cavity of wild type (WT) B6 male mice. After 2 hours, animals were injected with 100ug of anti-LILRB4 clone 1 or PBS control. After 24 hours, mice were sacrificed and collected by peritoneal lavage, and cells recovered from the peritoneum were counted by flow cytometry. Figure 18 shows that anti-LILRB4 antibody specifically depletes LILRB4-bearing cells in vivo.

[0398] Anti-NSM antibodies that target a given NSM protein deplete NSM, indicating that the anti-NSM antibody will reduce tumor growth when administered to a tumor-bearing subject.

[0399] Example 19: Reduction of tumor growth following administration of anti-TREM2 antibodies. Next, it was determined whether anti-NSM antibodies could reduce tumor growth in vivo.

[0400] Six-week-old male B6 mice were injected with MC38 colon carcinoma at T0. Mice randomized into treatment groups were treated with the indicated antibodies by intraperitoneal injection on days 5, 7, 11, and 15 after tumor implantation. Dosing: anti-PD-1 and Fc control were administered at 200ug / day, and anti-TREM2 (Pi1.2 clone 2) antibody was administered at 40ug, 20ug, 20ug, and 40ug on days 5, 7, 11, and 15. Tumors were measured with calipers and tumor volumes are shown. Data analysis was performed excluding the largest outliers for ...

Claims

[Claim 1] The invention described in the specification of this application.

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