Immune cell-derived secretory proteomes

Abstract

The present invention provides a composition comprising a secretory proteome obtained by culturing immune progenitor cells in the presence of an agent that activates the immune progenitor cells as activated immune cells. The invention also provides compositions for tissue regeneration, methods of generating macrophage-derived secretory proteomes, methods of screening drugs, and methods of culturing proliferative cells.

Description

TECHNICAL FIELD

[0001] The present disclosure broadly relates to immune cell-derived secretomes. In particular, the present disclosure relates to a composition comprising a secretome obtained from culturing cells in the presence of immune cells. BACKGROUND

[0002] Cancer cells require nutrients to grow and proliferate. During periods of nutrient stress in the microenvironment, it is not known whether or how cancer cells can utilize alternative resources to re-wire and survive in a patient. Patient tumors are more complex than in vitro culture systems. Patient tumors include a microenvironment surrounding the cancer cells. Nonetheless, laboratory drug testing still uses in vitro cancer cell cultures without the microenvironment, which remains an imperfect strategy for oncology drug discovery and translation.

[0003] The clinical significance of immune cell / macrophage density infiltrating tumors varies by body organ. Increased immune cell / macrophage density is associated with tumor progression and / or poor clinical outcome in certain organs (brain, breast, liver, kidney, ovary, pancreas, thyroid, head and neck). In colorectal cancer, increased immune cell / macrophage infiltration is associated with better prognosis, while the role of immune cell / macrophages remains controversial in bone, lung, and prostate cancer. The diversity of dynamic immune cell / macrophage polarization profiles adds an order of magnitude of complexity to the problem. Over the past decade, it has become increasingly recognized that infiltrating immune cells / macrophages dominate in brain tumors, but there is no consensus on the clinical significance of immune cell / macrophage infiltration correlating with patient outcomes in brain tumors. Some current strategies to study immune cell / macrophages infiltrating patient tumors include genomic analysis of micro-dissected regions of immune cell / macrophages in patient tumors, and single cell sequencing of individual immune cell / macrophages in patient tumors. These approaches involve separating immune cell / macrophage microenvironment compartments from tumor cell compartments in patient tumors that are collected. Newer approaches such as spatial transcriptomics allow for gene expression profiling without destroying the tumor structure. However, a common challenge to all of these approaches is that the excised patient tumor is immortalized at a single time point. Thus, the ability to study the in situ effects of macrophages that vary over time is lost.

[0004] Accordingly, there is a need to provide an alternative approach to study the effects of immune cell / macrophages on the tumor microenvironment. SUMMARY

[0005] In one aspect, the present invention provides a composition comprising a secretome obtained from culturing immune progenitor cells in the presence of an agent that activates immune progenitor cells to activated immune cells.

[0006] In some embodiments, the secretome comprises proteins including cytokines, hormones, antibodies, growth factors, extracellular matrix proteins, shedding receptors, coagulation factors, adhesion molecules, proteases, kinases, and / or glycoproteins.

[0007] In some embodiments, the secretome comprises one or more factors selected from the group consisting of CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8, and serpin El / PAI-1.

[0008] In some embodiments, the immune cells comprise myeloid cells, lymphoid cells, and / or innate immune cells.

[0009] In some embodiments, the immune progenitor cells are myeloid progenitor cells.

[0010] In some embodiments, the immune cells are macrophages expressing CD11b and / or CD163.

[0011] In some embodiments, the secretome is a macrophage-derived secretome.

[0012] In some embodiments, the agent comprises a stimulatory agent or an inhibitory agent.

[0013] In some embodiments, the agent is a bone marrow stimulatory agent.

[0014] In some embodiments, the agent is PMA and / or IL-4.

[0015] In some embodiments, the secretome maintains cell growth, cell proliferation, cryopreservation of cells, extends telomere length in cancer cells, is involved in metabolic reprogramming, identifies drug resistance, and / or prevents cancer cell death under nutrient stress conditions.

[0016] In another aspect, the present application provides a composition for tissue regeneration.

[0017] In yet another aspect, the present application provides a method of producing a macrophage-derived secretome, comprising culturing immune progenitor cells in the presence of a stimulatory agent, thereby producing a population of activated immune cells, and harvesting the secretome from the produced population of activated immune cells.

[0018] In some embodiments, the method comprises culturing the activated immune cells in the presence of diseased cells.

[0019] In some embodiments, the diseased cells are cells from a proliferative disease.

[0020] In some embodiments, the diseased cell is a brain tumor, atypical teratoid rhabdoid tumor (ATRT), and / or medulloblastoma.

[0021] In yet another aspect, the present application provides a method of screening a drug, comprising culturing the drug with a diseased cell in the presence of the composition disclosed herein.

[0022] In yet another aspect, the present application provides a method of culturing a proliferative cell, comprising culturing the proliferative cell in the composition disclosed herein. DETAILED DESCRIPTION

[0023] The tumor microenvironment comprises a variety of cell types such as immune cells, cancer-associated fibroblasts, endothelial cells, pericytes, and various other tissue-resident cell types. These host cells are known to play a critical role in the pathogenesis of cancer, for example, increased immune cell / macrophage density is associated with tumor progression and poor clinical outcomes. In view of the importance of the tumor microenvironment in cancer pathogenesis, it is necessary to provide a method to understand the role / influence of immune cells / macrophages in the tumor microenvironment. The present disclosure provides a method to study the role / influence of immune cells / macrophages in the tumor microenvironment, which solves at least one problem currently faced in studying immune cells / macrophages in the tumor / tumor microenvironment.

[0024] In one aspect, the present application provides a composition comprising a secretome obtained by culturing immune progenitor cells in the presence of an agent that activates immune progenitor cells to activated immune cells.

[0025] In some embodiments, the immune progenitor cells are myeloid progenitor cells.

[0026] In some embodiments, the present application provides a composition comprising a secretome obtained by culturing cells in the presence of an agent to produce immune cells.

[0027] In some embodiments, the present application provides a composition comprising a secretome obtained by culturing cells in the presence of an agent to produce immune cells,

[0028] wherein the immune cells are cells capable of expressing CD11b.

[0029] In some embodiments, the cells are a cell line.

[0030] In some embodiments, the cell line can include, but is not limited to, a myeloid cell line, a lymphoma cell line, and the like.

[0031] In some embodiments, the cell line can include, but is not limited to, human myeloid leukemia-derived cell line (U937), human lymphoma cell line (LK46), THP1, and the like.

[0032] In some embodiments, the cell line is a human myeloid leukemia-derived cell line (U937).

[0033] As used herein, the term “secretome” refers to the sum of the molecules of organic and inorganic constituents released by a biological cell, tissue, and / or organ. The secretome is a collection of constituents expressed by a biological cell, tissue, and / or organ and secreted into the extracellular space, including paracrine substances, exosomes, and microvesicles.

[0034] In some embodiments, the secretome can include constituents such as, but not limited to, polypeptides, polynucleotides, lipids, carbohydrates, exosomes, microvesicles, paracrine substances, and the like.

[0035] In some embodiments, the polynucleotides can include, but are not limited to, DNA, mRNA, miRNA, non-coding RNA, and the like.

[0036] In some embodiments, the secretome can include proteins such as, but not limited to, cytokines, hormones, antibodies, growth factors, extracellular matrix proteins, shed receptors, coagulation factors, adhesion molecules, proteases, kinases, glycoproteins, protease inhibitors, and the like.

[0037] In some embodiments, the composition includes cytokines such as chemotactic cytokines, chemokines, and lymphokines.

[0038] As used herein, the term “cytokine” includes chemokines, chemotactic cytokines, and lymphokines. Chemokines / chemotactic cytokines, such as CCL14, CCL2, CCL19, CCL5, and the like, are a family of small cytokines or signaling proteins secreted by cells that induce directed chemotaxis of leukocytes and other types of cells, including endothelial cells and epithelial cells. Lymphokines refer to a class of cytokines produced by lymphocytes. Their actions include attracting other immune cells (including macrophages and other lymphocytes) to sites of infection and subsequently activating these cells to prepare them to mount an immune response. Lymphokines secreted by helper T cells include, for example, IL-2, IL-3, IL-4, and the like.

[0039] In some embodiments, the cytokines can include pro-inflammatory and / or anti-inflammatory cytokines.

[0040] In some embodiments, the pro-inflammatory cytokines can include, but are not limited to, chemokine ligand 5 (CCL5 / RANTES), macrophage inflammatory protein-1 alpha / beta (MIP-1a / MIP-1b), macrophage migration inhibitory factor (MIF), interleukin-8 (IL-8), monocyte chemoattractant protein-1 (CCL2 / MCP-1), IL-6, TNF-a, IL-1b, and the like.

[0041] In some embodiments, the anti-inflammatory cytokines can include, but are not limited to, IL-1 receptor antagonist (IL-1ra / IL-IF3), IL-4, IL-10, IL-11, IL-13, and the like. In some embodiments, the composition can comprise a protease inhibitor.

[0042] In some embodiments, the composition can comprise a serine protease inhibitor, such as serpin El / PAI-1.

[0043] In some embodiments, the composition can comprise a single factor, two factors, three factors, four factors, five factors, six factors, seven factors, eight factors, nine factors, or ten factors.

[0044] As used herein, the term“factor” refers to a single component of a secretome.

[0045] In some embodiments, the composition comprises six factors. In some embodiments, the composition comprises seven factors.

[0046] In some embodiments, the secretome comprises one or more factors selected from the group consisting of CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8, and / or serpin El / PAI-1.

[0047] In some embodiments, the secretome comprises one or more factors selected from the group consisting of CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, and IL-8.

[0048] In some embodiments, the factors comprise CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, and / or IL-8.

[0049] In some embodiments, the composition obtained from immune cells, such as macrophages, can include, but is not limited to, CCL5 / RANTES, IL-1ra / IL-IF3, MIP-1a / MIP-1b, MIF, IL-8, CCL2 / MCP-1, Serpin El / PAI-1 (expressed from highest to lowest), etc.

[0050] In some embodiments, in the presence of diseased cells, such as tumor cells, the composition obtained from immune cells, such as macrophages / CD11b expressing macrophages, can include significantly increased CCL-2 / MCP-1, MIP-1a / MIP-1b, IL-8, MIF expression; and increased IL-1ra / IL-IF3, CCL-5 / RANTES, and Serpin El / PAI-1 expression. Advantageously, the present disclosure comprises a secretome product that is mixed with a plurality of important factors, and the biological dose of each factor is determined by stimulated macrophage biology assays in laboratory culture systems. This is different from most cytokine / chemokine products on the market that are produced and packaged individually. As shown in Figures 2A-2D each factor is produced in a large enough amount to be detected in standard culture assays, such as but not limited to cytokine blots, RNA sequencing, microarrays, etc.

[0051] The secretome during nutrient stress is involved in cancer growth / proliferation and prevents cancer cell death. The secretome is superior to standard (serum-containing or serum-free) growth media in promoting cancer growth / proliferation from 4 to 96 hours, and comparable to standard media in preventing cancer cell death from 4 to 96 hours.

[0052] The secretome is also involved in drug response of cancer cells. In standard media, drugs can act quickly. The drug response of the same drug in the secretome is attenuated. This suggests that drugs that are effective in standard media in laboratory in vitro tests can not be as effective in patient tumors with rich immune conditions. This can lead to drug failure in clinical trial phases because patient tumors can have rich immune microenvironments. Certain drugs are better at causing cancer cell death in vitro in the secretome compared to standard media. Identifying which drugs are capable of causing cancer cell death in patient tumors with rich immune conditions is critical for tailoring precision drugs for patients.

[0053] In some embodiments, the drug response of diseased cells, such as medulloblastoma cells, can be more sensitive in the presence of the secretome compared to standard media.

[0054] In some embodiments, the number of immune progenitor cells cultured / seeded can include at least 50 cells, at least 100 cells, at least 150 cells, at least 200 cells, at least 250 cells, at least 300 cells, at least 350 cells, at least 400 cells, at least 450 cells, at least 500 cells, at least 550 cells, at least 1000 cells, at least 1500 cells, at least 2000 cells, at least 2500 cells, or at least 500 cells. cells, at least 3000 cells, at least 3500 cells, at least 4000 cells, at least 4500 cells, at least 5000 cells, at least 5500 cells, at least 6000 cells, at least 6500 cells, at least 7000 cells, at least 7500 cells, at least 8000 cells, at least 8500 cells, at least 9000 cells, at least 9500 cells, at least 10,000 cells, at least 20,000 cells, at least 30,000 cells, at least 30,000 cells, at least 3500 cells, at least 40,000 cells, at least 4500 cells, at least 5000 cells, at least 5500 cells, at least 6000 cells, at least 6500 cells, at least 7000 cells, at least 7500 cells, at least 8000 cells, at least 8500 cells, at least 9000 cells, at least 9500 cells, at least 10,000 cells, at least 20,000 cells, cells, at least 30,000 cells, at least 40,000 cells, at least 50,000 cells, at least 60,000 cells, at least 70,000 cells, at least 80,000 cells, at least 90,000 cells, at least 100,000 cells, at least 150,000 cells, at least 200,000 cells, at least 250,000 cells, at least 300,000 cells, at least 350,000 cells, cells, at least 400,000 cells, at least 450,000 cells, at least 500,000 cells, at least 550,000 cells, at least 600,000 cells, at least 650,000 cells, at least 700,000 cells, at least 750,000 cells, at least 800,000 cells, at least 850,000 cells, at least 900,000 cells, at least 1,000,000 cells, etc.

[0055] In some embodiments, the number of immune progenitor cells cultured / inoculated can include about 50 cells, about 100 cells, about 150 cells, about 200 cells, about 250 cells, about 300 cells, about 350 cells, about 400 cells, about 450 cells, about 500 cells, about 550 cells, about 1000 cells, about 1500 cells, about 2000 cells, about 2500 cells, about 3000 cells, about 3500 cells, about 4000 cells, about 4500 cells, about 5000 cells, about 5500 cells, about 6000 cells, about 6500 cells, about 7000 cells, about 7500 cells, about 8000 cells, about 8500 cells, about 9000 cells, about 9500 cells, about 10,000 cells, about 20,000 cells, about 30,000 cells, about 40,000 cells, about 50,000 cells, about 60,000 cells, about 70,000 cells, about 80,000 cells, about 90,000 cells, about 100,000 cells, about 150,000 cells, about 200,000 cells, about 250,000 cells, about 300,000 cells, about 350,000 cells, about 400,000 cells, about 450,000 cells, about 500,000 cells, about 550,000 cells, about 600,000 cells, about 650,000 cells, about 700,000 cells, about 750,000 cells, about 800,000 cells, about 850,000 cells, about 900,000 cells, about 1,000,000 cells, and the like.

[0056] In some embodiments, the immune progenitor cells can be cultured in a petri dish, a 6-well plate, a 12-well plate, a 24-well plate, a 96-well plate, a T-25 flask, a T-75 flask, and the like.

[0057] In some embodiments, the immune progenitor cells can be cultured in a petri dish / flask / plate made of, such as but not limited to, glass, plastic, and the like.

[0058] In some embodiments, the immune cells can include, but are not limited to, myeloid cells, lymphoid cells, innate immune cells, and the like.

[0059] In some embodiments, the immune cells can include, but are not limited to, cells expressing CD11b, CD163, and the like.

[0060] In some embodiments, the immune cells are capable of expressing CD11b.

[0061] In some embodiments, the immune cells are CD11b-expressing cells. In some embodiments, the immune cells can be immune cells that express CD11b upon maturation or activation.

[0062] In some embodiments, the immune cells are macrophages.

[0063] In some embodiments, the macrophages can include any macrophage cell markers, but are not limited to cells expressing CD11b, CD14, CD16, CD64, CD163, CD68, MARCO, and the like.

[0064] In some embodiments, the immune cells are CD11b-expressing macrophages.

[0065] In some embodiments, the immune cells are CD11b- and / or CD163-expressing macrophages.

[0066] In some embodiments, the myeloid cells can include cells derived from myeloid progenitor cells, such as but not limited to macrophages, monocytes, dendritic cells, antigen presenting cells, and the like.

[0067] In some embodiments, the myeloid cells can include any cells expressing myeloid cell markers, such as but not limited to cells expressing CD11b, CD206, CD68, CD15, and the like.

[0068] In some embodiments, the lymphoid cells can include but are not limited to T lymphocytes, B lymphocytes, and the like.

[0069] In some embodiments, the lymphocytes can include but are not limited to cells expressing CD3, CD4, CD8, and the like.

[0070] In some embodiments, the innate immune cells can include but are not limited to neutrophils, natural killer cells, and the like.

[0071] In some embodiments, the neutrophils can include but are not limited to cells expressing CD16, CD15, CD10, CXCR2, and the like.

[0072] In some embodiments, the secretome is a macrophage-derived secretome.

[0073] Without wishing to be bound by theory, macrophages have been observed to infiltrate a variety of human tumors and are present in a variety of cancer types. The number of macrophages in the tumor stroma of patients is high, thus making them an extremely attractive and ideal target in the microenvironment. However, macrophages are dynamic and have many aspects and phenotypes, which are not fully understood in the field. In the present disclosure, the inventors of the present disclosure did not study macrophages, but rather studied the secretome of macrophages in the tumor microenvironment of patients, which provides benefits and advantages for detecting a more constant environment fluid around tumor cells. The inventors of the present disclosure hypothesized that various cytokine-chemokines from the secretome of macrophage origin continuously provide a critical niche for tumor progression / development and influence drug response for each individual tumor. In the absence of nutrients during nutrient stress, macrophages can provide this secretome as an alternative energy source for cancer cell survival. To explore the real-time dynamic interactions between macrophage-tumor ecosystems, the inventors of the present disclosure developed an assay that utilizes the secretome of human CD11b+ (pan-macrophage) cell origin to determine its effect on atypical teratoid rhabdoid tumor (ATRT) and medulloblastoma, both of which are embryonal brain tumors in children.

[0074] In some embodiments, the secretome is a cell-free macrophage-derived secretome.

[0075] In some embodiments, the cell-free macrophage-derived secretome is obtained from human and non-human organisms. In some embodiments, the non-human organisms can include, but are not limited to, mice, rats, non-human primates, and the like. In some embodiments, the background of mice can include, but are not limited to, C57 / BL6, BALB / c, CD-1, SCID, and the like. In some embodiments, the background of rats can include, but are not limited to, A / J, Sprague-Dawley, Wistar, and the like. In some embodiments, the non-human primates can include, but are not limited to, Rhesus macaques, Japanese macaques, Olive baboons, Squirrel monkeys, Marmosets, and the like.

[0076] In some embodiments, the cell-free macrophage-derived secretome is obtained from CD11b-enriched human and non-human organisms. In some embodiments, the cell-free macrophage-derived secretome is obtained from CD11b-enriched non-human organisms. In some embodiments, the cell-free macrophage-derived secretome is obtained from CD11b-enriched mice. In some embodiments, the CD11b-enriched mice can include, but are not limited to, corresponding mice of SCID / RAG2 immunocompromised / immunosuppressed mice, and the like.

[0077] In some embodiments, the secretome is a cell-free human macrophage-derived secretome.

[0078] Without wishing to be bound by theory, cancer cells require nutrients to grow and proliferate. It is not known whether or how cancer cells can rewire and survive in a patient if they lack nutrients during periods of nutrient stress in the microenvironment. Patient tumors are more complex than in vitro culture systems. Patient tumors include a microenvironment surrounding the cancer cells. Using in vitro culture-based media for drug laboratory testing remains an imperfect strategy for drug discovery and translation.

[0079] The methods of the present disclosure are directed to the situation of cancer cells under the conditions of their microenvironment. Macrophages are difficult to study because they encompass a diverse cell spectrum and not all phenotypes are well characterized. The inventors of the present disclosure utilize the secretome of macrophages, which provides the microenvironment context surrounding tumor cells. This enables the study of the role of the secretome surrounding cancer cells (derived from macrophages). Studies known in the art that study macrophage infiltrated patient tumors involve isolating the macrophage microenvironment compartment from tumor cells compartment / macrophages / immune cells, immortalizing them at a single time point. Advantageously, the present disclosure uses a secretome-based approach to circumvent this problem / solve this research challenge. This enables the study of the role of the secretome of macrophages surrounding cancer cells on an in situ mechanism and study the dynamic in situ interactions between the two compartment macrophage tumor ecosystem without disrupting the microenvironment context. Furthermore, studies in the art typically study the effect of individual factors on cancer cells one at a time (i.e., one factor at a time). In contrast, the present disclosure collects multiple factors in the tumor cell environment associated with patient tumors, which are secreted by CD11b+ cells in a biologic mass. The present disclosure determines the role of biologically relevant immune environment on the survival rate of cancer cells under nutrient depletion (such as stress) conditions and drug response in in vitro and in vivo screens. This provides a high commercial value and research asset and is highly applicable to the pharmaceutical industry. Furthermore, the secretome derived from human macrophages makes it more patient-relevant in drug screening.

[0080] Further, there is little understanding of the role of the immune / macrophage microenvironment in modulating patient tumor drug response. Drugs that are effective in the lab in vitro can very well be affected by the patient’s tumor macrophage / immune microenvironment when administered to the patient (these microenvironments do not exist in vitro in petri dishes of cancer cells). Thus, by providing cancer cells with a macrophage-derived secretome during high-throughput drug screening in the lab, the inventors of the present disclosure are able to objectively measure the impact of the secretome on drug efficacy, which correlates to the more immunologically functional patient tumor than cancer cells in petri dishes lacking an immune microenvironment. The present disclosure provides a paradigm shift in understanding of patient tumors with a secretome that is notably absent in in vitro testing studies in the art. The present disclosure provides a new appreciation that cancer cells do not rely solely on nutrients for survival and that cancer cells can exploit the secretome to evade cell death (e.g., shown by flow cytometry data).

[0081] In some embodiments, the agent can include, but is not limited to, a stimulant, an inhibitor, and / or the like.

[0082] In some embodiments, the stimulant can include, but is not limited to, vitamin D, IL-2, phorbol 12-myristate 13-acetate (PMA) and / or IL-4, LPS (lipopolysaccharide), and / or the like.

[0083] In some embodiments, the inhibitor can include an antibody, a receptor, and / or a CD11b inhibiting drug (binds and / or blocks CD11b). In some embodiments, the inhibitor can include, but is not limited to, GB1275, and / or the like.

[0084] In some embodiments, the agent is a stimulant.

[0085] In some embodiments, the agent is a myeloid stimulant.

[0086] In some embodiments, the agent is PMA and / or IL-4.

[0087] In some embodiments, the stimulant is PMA and IL-4.

[0088] In some embodiments, PMA is used at a concentration such as about 5 ng / ml to about 300 ng / ml, 15 ng / ml to about 250 ng / ml, 20 ng / ml to about 200 ng / ml, 25 ng / ml to about 150 ng / ml, 30 ng / ml to about 100 ng / ml, 35 ng / ml to about 50 ng / ml, 40 ng / ml to about 45 ng / ml, and / or the like.

[0089] In some embodiments, PMA is used at a concentration such as 0.01 ng / ml, 0.02 ng / ml, 0.03 ng / ml, 0.04 ng / ml, 0.05 ng / ml, 0.06 ng / ml, 0.07 ng / ml, 0.08 ng / ml, 0.09 ng / ml, 0.1 ng / ml, 0.2 ng / ml, 0.3 ng / ml, 0.4 ng / ml, 0.5 ng / ml, 0.6 ng / ml, 0.7 ng / ml, 0.8 ng / ml, 0.9 ng / ml, 1 ng / ml, 1.1 ng / ml, 1.2 ng / ml, 1.3 ng / ml, 1.4 ng / ml, 1.5 ng / ml, 1.6 ng / ml, 1.7 ng / ml, 1.8 ng / ml, 1.9 ng / ml, 2 ng / ml, 2.1 ng / ml, 2.2 ng / ml, 2.3 ng / ml, 2.4 ng / ml, 2.5 ng / ml, 2.6 ng / ml, 2.7 ng / ml, 2.8 ng / ml, 2.9 ng / ml, 3 ng / ml, 4 ng / ml, 5 ng / ml, 6 ng / ml, 7 ng / ml, 8 ng / ml, 9 ng / ml, 10 ng / ml, 15 ng / ml, 20 ng / ml, 30 ng / ml, 40 ng / ml, 50 ng / ml, 60 ng / ml, 70 ng / ml, 80 ng / ml, 90 ng / ml, 100 ng / ml, 150 ng / ml, 200 ng / ml, 250 ng / ml, 300 ng / ml, etc.

[0090] In some embodiments, IL-4 is used at a concentration such as about 5 ng / ml to about 200 ng / ml, 15 ng / ml to about 150 ng / ml, 20 ng / ml to about 100 ng / ml, 25 ng / ml to about 50 ng / ml, 30 ng / ml to about 40 ng / ml, etc.

[0091] In some embodiments, IL-4 is used at a concentration such as 0.01 ng / ml, 0.02 ng / ml, 0.03 ng / ml, 0.04 ng / ml, 0.05 ng / ml, 0.06 ng / ml, 0.07 ng / ml, 0.08 ng / ml, 0.09 ng / ml, 0.1 ng / ml, 0.2 ng / ml, 0.3 ng / ml, 0.4 ng / ml, 0.5 ng / ml, 0.6 ng / ml, 0.7 ng / ml, 0.8 ng / ml, 0.9 ng / ml, 1 ng / ml, 1.1 ng / ml, 1.2 ng / ml, 1.3 ng / ml, 1.4 ng / ml, 1.5 ng / ml, 1.6 ng / ml, 1.7 ng / ml, 1.8 ng / ml, 1.9 ng / ml, 2 ng / ml, 2.1 ng / ml, 2.2 ng / ml, 2.3 ng / ml, 2.4 ng / ml, 2.5 ng / ml, 2.6 ng / ml, 2.7 ng / ml, 2.8 ng / ml, 2.9 ng / ml, 3 ng / ml, 4 ng / ml, 5 ng / ml, 6 ng / ml, 7 ng / ml, 8 ng / ml, 9 ng / ml, 10 ng / ml, 15 ng / ml, 20 ng / ml, 25 ng / ml, 30 ng / ml, 35 ng / ml, 40 ng / ml, 45 ng / ml, 50 ng / ml, 55 ng / ml, 60 ng / ml, 65 ng / ml, 70 ng / ml, 80 ng / ml, 90 ng / ml, 100 ng / ml, 150 ng / ml, 200 ng / ml, etc.

[0092] In some embodiments, the reagent for generating immune cells is incubated with the cells for a period of time such as, but not limited to, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 12 hours, 24 hours, 36 hours, 48 hours, 72 hours, 92 hours, etc. In some embodiments, the reagent for generating immune cells is incubated with the cells for 48 hours.

[0093] In some embodiments, the reagent for generating immune cells is incubated with the cells for a period of time such as, but not limited to, no more than 1 hour, no more than 2 hours, no more than 3 hours, no more than 4 hours, no more than 5 hours, no more than 6 hours, no more than 12 hours, no more than 24 hours, no more than 36 hours, no more than 48 hours, no more than 72 hours, no more than 92 hours, etc. In some embodiments, the reagent for generating immune cells is incubated with the cells for no more than 48 hours.

[0094] In some embodiments, wherein after incubation with the reagent, the immune cells are washed and incubated alone or with diseased cells such as tumor cells.

[0095] In some embodiments, the population of macrophage-derived secretome comprises at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 90%, or at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or substantially all of the cells expressing CD11b.

[0096] In some embodiments, the population of cells produced by the stimulatory agent comprises at least 50%, 55%, 60%, 65%, 70%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% of CD11b expressing cells. In some embodiments, the population of cells produced by the stimulatory agent comprises at least 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% of CD11b expressing cells.

[0097] In some embodiments, the secretome maintains cell growth, cell proliferation, cryopreservation of cells, extends telomere length of cancer cells, is involved in metabolic reprogramming such as methyl group histidine metabolism, biotin metabolism, taurine and hypotaurine metabolism, identifies drug resistance, and / or prevents cancer cell death under nutrient stress conditions.

[0098] The inventors of the present disclosure show that the secretome produced in the present disclosure is superior to standard growth media (serum containing or serum free) in maintaining cancer cell growth or proliferation and preventing cancer cell death under nutrient stress / no nutrient conditions.

[0099] In another aspect, the present disclosure provides a method of producing a macrophage-derived secretome, comprising culturing immune progenitor cells in the presence of a stimulatory agent, thereby producing a population of activated immune cells, and harvesting the secretome from the produced population of activated immune cells.

[0100] In some embodiments, the present disclosure provides a method of generating a composition as described in the present disclosure, comprising culturing cells in the presence of an agent to generate immune cells, and harvesting the secretome produced by the immune cells.

[0101] In another aspect, the present disclosure provides a method of generating a composition, comprising culturing cells in the presence of an agent to generate immune cells, and harvesting the secretome produced by the immune cells.

[0102] In some embodiments, the secretome is obtained by culturing cells in the presence of an agent to produce immune cells and harvesting the secretome produced by the immune cells.

[0103] In some embodiments, the secretome is obtained by culturing cells in the presence of a stimulant to produce immune cells expressing CD11b and harvesting the secretome produced by the immune cells.

[0104] In some embodiments, the secretome is obtained by culturing myeloid cells in the presence of a stimulant to produce macrophages expressing CD11b and harvesting the secretome produced by the immune cells.

[0105] In some embodiments, the secretome is obtained by culturing U937 cells in the presence of a PMA+IL-4 cocktail to produce macrophages expressing CD11b and harvesting the secretome produced by the macrophages expressing CD11b.

[0106] In some embodiments, the secretome is obtained by culturing U937 cells in the presence of a PMA+IL-4 cocktail to produce macrophages expressing CD11b and harvesting the secretome produced by the macrophages.

[0107] In some embodiments, the secretome comprises CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, and / or IL-8.

[0108] In some embodiments, the secretome comprises CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8, and / or Serpin-E1 / PAI-1.

[0109] In some embodiments, the secretome is extracted / harvested by an extraction method such as, but not limited to, ultrafiltration, precipitation, dialysis, and the like.

[0110] In some embodiments, the secretome is extracted / harvested by removing the cells or fragments thereof from the culture medium.

[0111] In some embodiments, the secretome can be produced / harvested in 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 18 hours, 24 hours, 30 hours, 36 hours, 42 hours, 48 hours, and the like. In some embodiments, the secretome is produced / harvested in 48 hours. In some embodiments, the secretome is produced / harvested in 3 hours. In some embodiments, the secretome is produced / harvested in 24 hours. In some embodiments, the secretome is produced / harvested in 48 hours.

[0112] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 3 hours, at least 6 hours, at least 12 hours, at least 24 hours, at least 36 hours, at least 48 hours, at least 72 hours, etc.

[0113] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 3 hours.

[0114] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 24 hours. In some embodiments, the secretome harvested from the CD11b-expressing cells after incubation for at least 24 hours with the agent has a higher enhancing potential (such as higher tumor cell proliferation) compared to the secretome harvested at 3 hours.

[0115] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 48 hours. In some embodiments, the secretome harvested from the CD11b-expressing cells after incubation for at least 48 hours with the agent has a higher enhancing potential (such as higher tumor cell proliferation) compared to the secretome harvested at 3 hours.

[0116] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for about 3 hours, about 6 hours, about 12 hours, about 24 hours, about 36 hours, about 48 hours, about 72 hours, etc.

[0117] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for about 3 hours.

[0118] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for about 24 hours.

[0119] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for about 48 hours.

[0120] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for no more than 3 hours, no more than 6 hours, no more than 12 hours, no more than 24 hours, no more than 36 hours, no more than 48 hours, no more than 72 hours, etc.

[0121] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for no more than 3 hours.

[0122] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for no more than 24 hours.

[0123] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for no more than 48 hours.

[0124] In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 1 hour to at least 48 hours. In some embodiments, the secretome is harvested from the CD11b-expressing cells after incubation for at least 1 hour to at least 24 hours.

[0125] In some embodiments, the secretome is stable at a storage temperature, such as but not limited to 4°C, 0°C, -20°C, -80°C, and the like. In some embodiments, the secretome is stable at -80°C.

[0126] In some embodiments, the secretome is stable for 1 month, 3 months, 6 months, 9 months, 1 year, 1.5 years, 2 years, 2.5 years, 3 years, 3.5 years, 4 years, 5 years, 6 years, 7 years, 8 years, 9 years, 10 years, and the like. In some embodiments, the secretome is stable for 3 years. In some embodiments, the secretome is stable for 3 years at -80°C.

[0127] As used herein, the term“stable” refers to a fixed and stable state of reliability. A stable item / product is generally able to withstand fluctuations in thermal or physiological conditions. Thus, a stable item / product is understood to be able to withstand thermal variations that can lead to degradation or denaturation.

[0128] In another aspect, the present disclosure provides a method of producing a macrophage-derived secretome, comprising culturing cells in the presence of a stimulating agent, thereby producing a population of macrophages, and harvesting the secretome from the produced macrophages.

[0129] In some embodiments, the population of macrophages is a population of cells in which at least 1%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 90%, or at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or substantially all of the cells express CD11b.

[0130] The inventors of the present disclosure have developed a method of generating a macrophage-derived secretome. This secretome-based product is able to sustain cancer cells during: (1) nutrient stress; (2) drug response.

[0131] Advantageously, the inventors of the present disclosure provide a method that can be commercially scaled. The secretome of the present disclosure can be harvested in large quantities after culturing immune progenitor cells for 48 hours in the presence of reagents and packaged in cryovials that can be stably stored for 3 years or more at -80°C. The inventors of the present disclosure have old product stock that was stored 3 years ago that is as effective as freshly produced batches. It can be shipped to consumers / international partners on dry ice. Laboratories can be provided to pharmaceutical companies to test their drug libraries / to test the effects of microenvironmental factors on the efficacy of their new drugs before they enter patient clinical trials.

[0132] In some embodiments, the methods of the present disclosure comprise culturing cells in the presence of diseased cells.

[0133] In some embodiments, the methods of the present disclosure comprise culturing activated immune cells in the presence of diseased cells.

[0134] As used herein, the term “diseased cell” refers to a cell that is structurally or physiologically unhealthy. A diseased cell can be abnormal, damaged, or affected by an abnormality of a disease.

[0135] In some embodiments, the diseased cells described herein can comprise cells from a proliferative disease.

[0136] Proliferative diseases as described herein include tumors and / or inflammatory diseases. Proliferative cells as described herein include cells from a proliferative disease.

[0137] In some embodiments, the tumor can be a benign tumor. In some embodiments, the tumor can be a malignant tumor or cancer. In some embodiments, the disease is a cancer, including but not limited to breast cancer, lung cancer, colorectal cancer, etc. In some embodiments, the disease is a cancer, such as but not limited to brain tumors, medulloblastoma, embryonal brain tumors (atypical teratoid rhabdoid tumor (ATRT)), germ cell tumors, etc. In some embodiments, the cancer includes a subset of tumors and molecular / genomic subtypes that are prone to relapse, such as but not limited to solid cancers, liquid cancers, etc. In some embodiments, the solid cancers that are prone to relapse can include but are not limited to atypical teratoid rhabdoid tumor (ATRT), medulloblastoma, etc. In some embodiments, the liquid cancers that are prone to relapse can include but are not limited to leukemia, lymphoma, etc.

[0138] In some embodiments, the proliferative disease can be an inflammatory disease, such as an acute inflammatory disease and / or a chronic inflammatory disease. In some embodiments, the chronic inflammation / chronic inflammatory disease / acute inflammation / acute inflammatory disease can include but are not limited to ulcerative colitis, Crohn’s disease, infectious diseases, etc.

[0139] In some embodiments, the infectious disease can be caused by a bacterial pathogen, a viral pathogen, a fungal pathogen, or a parasite.

[0140] Examples of bacterial pathogens can include, but are not limited to, Escherichia coli, Mycobacteria spp, Salmonella spp, Staphylococcus spp, Clostridium difficile, Listeria monocytogenes, Group B streptococci, vancomycin-resistant enterococci (VRE), and the like.

[0141] Examples of viral pathogens can include, but are not limited to, human papillomavirus, rhinovirus, human cytomegalovirus in HIV-1 positive patients, hepatitis virus, coronavirus (CoV), severe acute respiratory syndrome (SARS), monkeypox virus, and the like.

[0142] Examples of fungal pathogens can include, but are not limited to, Botrytis cinerea, Pseudomonas syringae, Fusarium oxysporum, and the like.

[0143] Examples of parasites can include, but are not limited to, Leishmania parasites, Giardia lamblia, Cryptosporidium, Entamoeba, and the like.

[0144] In some embodiments, the inflammatory disease can be a neurodegenerative disease, such as neuroinflammation leading to neurodegeneration / brain damage / neural damage. In some embodiments, the disease can be a neurodegenerative disease, such as dementia, Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and the like. In some embodiments, the inflammatory disease can include, but is not limited to, fibrosis, muscle aging, and the like.

[0145] Without wishing to be bound by theory, it is known in the art that telomere length influences the lifespan of non-diseased cells. In non-diseased cells, if the telomeres can be lengthened, it will provide anti-aging properties / extend the lifespan of the cells. As the experimental data of the present disclosure show that the telomere length is not affected by the presence of the disease, the lengthening of the telomeres in non-diseased cells will not affect the disease progression. Figure 44) is shown, telomere length was tested in ATRT cancer cells. Telomere length (associated with senescence) in ATRT cancer cells was maintained and lengthened in the secretome for up to 96 hours. Telomere length was lengthened at time points of 48 to 72 hours and significantly lengthened at 96 hours. Thus, the secretome can further be associated with anti-senescence properties that would have a wide-ranging impact on many disease / anti-aging drug development in the health and medical fields.

[0146] In some embodiments, the diseased cell is a brain tumor.

[0147] In some embodiments, the diseased cell is an atypical teratoid rhabdoid tumor (ATRT).

[0148] In some embodiments, the diseased cell is a medulloblastoma.

[0149] In some embodiments, the diseased cell is a brain tumor, an atypical teratoid rhabdoid tumor (ATRT), and / or a medulloblastoma.

[0150] In some embodiments, ATRT includes molecular subtypes such as, but not limited to, MYC-ATRT, tyrosinase-ATRT (TYR-ATRT), sonic hedgehog-ATRT (SHH-ATRT), and the like.

[0151] The inventors of the present disclosure have disclosed that specific molecular subtypes of ATRT enriched with secretome match with macrophage enrichment profile (MYC-ATRT > TYR-ATRT > SHH-ATRT).

[0152] In some embodiments, the diseased cell can include, but is not limited to, a cancer cell line and / or a non-cancer cell line.

[0153] In some embodiments, the number of diseased cells cultured / seeded with activated immune cells can include at least 50 cells, at least 100 cells, at least 150 cells, at least 200 cells, at least 250 cells, at least 300 cells, at least 350 cells, at least 400 cells, at least 450 cells, at least 500 cells, at least 550 cells, at least 1000 cells, at least 1500 cells, at least 2000 cells, at least 2500 cells, at least 3000 cells, at least 3500 cells, at least 4000 cells, at least 4500 cells, at least 5000 cells, at least 5500 cells, at least 6000 cells, at least 6500 cells, at least 7000 cells, at least 7500 cells, at least 8000 cells, at least 8500 cells, at least 9000 cells, at least 9500 cells, at least 10,000 cells, and the like.

[0154] In some embodiments, the number of diseased cells cultured / inoculated with the activated immune cells may include about 50 cells, about 100 cells, about 150 cells, about 200 cells, about 250 cells, about 300 cells, about 350 cells, about 400 cells, about 450 cells, about 500 cells, about 550 cells, about 1000 cells, about 1500 cells, about 2000 cells, about 2500 cells, about 3000 cells, about 3500 cells, about 4000 cells, about 4500 cells, about 5000 cells, about 5500 cells, about 6000 cells, about 6500 cells, about 7000 cells, about 7500 cells, about 8000 cells, about 8500 cells, about 9000 cells, about 9500 cells, about 10000 cells, etc.

[0155] In some embodiments, diseased cells can be cultured with activated immune cells in a petri dish, a 6-well plate, a 12-well plate, a 24-well plate, a 96-well plate, a T-25 flask, a T-75 flask, or the like.

[0156] In some embodiments, cancer cell lines may include, but are not limited to, ATRT cell lines, medulloblastoma cell lines, and the like.

[0157] In some embodiments, ATRT cell lines may include, but are not limited to, CHLA-04, CHLA-05, CHLA-02, BT-12, CHLA-06, BT-37, ATRT95, CHLA-266, and the like.

[0158] In some embodiments, medulloblastoma cell lines may include, but are not limited to, Daoy, D341, CHLA-01, CHLA-01R, and the like.

[0159] In some embodiments, the medulloblastoma cell line may include a drug-resistant medulloblastoma cell line, such as but not limited to CHLA-01R.

[0160] like Figure 15 As shown, CHLA-06 is the most aggressive and fastest-growing in vitro phenotype among the panel of ATRT tumor models disclosed herein. ATRT95 grows too slowly to be suitable for in vitro experiments. Based on the assumption that the fastest-growing in vitro cell line would provide / secrete the most complete spectrum / mixture of tumor-promoting factors, the inventors of the present disclosure selected CHLA-06, the most aggressive ATRT tumor cell line among the panel of seven ATRT cell lines disclosed herein, to create the tumor compartment.

[0161] like Figure 46As shown, in the presence of drug-resistant medulloblastoma tumor cells, the composition produced by immune cells (such as CD11b+ cells) resulted in elevated expression levels of CCL2 / MCP-1, IL-1ra, MIP-1a / MIP-1b, and IL-8 (from highest to lowest expression) compared to when the diseased cells were not present. The expression levels of MIF, CCL5 / RANTES, Serpin El / PAI-1 were not elevated between the two conditions (i.e. presence vs. absence of drug-resistant medulloblastoma cell lines).

[0162] In some embodiments, the non-cancer cell lines can include, but are not limited to, skin cells, neural cells, brain cells, liver cells, heart cells, and the like.

[0163] In the experimental data of the present disclosure, the marker expression between patient tumors, ATRT cell lines, fetal and pediatric normal brain controls were compared. In patient tumors, as demonstrated by the inventors of the present disclosure in the cancer models of the present disclosure (ATRT and other types of brain tumors), the secretome plays an important role in the tumor microenvironment of patients and influences drug efficacy in vitro.

[0164] Without wishing to be bound by theory, cancer recurrence is an area of intense research in the field of oncology, but the role of macrophages in mediating cancer recurrence is not well understood. Pediatric brain cancer is a leading cause of cancer death in children. ATRT is a pediatric embryonal brain tumor that commonly occurs in infants and accounts for 15-20% of all brain tumors in children under 3 years of age. It is an aggressive brain tumor with historically poor survival outcomes (5-year survival rate of 10-20% for patients under 3 years of age). Past standard treatments include surgery, chemotherapy, and radiation, but none of these therapies are curative. A recently published trial, ACNS0333, used high-dose chemotherapy and peripheral blood stem cell rescue therapy to improve survival. However, this improvement in survival came at the cost of treatment toxicity from high-dose chemotherapy and the peripheral blood stem cell rescue therapy that is necessary afterwards. The trial also observed a high rate of treatment failure. More novel and effective drugs are needed, and a deeper understanding of the impact of the tumor microenvironment on drug efficacy and tumor biology in ATRT is needed.

[0165] The inventors of the present disclosure found that a macrophage-derived secretome is present in a high relapse risk subtype of ATRT, an aggressive childhood brain tumor. Since cancer cells are able to survive and proliferate under nutrient stress conditions / in the absence of any nutrients in the presence of the secretome, this provides a mechanism for cancer cells to survive until new nutrients are available and then rapidly proliferate. Thus, this provides a favorable mechanism for relapse. The inventors of the present disclosure found a six-factor secretome from macrophages that significantly maintains critical cell mass during nutrient stress in a childhood embryonal brain tumor, atypical teratoid rhabdoid tumor (ATRT). A particular ATRT subtype is shown to be enriched for secretome, matching the macrophage-enriched profile, and is a high relapse risk subtype. The secretome alters drug response, prevents cell death, and provides a pro-survival microenvironment to rescue cells affected by drugs. ATRT cells rearrange in the secretome to form a reticular structure that remains stable during drug exposure, suggesting a presence of a treatment-resistant mechanism. Medulloblastoma cells form the same filamentous chain-like structure arrangement as ATRT cells when grown in the secretome for 4 hours to 96 hours. Surprisingly, the secretome prevents tumor cell death for a long time in an aggressive tumor model and a cerebrospinal fluid disseminated model, suggesting its role in tumor resistance and relapse. The results of the present disclosure reveal for the first time a previously unexplored role of a unique macrophage secretome that provides an alternative energy source to maintain cancer cells during nutrient stress and is of significant importance to relapse subtypes. Since the inventors of the present disclosure have found that this six-factor secretome is enriched in many other adult cancer types, the secretome product can be applied to other cancer types. In addition, the secretome product can also be applied to other non-cancer human diseases that can share this secretome, such as chronic inflammation, ulcerative colitis, Crohn’s disease, Alzheimer’s disease / dementia, coronavirus disease, human immunodeficiency virus (HIV). Thus, it has a broad significance and application prospect.

[0166] The secretome can be used as a cell culture medium and for biomarker discovery in cell research. In addition, the secretome can also be used for therapeutic applications such as, but not limited to: tissue regeneration (such as skin regeneration / skin graft manufacturing, nerve / brain regeneration and / or degeneration, vasculature regeneration / angiogenesis, liver regeneration, tissue / organ regeneration for transplantation, cardiac regeneration, corneal regeneration (such as corneal graft synthesis), chondrocyte regeneration, etc.), wound healing, angiogenesis, osteogenesis, inflammation response treatment, cell cryopreservation, and / or drug discovery (such as personalized drug discovery). The secretome can also be used as a cell culture medium and for biomarker discovery in cell research, and as a drug / compound to extend telomeres of cells, thereby reversing the aging process of human cells (such as diseased and / or non-diseased cells).

[0167] In some embodiments, the secretome of the present disclosure can be used for:

[0168] i) therapeutics, such as drug screening, measuring effectiveness of drugs in secretome-rich tumors, and / or

[0169] ii) diagnostics, such as developing kits / assays for diagnosing secretome-rich tumors.

[0170] In some embodiments, the kits for diagnosing secretome-rich tumors can include the secretome factors disclosed herein.

[0171] In another aspect, the present disclosure provides a composition for tissue regeneration.

[0172] In some embodiments, the present disclosure provides a method for tissue regeneration. In some embodiments, the tissue can include, but is not limited to, skin, chondrocyte / cartilage, cornea, liver, heart, nerve, vasculature, etc.

[0173] In some embodiments, the present disclosure provides a method of enhancing or initiating skin regeneration, comprising administering the secretome described herein to a subject in need thereof or to cells from a subject in need thereof. In some embodiments, the subject in need of skin regeneration can include, but is not limited to, a burn patient, etc. In some embodiments, the method can be a dermatological or cosmetic method. In some embodiments, the method of skin regeneration can include the effective generation of skin grafts using the secretome of the present disclosure.

[0174] In some embodiments, the secretome of the present disclosure can be used for skin regeneration. In some embodiments, skin regeneration can include effective generation of skin grafts using the secretome of the present disclosure. In some embodiments, skin regeneration can be used for dermatological / cosmetic applications. In some embodiments, skin regeneration can be used for patients such as, but not limited to, burn patients. In some embodiments, skin regeneration can include skin grafts for keloid surgery.

[0175] In some embodiments, the present disclosure provides a method of enhancing or initiating nerve / brain regeneration / anti-aging, comprising administering the secretome described herein to a subject in need thereof or cells from a subject in need thereof. In some embodiments, a subject in need of nerve / brain regeneration / anti-aging can include, but is not limited to, patients with stroke, Alzheimer’s disease, vascular dementia, Lewy body disease, and the like.

[0176] In some embodiments, the secretome of the present disclosure can be used for nerve / brain regeneration / anti-aging. In some embodiments, nerve / brain regeneration can be used for conditions such as, but not limited to, stroke, Alzheimer’s disease, vascular dementia, Lewy body disease, and the like.

[0177] In some embodiments, the present disclosure provides a method of enhancing or initiating spinal cord regeneration, comprising administering the secretome described herein to a subject in need thereof or cells from a subject in need thereof. In some embodiments, a subject in need of spinal cord regeneration can include, but is not limited to, patients with nerve / spinal cord breaks, and the like.

[0178] In some embodiments, the secretome of the present disclosure can be used for spinal cord regeneration. In some embodiments, spinal cord regeneration can be used for conditions such as, but not limited to, patients with nerve / spinal cord breaks, and the like.

[0179] In some embodiments, the present disclosure provides a method of enhancing or initiating vasculogenic / angiogenic regeneration, comprising administering the secretome described herein to a subject in need thereof or cells from a subject in need thereof. In some embodiments, a subject in need of vasculogenic regeneration can include, but is not limited to, patients with vascular blockage / dysfunction (such as heart vessels, leg vessels), diabetic patients, and the like.

[0180] In some embodiments, the secretome of the present disclosure can be used for vasculogenic regeneration. In some embodiments, vasculogenic regeneration can be used for conditions such as, but not limited to, patients with vascular blockage / dysfunction (such as heart vessels, leg vessels), diabetic patients, coronary heart disease patients (e.g., patients who are about to have a heart attack due to vascular blockage), and the like. In some embodiments, vasculogenic regeneration can be performed using stem cells such as induced pluripotent stem cells (iPSCs) of endothelial cells.

[0181] In some embodiments, the present invention provides a method for enhancing or initiating cardiac regeneration, comprising administering the secretome described herein to a subject in need thereof or cells derived therefrom. In some embodiments, subjects in need of cardiac regeneration may include, but are not limited to, patients in need of heart transplantation.

[0182] In some embodiments, the secretome of the present disclosure can be used for cardiac regeneration. In some embodiments, cardiac regeneration can be used, for example, but not limited to, in patients requiring cardiac transplantation.

[0183] In some embodiments, the present invention provides a method for enhancing or initiating liver regeneration, comprising administering the secretome described herein to a subject in need thereof or a cell derived from a subject in need thereof. In some embodiments, a subject in need of liver regeneration may include, but is not limited to, a patient in need of a liver transplant.

[0184] In some embodiments, the secretomes disclosed herein can be used for liver regeneration. In some embodiments, liver regeneration can be used, for example, but not limited to, in patients requiring liver transplantation. In some embodiments, liver regeneration can be performed using hepatocytes and / or hepatoma cells. In some embodiments, the present invention provides a method for enhancing or initiating cryopreservation of cells, comprising administering a secretome described herein to a subject in need thereof or to cells derived from a subject in need thereof.

[0185] In some embodiments, the present invention provides a method of enhancing or initiating cryopreservation of cancer cells and / or healthy cells, comprising administering to a subject in need thereof a secretome as described herein.

[0186] In some embodiments, the secretomes disclosed herein can be used for cryopreservation of cells. In some embodiments, the secretomes disclosed herein can be used for cryopreservation of cancer cells and / or healthy cells. In some embodiments, healthy cells that can be cryopreserved using the secretomes include, but are not limited to, eggs, sperm, umbilical cord blood, and the like. This can be used to preserve the fertility of cells such as, but not limited to, eggs, sperm, and the like.

[0187] Without wishing to be bound by theory, studies in the field have cryopreserved cells in standard culture medium containing dimethyl sulfoxide (DMSO) to maintain cell viability. The secretomes disclosed herein can be used to cryopreserve cells and their performance can be compared to that using standard culture medium. In some embodiments, the present invention provides a drug discovery method comprising contacting the secretomes described herein with an agent of interest. In some embodiments, the present invention provides a method for testing the effect of a drug / antiviral agent against a disease in the presence of a secretome.

[0188] In some embodiments, the secretome of the present disclosure can be used for drug discovery. In some embodiments, the secretome of the present disclosure can be used to test the effect of a drug / anti-viral agent against a disease in the presence of the secretome. In some embodiments, these diseases can include, but are not limited to, coronavirus disease (COVID-19), human immunodeficiency virus (HIV) disease, and the like.

[0189] In some embodiments, the present disclosure provides a method of enhancing or initiating chondrocyte / cartilage regeneration, comprising administering the secretome described herein to a subject in need thereof. In some embodiments, the subject in need of chondrocyte / cartilage regeneration can include, but is not limited to, a patient with cartilage injury and in need of cartilage repair, a patient / elderly patient with cartilage degeneration at the knee, hip, spine, osteoarthritis, and the like.

[0190] In some embodiments, the secretome of the present disclosure can be used for chondrocyte regeneration. In some embodiments, chondrocyte regeneration can be used for, such as but not limited to, a patient with cartilage injury and the like.

[0191] In some embodiments, the present disclosure provides a method of enhancing or initiating corneal regeneration / corneal graft synthesis, comprising administering the secretome described herein to a subject in need thereof. In some embodiments, the subject in need of corneal regeneration / corneal graft synthesis can include, but is not limited to, a patient with corneal damage / injury and in need of corneal repair, and the like.

[0192] In some embodiments, the secretome of the present disclosure can be used for corneal regeneration / corneal graft synthesis. In some embodiments, corneal regeneration can be used for, such as but not limited to, a patient with corneal damage / injury and the like.

[0193] In another aspect, the present disclosure provides a method of testing / screening a drug / inhibitor / compound, comprising culturing the drug with a diseased cell in the presence of the composition of the present disclosure.

[0194] In some embodiments, the drug / inhibitor / compound can include, but is not limited to, a drug (such as a tumor drug, an anti-inflammatory drug, and the like), a compound (including but not limited to a naturally occurring compound, a synthetic compound, and the like), a small molecule, an antigen-binding protein (such as an antibody), and the like.

[0195] In some embodiments, the drug / inhibitor / compound works if the diseased cell dies; or, wherein the drug / inhibitor / compound does not work if the diseased cell grows vigorously.

[0196] The inventors of the present disclosure show that drug responses are inhibited in the presence of the secretome of the present disclosure. Specifically, the secretome of the present disclosure is enriched in high-risk tumors, such as childhood brain tumors (ATRT), and the presence of the secretome in vitro with cancer cells reduces the efficacy of potent anti-cancer drugs. Thus, drugs that are potent in standard media during in vitro testing can not be as potent in patient tumors that are in an immune-rich condition.

[0197] The secretome product of the present disclosure provides a laboratory test of diseased cells, such as any type of cancer cell, in an immune-rich condition by mimicking the microenvironmental conditions in patient tumors, allowing testing of new drugs / drug types on cancer cells, or screening of compounds to identify drugs that are potent against diseased / cancer cells in an immune-rich in vitro culture. It enables the inventors of the present disclosure to identify cancer cells that can be more sensitive to immune microenvironment modulation. It also enables the inventors of the present disclosure to assess whether a new drug can be more potent in an immune-rich patient tumor and to identify drugs that will fail in certain tumors (immune-rich tumors) before the drug is used in a phase I clinical trial in patients. Clinical trials are costly and a clinical trial failure will increase the cost of drug development. This is a critical step - the efficacy of a drug in an immune-rich condition is not clear - and this can explain why some drugs that are found to be potent in the laboratory fail when administered to patients during clinical trials. The secretome product will provide a drug development tool that enables high-throughput drug discovery by testing new drugs / drug libraries in an immune-rich condition in vitro on cancer cells. This test can be applied in a laboratory setting before patients during clinical trials, which is very useful to the pharmaceutical industry. The secretome also allows screening of patient tumors that are more likely to respond to certain drugs and selection of patients with immune-rich tumors that are suitable for clinical trials.

[0198] In some embodiments, the methods of the present disclosure comprise tailoring drugs / inhibitors / compounds according to markers expressed in the diseased cells.

[0199] In some embodiments, the markers expressed in ATRT cells can include cell cycle markers / cell cycle inhibitors. In some embodiments, the markers expressed in ATRT cells can include markers that are upregulated in cancer compared to normal tissue. In some embodiments, the markers expressed in ATRT cells can include, but are not limited to, Maternal Embryo Leucine Kinase (MELK), Kinesin Family Member 11 (KIF11), and the like. In some embodiments, the marker expressed in ATRT cells is Maternal Embryo Leucine Kinase (MELK).

[0200] In some embodiments, the drug / inhibitor / compound is a MELK inhibitor. In some embodiments, the MELK inhibitor is 1-(6-(3,5-dichloro-4-hydroxyphenyl)-4-(((1r,4r)-4-((dimethylamino)methyl)cyclohexyl)amino)-1,5-naphthyridin-3-yl)ethenone (OTSSP167). In some embodiments, the drug / inhibitor / compound is a Kifl 1 inhibitor. In some embodiments, the Kifl 1 inhibitor is Ispinesib.

[0201] In some embodiments, OTSSP167 is used at a concentration such as about 0.01 nM to about 600 nM, about 0.05 nM to about 550 nM, about 0.1 nM to about 500 nM, about 0.15 nM to about 450 nM, about 0.2 nM to about 400 nM, about 0.25 nM to about 350 nM, about 0.3 nM to about 300 nM, about 0.35 nM to about 250 nM, 0.4 nM to about 200 nM, 0.45 nM to about 150 nM, 0.5 nM to about 100 nM, 1 nM to about 50 nM, 1.5 nM to about 40 nM, 2 nM to about 45 nM, 2.5 nM to about 40 nM, 3 nM to about 35 nM, 3.5 nM to about 30 nM, 4 nM to about 25 nM, 4.5 nM to about 20 nM, 5 nM to about 15 nM, 5.5 nM to about 10 nM, etc.

[0202] In some embodiments, OTSSP167 is used at a concentration such as 0.01 nM, 0.05 nM, 0.1 nM, 0.15 nM, 0.2 nM, 0.25 nM, 0.3 nM, 0.35 nM, 0.4 nM, 0.45 nM, 0.5 nM, 1 nM, 1.5 nM, 2 nM, 2.5 nM, 3 nM, 3.5 nM, 4 nM, 4.5 nM, 5 nM, 5.5 nM, 6 nM, 6.5 nM, 7 nM, 7.5 nM, 8 nM, 8.5 nM, 9 nM, 9.5 nM, 10 nM, 15 nM, 20 nM, 25 nM, 30 nM, 35 nM, 40 nM, 45 nM, 50 nM, 55 nM, 60 nM, 65 nM, 70 nM, 75 nM, 80 nM, 85 nM, 90 nM, 95 nM, 100 nM, 150 nM, 200 nM, 250 nM, 300 nM, 350 nM, 400 nM, 450 nM, 500 nM, 550 nM, 600 nM, etc.

[0203] In some embodiments, Ispinesib is used at a concentration such as about 0.01 nM to about 600 nM, about 0.05 nM to about 550 nM, about 0.1 nM to about 500 nM, about 0.15 nM to about 450 nM, about 0.2 nM to about 400 nM, about 0.25 nM to about 350 nM, about 0.3 nM to about 300 nM, about 0.35 nM to about 250 nM, 0.4 nM to about 200 nM, 0.45 nM to about 150 nM, 0.5 nM to about 100 nM, 1 nM to about 50 nM, 1.5 nM to about 40 nM, 2 nM to about 45 nM, 2.5 nM to about 40 nM, 3 nM to about 35 nM, 3.5 nM to about 30 nM, 4 nM to about 25 nM, 4.5 nM to about 20 nM, 5 nM to about 15 nM, 5.5 nM to about 10 nM, etc.

[0204] In some embodiments, Ispinesib is used at a concentration such as about 0.01 nM to about 600 nM, about 0.05 nM to about 550 nM, about 0.1 nM to about 500 nM, about 0.15 nM to about 450 nM, about 0.2 nM to about 400 nM, about 0.25 nM to about 350 nM, about 0.3 nM to about 300 nM, about 0.35 nM to about 250 nM, 0.4 nM to about 200 nM, 0.45 nM to about 150 nM, 0.5 nM to about 100 nM, 1 nM to about 50 nM, 1.5 nM to about 40 nM, 2 nM to about 45 nM, 2.5 nM to about 40 nM, 3 nM to about 35 nM, 3.5 nM to about 30 nM, 4 nM to about 25 nM, 4.5 nM to about 20 nM, 5 nM to about 15 nM, 5.5 nM to about 10 nM, etc.

[0205] As shown by the experimental data of the present disclosure, six ATRT tumor cell lines were cultured in macrophage-derived secretome and compared to normal brain controls. Maternal embryonic leucine zipper kinase (MELK) was found to be highly expressed in ATRT subtypes, while expression was lower in normal brain samples. The inventors of the present disclosure demonstrated that the I / II phase molecular inhibitor of MELK, OTSSP167, was effective in a panel of six ATRT cell lines and in an aggressive orthotopic xenograft mouse model. The presence of secretome reduced the drug efficacy of OTSSP167 in the early tumor formation process of ATRT cell lines and medulloblastoma. The I / II phase molecular inhibitor, (R)-N-(3-aminopropyl)-N-(l-(3-benzyl-7-chloro-4-oxo-3,4-dihydroquinazolin-2-yl)-2-methylpropyl)-4-methylbenzamide (Ispinesib), was also tested in ATRT cell lines and medulloblastoma. The drug efficacy of Ispinesib was reduced in the presence of secretome in the early tumorigenesis process of ATRT cell lines and medulloblastoma. Secretome can make medulloblastoma cells more viable compared to standard medium without drugs. In the presence of OTSSP167, neurospheres (primary and recurrent medulloblastoma derived from the same patient) had higher survival rates in secretome than in standard medium. In the presence of Ispinesib, three medulloblastoma cell lines (also neurospheres) had higher survival rates in secretome than in standard medium. In some cases, as shown in FIG. 41, some medulloblastoma cell lines were more sensitive to drug treatment (e.g., OTSSP167 or ispinesib) in the presence of secretome than in standard medium. Secretome protected tumor cells from drug killing in medulloblastoma cell lines that proliferated in neurosphere (stem cell-like) form. The present disclosure highlights a research void in the art where drug testing in vitro on cancer cell lines is only performed in standard medium.

[0206] As used herein, the term “neurosphere” refers to a three-dimensional free-floating colony formed in the presence of mitogens, consisting of hundreds of cells, of which a small fraction are stem cells and the rest are progenitor cells. Neurospheres can be derived from primary and recurrent diseased cells of the same patient, such as medulloblastoma. Neurospheres are typically enriched in stem cells.

[0207] FIG. 43 also demonstrates the role of secretome in promoting tumor progression in vivo. The inventors of the present disclosure injected another brain tumor type (germ cell tumor, a metastatic tumor) into immunosuppressed mice in the presence of secretome versus in the presence of standard medium (standard method). Mice injected with brain tumor in the presence of secretome started to die, while mice injected with brain tumor in standard medium (without secretome) were still alive.

[0208] In some embodiments, the present disclosure investigates pathways altered by the secretome in the cancer cell microenvironment. In some embodiments, methods of investigating pathways altered by the secretome in the cancer cell microenvironment can include, but are not limited to, RNA sequencing, metabolomics (such as semi-targeted metabolomics), protein phosphorylation arrays, antibody array assays (such as single sample, phospho-probe array (PEX100)), whole antibody array assays (such as cytokine profile antibody array (SCK100)), whole genome sequencing, whole exome sequencing, and the like.

[0209] In some embodiments, the present disclosure investigates the effect of the secretome on metabolic changes in the tumor. In some embodiments, methods of investigating metabolic changes in the tumor can include, but are not limited to, metabolomics (such as semi-targeted metabolomics (full scan), non-targeted electrostatic field orbitrap), and the like.

[0210] In some embodiments, the present disclosure investigates the effect of the secretome on vascular changes in the tumor. In some embodiments, vascular changes in the tumor can be investigated using in vivo models and / or in vitro models.

[0211] In some embodiments, in vivo models can include, but are not limited to, brain tumor models, non-brain tumor models, non-tumor brain models, patient-derived orthotopic xenograft models, and the like.

[0212] The present disclosure includes obtaining the brain of an in vivo model (such as a mouse), sectioning the brain tissue (such as a control sample, i.e., a sample injected with tumor cells and standard media), staining the blood vessels using methods such as immunohistochemistry, quantifying and comparing the blood vessels between the secretome and the standard media.

[0213] In some embodiments, a brain tumor model (such as a brain tumor model) can include endothelial / vessel iPSCs co-cultured with brain tumor cells in the secretome and the standard media being compared.

[0214] As shown in FIG. 43 of the present disclosure, the secretome affects the growth and survival of mouse brain tumors. Five weeks after implanting tumor cells into the mouse brain, 41.2% of the mice in the secretome group died / were sick, while only 18.8% of the mice in the standard media group died / were sick.

[0215] In some embodiments, a non-brain tumor model can include endothelial / vessel iPSCs co-cultured with non-brain tumor cells in the secretome and the standard media being compared. In some embodiments, non-brain tumor brain cells can include, but are not limited to, Alzheimer’s cells, Parkinson’s cell types, neuronal cell types, neurodegenerative cell line models.

[0216] In some embodiments, the non-tumor brain model can include a group of mice injected with a secretome and free of tumor cells. In some embodiments, the non-tumor brain model can be used to study changes in blood vessels and / or brain tissue, such as brain parenchyma, and the effects of the secretome on neurodegeneration and / or neuroregeneration of brain cells.

[0217] In some embodiments, the present disclosure includes the use of an in vitro blood vessel model, such as induced pluripotent stem cells (iPSCs). In some embodiments, the blood vessel formation, such as the pattern and number, is compared when grown in the secretome and a comparative standard medium.

[0218] In some embodiments, the present disclosure uses a three-dimensional in vitro model for, such as but not limited to, drug screening, morphological / microscopy, creating composite materials to study interactions with blood vessels / fibroblasts, etc. In some embodiments, the three-dimensional in vitro model includes a three-dimensional gel containing the secretome of the present disclosure.

[0219] In another aspect, the present disclosure provides a method of culturing proliferative cells, comprising culturing the proliferative cells in the composition of the present disclosure.

[0220] In some embodiments, the method of the present disclosure includes observing the expression of a marker in the proliferative cells in the presence of the composition of the present disclosure.

[0221] In some embodiments, the marker expressed in the proliferative cells can include, but is not limited to, MELK, kinesin-like protein (KIF11 / kinesin-5 / Eg5 / BimC), etc. The inventors of the present disclosure have confirmed that MELK is enriched in patient ATRT tumors of three ATRT subtypes.

[0222] In some embodiments, the method of the present disclosure includes observing morphological changes of the proliferative cells.

[0223] In some embodiments, the morphology of the proliferative cells can include, but is not limited to, cluster structure in a suspended state, filamentous chain structure, network structure (stretched over a long distance in a culture bottle), interwoven chain structure, etc. In some embodiments, the morphology of the proliferative cells is changed from a cluster structure in a suspended state to a filamentous chain structure in the presence of the secretome.

[0224] Without wishing to be bound by theory, the inventors of the present disclosure have found that the secretome described herein is able to maintain tumor cells in a network interwoven structure, thereby allowing the tumor cells to stay together / survive in this structure. It is believed that the secretome can be involved in cell polarity maintenance, thereby directing the tumor cells to arrange in this manner.

[0225] In another aspect, the present application provides a method of identifying a secretome phenotype of a disease, comprising culturing a diseased cell with an immune cell, such as a macrophage expressing CD11b, obtaining / extracting the medium of the cultured cells, thereby obtaining a secretome, analyzing and / or mapping the identity of individual components of the secretome, thereby providing a secretome phenotype of the disease.

[0226] In some embodiments, the present application provides a method of identifying a secretome phenotype of a disease, comprising extracting RNA and performing methods known in the art, such as but not limited to RNA-seq, reverse transcription polymerase chain reaction (RT-PCR) to measure transcript expression or protein expression, such as but not limited to ELISA.

[0227] In some embodiments, the disease described herein can comprise a proliferative disease.

[0228] The proliferative disease described herein comprises a tumor and / or an inflammatory disease.

[0229] In some embodiments, the tumor can be a benign tumor. In some embodiments, the tumor can be a malignant tumor or a cancer. In some embodiments, the disease is a cancer, including but not limited to breast cancer, lung cancer, colorectal cancer, etc. In some embodiments, the disease is a cancer, such as but not limited to brain tumor, medulloblastoma, embryonal brain tumor (atypical teratoid rhabdoid tumor (ATRT)), germ cell tumor, etc. In some embodiments, the cancer comprises a subset of tumors and molecular / genomic subtypes that are prone to relapse, such as but not limited to solid cancer, liquid cancer, etc. In some embodiments, the solid cancer that is prone to relapse includes but is not limited to atypical teratoid rhabdoid tumor (ATRT), etc. In some embodiments, the liquid cancer that is prone to relapse can include but is not limited to leukemia, lymphoma, etc.

[0230] In some embodiments, the proliferative disease can be an inflammatory disease, such as an acute inflammatory disease and / or a chronic inflammatory disease. In some embodiments, the chronic inflammation / chronic inflammatory disease / acute inflammation / acute inflammatory disease can include but is not limited to ulcerative colitis, Crohn’s disease, infectious disease, etc.

[0231] In some embodiments, the infectious disease can be caused by a bacterial pathogen, a viral pathogen, a fungal pathogen, or a parasite.

[0232] Examples of bacterial pathogens can include but are not limited to Escherichia coli, Mycobacterium, Salmonella, Staphylococcus, Clostridium difficile, Listeria monocytogenes, Group B Streptococcus, Vancomycin-resistant Enterococcus (VRE), etc.

[0233] Examples of viral pathogens can include, but are not limited to, human papillomavirus, rhinovirus, human cytomegalovirus in HIV-1 positive patients, hepatitis virus, coronavirus (CoV), severe acute respiratory syndrome (SARS), monkeypox virus, and the like.

[0234] Examples of fungal pathogens can include, but are not limited to, Botrytis cinerea, Pseudomonas syringae, Fusarium oxysporum, and the like.

[0235] Examples of parasites can include, but are not limited to, Leishmania parasites, Giardia lamblia, Cryptosporidium, Entamoeba, and the like.

[0236] In some embodiments, the inflammatory disease can be a neurodegenerative disease, such as neuroinflammation leading to neurodegeneration / brain injury / neural injury. In some embodiments, the disease can be a neurodegenerative disease, such as dementia, Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and the like. In some embodiments, the inflammatory disease can include, but is not limited to, fibrosis, muscle aging, and the like.

[0237] In some embodiments, the disease is a brain tumor.

[0238] In some embodiments, the disease is atypical teratoid rhabdoid tumor (ATRT).

[0239] In some embodiments, the disease is medulloblastoma.

[0240] In some embodiments, ATRT includes molecular subtypes such as, but not limited to, MYC-ATRT, tyrosinase-ATRT (TYR-ATRT), sonic hedgehog-ATRT (SHH-ATRT), and the like.

[0241] The inventors of the present disclosure have revealed specific molecular subtypes of ATRT that are enriched in secretome, matching macrophage-enriched profiles (MYC-ATRT > TYR-ATRT > SHH-ATRT). In some embodiments, the disease can include, but is not limited to, cancer cell lines and / or non-cancer cell lines.

[0242] In some embodiments, cancer cell lines can include, but are not limited to, ATRT cell lines, medulloblastoma cell lines, and the like.

[0243] In some embodiments, ATRT cell lines can include, but are not limited to, CHLA-04, CHLA-05, CHLA-02, BT-12, CHLA-06, BT-37, CHLA-266, and the like.

[0244] In some embodiments, medulloblastoma cell lines can include, but are not limited to, Daoy, D341, CHLA-01, CHLA-01R, and the like.

[0245] In some embodiments, non-cancerous cell lines may include, but are not limited to, skin cells, nerve cells, brain cells, and the like.

[0246] Without wishing to be bound by theory, each disease type (such as each cancer type) can be further subdivided into different molecular subtypes. Some molecular subtypes have a secretome phenotype, while others do not. Figures 2A-2D As shown by experimental data in [ 15 ], using ATRT as an example, certain molecular subtypes have distinct secretome phenotypes. Therefore, it is envisioned that the expression of secretome markers in individual patient tumors could be examined to identify tumors enriched in secretomes. This could allow the development of personalized therapies for precision medicine by matching drugs to individual secretome phenotypes. Drug testing could also be performed to improve drug efficacy based on individual secretome phenotypes.

[0247] The inventors' laboratories possess screening capabilities capable of identifying the secretome phenotype of each cancer type, enabling the development of personalized therapies for precision medicine. This allows personalized screening of individual patient tumors for drug testing. They can directly assess whether an individual patient's tumor possesses a secretome phenotype, thereby matching patients with drugs that are most effective against tumors with this secretome phenotype and improving drug efficacy.

[0248] In some embodiments, the diseased cells are cultured with the immune cells for a period of time such as, but not limited to, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours, 24 hours, 36 hours, 48 ​​hours, 3 days, 4 days, 5 days, 6 days, 1 week, 2 weeks, 3 weeks, 4 weeks, etc.

[0249] In another aspect, the present invention provides a pan-cancer secretome atlas comprising a database of multiple secretome phenotypes of multiple diseases.

[0250] In some embodiments, the disease comprises multiple cancers, optionally 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 or more cancers.

[0251] In some embodiments, the diseases include 37 cancers. In some embodiments, the 37 cancers in the pan-cancer secretome atlas database include adrenocortical carcinoma, bladder urothelial carcinoma, breast invasive carcinoma, cervical squamous cell carcinoma and cervical adeno carcinoma, cholangiocarcinoma, colon adenocarcinoma, colorectal adenocarcinoma, diffuse large B-cell lymphoma, glioblastoma multiforme, glioma, head and neck squamous cell carcinoma, kidney chromophobe carcinoma, pan-kidney cohort (KICH+KIRC+KIRP), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, acute myeloid leukemia, low grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, pheochromocytoma and paraganglioma, prostate adenocarcinoma, rectal adenocarcinoma, sarcoma, skin cutaneous melanoma, testicular germ cell tumors, thyroid carcinoma, thymoma, uterine corpus endometrial carcinoma, uterine carcinosarcoma, uveal melanoma, intracranial germ cell tumors, atypical teratoid rhabdoid tumor, and medulloblastoma.

[0252] In some embodiments, the pan-cancer secretome atlas can include diseases with secretome phenotypes, such as but not limited to cancers, acute / chronic inflammatory diseases, etc.

[0253] As shown in the experimental data, the inventors of the present disclosure developed a pan-cancer secretome atlas that can be used to investigate 37 adult cancer types in genomic databases. The pan-cancer secretome atlas is a complement to the secretome product and allows identification and selection of cancer types with secretome phenotypes. The inventors of the present disclosure found that the secretome of the present disclosure is elevated in patient tumors of multiple cancer types compared to matched normal tissue controls. Pharmaceutical companies / researchers can use the internal pan-cancer secretome atlas to select specific cancer types and / or non-cancer inflammatory diseases to test their new drugs / chemical agents using the secretome product of the present disclosure for screening. Pharmaceutical companies can also screen large internal compound libraries on cancer cell lines and / or non-cancer cell lines selected by the atlas of the present disclosure.

[0254] In some embodiments, the gene expression of secretome grown medulloblastoma and ATRT cells can be compared to standard media grown medulloblastoma and ATRT cells using methods known in the art such as but not limited to RNA sequencing, whole genome sequencing. In some embodiments, telomere analysis can be performed using the secretome of the disclosure (such as using Pacbio). In some embodiments, changes in secretome grown tumor cells can be compared to standard media grown tumor cells (such as but not limited to using Full moons biosystems / Phosphoexplorer array) to examine other proteins in the secretome. In some embodiments, cytokine levels in the secretome can be assessed using a cytokine analysis antibody array (such as but not limited to Full moons biosystems / Phosphoexplorer array). In some embodiments, secretome based freezing media can be used for longer periods of time compared to standard freezing media to examine viability upon recovery and cell proliferation over time after recovery.

[0255] The present disclosure also discloses a composition or method described herein.

[0256] In summary, the inventors of the present disclosure created an in vitro assay for deriving a secretome from macrophages. The inventors of the present disclosure used expression profile data from a large patient cohort to match this secretome to different molecular subtypes of pediatric brain tumors and ATRT compared to normal brain controls. A broad panel of six ATRT tumor cell lines were cultured in macrophage derived secretome to determine their mechanistic impact on ATRT cell growth proliferation. The inventors of the present disclosure found that Maternal Embryonic Leucine Zipper Kinase (MELK) is highly expressed in ATRT subtypes and less so in normal brain. The inventors of the present disclosure tested the I / II phase molecular inhibitor of MELK, OTSSP167, on ATRT cell lines. The inventors of the present disclosure investigated the impact of secretome on the drug efficacy of OTSSP167 against ATRT cells. The inventors of the present disclosure also found that MELK is highly expressed in medulloblastoma and tested OTSSP167 on five medulloblastoma cell lines. OTSSP167 and ispinesib were tested for their effect on medulloblastoma in secretome as shown in Figure 41. Figures 41A-41C Secretome was shown to protect tumor cells from drug killing in medulloblastoma cell lines that proliferate in neurospheres (stem cell like) form.

[0257] The present disclosure includes the identification of a secretome of proteins (CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8) and methods of generating the secretome of proteins. Human myeloid-derived cells U937 were chemically stimulated with a cocktail (PMA+IL-4) to massively generate (panmacrophage) CD11b+ cells. A six-factor secretome was harvested from these chemically induced cells. The six factors (CCL2 / MCP-1 21,22, MIP-1a / MIP-1b 22,23, CCL5 / RANTES 22,24-26, MIF 27-29, IL-1ra / IL-IF3 30, IL-8 6) have been described by studies known in the art to influence macrophages or tumorigenesis, respectively.

[0258] The inventors of the present disclosure found that the secretome of proteins is able to support tumor cell proliferation in ATRT and / or medulloblastoma during early tumor development and under nutritional stress. The secretome of proteins is comparable to standard medium in preventing cancer cell death. These findings indicate that this six-factor secretome of proteins is able to maintain a critical mass of cancer cells even in the absence of nutrients. Furthermore, the inventors of the present disclosure revealed a specific molecular subtype of ATRT that is enriched in the secretome of proteins, which matches the macrophage-enriched profile (MYC-ATRT > TYR-ATRT > SHH-ATRT). The high recurrence risk subtype is both enriched in the secretome of proteins and macrophages. The inventors of the present disclosure found that MELK is enriched in patient ATRT tumors and is a universal target for the three ATRT subtypes. OTSSP167, a MELK molecular inhibitor, was effective in a panel of six ATRT cell lines and in an aggressive orthotopic xenograft mouse model constructed from autopsy samples from patients with tumor dissemination (p=0.032). The presence of the secretome of proteins reduces the efficacy of drugs during early tumor formation, thus providing a pro-survival microenvironment for tumor cells at the early stages of drug response.

[0259] The secretome of proteins of the present disclosure is able to enable cancer cells to survive in harsh, nutrient-deprived environments and allows cancer cells to proliferate without nutrients when added to cancer cells in vitro. The secretome of proteins of the present disclosure is comparable to standard medium in preventing cancer cell death.

[0260] The inventors of the present disclosure found that this secretome is enriched in high-risk tumors of several childhood brain tumor types, including a subset of tumors that are prone to relapse as well as many adult cancers. The secretome products of the present disclosure coexist with cancer cells in vitro: (a) reduce the efficacy of effective anti-cancer drugs against aggressive embryonal brain tumors in infants, atypical teratoid rhabdoid tumor (ATRT). This is relevant to patients being tested for new drugs and clinical trials; (b) provide a rich immune condition for laboratory testing of cancer cells; (c) can be used to test / identify new drugs on cancer cells / screen for compounds effective against cancer cells in an immune-rich in vitro culture that mimics the conditions of the patient’s tumor microenvironment; (d) enable us to identify cancer cells that are more responsive to immune microenvironment modulation; (e) enable us to assess whether a new drug is likely to be potentially effective against an immune-rich patient’s tumor. This is a critical step - the efficacy of drugs in rich immune conditions is not well understood - which can perhaps explain why some drugs that are found to be effective in the laboratory fail when administered to patients during clinical trials; (f) provide a tool that enables in vitro testing of new drugs in the laboratory under rich immune conditions before being applied to patients during clinical trials. This would be of great benefit to the pharmaceutical industry.

[0261] In addition, the secretome products of the present disclosure: (1) allow the inventors of the present disclosure to screen for patient tumors that are more likely to respond to certain drugs; (2) select patients with immune-rich tumors for clinical trials.

[0262] The results of the present disclosure indicate that the secretome provides a favorable tumor ecosystem that enables malignant cells to survive under conditions of nutrient deprivation and other selective pressures such as drug response, and is critical in high relapse risk subtypes. This approach can be applied to other cancers. The inventors of the present disclosure found in genomic databases that this secretome is similarly enriched in other brain tumor types as well as many adult cancers.

[0263] The term "micro" as used herein is to be broadly interpreted to include sizes from about 1 micron to about 1000 microns.

[0264] The term "nano" as used herein is to be broadly interpreted to include sizes less than about 1000 nanometers.

[0265] The terms "coupled" or "connected" or "attached" as used in the present specification, unless otherwise indicated, are intended to encompass both direct connections and indirect connections through one or more intermediate devices.

[0266] The term "associated" as used herein when referring to two elements means a broad relationship between the two elements. The relationship includes, but is not limited to, a physical, chemical, or biological relationship. For example, when element A is associated with element B, element A and B can be directly or indirectly connected to each other, or element A can comprise element B, and vice versa.

[0267] The term "adjacent" as used herein when referring to two elements means that one element is in close proximity to the other element, and can but is not limited to elements that are in contact with each other, or can further include elements that are separated by one or more other elements located therebetween. For example, a cleaving compound described herein cleaves an oligonucleotide (e.g., a primer, a probe, etc.) within or adjacent to a cleavage domain. Thus, the term "adjacent" means that the cleaving compound cleaves the oligonucleotide at either the 5' end or the 3' end of the cleavage domain. In some embodiments of the disclosure, the cleavage reaction produces a 5'-phosphate group and a 3'-hydroxyl group.

[0268] The term "and / or", such as "X and / or Y", should be understood as "X and Y" or "X or Y", and should be understood to provide clear support for both meanings or either meaning. In addition, in the description herein, the word "substantially" whenever used should be understood to include but not be limited to "completely" or "entirely", etc. As used herein, the term "substantially no" or "very low" refers to a sequence homology with a target nucleic acid (e.g., any human gene) of less than at least 20%, or 19%, or 18%, or 17%, or 16%, or 15%, or 14%, or 13%, or 12%, or 11%, or 10%, or 9%, or 8%, or 7%, or 6%, or 5%, or 4%, or 3%, or 2%, or 1%, or 0.9%, or 0.8%, or 0.7%, or 0.6%, or 0.5%, or 0.4%, or 0.3%, or 0.2%, or 0.1%, or 0.01%. In some embodiments, the term "substantially no" or "very low" sequence homology refers to a sequence that is significantly different from the control gene and the target nucleic acid (e.g., any human gene). In addition, whenever terms such as "comprising" and "including" are used, they are intended to be non-limiting descriptive language in that they broadly include the elements / components described after these terms, as well as other components not explicitly listed. For example, when "comprising" is used, reference to "a" feature is also intended to mean "at least one" of that feature. Terms such as "consisting of..." can be considered as subsets of terms such as "comprising" and "including" in the appropriate context. Therefore, in the embodiments disclosed herein that use terms such as "comprising" and "including", it should be understood that these embodiments provide guidance for corresponding embodiments using terms such as "consisting of..." In addition, whenever terms such as "about" and "approximately" are used, they generally refer to reasonable variations, for example, a variation of ±5% of the disclosed value, or a difference of 4% of the disclosed value, or a difference of 3% of the disclosed value, or a difference of 2% of the disclosed value, or a difference of 1% of the disclosed value.

[0269] In addition, in the description herein, some values ​​may be disclosed in the form of ranges. The numerical values ​​representing the range endpoints are intended to illustrate preferred ranges. Whenever a range is described, the range is intended to encompass and teach all possible subranges and individual numerical values ​​within the range. In other words, the endpoints of a range should not be understood as unchangeable restrictions. For example, a range description of 1% to 5% is intended to specifically disclose subranges such as 1% to 2%, 1% to 3%, 1% to 4%, 2% to 3%, and individual numerical values ​​within the range, such as 1%, 2%, 3%, 4% and 5%. It should be understood that individual numerical values ​​within the range also include integers, fractions and decimals. In addition, whenever a range is described, the range is intended to encompass and teach the value of retaining up to 2 decimal places or significant figures (if applicable) from the numerical endpoints shown. For example, description of a range of 1% to 5% is intended to specifically disclose a range of 1.00% to 5.00%, and a range of 1.0% to 5.0%, and encompasses all intermediate values ​​between these ranges (such as 1.01%, 1.02%, ..., 4.98%, 4.99%, 5.00%, and 1.1%, 1.2%, ..., 4.8%, 4.9%, 5.0%, etc.). This specific disclosure is intended to apply to any depth / breadth of the ranges.

[0270] In addition, when describing certain embodiments, the present disclosure may disclose methods and / or processes as a specific order of steps. However, unless otherwise required, it should be understood that the method or process should not be limited to the specific order of steps disclosed. Other order of steps are also possible. The specific order of steps disclosed herein should not be construed as overly limiting. Unless otherwise required, the methods and / or processes disclosed herein should not be limited to the steps performed in the order described. The order of steps can vary, but still be within the scope of the present disclosure.

[0271] Furthermore, it should be understood that although the present disclosure provides embodiments having one or more features / characteristics discussed herein, one or more of these features / characteristics may also be abandoned in other alternative embodiments, and the present disclosure provides support for such abandonment and these related alternative embodiments.

[0272] Experimental part

[0273] method

[0274] Immunohistochemistry

[0275] CD163 immunolocalization was performed on formalin-fixed, paraffin-embedded primary pediatric ATRT specimens using a commercially available anti-CD163 polyclonal antibody. An automated microscopy system was used. Stained sections were reviewed at study entry by a pathologist who was blinded to the study data / hypothesis. Because monocytes stain positively for CD163, while lymphocytes stain negatively, human tonsil sections served as positive and negative controls.

[0276] Primary tumor samples

[0277] Fresh tumor samples were snap-frozen in liquid nitrogen and stored at -80°C. Between 1994 and 2014, 10 primary pediatric ATRT cases were collected. A panel of eight patient-derived ATRT cell lines was obtained from international collaborating institutions. RNA was extracted for RNA sequencing and quantitative reverse transcription polymerase chain reaction (qRT-PCR) in this publication. Tumor samples were collected from untreated patients at diagnosis and before treatment initiation.

[0278] RNA-Seq, gene expression microarray, and classification of SHH-ATRT, MYC-ATRT, and TYR-ATRT

[0279] RNA was extracted using TRIzol from fresh-frozen patient ATRT tumor samples and a panel of eight patient-derived ATRT cell lines. For the discovery set, RNA sequencing was used to analyze the expression profiles of RNA from 10 primary human ATRT tumors, eight ATRT cell lines, and 10 control brain tissues. For the validation set, CEL files from 49 characterized patient ATRT tumors were used. The subtype identity of each patient tumor was determined using published subtype-specific gene sets. Human primary ATRT was classified into the following molecular subtypes: Sonic Hedgehog (SHH)-ATRT, MYC-ATRT, and TYR-ATRT.

[0280] Transcriptome sequencing (RNA-Seq)

[0281] Whole-genome transcriptome analysis was performed on 28 samples (10 primary human ATRT, 8 ATRT cell lines, and 10 control brain tissue RNA) using a high-throughput sequencing system. Total RNA was extracted and treated with DNase I, mRNA was isolated using Oligo(dT), fragmented using fragmentation buffer, and cDNA was synthesized. Short fragments were purified and re-dissolved with EB buffer, and single nucleotide A (adenine) was added. Adapter sequences were added to the short fragments, and then appropriate fragments were selected for PCR amplification. For quality assurance / quality control (QA / QC) of the sample library, the inventors of the present disclosure used an automated electrophoresis platform and a real-time PCR system. The library was sequenced using a high-throughput sequencing system. Paired-end 2×100 base pair reads were generated on the high-throughput sequencing system, with an average read length of 8.96Gb per sample. Before downstream analysis, low-quality sequencing reads were removed, and clean reads were mapped to the hg19 reference genome using HISAT, with an average of 85.42% of reads mapped to the reference genome. After mapping the sequencing reads to the reference genome, transcriptomes were reconstructed, and a total of 23,672 coding genes were identified.

[0282] RNA sequencing data analysis

[0283] Raw reads were quality controlled and filtered clean reads were aligned and mapped to the reference genome using sequence alignment tools. For gene expression analysis, clean reads were mapped to the reference genome using sequence alignment tools. Gene expression levels were calculated using RNA sequencing quantification tools. Statistical analysis was performed using analysis software to identify differentially expressed genes between patient tumors and normal brain controls. Differentially expressed genes were generated using the false discovery rate (FDR) method with p-value < 0.05 and a cutoff of fold change > 2.

[0284] Microarray data analysis

[0285] The inventors of the present disclosure downloaded gene expression microarray data for 49 ATRT patient tumors from a database. Meta data containing tumor subtype identity for the 49 ATRT samples were downloaded. ATRT patient samples have been previously identified into three subtypes (MYC-ATRT, SHH-ATRT, and TYR-ATRT). Of the 49 patient tumors, 15 tumors were of the MYC subtype, 16 tumors were of the SHH subtype, and 18 tumors were of the TYR subtype. The 49 raw CEL files were imported into analysis software. RMA background correction and quantile normalization were performed. Gene expression values were log2 transformed and used for subsequent gene expression analysis.

[0286] Statistical analysis

[0287] Statistical tests such as Student’s T-test were used to compare marker expression between patient tumors, control brain tissue, and cell lines. Statistical analysis was performed to determine intergenic correlation of markers. A cutoff of p-value < 0.05 was used to identify significant canonical pathways. A -log(p-value) greater than 1.3 indicates p < 0.05. Z-scores indicate the degree of observed change in gene expression level (increase / decrease) indicating whether the expected change is associated with pathway activation or inhibition. An activation Z-score (Z-score > 2) Figure 3E ) indicates that the pathway is predicted to be activated, while an inhibition Z-score (Z-score < -2) indicates that the pathway is predicted to be inhibited.

[0288] Quantitative real-time polymerase chain reaction

[0289] Total RNA was extracted from cultured cells of 7 ATRT cell lines and 4 other embryonic brain tumor cell lines using TRIzol reagent and reverse transcribed using High Capacity RNA to cDNA kit. Real-time PCR was performed using the kit. Each sample was loaded in triplicate. SYBR-green primers used for the reaction were MELK (H_MELK_l) and housekeeping gene GAPDH (H_GAPDH_l). PCR reaction was as follows: initial polymerase activation at 95°C for 2 minutes, followed by 40 cycles of amplification (95°C denaturation for 5 seconds; 65°C annealing for 10 seconds; 72°C elongation for 20 seconds). Relative expression of each mRNA was calculated by the formula of 2 -ΔΔCt

[0290] Proliferation assay (standard growth medium)

[0291] Tumor cells were seeded in quadruplicate (n=4) under each treatment condition Figure 5B ). OTSSP167 was added. Cell proliferation was assayed and optical density (OD) was measured using a fluorescence / luminescence detection system.

[0292] Flow cytometry

[0293] Cultured tumor cells were treated with OTSSP167 to detect apoptosis Figure 5C ). Cells were collected at each time point and stained with Annexin V-FITC and PI. Stained cells were then analyzed by flow cytometry with excitation wavelengths of 488 nM (FITC) and 595 nM (PI), respectively. Cultured cells were treated with OTSSP167 to study cell cycle changes. Cells were collected and fixed with absolute ethanol. Fixed cells were stained with PI / RNase A premix (PI and RNase A) and then subjected to flow cytometry analysis.

[0294] Flow cytometry analysis of macrophage marker expression

[0295] Human myeloid-derived cells (U937) were treated with PMA and different concentrations of IL-4 (or different cytokine combinations) and harvested at different incubation time points. Cells were stained with PE-conjugated anti-human CDl lb antibody or PE-conjugated anti-human CD163 antibody for 10 minutes. Isotype control PE-conjugated REA control antibody was used to verify antibody specificity. Stained cells were then analyzed by flow cytometry.

[0296] Apoptosis detection of OTSSP167-treated cells cultured in standard medium compared to six-factor secretome

[0297] ​Tumor cells were incubated in standard growth medium or six-factor secretome for three different time periods, 4 hours, 24 hours, 48 hours and 96 hours, respectively. Figure 5G To investigate the killing effect of OTSSP167, tumor cells incubated under each condition (standard growth medium or six-factor secretome) were treated with OTSSP167. Cells were collected at the corresponding time points and stained with FITC-Annexin V and / or propidium iodide. Then, the stained cells were analyzed by flow cytometry with excitation wavelengths of 488 nM (FITC) and 595 nM (PI), respectively. A total of 10,000 cells were analyzed for each measurement.

[0298] Serum-free supernatants

[0299] Human myeloid-derived cells (U937) were seeded at a fixed density and stimulated with PMA and IL-4 for 48 hours to obtain CD11b+ cells. Stimulated human myeloid-derived macrophages were harvested without trypsinization (biological replicates 1 in Figure 4D and Figure 5E ) and with trypsinization (biological replicates 2 and 3 in Figure 4D and Figure 5E ). These cells highly expressed CD11b+ ( Figure 14A ) with or without trypsinization. CD11b+ cells were washed twice with PBS. CD11b+ cells were seeded at a fixed density in 1 ml of pure RPMI (serum-free) to obtain CD11b+ supernatant (condition 2). CD11b+ cells (same density) were co-cultured with tumor cells at a 1:1 ratio in pure RPMI (serum-free) to obtain co-culture supernatant (condition 3). Tumor cells were seeded at the same density to obtain tumor supernatant (condition 1). After incubation at 37°C and 5% CO2 for 3 hours, the supernatants were collected by centrifugation, verified for the absence of cells (Figure 18) and stored at -80°C before further use.

[0300] Cell proliferation assay (secretome-based or growth medium-based)

[0301] Tumor cells were suspended in three cell-free supernatants: CD11b+ supernatant, tumor supernatant and CD11b+-tumor co-culture supernatant. Standard growth medium and pure RPMI conditions were used as positive and negative controls, respectively. Cells were seeded. For drug treatment groups, cells were treated with DMSO or OTSSP167. Within 3 days, cell viability was determined at time points of 4 hours, 24 hours, 48 hours and 72 hours, respectively, using a kit. The optical density (OD) Figure 4A , 4B, Figure 18). All other absorbances (OD) were measured at 450 nm using a multi-label microplate reader. The absorbance of the wells containing serum-free pure RPMI served as a blank control.

[0302] Cytokine analysis

[0303] Assess the cytokines present in the cell supernatant using a cytokine array. Use 700 μl of supernatant. Visualize the cytokine spots using an imaging system.

[0304] Immunoblotting

[0305] Cells were lysed on ice using RIPA buffer containing 1% protease and phosphatase inhibitor cocktail. Protein samples were first denatured at 95°C using Laemmli buffer containing 5% β-mercaptoethanol. Protein concentration was determined using a protein assay kit. Protein lysates were re-dissolved and equal amounts of denatured proteins were electrophoresed on NuPAGE 4-12% Bis-Tris protein gels and then transferred to PVDF membranes. Membrane blotting of phosphorylated histone H2A.X was performed using 1x TBS-T (10x Tris-buffered saline, 0.1% 20). Other membrane blots were blocked with 5% nonfat milk in 1x TBS-T for 1 hour and incubated with the corresponding primary antibodies overnight at 4°C. Protein bands were visualized using a Western blotting substrate and an imaging system. Primary antibodies used were: Eg5, PARP lysate, β-actin, caspase-3 lysate, as well as p53, p-histone H2A.X, and p21. Secondary antibodies included: HRP-linked anti-rabbit IgG and HRP-linked anti-mouse IgG.

[0306] Statistical analysis

[0307] All data are expressed as mean ± SD (standard deviation). Statistical analysis (such as unpaired Student's t-test) was performed to determine the statistical significance of differences between groups. *p < 0.05, **p < 0.01, ***p < 0.001 were considered statistically significant.

[0308] Orthotopic implantation of patient-derived tumor cells into the mouse brain

[0309] Rag2 / severe combined immunodeficiency (SCID) mice were housed in a pathogen-free facility. Tumor cells (1×10 -5Surgical implantation into the mouse brain. The present disclosure study follows the general recommendations in the ARRIVE guidelines 2.0 (https: / / arriveguidelines.org / ). The sample size of the present disclosure is small. The inventors of the present disclosure did not use any method to generate a randomized sequence. Animals were randomly assigned to treatment and control groups, with approximately equal number of animals in each group. The inventors of the present disclosure recently published an article indicating that gender does not statistically affect treatment outcome, so both genders were included in the present disclosure study. The animals of the present disclosure were housed in side-by-side cages in the same location and managed by the animal department and the team of the present disclosure according to a standardized maintenance protocol to minimize any confounding factors. The inventors of the present disclosure did not employ any special strategy to minimize other confounding factors. Animals assigned to treatment groups were treated cage by cage. Blinding was not possible because the inventors of the present disclosure have a small team of 2-3 people working with the animals and all of them are involved in all stages and daily routines of the animal work. Independent batches consisting of different litters were used to minimize bias due to same-litter effects. The inventors of the present disclosure have previously published papers using this animal protocol and have not deposited it in any repository / registry in any other way.

[0310] Intraperitoneal administration of drugs

[0311] OTSSP167 was dissolved in Cremophor EL, dimethyl sulfoxide, A daily dose of 5 mg / kg of OTSSP167 was administered to mice by intraperitoneal injection for 14 days. Ten animals were studied (5 in the treatment group and 5 in the control group). For the 94B batch, Ispinesib was dissolved in a solution of Cremophor EL, dimethyl sulfoxide and water. Ispinesib was administered intraperitoneally every four days, three times, with a repeat course on day 21. The dose of Ispinesib was 10 mg / kg.

[0312] Clinical staging system to monitor the health of the mice

[0313] We used the previously published clinical staging system to carefully monitor the health of the mice daily. When the mice presented signs of severe neurological deficit or imminent death, they were euthanized according to the protocol of the present disclosure.

[0314] Statistical analysis of animal survival

[0315] The survival of each mouse was defined as the number of days from the date of tumor implantation to the date of death (overall survival), with event = 1 and censored subjects = 0. Data were censored for mice alive at the time of analysis. All Kaplan-Meier survival curves were plotted and survival analysis was performed.

[0316] result

[0317] M2 macrophages are associated with poorer survival in patients with medulloblastoma, another childhood embryonal brain tumor. The inventors of the present disclosure first examined macrophage infiltration of ATRT tumors from four patients by immunohistochemical staining using a monoclonal antibody to CD163, an M2 macrophage marker. CD163 is expressed only on alternatively activated or M2 polarized macrophages. Patient ATRT tumors depicted a structure where a macrophage compartment intersected with a tumor cell compartment; this macrophage compartment was notably absent in normal brain tissue ( Figures 1A-1B ). Figures 1A-1B The macrophage-tumor ecosystem is shown, depicting the challenges of studying infiltrating macrophages in patient tumors. Atypical teratoid rhabdoid tumor (ATRT) exhibits the following architecture: a macrophage compartment (absent in normal brain tissue) connected to a tumor cell compartment. Morphologically, CD163 is expressed on macrophages but not on tumor cells. The macrophage-rich compartment has a high density of macrophages and is nested at the tumor border (the edge of a patient tumor resected from normal brain) ( Figure 1A There is almost no macrophage infiltration in normal brain (control) ( Figure 1A Heterogeneity in intratumoral macrophage infiltration was observed between patient tumors and within each individual patient tumor (patients 1-4), with the stroma being significantly more infiltrated with macrophages compared to the tumor compartment (p = 0.022, paired t-test, Figure 1B Macrophages sometimes formed well-defined perivascular rings, suggesting that their origin was related to circulating myeloid cells in patient 4 ( Figure 1B The inventors of the present disclosure investigated a mixed panel of 13 pediatric brain tumors from the same institution and found that a significant proportion of patients had similar enrichment of CD163 macrophages in their tumors ( Figure 13 The inventors of the present disclosure observed that not all patient tumors within each histological type showed high CD163 expression—of the two ATRT tumors in this cohort, one showed CD163hi expression and the other showed CD163lo ( Figure 13 ). This suggests that within a single histological type, macrophage infiltration varies between patient tumors.

[0318] Many current strategies for studying macrophages in patient tumors involve exploring the spatial relationships of macrophages within immortalized tumors at a single time point ( Figure 1C ), such as genomic analysis of microdissected regions of macrophages in patient tumors (Strategy 1), single-cell sequencing of individual macrophages in patient tumors (Strategy 2), and spatial transcriptomics (Strategy 3). Challenges of Strategy 1 include missing the scattered invasive macrophages in the patient tumor ( Figure 1B), while the limitations of strategy 2 include: (1) the high cost of sequencing a large number of single cells, (2) the data is limited by the number of cells sequenced (cost limitation), and (3) ensuring that the sequenced single cell population is well representative. The common problem of strategies 1 and 2 is that both methods require the separation of the macrophage microenvironment compartment from the tumor compartment. The common challenge faced by all three strategies is the lack of dynamic data on the spatial information of macrophages extracted from human tumors - macrophages are immortalized at a single time point after resection from patient tumors, resulting in the loss of the opportunity to study the in situ real-time interaction between tumor and macrophage compartments. To address this issue, the secretome of human CD11b+ (pan-macrophage) cells was obtained ( Figure 2A The inventors of the present disclosure first treated human myeloid-derived cells with a PMA-cytokine mixture to induce CD11b (pan-macrophage marker) expression. CD11b (pan-macrophage marker) expression persisted up to 80-90% ( Figure 2A , Figure 14A ), while CD163 (M2 macrophage marker) expression was very low ( Figure 14B ).

[0319] An array analysis of 36 cytokines and chemokines was performed to compare the secretion factors under three different conditions: (1) tumor cell conditioned medium only, (2) CD11b+ cell conditioned medium only, and (3) tumor-CD11b+ co-culture. The results showed that the 6 cytokines and chemokines released by CD11b+ macrophages in the microenvironment showed an enrichment pattern ( Figure 2B The inventors of the present disclosure used the most aggressive ATRT tumor cell (CHLA-06) from the seven ATRT cell lines in the present disclosure to construct the tumor compartment ( Figure 15 ), based on the hypothesis that the fastest growing cell line in vitro, CHLA-06, would secrete the most complete spectrum of tumor-promoting factors. Importantly, the presence of tumor cells enhanced the production of these six specific cytokines-chemokines (CCL2 / MCP-1, MIP-1α / MIP-1β, CCL5 / RANTES, MIF, IL-1ra / ILIF3, IL-8) by CD11b+ cells ( Figure 2B ). Tumor cells isolated from culture do not produce this group of cytokines except MIF ( Figure 2B ), indicating that this group of cytokines is unique to CD11b+ cells and is released by them. In the discovery set (RNA sequencing, n = 28 samples), 10 patient tumors, 10 controls (normal brain tissue controls from different brain regions of the cerebellum, cerebrum, and pons), and 8 patient-derived cell lines were compared. This secretome was enriched only in patient tumors, but not in normal brain controls or patient-derived tumor cell lines (Figure 2C , Figure 16A ). The secretome was significantly depleted in normal brain controls ( Figure 2C ). Notably, this enrichment pattern in patient tumors was reproduced in an expanded 36 cytokine-chemokine panel (all candidate factors on the cytokine array platform, Figure 2B ). Thus, Figure 2A and Figure 2B show that the secretome derived from CD11b+macrophages is enriched in specific molecular subtypes of ATRT.

[0320] The inventors of the present disclosure next compared the secretome enrichment pattern in patient tumors of the three different ATRT molecular subtypes (MYC-ATRT, SHH-ATRT, TYR-ATRT) in a validation set comprising 49 patient ATRT tumors classified by molecular subtype. The secretome enrichment was most abundant for MYC-ATRT, followed by TYR-ATRT, while SHH-ATRT had almost no secretome enrichment ( Figure 2D , Figure 16B ). Similarly, the enrichment pattern of the expanded 36 cytokine-chemokine panel (all candidate factors on the cytokine array platform) reproduced the secretome enrichment pattern in the three ATRT molecular subtypes (MYC > TYR > SHH) and was significant only in patient ATRT tumors in both the discovery set ( Figure 2C ) and the validation set ( Figure 2D ), but not in normal brain or cell lines.

[0321] Figures 3A-3E show that the macrophage enrichment pattern in patient tumors matches the secretome enrichment subtype. Macrophage infiltration density further mirrors the enrichment pattern of the secretome. Quantitative bioinformatic assessment of macrophage markers (RNA sequencing, n=28 samples) in patient tumors, control groups and patient-derived tumor cell lines confirmed that patient tumors are enriched in CD11b (pan-macrophage marker) and CD163 macrophages (M2 macrophage marker), but not in tumor cell lines and normal brain tissue ( Figure 3A ). CD11b and CD163 macrophage content was relatively low in control brain tissue. Macrophage markers of different subpopulations, in particular CD11b and CD163, correlated well in patient tumors, but not in tumor cell lines and normal brain tissue ( Figure 3B , Figure 17). Among the three molecular ATRT subtypes in the validation set, MYC-ATRT and TYR-ATRT were macrophage-enriched tumors ( Figures 3C-3D), matching the subtype enriched for secretome, suggesting that different signaling pathways influence macrophage recruitment and function in tumors of patients with these secretome-enriched subtypes. The inventors of the present disclosure further investigated other macrophage markers in the discovery and validation sets and observed similar trends (Figures 7-11). Figures 7A-7D Expression of other macrophage markers (TREM2 and CD206) in the discovery (n=28) and validation (n=49) sets is shown. Dot plots indicate Figure 7A and Figure 7C Expression of TREM2 and CD206 by RNA sequencing in the discovery (n=28) set, Figure 7B and Figure 7D Expression of TREM2 and CD206 by Affymetrix U133plus 2.0 in the validation (n=49) set, classified by molecular subtype. SHH-ATRT is low macrophage and low secretome. Tumors showing M2 macrophage enrichment phenotype (CD163hi) are typically MYC-ATRT and TYR-ATRT and are significantly enriched in dendritic cell maturation pathway and complement system ( Figure 3E ). These findings corroborate the immunohistochemistry findings of the present disclosure that macrophages are present only in patient tumors ( Figures 1A-1B ), but not in normal brain tissue controls or patient-derived tumor cell lines.

[0322] To elucidate the influence of the secretome on tumor cell proliferation, the inventors of the present disclosure cultured a panel of 6 ATRT cell lines from individual patients ( Figure 2B ) under three in vitro macrophage-tumor microenvironment conditions they developed: Condition 1 - tumor cell factors, Condition 2 - CD11b+ cell factors, Condition 3 - CD11b+ co-cultured with tumor cells factors. Figures 4A-4H It is shown that during nutrient stress, tumor cells proliferate and rearrange in the macrophage secretome, forming extensive, interwoven reticular structures that connect cells over long distance radii. The inventors of the present disclosure compared the growth of 6 tumor cell lines ( Figures 4A-4B ) over 72 hours in all 3 microenvironment conditions (using supernatants of the respective cell origin cultured in RPMI basal medium without any serum or growth factors) compared to pure RPMI basal medium (control, without any serum or growth factors). Clearly, pure RPMI basal medium (control, without any serum or growth factors) is in a state of nutrient stress and cannot support tumor cell proliferation ( Figures 4A-4B ) from CD11b+ cell factors ( Figure 4A ) and CD11b+ co-cultured with tumor cells factors ( Figure 4B) compared to tumor cell cytokines resulted in higher tumor cell proliferation Figure 18A ) In all 6 ATRT cell lines, 2 cell lines (CHLA-02 and BT-37) had a significant increase in optical density (OD) readings above the baseline OD readings of the secretome (Figure 19). BT-37 is a patient-derived ATRT xenograft cell line. This can indicate that certain tumor cell lines can retain an intrinsic ability to respond to macrophage-associated factors. Notably, the 2 cell lines that exhibited higher proliferative capacity (CHLA-02, BT-37) were slightly enriched in secretome compared to all other cell lines (secretome blank group, Figure 2C ) This indicates that through in vitro passaging, most tumor cell lines can lose components of the microenvironmental response factors / receptors in the stroma, as indicated by the less growth-inducing response to exogenous secretome stimulation in the other 4 / 6 ATRT cell lines. The growth-promoting effect of these supernatants peaked at 72 hours, after which there was a downward trend in tumor proliferation rate Figure 4B 、 4C and 4D).

[0323] These results also indicate that the cytokine-chemokine combination alone, without the addition of standard growth media supplements, is not sufficient to sustain tumor growth in vitro for more than 72 hours (standard in vitro nutrients also require replacement every 48-72 hours for standard cell culture of these cell lines). This indicates that this macrophage-tumor microecosystem can provide an early and temporary ecological niche for the initial tumor growth burst and provide an alternative energy source during periods of nutrient stress when the microenvironment lacks nutrients. Supernatants derived from CD1 lb+and tumor cell co-culture provided the best sustained growth-promoting effect at 72 hours compared to CD1 lb+supernatants Figure 2B , Figure 4). Conditioned media derived from tumor cells was not effective in sustaining tumor growth Figure 18A , indicating a deficiency in tumor cell cytokines Figure 2B . The combination of the six factors was effective. Previous cytokine array results showed that the content of these six specific cytokine-chemokines was higher in supernatants derived from CD1 lb+and tumor cell co-culture factors compared to CD1 lb+media Figure 2B . These six factors - CCL2 / MCP-1, MIP-1 a / MIP-1 b, CCL5 / RANTES, MIF, IL-1 ra / ILIF3, and IL-8 - have been independently described as influencing macrophages or tumorigenesis.

[0324] Furthermore, the inventors of the present disclosure first observed that this unique combination of 6 factors was able to prevent tumor cell death in all four ATRT cell lines tested (CHLA-02, BT-37, CHLA-04, CHLA-06, Figure 4E ) for up to 48 hours. The secretome was as effective as standard growth media in preventing cancer cell death for up to 48 hours, significantly maintaining a critical mass of cancer cells during periods of nutrient stress. At longer time points of 72-96 hours, more cell death occurred with the secretome compared to standard growth media ( Figure 4E ), suggesting that the secretome is able to provide initial support, but is insufficient to sustain long term without a supply of nutrients. Of particular note, the secretome was able to prevent cell death in CHLA-04, which was derived from a recurrent ATRT tumor obtained at autopsy, which had extensively disseminated to the brain and cerebrospinal fluid ( Figure 4E ). This suggests that in this highly aggressive tumor model, while the secretome does not cause high tumor proliferation ( Figure 4A 、 4B ), it is able to prevent tumor cell death for longer periods of time, thus contributing to a mechanism of tumor survival and dissemination. The secretome was also observed to have a similar ability to prevent cell death for long periods of time (72-96 hours) in the most aggressive and fastest growing ATRT cell line in vitro, CHLA-06 ( Figure 4E ), but did not support high tumor proliferation ( Figure 4A 、 4B ). These findings in the most aggressive cell line (fastest growing in vitro) (CHLA-06) and in a recurrent tumor obtained at autopsy (extensively disseminated to the brain and cerebrospinal fluid) (CHLA-04), suggest that the secretome can be one mechanism in tumor resistance and recurrence.

[0325] The inventors of the present disclosure found that tumor cells, which normally grow in neurospheres in standard growth media, reorganized themselves to form an interwoven network of cells that linearly connected cells at long distance radii (linear pattern) in vitro when grown in the secretome after 24 hours of nutrient stress ( Figure 4F 、 4G , FIGS. 20-24). Cancer cells cultured in vitro have never exhibited this ability under standard media conditions. This observation suggests that there is cross-talk between cells in the secretome microenvironment during periods of nutrient stress or deprivation that is critical for tumor cell survival, which reorganize into a network to maintain strong resistance in the absence of a stable and continuous supply of nutrients. Figures 12A-12HLarge image micrographs were presented, capturing large area tumor cells (CHLA-02) grown in T75 flasks, demonstrating the unique interwoven network structure of tumor cells grown on secretome, in contrast to tumor cell clusters grown in standard growth medium (control).

[0326] Next, to evaluate the role of secretome in modulating drug response in tumor compartment, the inventors of the present disclosure collated potential cell cycle targets in ATRT patient tumors and corresponding molecular inhibitors available. The inventors of the present disclosure surmised that tumor compartment would be enriched in cell cycle genes during rapid tumor growth and cell division, and thus cell cycle genes would provide suitable targets to inhibit growth of tumor compartment. The inventors of the present disclosure and other research groups found that Maternal Embryonic Leucine Zipper Kinase (MELK) is enriched in patient ATRT tumors and other types of tumors. Figures 5A-5H It was shown that secretome hinders drug response and provides a protective microenvironment to rescue tumor cells from initial drug damage. The inventors of the present disclosure further identified MELK as a universal target for three ATRT subtypes Figure 5A ). MELK is expressed in 6 out of 7 ATRT cell lines (Figure 25, BT-37 has low expression, ATRT-95 has no expression). MELK molecular inhibitor OTSSP167 is effective in all 6 ATRT cell lines in nanomolar range Figure 5B , Figure 26 ). OTSSP167 induced apoptotic death of ATRT cells (CHLA-02, BT-37), leading to apoptotic cell death (58.1% early and late apoptotic cells in BT-37 cells, 50.7% apoptotic cells in CHLA-02 cells after 48 hours of OTSSP167 treatment, Figure 5C ). Immunoblotting showed that p-histone H2A.X increased in CHLA-02 and BT-37 cells after 24, 48 and 72 hours of OTSSP167 treatment Figure 5D ), indicating that OTSSP167 induced DNA damage. c-PARP also increased after OTSSP167 treatment Figure 5D ), supporting activation of intrinsic apoptotic pathway. p53 increased after OTSSP167 treatment, consistent with normal stress response. The inventors of the present disclosure selected two cell lines, CHLA-02 and BT-37, which showed strong growth proliferation ability in secretome (Figure 4), to examine drug response in the presence of secretome.

[0327] The inventors of the present disclosure found that the presence of secretome reduced drug efficacy at initial stage Figure 5E ​), thereby providing a pro-survival microenvironment for rescuing tumor cells during the early drug response period. The inventors of the present disclosure have shown that tumor cells cultured in standard growth medium containing OTSSP167 exhibit rapid and sustained inhibition of tumor growth, indicating a rapid and effective drug response in standard growth medium (CHLA-02, BT-37, Figure 5E In contrast, tumor cells cultured in the presence of secretomes derived from CD11b+ cell-conditioned medium or from supernatants co-cultured with CD11b+ and tumor cell factors consistently demonstrated a diminished tumor growth inhibitory response to OTSSP167 in the secretome microenvironment ( Figure 5E A combination of six factors effectively inhibited the drug response, indicating that the drug is less effective in the secretome-rich microenvironment compared to in vitro screening using standard growth medium. Within patient tumors, these six factors were enriched in the microenvironment, suggesting that the drug is less effective in the secretome-rich microenvironment of patient tumors.

[0328] The secretome is a scalable and clinically relevant resource for laboratory-stage phenotypic screening of drug testing in a variety of cancer cell lines. It can predict the pro-survival active components of a limited pool of microenvironmental cytokines and chemokines. It serves as a tool to measure drug efficacy in the presence of minute amounts of the pool of microenvironmental factors. Furthermore, these factors remain stable during long-term storage at -80°C and retain their efficacy after 3 years of long-term storage at -80°C ( Figure 4D : Results of CHLA-02 (replicate 1) and BT-37 assays (replicate 1) using supernatants stored at -80°C for 3 years). The disclosed six-factor secretome drug screening method can provide an easily accessible and scalable resource for in vitro laboratory testing of other cancer types to identify cancers that utilize the secretome as an alternative energy source. The secretome provides a favorable tumor ecosystem that reprograms malignant cells to survive nutritional stress and other selective pressures (such as early drug response). In addition, when treated with OTSSP167, tumor cells maintain their interwoven structure in the secretome ( Figure 5H 、 5E , Figure 27, Figure 28), in contrast, tumor cells (CHLA-02) disaggregated into smaller clusters when treated with OTSSP167 in standard growth medium, suggesting that the secretome provides a potential mechanism of treatment resistance.

[0329] These findings suggest that the secretome supports a pro-survival microenvironmental model that favors tumor cell survival during nutrient stress and exogenous drug stress. In the native, drug-free state, media nutrients induce a slow increase in proliferation rate, whereas the six-factor secretome microenvironment elicits a rapid and sustained proliferation rate in the nutrient-poor cancer cell microenvironment (Figure 4). This suggests that the secretome provides a superior ecosystem for a tumor growth surge during nutrient deprivation. In the drug-exposed state, the proliferative response of the tumor to OTSSP167 is inhibited in the presence of the secretome Figure 5E ), whereas, in contrast, drug exposure in the standard media nutrient environment leads to a rapid inhibition of tumor proliferation. This suggests that drugs that show efficacy in vitro in the standard growth media (traditional drug testing methods) are less effective when tested in the same cell lines in the secretome screen.

[0330] This four-pronged mechanism of the secretome is able to (1) induce a rapid early growth surge and (2) prevent tumor cell death during nutrient stress, while (3) inhibiting the drug response of tumor cells and maintaining a stable interwoven network structure of tumor cells upon exposure to drugs, providing a strong advantage for tumor cell resistance and treatment resistance Figure 4G ). Some patient tumors are rich in secretome Figures 2C-2D ), highlighting the gap in translating in vitro effective drugs into clinical trial processes, and thus, there is an unmet need for a more accurate match of patient tumors that are rich in secretome and can be weakly responsive to certain drugs.

[0331] Another consideration is that macrophages can provide these secretome microecosystems to promote tumor recurrence (a secretome microecosystem is an alternative energy source that prevents cell death Figure 4E , 4F ) and accelerate a tumor growth surge of residual cancer cells that reside near the tumor margin after a majority of surgical resection of a tumor (a mechanism of tumor recurrence) Figure 4D ). The inventors of the present disclosure observed that in some resected patient tumors, there were macrophage-rich compartments with high density of macrophages nested at the tumor boundary Figure 1A ). This observation was further confirmed by the finding that common recurrent subtypes of ATRT-MYC-ATRT, TYR-ATRT Figure 6 ) are also macrophage-enriched and secretome-rich subtypes Figures 2C-2D). Data from patients with SHH-ATRT reported in ACNS0333 showed no relapses within the first 6 months, with a cumulative incidence (CI) of relapse of 37.5% at 4 years; while the CI of relapse at 6 months for TYR-ATRT and MYC-ATRT patients were 33.3% and 26.7%, respectively, and the CI of relapse at 4 years were 46.3% and 73.3%, respectively (p=0.088, unpublished data). Although ACNS0333 was not sufficient to determine prognostic indicators of relapse, this trend is still of interest. Larger datasets are needed to investigate these variables.

[0332] A limitation of the present disclosure study is that the in vitro assay of the present disclosure only employed 6 factors (identified from 36 candidate factors on the cytokine array). The detection threshold is limited by the minimum amount of protein that can be detected by the cytokine array. Serum-free / cell-free supernatant Figure 2B ) can contain other factors, but in lesser amounts that cannot be assessed by this assay. A greater chemokine-cytokine profile can be detected using higher specification protein assays, such as mass spectrometry. However, the data of the present disclosure has demonstrated that patient tumors, especially MYC-ATRT and TYR-ATRT, are highly enriched in 36 candidate factors on the cytokine array Figures 2B-2C), can contain more than 36 cytokine-chemokines. Using high resolution protein assays to define all cytokine-chemokines provides little help in understanding the mechanistic function of the entire secretome profile in a patient's tumor. More importantly, the inventors of the present disclosure have been able to infer the impact of this culture system containing a minimum of 6 factors on the outburst of tumor growth and inhibition of drug efficacy using this system. Another consideration is that the secretome assay of the present disclosure measures for up to 72 hours. In the in vitro assay of the present disclosure, the amount of protein produced by CD1 lb+ cells is physiologic, not infinite. Therefore, this assay also mimics the biological concentration of endogenous secretome production in a patient's tumor, and the data of the present disclosure reproduce this: a small amount of this cytokine-chemokine cocktail in a patient's tumor is sufficient to support the initial outburst of growth that is critical in the initiation process of a tumor. The problem becomes more severe within a patient's tumor, as resident macrophages can continuously produce a secretome as an alternative energy source to sustain a minimal critical pool of cancer cells during periods of nutrient stress until the nutrient source is replenished through the new tumor vasculature. This is important in solid tumors: the accessibility of nutrients within a solid tumor is regulated by the proximity to the vasculature. Rapidly expanding solid tumors require a continuous supply of oxygen and nutrients for growth and survival, which needs to be maintained by the tumor neovasculature. Cells located near the vasculature utilize nutrients and oxygen to promote proliferation. However, cells that are distal to the vasculature have reduced accessibility to nutrients, and need to utilize alternative energy resources such as the macrophage secretome. Therefore, drugs that are effective under both nutrient- abundant and secretome-based conditions would be highly attractive.

[0333] Other smaller datasets have independently reported macrophage infiltration in ATRTs with subtype-specific differences, however, previous analyses showed that CD68+ microglia / macrophage infiltration was significantly higher in SHH-ATRTs (16 tumors) than in TYR-ATRTs (10 tumors, p=0.0006) and MYC-ATRTs (8 tumors, p=0.0157), which contrasts with the current disclosure revealing that SHH-ATRTs comprise a tumor subtype of macrophage-depleted. This also reinforces the challenge highlighted by the inventors of the present disclosure previously: when studying macrophages in patient tumors, samples are harvested at a single time point and immortalized. In the process, the inventors of the present disclosure lose the opportunity to study the in situ real-time dynamics of macrophages and tumor compartments as an ecosystem. While the assessment of CD163 as a M2 macrophage marker can not be fully elucidated, many other studies have consistently used CD163 for this purpose, including studies of tumors and cell lines. Moreover, tumor infiltrating macrophages in the brain include resident microglia that enter the brain and circulating monocytes of myeloid origin. There is still controversy regarding the presence of Ml and M2 microglia. The mechanism approach of the present disclosure with secretome assays enables multiple time point sampling to study the environment during tumor development.

[0334] From the data of the present disclosure for BT-37, Figure 5E ) unlike other cell lines (CHLA-02), this xenograft-derived cell line supernatant can support some tumor growth on its own, suggesting that mouse stromal components in the xenograft cell line (BT-37) can contain growth-promoting factors that can not be present in patient-derived cell lines (CHLA-02) after long-term passaging. In vivo experiments, OTSSP167 effectively prolonged the survival of animals in a patient-derived orthotopic xenograft ATRT mouse model obtained by active necropsy Figure 5F ). But as with most preclinical tests, although the administered drug was able to slow tumor growth, the mice eventually died of the tumor. This is the gap in clinical translation. Microenvironmental factors constantly secreted by other cell types in host tissues can provide critical pro-survival microenvironments for early tumor cells. Even in the absence of environmental nutrients, tumor cells can maintain survival, which in turn raises the important challenge of tumor recurrence. The assays of the present disclosure show that tumor cells can regain viability in a microenvironment with fewer surviving tumor cells (such as after surgical partial resection / treatment) as long as the supporting cell type (macrophages) provides a minimal secretome. Figure 6). As drug exposure times for in vitro assays can differ significantly from drug exposure times achievable in vivo, the in vivo data of the present disclosure ultimately demonstrate that the therapeutic activity of OTSSP167 can induce tumor growth retardation at OTSSP167 levels achievable in vivo. Our results indicate that OTSSP167 has in vivo clinical effectiveness on the ATRT model of the present disclosure with positive necropsy (p = 0.032, Figure 5F ). OTSSP167 has been shown to penetrate the blood-brain barrier of another mouse model of ATRT. Taken together, the data of the present disclosure reveal for the first time the functional features of the secretome in the macrophage-tumor ecosystem that can overcome the nutrient-deprived state by providing a sustained pro-survival microenvironment. This secretome can re-activate a small but critical reservoir of surviving tumor cells, which can be an important mechanism of relapse and treatment resistance.

[0335] The studies of the present disclosure fill a knowledge gap on how the macrophage-associated secretome mechanistically influences tumor proliferation during nutrient stress by providing an alternative energy source. Furthermore, these findings also raise further questions on how such macrophage-associated secretomes influence the clinical success rate of drugs in the process of clinical trial translation, as drugs are traditionally tested in vitro using standard culture media, but patient tumors can be enriched in secretomes. The inventors of the present disclosure propose a secretome screen as a companion phenotype assay to identify drugs effective in a chemokine-cytokine environment to assess the contribution of tumor microenvironmental factors and in combination with traditional in vitro drug screening using standard growth media and in vivo preclinical testing. The methods of the present disclosure add value to drug selection and patient stratification strategies to reduce the clinical risk of relapse after surgical resection and after drug treatment. This is particularly important for the high relapse risk population of MYC and TYR subtypes, which are the subtypes enriched in macrophages and six-factor secretomes.

[0336] In summary, the inventors of the present disclosure have discovered that a macrophage-derived secretome enables cancer cell proliferation in a nutrient-deficient microenvironment within the cancer cell microenvironment of pediatric embryonal brain tumors (ATRT) during early tumor development. This secretome is comparable to standard growth medium in preventing cancer cell death and significantly maintains a critical mass of cancer cells during periods of nutrient stress. Specific molecular subtypes of ATRT exhibit a secretome enrichment pattern that matches that of macrophages. Subtypes at high risk of relapse were found to be enriched in both the secretome and macrophages. The results of this disclosure reveal for the first time a previously unexplored role for a unique macrophage secretome in providing an alternative energy source to sustain cancer cell survival when nutrients are depleted, as well as its impact on recurrent subtypes. Furthermore, the secretome alters the response of ATRT cells to drugs. Clearly, the presence of the secretome reduces the efficacy of OTSSP167 and prevents cancer cell death during early tumor formation, thereby providing a pro-survival microenvironment that rescues drug-affected cells during early drug exposure. Drugs that are screened to be effective against cancer cells in standard culture medium may not be equally effective in the secretome phenotype of a patient's tumor. Surprisingly, the secretome prevented tumor cell death for a long time in both an invasive tumor model and a cerebrospinal fluid dissemination model, suggesting a role in tumor drug resistance and recurrence. The inventors of the present disclosure discovered that tumor cells that are normally grown in neurospheres in standard growth medium, when instead grown in secretomes, rearranged themselves after 24 hours in vitro to form interwoven network structures that linearly connected cells with long-range radii in vitro. This observation suggests that during periods of nutrient stress or nutrient deprivation, crosstalk exists between cells in the secretome microenvironment, which is critical for tumor cells to survive and maintain stress resistance in the absence of a stable and continuous nutrient supply. Furthermore, when treated with OTSSP167, tumor cells maintained these interwoven structures in the secretome, suggesting a potential mechanism of drug resistance. Therefore, the secretome of the present disclosure can be used to identify drug resistance in cells that respond to drug treatment.

[0337] Compared to standard culture medium, diseased cells (such as medulloblastoma cells) may be more sensitive to drugs in the presence of secretomes. In response to OTSSP167, neurosphere CHLA01 (primary tumor cells) and CHLA01R (recurrent tumor cells) had higher survival rates, while Dao7 and D341 medulloblastoma cells had higher cell death rates in secretomes than in standard culture medium. In response to Ispinesib, D341, CHLA-01, and CHLA-01R had higher survival rates in secretomes than in standard culture medium. In addition, Figures 37A-37CIt was shown that CHLA-02 cells experienced more cell death when OTSSP167 was used in the secretome compared to standard media conditions. Figures 38A-38C It was shown that BT-37 cells experienced more cell death when OTSSP167 was used in the secretome compared to standard media conditions.

[0338] The present disclosure shows a summary of metabolomics studies utilizing non-targeted Orbitrap assays (Figures 47-50). Data was analyzed using MetaboAnalyst 6.0 software. Sample 1 included CHLA01 grown in standard media, and sample 2 included CHLA01 grown in secretome. Three replicates were performed for CHLA01 grown in standard media compared to three replicates for CHLA01 grown in secretome (total of six experiments). Part 1 analysis included using the full list of metabolites (all) that appeared in the six experiments described above (without expression values), using pathway metabolite group libraries: (1) SMPDB - Small Molecule Pathway Database (99 metabolite groups based on normal human metabolic pathways). The top 25 enriched metabolite groups indicated that both CHLA01 tumor cells cultured in secretome and standard media were enriched in methylthiohistidine metabolism. Part 2 analysis included using upregulated or downregulated metabolites detected in tumor cells (CHLA01) cultured in secretome for 24 hours compared to tumor cells cultured in standard media for 24 hours, which were generated in the experiments of the present disclosure (3 replicates for each of the two samples), using pathway metabolite group libraries: (1) SMPDB - Small Molecule Pathway Database (99 metabolite groups based on normal human metabolic pathways), (2) KEGG (80 metabolite groups based on KEGG human metabolic pathways (December 2023)), and (3) Drug-Related library (461 metabolite groups based on drug pathways from SMPDB).

[0339] Upregulated pathways in the SMPDB database included biotin metabolism (top 1 pathway with an enrichment ratio > 25), taurine and hypotaurine metabolism (top 2 pathways with an enrichment ratio > 15), and ammonia cycle pathway (enrichment ratio > 10). Downregulated pathways in the SMPDB database included methylthiohistidine metabolism (enrichment ratio > 12). Upregulated pathways in the KEGG database included taurine and hypotaurine metabolism (top 1 pathway with an enrichment ratio > 25) and biotin metabolism (top 2 pathways with an enrichment ratio > 20). Downregulated pathways in the KEGG database included: valine, leucine, and isoleucine biosynthesis (top 1 pathway with an enrichment ratio > 25), phenylalanine, tyrosine, and tryptophan biosynthesis (top 1 pathway with an enrichment ratio > 25). Pathways that appeared in the upregulated drug pathways in the SMPDB database included amikacin pathway.

[0340] Thus, important metabolic pathways emerging from the metabolomics study include methyl group histidine metabolism, biotin metabolism, taurine and hypotaurine metabolism, etc. Methyl group histidine metabolism emerged as an important metabolic pathway when combining the metabolite lists of two tumor cells (CHLA01) grown in secretome and standard media. Methyl group histidine is known to be associated with cancer cachexia, suggesting that the secretome reprograms cancer cell metabolism. In the actual patient tumor environment, the secretome microenvironment can produce metabolites that promote weight loss in cancer patients (cancer cachexia) by altering metabolic / nutrient utilization. In vitro anticancer drug screening, if it can identify drugs that downregulate methyl group histidine metabolism in cancer cells (in the secretome microenvironment), will not only slow down the patient's cancer progression, but also avoid the patient from suffering from cancer cachexia. If anticancer drug screening is only performed on standard media, metabolites that change in the secretome (such as methyl group histidine) will be missed. Therefore, the secretome as a companion drug development tool will advantageously provide this additional important parameter for identifying effective drugs that can avoid patients from developing cancer cachexia. The data of the present disclosure show that methyl group histidine metabolism (enrichment ratio > 12) is downregulated in tumor cells (CHLA01) grown in secretome compared to standard media. This can indicate that cancer cells in a state of nutrient deficiency (in cachexia patients with low muscle reserves) can switch to utilizing the secretome for nutritional support and continue tumor growth.

[0341] Biotin metabolism is more abundant in tumor cells (CHLA01) grown in secretome compared to standard media. Biotin has been shown to be more abundant in tumor tissue than in non-tumor tissue. Taurine and hypotaurine metabolism is enriched in tumor cells (CHLA01) grown in secretome compared to standard media. This pathway is associated with glioma and childhood brain tumors. Targeted drugs effective in secretome become an important and attractive strategy.

[0342] Significant translation of metabolomic study data / clinical implications

[0343] A. Methyl group histidine metabolism emerged as an important metabolic pathway when combining the metabolite lists of both tumor cells (CHLA01) grown in secretome and standard media.

[0344] Methionine is known to be associated with cancer cachexia, suggesting that the secretome reprograms the metabolism of cancer cells. In the actual patient tumor environment, the secretome microenvironment can produce metabolites that promote weight loss in cancer patients (cancer cachexia) by altering metabolic / nutrient utilization. In vitro anticancer drug screening can not only slow the progression of cancer in patients, but also avoid patients from developing cancer cachexia if drugs that downregulate methionine metabolism in cancer cells (in the secretome microenvironment) can be identified. If anticancer drug screening is performed only on standard media, metabolites that are altered in the secretome (such as methionine) will be missed. Thus, the secretome as a companion drug development tool will advantageously provide this additional important parameter to identify effective drugs that can avoid patients from developing cancer cachexia. The data of the present disclosure show that methionine metabolism (enrichment ratio > 12) is downregulated in tumor cells (CHLA01) grown in the secretome compared to standard media. This can suggest that cancer cells in a state of nutrient deficiency (in cachexia patients with low muscle reserves) can switch to utilize the secretome for nutritional support to continue tumor growth. Thus, effective targeted drugs in the secretome become an important and attractive strategy.

[0345] B. Biotin metabolism is enriched in tumor cells (CHLA01) grown in the secretome compared to standard media. Biotin levels have been shown to be higher in tumor tissue than in non-tumor tissue, which is associated with overexpression of biotin receptors.

[0346] Cancer cells appear to hijack biotin metabolism to maintain their proliferation. These observations also motivated efforts to develop biotin-based cancer therapeutic drug delivery systems. The enrichment of biotin metabolism in CHLA01 grown in the secretome also suggests that the ability of cancer cells to survive and proliferate in the secretome (and the secretome phenotype of patient tumors) is enhanced and potentiated, as described in the present disclosure.

[0347] Biotin is a water-soluble vitamin essential for all living organisms as it plays a crucial role in carboxylation reactions. In non-cancerous cells, the main function of biotin is as a coenzyme for biotin-dependent carboxylases, including acetyl-CoA carboxylase 1 (ACC1), ACC2, methylcrotonyl-CoA carboxylase 1 (MCCC1), propionyl-CoA carboxylase (PCC), and pyruvate carboxylase (PC), which play key roles in fatty acid metabolism, gluconeogenesis, and amino acid catabolism. These carboxylases are synthesized in an inactive form (apocarboxylases) and require activation by biotinylation via holocarboxylase synthetase (HLCS). Subsequently, biotin must be released from the holocarboxylases, which requires catalysis by biotinidase. Although less well understood, histones can also be biotinylated by HLCS, and the levels of biotinylated histones can influence cell proliferation, epigenetic, and gene expression changes. As expected, cancer cells appear to hijack biotin metabolism to sustain their proliferation. Biotin levels are higher in tumor tissue than in non-tumor tissue, which is associated with overexpression of biotin receptors. These observations have also motivated efforts to develop biotin-based cancer drug delivery systems. Given the ubiquitous and critical role of regulated biotin metabolism in nature, targeting biotin regulation in a dysregulated pathway can be a potential approach to inhibit GBM.

[0348] The dependence of GBM on biotin distribution suggests that rational co-targeting of biotin-dependent metabolic and epigenetic pathways can be explored to eliminate GSCs. Biotin is a water-soluble vitamin essential for all living organisms as it plays a crucial role in carboxylation reactions. Although the metabolism of biotin and its role in intermediary metabolism have been well established, biotin remains one of the least understood water-soluble vitamins in terms of its nutritional requirements and responsiveness to physiological and pharmacological states. In recent years, significant progress has been made in understanding biotin nutrition through the description of biotin turnover kinetics and regulatory mechanisms and the improvement of methods for biotin status assessment. In addition, the potential role of biotin in gene expression regulation has been further recognized through the description of gene expression changes upon biotin deficiency and new descriptions of biotinidase activity.

[0349] C. Taurine and Hypotaurine metabolism is enriched in secreted proteome in tumor cells (CHLA01) grown in comparison to standard media. This pathway is associated with glioma and childhood brain tumors.

[0350] Cryopreservation of cells

[0351] The inventors of the present disclosure found that the secretome has an additional function of cell cryopreservation (Figure 51), which is a new alternative method that is not inferior or superior to the cell cryopreservation method based on standard medium (traditional method). The inventors of the present disclosure made a cryopreservation medium using 90% secretome and 10% DMSO. CHLA01R cells were frozen using a cryopreservation medium made of 90% 6-factor secretome and 10% DMSO. The inventors of the present disclosure froze 2.49 million live cells (viability of 63%) in 1.9 ml of a cryopreservation medium made of 90% secretome and 10% DMSO, put into a programmed cooling box (Mr Frosty), placed at -80 degrees Celsius, and then transferred to liquid nitrogen within 24 hours, which is the standard protocol for cryopreservation. The inventors of the present disclosure took out the cells after 65 hours, and the total cell count was slightly higher than that at the time of freezing, 27 million cells (51% survival rate). About 10% loss of viability was similar to the results of our standard medium-based cryopreservation medium using CHLA01R cells, and it can even be superior to the latter. In addition, the cells were taken out after 188 hours, and the total cell count was higher than that at the time of freezing, 30 million cells (47% survival rate). About 15% loss of viability was similar to the results of our standard medium-based cryopreservation medium using CHLA01R cells, and it can even be superior to the latter. Interestingly, during the distribution process (room temperature) / freezing process using a secretome-based cryopreservation medium, cells seem to be able to maintain or even possibly recover viability, which does not usually occur with standard medium-based cryopreservation medium. Usually, the total number of live cells decreases after going through the harsh cryopreservation process of freezing-thawing-removal. Therefore, the freezing medium made of 90% secretome and 10% DMSO is comparable to, or even possibly superior to, the freezing medium made of standard medium and 10% DMSO.

[0352] Conceptual advances / clinical relevance: The strategy of the present disclosure has important clinical implications. Success in many preclinical studies has not been matched with equivalent success in clinical trials. This novel macrophage secretome provides a superior ecosystem that offers an alternative energy source for the rapid growth of tumors during periods of nutrient stress. The inventors of the present disclosure found that drugs that show efficacy in vitro in standard growth media (traditional drug testing methods) have reduced efficacy when tested on the same cell lines in secretome screening. Some patient tumors are rich in secretome, while in vitro drug testing conditions are nutrient-rich and lack secretome. This highlights the gap in translating in vitro effective drugs into clinical trial processes, i.e., the need for a more accurate match to patient tumors that are rich in secretome and can respond less well to certain drugs has not been met. This problem is particularly pronounced in solid tumors: the growth and survival of rapidly expanding solid tumors requires a continuous supply of oxygen and nutrients, which needs to be maintained by the tumor neovasculature. When these nutrient supplies are insufficient, the presence of the macrophage secretome can provide the required environment as an immediate alternative energy source to rescue and sustain tumor cells that are distanced from the blood supply. Thus, tumor cells can survive for a period of time before the new nutrient supply enriches the microenvironment through newly formed tumor neovasculature. Recurrence is one of the main causes of cancer death. The ability of the macrophage secretome to proliferate residual tumor cells during disease recurrence will be an important mechanism of tumor recurrence. BRIEF DESCRIPTION OF DRAWINGS

[0353] Those of ordinary skill in the art will be better able to understand and more readily comprehend the exemplary embodiments of the present disclosure after review of the following discussion together with the accompanying drawings. The exemplary embodiments do not necessarily indicate the scope of the present disclosure, which is defined only in the appended claims.

[0354] Figure 1A Immunohistochemical staining of ATRT tumors with CD163 monoclonal antibody shows morphologically that CD163 is expressed on macrophages but not tumor cells. The macrophage-rich compartment indicated by the arrow has a high density of macrophages (dark cells stained by CD163 antibody), and the arrow indicates nesting at the tumor boundary. Normal brain tissue (control) has almost no macrophage infiltration.

[0355] Figure 1BIntra-tumoral heterogeneity of macrophage (dark cells stained with CD163 antibody) infiltration within each single patient tumor (patients 1-4) showed that stroma was significantly, densely infiltrated by macrophages compared to tumor compartments (p=0.022, paired t-test). An expanded independent validation cohort showed similar trends of immunohistochemical findings of macrophage infiltration in multiple types of mixed childhood brain tumors Figure 13 Macrophages formed distinct perivascular rings, suggesting an origin related to circulating myeloid cells in patient 4.

[0356] Figure 1C A schematic diagram showing the strategies of studying macrophage-infiltrated patient tumors, including Strategy 1: molecular analysis of dissected regions of macrophages in patient tumors, and Strategy 2: single-cell sequencing of individual macrophages in patient tumors. Challenges of Strategy 1 include missing infiltrating macrophages scattered in patient tumors, while challenges of Strategy 2 include: (1) high cost of sequencing a large number of single cells; (2) data limited by the number of sequenced cells (cost limitation); and (3) ensuring that the sequenced single-cell population is well representative. A common problem of Strategy 1 and Strategy 2 is that both strategies require separating macrophage microenvironment compartments from tumor compartments at a single time point, thus losing the opportunity to study in situ real-time dynamics between tumor and macrophage compartments.

[0357] Figure 2A A schematic diagram showing an in vitro system using CD11b+ human myeloid-derived cells to obtain a six-factor secretome.

[0358] Figure 2B A schematic diagram / footprint showing three conditions of macrophage-tumor microenvironment established in vitro: (1) tumor cytokines, (2) CD11b+ cytokines, (3) CD11b+ and tumor cell co-culture factors. 36 cytokine-chemokine array analysis of the above-conditioned media and co-culture supernatants demonstrated a six-factor cytokine enrichment pattern associated with CD11b+ macrophages in the microenvironment. The presence of tumor cells enhanced the production of specific cytokine-chemokines (CCL2 / MCP-1, MIP-1a / MIP-1b, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8) by CD11b+ cells.

[0359] Figure 2CThe shown heatmap demonstrates 6-factor secretome enrichment in patient tumors compared to normal brain tissue and tumor cell lines in a discovery set of 28 samples (RNA sequencing), which includes 10 patient tumors, 8 patient-derived cell lines and 10 controls (child and fetal normal brain tissue). The enrichment pattern of the expanded 36 cytokine-chemokine panel (candidates on the cytokine array platform) recapitulates the 6-factor secretome pattern. According to the heatmap, ATRT patient tumors are upregulated, while normal brain controls and ATRT tumor cell lines are downregulated.

[0360] Figure 2D The shown heatmap demonstrates 6-factor secretome enrichment in patient tumors of specific ATRT molecular subtypes (MYC > TYR > SHH) in a validation set of 49 patient ATRT tumors classified by molecular subtype (GSE70678; Affymetrix U133 plus 2.021). The enrichment pattern of the expanded 36 cytokine-chemokine panel (candidates on the cytokine array platform) recapitulates the 6-factor secretome enrichment pattern in the three ATRT molecular subtypes (MYC > TYR > SHH) and is evident in patient ATRT tumors in both Figure 2C (discovery set) and Figure 2D (validation set). According to the heatmap, MYC-ATRT is highly upregulated, TYR-ATRT is upregulated, while SHH-ATRT is downregulated.

[0361] Figure 3A The shown dot plot shows expression of CD163 (M2 macrophages) and CD1 1 b / ITGAM (total macrophages) in the discovery set (n=28) classified by molecular subtype.

[0362] Figure 3B The shown dot plot shows expression of CD163 (M2 macrophages) and CD1 1 b / ITGAM (total macrophages) in the validation set (n=49) classified by molecular subtype. Patient tumors are enriched for CD1 1 b / ITGAM (pan-macrophages) and CD163 (M2 macrophages), but not in tumor cell lines (Student's T-test. **: p<0.005, NS: not significant). CD1 1 b expression is 1 12-fold higher in patient tumors compared to cell lines (patient tumors: cell lines), and CD163 expression is 1083-fold higher (Figure 17).

[0363] Figure 3C The shown dot plot shows expression of CD163 (M2 macrophages) and CD1 1 b / ITGAM (total macrophages) in the validation set (n=49) classified by molecular subtype. Patient tumors are enriched for CD1 1 b / ITGAM (pan-macrophages) and CD163 (M2 macrophages), but not in tumor cell lines (Student's T-test. **: p<0.005, NS: not significant). CD1 1 b expression is 1 12-fold higher in patient tumors compared to cell lines (patient tumors: cell lines), and CD163 expression is 1083-fold higher (Figure 17). Figure 3A (discovery set) and Figure 3BFigure 6. Correlation plot of total macrophage marker (CD11b / ITGAM) with M2 macrophage associated marker (CD163) in patient tumors, patient-derived ATRT tumor cell lines, and normal brain controls. Macrophage markers of different subsets correlate well in patient tumors, but not significantly in tumor cell lines or normal brain tissue. Pearson correlation (p-value < 0.05 and R 2 >0.6) indicates that the two genes are highly positively correlated in gene expression. Both MYC-ATRT and TYR-ATRT are macrophage-rich tumors, matching the 6-factor secretion proteome-enriched subtype. SHH-ATRTs are low in macrophage content and also less enriched in the 6-factor secretion proteome.

[0364] Figure 3D Figure 7. Graph showing that tumors exhibiting an M2 macrophage-enriched phenotype (CD163+) are typically MYC-ATRT and TYR-ATRT.

[0365] Figure 3E Figure 8. Bar graph showing that tumors with high CD163 expression are significantly enriched in pathways related to dendritic cell maturation pathway and complement system (positive z-score, see Methods section).

[0366] Figure 4A and Figure 4B Figure 19. Bar graph showing the growth-promoting effect of each in vitro microenvironment condition medium (derived from basal medium RPMI) on five patient-derived ATRT cell lines (CHLA-04, CHLA-02, CHLA-05, CHLA-06, CHLA-266) and one patient-derived xenograft cell line (BT-37) at days 0-3, and compared to basal medium RPMI control condition. Figure 4A Figure 20. Shows supernatant derived from CD11b+ cells (microenvironment 1). Figure 4B Figure 21. Shows supernatant derived from CD11b+ cells co-cultured with tumor cells (microenvironment 2). Supernatant derived from tumor cells (microenvironment 3) is shown in Figure 18. Two cell lines (CHLA-02 and BT-37) exhibit higher proliferation rates in CD11b+ conditioned medium and CD11b+-tumor cell co-cultured supernatant compared to other cell lines.

[0367] Figure 4C and Figure 4DBar graph showing that cancer cells can utilize this secretome to sustain their proliferation during a resource-limited, nutrient-deficient state. The secretome derived from CD11b+ macrophages co-cultured with tumor cells (CHLA-02 and BT-37) provided a more sustained tumor proliferation effect compared to the secretome derived from CD11b+ cells alone (actual p-values ​​are shown in Figure 39).

[0368] Figure 4E Flow cytometry using AnV / PI was shown to compare cell death between standard growth medium and the six-factor secretome ( FIG. 36 ).

[0369] Figure 4F Micrographs (magnification 4x, 10x, 20x) show that after 24 hours of nutrient stress, tumor cells rearranged themselves in the 6-factor secretome to form extensive, interwoven network structures connecting cells over long radiuses (CHLA-02 in T75 flasks), in contrast to growing in clusters during nutrient-rich conditions (standard growth medium).

[0370] Figure 4G The large image micrograph shown captures a large area of ​​tumor cells (CHLA-02) grown in a T75 flask, demonstrating that the tumor cells exhibit a unique interwoven network structure with linear arrangements of six secretome factors (arrows, white irregular lines; linear pattern), in contrast to clusters of tumor cells grown in standard growth medium (white circles) ( Figure 13 ). Click to enlarge Figure 12B The “+” sign on the right shows the linear network structure of tumor cells. The inset (boxed area) has been enlarged to show a local magnified view.

[0371] Figure 4H The schematic shown depicts a four-fold mechanism of the secretome that can (1) induce a rapid early growth spurt and (2) prevent tumor cell death during nutrient stress, while (3) inhibiting the drug response of tumor cells and maintaining a stable interwoven network of tumor cells upon drug exposure, providing a powerful advantage for tumor cell stress tolerance and treatment resistance.

[0372] Figure 5AA schematic and plot showing that Maternal embryonic leucine zipper kinase (MELK) is a common target for 3 ATRT subtypes. Dot plot showing the expression of MELK in patient tumors, tumor cell lines and normal brain tissue controls (fetal and pediatric) in the discovery set (RNA sequencing, n=28) and validation set (Affymetrix U133 plus 2.0, n=49). Student T-test. *: p<0.05, **: p<0.005. (Figure 25). OTSSP167 is a cell cycle inhibitor against MELK (in phase 1 / 2 trial in adult cancers) for targeting tumor compartments commonly found in patient tumors and tumor cell lines. Bar graph showing qRT-PCR validation of MELK in ATRT cell lines Figure 25A

[0373] Figure 5B A plot showing the dose response effect of OTSSP167 on six ATRT cell lines over 13 days. OTSSP167 is effective in the nanomolar range Figure 26

[0374] Figure 5C and Figure 5D Flow cytometry or western blot data showing OTSSP167 induced apoptotic cell death in ATRT cells. Flow cytometry analysis of apoptotic cell death (annexin V+PI-) and cell cycle analysis of CHLA-02 (day 4 IC50 dose - 20.76 nM) and BT-37 (day 4 IC50 dose - 70.42 nM) treated with OTSSP167. Immunoblotting demonstrates increased p-histone H2A.X as CHLA-02 and BT-37 cells are treated with OTSSP167 for 24, 48 and 72 hours, suggesting OTSSP167 induces DNA damage. c-PARP also increases with OTSSP167 treatment, supporting activation of intrinsic apoptotic pathways.

[0375] Figure 5E The plot and numbers shown demonstrate that in the unmedicated state (DMSO-vehicle control), the 6-factor secretome elicits a rapid growth surge, in contrast to the gradual increase in tumor proliferation promoted by standard growth media. In the presence of drug (OTSSP167), inhibition of rapid growth is observed in standard growth media, in contrast to the dampened drug response in the secretome microenvironment. OTSSP167 is less efficacious in the 6-factor secretome compared to standard growth media. (*: p<0.005, **: p<0.0005, NS: not significant). Actual p-values are shown in Figure 39.

[0376] Figure 5F ​​The graph shown demonstrates that overall survival of animals was significantly improved with OTSSP167 treatment in a patient-derived orthotopic xenograft (PDOX) model from an aggressive autopsy (p=0.032, log-rank test).

[0377] Figure 5G Flow cytometry using AnV / PI is shown comparing cell death in the 6-factor secretome of OTSSP167 treated BT-37 and CHLA (Fig. 37, Fig. 38). OTSSP167 treated BT-37 cells experienced more cell death in the secretome than CHLA-02 cells after 24-48 hours.

[0378] Figure 5H Micrographs (10x magnification) are shown: in contrast to tumor cells (CHLA-02) that split into smaller clusters when treated with OTSSP167 in standard growth media, tumor cells treated with OTSSP167 in the secretome maintained their interwoven network structure, suggesting a potential mechanism of therapeutic resistance provided by the secretome.

[0379] Figure 6 A graphical summary is shown that schematically depicts the significance of the studies of the present disclosure in drug screening and patient relapse.

[0380] Figure 7A A graph of patient tumors (discovery set) is shown that are enriched for TREM2 and expression of TREM2 follows the trend of CD11b / ITGAM (pan-macrophages) and CD163 macrophages (M2 macrophages), but not tumor cell lines. TREM2 expression in patient tumors is 12572-fold higher than cell lines (Student's T-test. **: p<0.005) and CD206 expression is 141-fold higher (Student's T-test. **: p<0.005) compared to cell lines. TREM2 expression on control normal brain tissue is low, similar to CD11b / ITGAM and CD163.

[0381] Figure 7B A graph of TREM2 expression in 3 ATRT subtypes (validation set) is shown with median ranges between 6.8-7.6, with significantly reduced variability between subtypes compared to CD11b (median range 5-6.6, Figure 3A ) and CD163 (median range 7.6-10.2).

[0382] Figure 7C A graph is shown where CD206 expression on RNA-seq (discovery set) is overall lower than TREM2, but follows a similar overall trend as TREM2.

[0383] Figure 7D A plot showing CD206 expression in the 3 ATRT subtypes (validation set) is shown, where CD206 is enriched to a greater extent in MYC-ATRT and TYR-ATRT than in SHH-ATRT. A similar trend is observed in CD11b / ITGAM and CD163 Figure 3B

[0384] Figure 8A A plot showing the correlation of CD206 with the macrophage marker CD11b / ITGAM in patient tumors, patient-derived ATRT tumor cell lines, and normal brain tissue controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. Correlation of different subpopulation of macrophage markers with CD206 is low on the RNA-sequencing platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0385] Figure 8B A plot showing the correlation of CD206 with the macrophage marker CXCL10 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain tissue controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. Correlation of different subpopulation of macrophage markers with CD206 is low on the RNA-sequencing platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0386] Figure 8C A plot showing the correlation of CD206 with the macrophage marker TREM2 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain tissue controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. Correlation of different subpopulation of macrophage markers with CD206 is low on the RNA-sequencing platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0387] Figure 8D A plot showing the correlation of CD206 with the macrophage marker CD68 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain tissue controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. Correlation of different subpopulation of macrophage markers with CD206 is low on the RNA-sequencing platform. Pearson correlation (p-value < 0.05 and R 2 ​>0.6) indicates that the two genes are highly positively correlated in gene expression.

[0388] Figure 8E A plot showing the correlation of CD206 with macrophage marker CD163 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain tissue controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. On the RNA-sequencing platform, the correlation of different subpopulation macrophage markers with CD206 was low. Pearson correlation (p-value < 0.05 and R 2 >0.6) indicates that the two genes are highly positively correlated in gene expression.

[0389] Figure 9A A plot showing the correlation of CD206 with macrophage marker CD68 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0) is shown. On the Affymetrix U133 plus 2.0 platform, the correlation of CD206 with CD163 was very good (R 2 = 0.8), while other macrophage markers (i.e., CD68, CXCL10, CDl lb / ITGAM) of various subpopulations had a poor correlation with CD206. Pearson correlation (p-value < 0.05 and R 2 >0.6) indicates that the two genes are highly positively correlated in gene expression.

[0390] Figure 9B A plot showing the correlation of CD206 with macrophage marker CD163 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0) is shown. On the Affymetrix U133 plus 2.0 platform, the correlation of CD206 with CD163 was very good (R 2 = 0.8), while other macrophage markers (i.e., CD68, CXCL10, CDl lb / ITGAM) of various subpopulations had a poor correlation with CD206. Pearson correlation (p-value < 0.05 and R 2 >0.6) indicates that the two genes are highly positively correlated in gene expression.

[0391] Figure 9C A plot showing the correlation of CD206 with macrophage marker CXCL10 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0) is shown. On the Affymetrix U133 plus 2.0 platform, the correlation of CD206 with CD163 was very good (R 2= 0.8), while other macrophage markers of various subpopulations (i.e., CD68, CXCL10, CDl lb / ITGAM) had a poor correlation with CD206. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0392] Figure 9D A plot showing the correlation of CD206 with macrophage marker CDl lb / ITGAM in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0) is shown. On the Affymetrix U133 plus 2.0 platform, CD206 had a very good correlation with CDl lb / ITGAM (R 2 = 0.8), while other macrophage markers of various subpopulations (i.e., CD68, CXCL10, CDl lb / ITGAM) had a poor correlation with CD206. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0393] Figure 10A A plot showing the correlation of TREM2 with macrophage marker CD68 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. On the RNA-sequencing platform, CDl lb / IGTAM had a very good correlation with TREM2 (R 2 = 0.83), while other macrophage markers of various subpopulations (i.e., CD68, CXCL10, CD163) had a poor correlation with TREM2. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0394] Figure 10B A plot showing the correlation of TREM2 with macrophage marker CD68 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. On the RNA-sequencing platform, CDl lb / IGTAM had a very good correlation with TREM2 (R 2 = 0.83), while other macrophage markers of various subpopulations (i.e., CD68, CXCL10, CD163) had a poor correlation with TREM2. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0395] Figure 10C A plot of TREM2 correlation with macrophage marker CD 11 b / ITGAM in patient tumors, patient-derived ATRT tumor cell lines, and normal brain controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. CD 11 b / IGTAM has a very good correlation with TREM2 (R 2 = 0.83) on the RNA-sequencing platform, while other macrophage markers (i.e., CD68, CXCL10, CD163) of various subsets have a poor correlation with TREM2. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0396] Figure 10D A plot of TREM2 correlation with macrophage marker CD163 in patient tumors, patient-derived ATRT tumor cell lines, and normal brain controls in the discovery set (RNA-sequencing: patient tumors, tumor cell lines, normal brain tissue) is shown. CD 11 b / IGTAM has a very good correlation with TREM2 (R 2 = 0.83) on the RNA-sequencing platform, while other macrophage markers (i.e., CD68, CXCL10, CD163) of various subsets have a poor correlation with TREM2. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0397] Figure 11A A plot of TREM2 correlation with macrophage marker CD68 in patient tumors of 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0) is shown. TREM2 has some correlation with CD 11 b / ITGAM (R 2 = 0.58), with similar trend on Affymetrix U133 plus 2.0 (Figure 10), but with a poor correlation. TREM2 also has some correlation with CD68 (R 2 = 0.57). Other macrophage markers (i.e., CXCL10, CD163, CD206) of various subsets have a poor correlation with TREM2 on the Affymetrix U133 plus 2.0 platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0398] Figure 11BFigure 10 shows a plot of the correlation of TREM2 with macrophage marker CD206 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0). TREM2 has some correlation with CD11b / ITGAM (R 2 = 0.58), with similar trend on Affymetrix U133 plus 2.0 (Figure 10), but less correlation. TREM2 also has some correlation with CD68 (R 2 = 0.57). Other macrophage markers (i.e., CXCL10, CD163, CD206) have less correlation with TREM2 across subgroups on the Affymetrix U133 plus 2.0 platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0399] Figure 11C Figure 11 shows a plot of the correlation of TREM2 with macrophage marker CD163 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0). TREM2 has some correlation with CD11b / ITGAM (R 2 = 0.58), with similar trend on Affymetrix U133 plus 2.0 (Figure 10), but less correlation. TREM2 also has some correlation with CD68 (R 2 = 0.57). Other macrophage markers (i.e., CXCL10, CD163, CD206) have less correlation with TREM2 across subgroups on the Affymetrix U133 plus 2.0 platform. Pearson correlation (p-value < 0.05 and R 2 > 0.6) indicates that the two genes are highly positively correlated in gene expression.

[0400] Figure 11D Figure 12 shows a plot of the correlation of TREM2 with macrophage marker CXCL10 in patient tumors of the 3 ATRT subtypes in the validation set (Affymetrix U133 plus 2.0). TREM2 has some correlation with CD11b / ITGAM (R 2 = 0.58), with similar trend on Affymetrix U133 plus 2.0 (Figure 10), but less correlation. TREM2 also has some correlation with CD68 (R 2=0.57). Other macrophage markers of various subsets (i.e., CXCL10, CD163, CD206) were less correlated with TREM2 on the Affymetrix U133 plus 2.0 platform. Pearson correlation (p value < 0.05 and R 2 >0.6) indicated that the two genes were highly positively correlated in gene expression.

[0401] Figure 11E Figure 2 shows the correlation between TREM2 and the macrophage marker CD11b / ITGAM in patient tumors of three ATRT subtypes in the validation set (Affymetrix U133 plus 2.0). TREM2 has a certain correlation with CD11b / ITGAM (R 2 =0.58), and the trend on Affymetrix U133 plus 2.0 was similar (Figure 10), but the correlation was poor. TREM2 also had a certain correlation with CD68 (R 2 =0.57). Other macrophage markers of various subsets (i.e., CXCL10, CD163, CD206) were less correlated with TREM2 on the Affymetrix U133 plus 2.0 platform. Pearson correlation (p value < 0.05 and R 2 >0.6) indicated that the two genes were highly positively correlated in gene expression.

[0402] Figure 12A and Figure 12C Shown are microscopic images of CHLA-02 cells taken after 24 hours of incubation in standard growth medium. Tumor cells grown in standard medium formed clusters of various sizes (circles), while tumor cells grown in the 6-factor secretome ( Figure 12B and 12D ) form interwoven reticular filamentous chains, with cells arranged linearly (irregular white lines). Click to enlarge Figure 12B The “+” on the right shows a linear reticular pattern of tumor cells. The inset (white boxed area) has been enlarged to show a detailed view (2.6 mm x 2.07 mm flask area). Figure 12C Data collected using a fluorescence microscope are shown: 4 macromicrographs were collected per flask at each time point (24 hours and 48 hours). Each macromicrograph covered an area of ​​1.36 cm x 1.08 cm of the flask. The orientation of the captured micrographs was in the counterclockwise order shown in the following frames 1, 3, 4, and 2. Each macromicrograph consisted of 324 (18×18) smaller micrographs that were stitched together by the microscope with a 10% overlap. Each macromicrograph = a total of 324 smaller micrographs stitched together with a 10% overlap.

[0403] Figure 12B and Figure 12D Microscope pictures of CHLA-02 taken after 24 hours of incubation in the 6-factor secretion proteome are shown. Tumor cells grown in standard media form clusters of various sizes (circles), while tumor cells grown in the 6-factor secretion proteome form interwoven, net-like, filamentous chains with cells arranged linearly (irregular white lines). Click on the "+" to view the linear, net-like pattern of tumor cells at higher magnification Figure 12B Figure 12D

[0404] Figure 12E Microscope pictures of CHLA-02 taken after 48 hours of incubation in the 6-factor secretion proteome are shown. Tumor cells grown in standard media form clusters of various sizes (circles), while tumor cells grown in the 6-factor secretion proteome form interwoven, net-like, filamentous chains with cells arranged linearly (irregular white lines). Click on the "+" to view the linear, net-like pattern of tumor cells at higher magnification Figure 12F

[0405] Figure 12F Microscope pictures of CHLA-02 taken after 48 hours of incubation in the 6-factor secretion proteome are shown. Tumor cells grown in standard media form clusters of various sizes (circles), while tumor cells grown in the 6-factor secretion proteome form interwoven, net-like, filamentous chains with cells arranged linearly (irregular white lines). Click on the "+" to view the linear, net-like pattern of tumor cells at higher magnification Figure 12F

[0406] Figure 12G ​​​​Microscope pictures of CHLA-02 taken after 48 hours of incubation in standard growth media are shown. Tumor cells grown in standard media form clusters of various sizes (circles), while tumor cells grown in the 6-factor secretome form interwoven, net-like, filamentous chains with cells in linear arrangement (irregular white lines). Click on the "+" for zoom Figure 12F on the linear, net-like pattern of tumor cells.

[0407] Figure 12H Microscope pictures of CHLA-02 taken after 48 hours of incubation in the 6-factor secretome are shown. Tumor cells grown in standard media form clusters of various sizes (circles), while tumor cells grown in the 6-factor secretome form interwoven, net-like, filamentous chains with cells in linear arrangement (irregular white lines). Click on the "+" for zoom Figure 12F on the linear, net-like pattern of tumor cells.

[0408] Figure 13 An immunohistochemical survey of CD163+M2 macrophage infiltration in 13 pediatric brain tumors from a single institution of multiple mixed types, including three histological brain tumor types, is shown. The inventors of the present disclosure found an enrichment of CD163-expressing macrophages in a large proportion of patient tumors across different histological types. The inventors of the present disclosure observed that not all patient tumors within each histological type exhibited high CD163 expression: two ATRT tumors in this cohort, one exhibited CD163hi expression and the other exhibited CD163lo, supporting our findings on the gene expression platform in Figure 3. This indicates that within a single histological type, patient tumors differ in macrophage infiltration.

[0409] Figure 14A Flow cytometry plots showing generation of CD11b+human myeloid-derived cells are shown. Unstimulated human myeloid-derived cells (U937) express little CD11b. U937 cells were stimulated with different cytokines / chemokines that are known to influence macrophages in the presence of PMA. Different combinations of proteins were tested on U937 and after PMA stimulation. IL-4 (arrow) induced the highest expression of CD11b, a pan-macrophage marker. The highest expression of CD11b, a pan-macrophage marker, was achieved using PMA and IL-4 (10 ng / ml or 20 ng / ml) (80-90%) Figure 2A PMA was tested with various cytokines to stimulate human myeloid-derived cells. The largest number of CD11b+cells was obtained with PMA + IL-4 stimulation.

[0410] Figure 14BFlow cytometry plots showing very low CD163 (M2 macrophage marker) expression.

[0411] Figure 15 Microscopy images showing growth morphology of a large panel of 7 patient tumor-derived ATRT cell lines and 1 patient-derived patient-derived orthotopic xenograft (PDOX) cell line of the disclosure. Of the 8 ATRT cell lines, CHLA-06 is the most aggressive and fastest growing in vitro phenotype of the panel of ATRT tumor models of the disclosure. ATRT95 grows too slowly to be suitable for in vitro experiments. Based on the assumption that the fastest growing in vitro cell line will provide / secret the most complete tumor-promoting factor profile / mix, the inventors of the disclosure selected CHLA-06 (the most aggressive ATRT tumor cell) from the panel of 7 ATRT cell lines of the disclosure to create the tumor compartment.

[0412] Figure 16A Graph showing zoomed-in view of the 6-factor secretome in the discovery set (RNA- sequencing, n=28). Tumors express higher levels of the 6-factor secretome. The probe for RANTES (CCL5) on the RNA-sequencing platform does not appear to work as well on RNA-sequencing.

[0413] Figure 16B Graph showing Affymetrix U133 plus 2.0 platform in the validation set, RANTES (CCL5) is expressed at higher levels in MYC-ATRT and TYR-ATRT compared to SHH-ATRT. Zoomed-in view of the 6-factor secretome in the ATRT validation set (GSE70678; Affymetrix U133 plus 2.0, n=49) by molecular subtype classification. MYC-ATRT and TYR-ATRT express higher levels of the 6-factor secretome, with the exception of CXCL8, which is similarly expressed in the 3 ATRT subtypes using the Affymetrix U133 plus 2.0 platform.

[0414] Figure 17A Graph showing correlation of the pan-macrophage marker CD11b (ITGAM) with M2 macrophage markers (CD163, CD68) in the discovery set (RNA-sequencing, n=28) and validation set (GSE70678; Affymetrix U133 plus 2.0, n=49). CD11b, CD163, and CD68 correlate well in tumor samples in the discovery set and validation set by molecular subtype classification (MYC-subtype, SHH-subtype, and TYR-subtype). In the discovery set, macrophage marker correlation is poor in cell lines and normal brain tissue controls (fetal and pediatric brain tissue).

[0415] Figure 17B Plots showing poor correlation of pan-macrophage marker CD11b (ITGAM) with M1 macrophage marker (CXCL10) in both discovery and validation sets. Poor correlation with normal brain tissue and cell lines.

[0416] Figure 17C Plots showing good correlation of M2 macrophage markers (CD163 and CD68) with each other in patient tumors in both discovery and validation sets.

[0417] Figure 17D Plots showing good correlation of M1 macrophage marker (CXCL10) with two M2 macrophage markers (CD163 and CD68) in patient tumors in the validation set. Poor correlation with cell lines and normal brain tissue in the discovery set.

[0418] Figure 17E Table showing comparison of gene expression of macrophage markers in the discovery and validation sets.

[0419] Figure 18A Plots showing that only 2 cell lines (CHLA-02 and BT-37) showed a significant increase in optical density (OD) readings over baseline OD readings for the 6-factor secretion proteome in all 6 ATRT cell lines studied. Supernatants derived from CD11b+ cells (A) and CD11b+ and tumor cell co-cultures (B) resulted in higher tumor cell proliferation compared to tumor cell cytokines alone. Figure 4A ) and CD11b+ and tumor cell co-cultures ( Figure 4B ) did not show a significant increase in OD readings over baseline OD readings for the 6-factor secretion proteome in all 6 ATRT cell lines studied. Supernatants derived from CD11b+ cells (A) and CD11b+ and tumor cell co-cultures (B) resulted in higher tumor cell proliferation compared to tumor cell cytokines alone.

[0420] Figure 18B Microscopy images showing that the conditioned media from cell lines, CD11b+ cells, or co-culture supernatants (CD11b+ cells + tumor cells) were free of cells. Scale bar: 100 μm, magnification: 10x.

[0421] Figure 19AA graph showing the minimal baseline optical density (OD) of the 6-factor secretome is shown. Inventors of the present disclosure compared the baseline absorbance of 20% (20ul) RPMI: 80% (80ul) 6-factor secretome and 40% (40uL) RPMI: 60% (60ul) 6-factor secretome (without tumor cells) and the difference was not statistically significant (p-value > 0.05, Welch unpaired T-test). Inventors of the present disclosure employed the former ratio for the assays of the present disclosure. Therefore, the absorbance (OD reading) in the proliferation assay using the 6-factor secretome is not attributed to the baseline absorbance of the secretome.

[0422] Figure 19B A graph showing macrophages that were not trypsin digested and trypsin digested macrophages is shown. Macrophages were harvested with or without trypsin digestion, replated and secretome harvested. The 6-factor secretome obtained from macrophages that were not trypsin digested induced CHLA-02 proliferation at the same seeding density (p-value < 0.05, Welch unpaired T-test) as the 6-factor secretome obtained from macrophages that were trypsin digested.

[0423] Figure 19C A graph showing that the 6-factor secretome harvested from increased macrophage seeding density did not result in higher CHLA-02 proliferation rate is shown. Macrophage seeding density was increased by 10% and 20% and treated with PMA + IL-4 for 48 hours. Macrophages were harvested at 110% density or 120% density in pure RPMI. Increasing macrophage seeding density did not result in any significant increase in CHLA-02 proliferation.

[0424] Figure 20A Microscopy images showing the chemotactic effect of the 6-factor secretome on CHLA-02 cultured in a T25 flask are shown. CHLA-02 cells grow as suspended clusters in standard growth media. CHLA-02 cells cultured in the 6-factor secretome form extensive, interwoven network structures that connect cells over long distance radii (filamentous chains) at 24 hours, rather than forming cell clusters. Scale bar: 100 pm, magnification: 4x.

[0425] Figure 20B Microscopy images showing the chemotactic effect of the 6-factor secretome on CHLA-02 cultured in a T25 flask are shown. CHLA-02 cells grow as suspended clusters in standard growth media. CHLA-02 cells cultured in the 6-factor secretome form extensive, interwoven network structures that connect cells over long distance radii (filamentous chains) at 48 hours, rather than forming cell clusters. Scale bar: 100 pm, magnification: 4x.

[0426] Figure 21A Microscopy images showing the chemoattractive effect of the 6-factor secretome on CHLA-02 cultured in a T75 flask. CHLA-02 cells grow as suspended clusters in standard growth media. CHLA-02 cells cultured in the 6-factor secretome form cell clusters at 4 hours. Scale bar: 100 pm, magnification: 4x.

[0427] Figure 21B Microscopy images showing the chemoattractive effect of the 6-factor secretome on CHLA-02 cultured in a T75 flask. CHLA-02 cells grow as suspended clusters in standard growth media. CHLA-02 cells cultured in the 6-factor secretome form extensive, interwoven network structures that connect cells over long distance radii (filamentous chains) at 24 hours, rather than forming cell clusters. Scale bar: 100 pm, magnification: 4x.

[0428] Figure 21C Microscopy images showing the chemoattractive effect of the 6-factor secretome on CHLA-02 cultured in a T75 flask. CHLA-02 cells grow as suspended clusters in standard growth media. CHLA-02 cells cultured in the 6-factor secretome form extensive, interwoven network structures that connect cells over long distance radii (filamentous chains) at 48 hours, rather than forming cell clusters. Scale bar: 100 pm, magnification: 4x.

[0429] Figure 22A Microscopy images showing the effect of incubating CHLA-02 cultured in a T75 flask in the 6-factor secretome for 4 hours, observed at various magnifications in a T75 flask. Replicate experiment: CHLA-02 cells grow as suspended clusters in standard growth media. At 4x magnification, CHLA-02 cells cultured in the 6-factor secretome form cell clusters at 4 hours. Scale bar: 100 pm.

[0430] Figure 22B Microscopy images showing the effect of incubating CHLA-02 cultured in a T75 flask in the 6-factor secretome for 4 hours, observed at various magnifications in a T75 flask. Replicate experiment: CHLA-02 cells grow as suspended clusters in standard growth media. At 10x and 20x magnification, CHLA-02 cells cultured in the 6-factor secretome form cell clusters at 4 hours. Scale bar: 100 pm.

[0431] Figure 23AMicroscopy images showing the chemoattractive effect of CHLA-02 incubated for 24 hours in the 6-factor secretion media observed at various magnifications in a T75 culture flask. Replicate experiment: CHLA-02 cells were grown in suspension in standard growth media. At 4x magnification, CHLA-02 cells cultured in the 6-factor secretion media formed extensive, interwoven network structures that connected cells over long distance radii after 24 hours. Scale bar: 100 pm.

[0432] Figure 23B Microscopy images showing the chemoattractive effect of CHLA-02 incubated for 24 hours in the 6-factor secretion media observed at various magnifications in a T75 culture flask. Replicate experiment: CHLA-02 cells were grown in suspension in standard growth media. At 10x and 20x magnification, CHLA-02 cells cultured in the 6-factor secretion media formed extensive, interwoven network structures that connected cells over long distance radii after 24 hours. Scale bar: 100 pm.

[0433] Figure 23C Microscopy images showing the chemoattractive effect of CHLA-02 incubated for 48 hours in the 6-factor secretion media observed at various magnifications in a T75 culture flask. Replicate experiment: CHLA-02 cells were grown in suspension in standard growth media. At 4x magnification, CHLA-02 cells cultured in the 6-factor secretion media formed extensive, interwoven network structures that connected cells over long distance radii after 48 hours. Scale bar: 100 pm.

[0434] Figure 23D Microscopy images showing the chemoattractive effect of CHLA-02 incubated for 48 hours in the 6-factor secretion media observed at various magnifications in a T75 culture flask. Replicate experiment: CHLA-02 cells were grown in suspension in standard growth media. At 10x and 20x magnification, CHLA-02 cells cultured in the 6-factor secretion media formed extensive, interwoven network structures that connected cells over long distance radii after 48 hours. Scale bar: 100 pm.

[0435] Figure 24A Microscopy images showing the effect of the 6-factor secretion media on CHLA-02 cultured in a T75 culture flask at longer time points. CHLA-02 cultured in the 6-factor secretion media at longer time points formed cell clusters as the filamentous chains of CHLA-02 cells became less pronounced (disintegrated) at 72 hours. Scale bar: 100 pm, magnification: 4x.

[0436] Figure 24B Microscopic images showing the effects of the six-factor secretome on CHLA-02 cells cultured in T75 flasks at longer time points. CHLA-02 cells cultured in the six-factor secretome formed cell clusters at longer time points, as filamentous chains of CHLA-02 cells became less pronounced (disassembled) by 96 hours. Scale bar: 100 μm, magnification: 4x.

[0437] Figure 24C Microscope images showing the effects of the six-factor secretome cultured in T75 flasks at higher magnification and longer time points. CHLA-02 cells cultured in the six-factor secretome formed cell clusters at longer time points, as filamentous chains of CHLA-02 cells became less apparent (disintegrated) by 72 hours. Scale bar: 100 μm, magnification: 10x.

[0438] Figure 24D Microscope images showing the effects of the six-factor secretome cultured in T75 flasks at higher magnification and longer time points. CHLA-02 cells cultured in the six-factor secretome formed cell clusters at longer time points, as filamentous chains of CHLA-02 cells became less apparent (disintegrated) by 96 hours. Scale bar: 100 μm, magnification: 10x.

[0439] Figure 25A Shown are bar graphs showing qRT-PCR validation of MELK in the ATRT cell line and cell lines from other embryonal brain tumor types.

[0440] Figure 25B A table comparing MELK expression in the discovery and validation sets is shown. P values ​​were calculated using Student's T-test.

[0441] Figure 26 A line graph showing the efficacy of OTSSP167 on MELK-high BT-37 cells (5 nM dose) and MELK-low CHLA-04 (50 nM dose) is shown.

[0442] Figure 27A Microscope images showing the effect of OTSSP167 on the six-factor secretome of CHLA-02 cells cultured in T75 flasks. CHLA-02 cells treated with OTSSP167 grew in suspension and clusters in standard growth medium. CHLA-02 cells treated with OTSSP167 formed clusters within 4 hours of the six-factor secretome. Scale bar: 100 μm, 4x magnification.

[0443] Figure 27BMicroscopy images showing the effect of OTSSP167 on CHLA-02 in 6-factor secretion proteome cultured in T75 flasks. OTSSP167 treated CHLA-02 cells grow in clusters suspended in standard growth media. CHLA-02 cells treated with OTSSP167 in 6-factor secretion proteome form filamentous chains at 24 hours. Scale bar: 100 μm at 4x magnification.

[0444] Figure 27C Microscopy images showing the effect of OTSSP167 on CHLA-02 in 6-factor secretion proteome cultured in T75 flasks. OTSSP167 treated CHLA-02 cells grow in clusters suspended in standard growth media. CHLA-02 cells treated with OTSSP167 in 6-factor secretion proteome form even more pronounced filamentous chains floating at 48 hours. Scale bar: 100 μm at 4x magnification.

[0445] Figure 28A Microscopy images showing the effect of OTSSP167 on CHLA-02 in 6-factor secretion proteome cultured in T75 flasks at higher magnification. OTSSP167 treated CHLA-02 cells grow in clusters suspended in standard growth media. CHLA-02 cells treated with OTSSP167 in 6-factor secretion proteome appear as cell clusters at 4 hours. Scale bar: 100 μm at 10x magnification.

[0446] Figure 28B Microscopy images showing the effect of OTSSP167 on CHLA-02 in 6-factor secretion proteome cultured in T75 flasks at higher magnification. OTSSP167 treated CHLA-02 cells grow in clusters suspended in standard growth media. CHLA-02 cells treated with OTSSP167 in 6-factor secretion proteome form filamentous chains at 24 hours. Scale bar: 100 μm at 10x magnification.

[0447] Figure 28C Microscopy images showing the effect of OTSSP167 on CHLA-02 in 6-factor secretion proteome cultured in T75 flasks at higher magnification. OTSSP167 treated CHLA-02 cells grow in clusters suspended in standard growth media. CHLA-02 cells treated with OTSSP167 in 6-factor secretion proteome form even more pronounced filamentous chains floating at 48 hours. Scale bar: 100 μm at 10x magnification.

[0448] Figure 29AMicroscopy images showing no difference in gross morphology of BT-37 cells cultured in standard media versus 6-factor secretion media in T75 flasks. BT-37 cells exhibit mixed morphology: growing in clusters, monolayers, and suspended clusters in standard growth media. BT-37 cells cultured in 6-factor secretion media show no significant difference compared to standard growth media at 4 hours. Scale bar: 100 μm, magnification: 4x.

[0449] Figure 29B Microscopy images showing no difference in gross morphology of BT-37 cells cultured in standard media versus 6-factor secretion media in T75 flasks. BT-37 cells exhibit mixed morphology: growing in clusters, monolayers, and suspended clusters in standard growth media. BT-37 cells cultured in 6-factor secretion media show no significant difference compared to standard growth media at 24 hours. Scale bar: 100 μm, magnification: 4x.

[0450] Figure 29C Microscopy images showing no difference in gross morphology of BT-37 cells cultured in standard media versus 6-factor secretion media in T75 flasks. BT-37 cells exhibit mixed morphology: growing in clusters, monolayers, and suspended clusters in standard growth media. BT-37 cells cultured in 6-factor secretion media show no significant difference compared to standard growth media at 48 hours. Scale bar: 100 μm, magnification: 4x.

[0451] Figure 30A Microscopy images showing no difference in gross morphology of BT-37 cells cultured in standard media versus 6-factor secretion media in T75 flasks at longer time points. BT-37 cells exhibit mixed morphology: growing in clusters, monolayers, and suspended clusters in standard growth media. BT-37 cells cultured in 6-factor secretion media appear more sparse at 72 hours compared to standard growth media, but otherwise show no significant difference. Scale bar: 100 μm, magnification: 4x.

[0452] Figure 30B Microscopy images showing no difference in gross morphology of BT-37 cells cultured in standard media versus 6-factor secretion media in T75 flasks at longer time points. BT-37 cells exhibit mixed morphology: growing in clusters, monolayers, and suspended clusters in standard growth media. BT-37 cells cultured in 6-factor secretion media appear more sparse at 96 hours compared to standard growth media, but otherwise show no significant difference. Scale bar: 100 μm, magnification: 4x.

[0453] Figure 31A Microscope images of more cell clusters of BT-37 treated with OTSSP167 in T75 flasks observed at longer time points in 6-factor secretion proteome. BT-37 cells treated with OTSSP167 exhibited mixed morphology: growing in monolayer and in suspension clusters in standard media. There was no apparent difference in 4 hours in 6-factor secretion proteome treated BT-37 cells with OTSSP167 and standard media. Scale bar: 100 μm, magnification: 4x.

[0454] Figure 31B Microscope images of more cell clusters of BT-37 treated with OTSSP167 in T75 flasks observed at longer time points in 6-factor secretion proteome. BT-37 cells treated with OTSSP167 exhibited mixed morphology: growing in monolayer and in suspension clusters in standard media. More apparent cell clusters were formed in 24 hours in 6-factor secretion proteome treated BT-37 cells with OTSSP167. Scale bar: 100 μm, magnification: 4x.

[0455] Figure 31C Microscope images of more cell clusters of BT-37 treated with OTSSP167 in T75 flasks observed at longer time points in 6-factor secretion proteome. BT-37 cells treated with OTSSP167 exhibited mixed morphology: growing in monolayer and in suspension clusters in standard media. More apparent cell clusters were formed in 48 hours in 6-factor secretion proteome treated BT-37 cells with OTSSP167. Scale bar: 100 μm, magnification: 4x.

[0456] Figure 32A Microscope images of adherent cells formed in 6-factor secretion proteome of CHLA-04 in T75 flasks. CHLA-04 cells grew in suspension clusters in standard growth media. CHLA-04 cells cultured in 6-factor secretion proteome exhibited growth morphology of adherent cells and floating single cells in 4 hours. Scale bar: 100 μm, magnification: 4x.

[0457] Figure 32B Microscope images of adherent cells formed in 6-factor secretion proteome of CHLA-04 in T75 flasks. CHLA-04 cells grew in suspension clusters in standard growth media. CHLA-04 cells cultured in 6-factor secretion proteome formed adherent cell clusters in 24 hours. Scale bar: 100 μm, magnification: 4x.

[0458] Figure 32CMicroscopy images of CHLA-04 forming adherent cell clusters in a 6-factor secretion proteome in a T75 flask are shown. CHLA-04 cells grow as floating clusters in standard growth media. CHLA-04 cells cultured in a 6-factor secretion proteome form adherent cell clusters at 48 hours. Scale bar: 100 μιη, magnification: 4x.

[0459] Figure 33A Microscopy images of CHLA-04 forming smaller cell clusters in a 6-factor secretion proteome in a T75 flask at longer time points are shown. CHLA-04 grows as floating small cell clusters in standard growth media at 4 hours. Scale bar: 100 μιη, magnification: 4x.

[0460] Figure 33B Microscopy images of CHLA-04 forming smaller cell clusters in a 6-factor secretion proteome in a T75 flask at longer time points are shown. CHLA-04 cells cultured in a 6-factor secretion proteome form smaller adherent cell clusters at longer time points compared to cell clusters at 72 hours under standard growth media conditions. Scale bar: 100 μιη, magnification: 4x.

[0461] Figure 33C Microscopy images of CHLA-04 forming smaller cell clusters in a 6-factor secretion proteome in a T75 flask at longer time points are shown. CHLA-04 cells cultured in a 6-factor secretion proteome form smaller adherent cell clusters at longer time points compared to cell clusters at 96 hours under standard growth media conditions. Scale bar: 100 μιη, magnification: 4x.

[0462] Figure 34A Microscopy images with low magnification demonstrating similar growth morphology of CHLA-06 in a T75 flask in standard growth media and in a 6-factor secretion proteome are shown. CHLA-06 cells exhibit mixed morphology in standard growth media: cells grow in single cell morphology, adherent or in suspension. CHLA-6 cells are less confluent when cultured in a 6-factor secretion proteome, but there is no difference in morphology compared to standard growth media at 4 hours, (b) 24 hours and (c) 48 hours. Scale bar: 100 μιη, magnification: 4x.

[0463] Figure 34BMicroscopy images with low magnification are shown demonstrating similar growth morphology of CHLA-06 in T75 flasks in standard growth media and in the 6-factor secretion media. CHLA-06 cells exhibited mixed morphology in standard growth media: cells grew adherent or in suspension as single cells. CHLA-6 cells were less confluent when cultured in the 6-factor secretion media, but there was no difference in morphology at 24 hours compared to standard growth media. Scale bar: 100 μιη, magnification: 4x.

[0464] Figure 34C Microscopy images with low magnification are shown demonstrating similar growth morphology of CHLA-06 in T75 flasks in standard growth media and in the 6-factor secretion media. CHLA-06 cells exhibited mixed morphology in standard growth media: cells grew adherent or in suspension as single cells. CHLA-6 cells were less confluent when cultured in the 6-factor secretion media, but there was no difference in morphology at 48 hours compared to standard growth media. Scale bar: 100 μιη, magnification: 4x.

[0465] Figure 35A Microscopy images with high magnification are shown demonstrating morphological changes of CHLA-06 in T75 flasks in the 6-factor secretion media. CHLA-06 cells were adherent and in suspension and exhibited a candy-like morphology when cultured in standard growth media, but formed suspended round single cells and were less confluent at 24 hours when cultured in the 6-factor secretion media. Scale bar: 100 μιη, magnification: lOx.

[0466] Figure 35B Microscopy images with high magnification are shown demonstrating morphological changes of CHLA-06 in T75 flasks in the 6-factor secretion media. CHLA-06 cells were adherent and in suspension and exhibited a candy-like morphology when cultured in standard growth media, but formed suspended round single cells and were less confluent at 48 hours when cultured in the 6-factor secretion media. Scale bar: 100 μιη, magnification: lOx.

[0467] Figure 36A Bar graphs showing no significant changes in cell cycle in BT-37 when compared by flow cytometry using PI in standard growth media or in the 6-factor secretion media are shown.

[0468] Figure 36B Flow cytometry graphs using AnV / PI comparing cell death between standard growth media and the 6-factor secretion media are shown. Figure 4E ).

[0469] Figure 37A Bar graphs and flow cytometry graphs are shown where cell death (apoptosis and necrosis) from 4-48 hours follow similar trends under secretome and standard growth media conditions in naive state with more cell death at the longer time point of 48 hours.

[0470] Figure 37B Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions as time is extended beyond 72-96 hours.

[0471] Figure 37C Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions after treatment with OTSSP167 and with higher percentage of cell death at the longer time point of 24-48 hours.

[0472] Figure 38A Bar graphs and flow cytometry graphs are shown where cell death (apoptosis and necrosis) from 4-48 hours follow similar trends under secretome and standard growth media conditions in naive state with more cell death at the longer time point of 48 hours.

[0473] Figure 38B Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions as time is extended beyond 72-96 hours.

[0474] Figure 38C Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions after treatment with OTSSP167 and with higher percentage of cell death at the longer time point of 24-48 hours.

[0475] Figure 39A Bar graphs and flow cytometry graphs are shown where cell death (apoptosis and necrosis) from 4-48 hours follow similar trends under secretome and standard growth media conditions in naive state with more cell death at the longer time point of 48 hours. Figure 4C Bar graphs with p values of the graphs shown.

[0476] Figure 39B Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions as time is extended beyond 72-96 hours. Figure 4D Bar graphs with p values of the graphs shown.

[0477] Figure 39C Bar graphs and flow cytometry graphs are shown where cell death is more pronounced in secretome compared to standard growth media conditions after treatment with OTSSP167 and with higher percentage of cell death at the longer time point of 24-48 hours. Figure 5E Bar graphs with p values of the graphs shown.

[0478] Figure 39D Bar graphs and flow cytometry graphs are shown where cell death (apoptosis and necrosis) from 4-48 hours follow similar trends under secretome and standard growth media conditions in naive state with more cell death at the longer time point of 48 hours. Figure 5E Bar graphs with p values of the graphs shown.

[0479] Figure 40A shows Figure 5D Blot 1 - original blot of CHLA-02.

[0480] Figure 40B shows Figure 5D Blot 2 - original blot of CHLA-02.

[0481] Figure 40C shows Figure 5D Blot 1 - original blot of BT-37.

[0482] FIG. 40D shows FIG. 5D Blot 2 - original blot of BT-37.

[0483] FIG. 40E shows FIG. 5D Blot 3 - original blot of BT-37.

[0484] FIG. 41A shows bar graph of secretome always keeping medulloblastoma cells more viable compared to standard media.

[0485] FIG. 41B shows bar graph of OTSSP167: Daoy, D341 have higher cell death in secretome compared to media. OTSSP167: neurospheres CHLA01 (primary tumor cells) and CHLA01R (recurrent tumor cells) have higher survival in secretome than standard media.

[0486] FIG. 41C shows bar graph of 3 cell lines (D341, CHLA01, CHLA01R) treated with ispinesib. Cells have higher survival in secretome than standard media. Gray scale: focus on bottom-most = viable cells.

[0487] FIG. 42 shows results of multi-parameter flow cytometry analysis of mouse spleen using a 27-marker panel of immune cells. This figure includes results of multi-parameter flow cytometry analysis of mouse spleen using a 27-marker panel of immune cells (T cells, B cells, myeloid cells, NK cells). CD11b (circles) is highly expressed in strain B, but not in strain A. Another marker that is highly expressed on the tSNE plot is CD44, which is highly expressed in mouse spleen tissue, and its main function in lymphocytes and macrophages is to mediate interactions with endothelial cells (Kennel et al., 1993).

[0488] FIG. 43A shows Class 1 brain tumorIn vivo data. Patient-derived orthotopic xenograft brain tumor model. A total of 33 mice. 17 mice were implanted with tumor cells in secretome (Group A). 16 mice were implanted with tumor cells in standard medium (control group, Group B). All mice were performed in the same experimental environment. Mice were staged using our previously established staging criteria (Elghetany, Teo. Scientific Reports 2021). 81.2% of mice in Group B (tumor + medium) were healthy, while only 58.9% of mice in Group A (tumor + secretome) were healthy. Kaplan Meier curve: Mice in Group A (implanted with tumor + secretome) had faster tumor progression and significantly shorter survival compared to Group B (implanted with tumor + medium). p = 0.0054.

[0489] FIG. 43B Survival plot is shown Class 2 brain tumor: medulloblastoma In this particular molecular subtype of medulloblastoma, there was no statistical difference in survival between Group A (mice implanted with tumor + secretome) and Group B (mice implanted with tumor + medium). p = 0.3786. However, mice implanted with tumor + secretome had a faster progression trend of disease.

[0490] In the same particular molecular subtype of medulloblastoma as the 93B batch, another batch of 21 mice were implanted with tumor + secretome in the same experimental environment (94B batch). All 21 mice successfully formed brain tumors. We have previously demonstrated that Ispinesib is an effective drug for treating medulloblastoma (Elghetany, Teo. Scientific Reports 2021). The data presented here show that Ispinesib is also effective against PDX brain tumors implanted with secretome + tumor.

[0491] FIG. 44 CHLA-02 Southern blot is shown: Teleblot shows that telomere length is maintained at comparable levels to standard medium within the secretome. The effect lasted up to 96 hours.

[0492] FIG. 45 Bar chart showing tumor cells exhibiting the highest proliferative capacity at day 0 when treated with secretome harvested at 22 hours to 48 hours.

[0493] FIG. 46Cytokine analysis using Cytokine Profiling is shown comparing supernatants harvested from drug resistant medulloblastoma tumor cells co-cultured with CD11b+ cells, and supernatants harvested from CD11b+ conditioned media. Release of CCL2 / MCP-1, IL-1Ra, MIP-1a / MIP1B was higher when co-cultured in drug resistant cells.

[0494] FIG. 47A Volcano plot using fold change of 2, raw p-value = 0.1, equal variance is shown. Metabolites from sample 2 (CHLA01 + secretome, cultured for 24 hours) were compared to metabolites from sample 1 (CHLA01 + standard media, cultured for 24 hours). 29 metabolites were significantly upregulated by tumor cells in the secretome (dashed line), and 64 metabolites were significantly downregulated by tumor cells in the secretome (bold line). CHLA-01. Sample 1 and 2 were run in triplicate. Sample 1: CHLA01 + standard media, cultured for 24 hours. Sample 2: CHLA01 + secretome, cultured for 24 hours. All data shown was analyzed using MetaboAnalyst 6.0 software, normalized using protein concentration. A 10% variance filter was applied to the dataset based on interquartile range (IQR). Samples were normalized by the median. Data transformation was log-transformed. No data scaling was applied.

[0495] FIG. 47B Heatmap using normalized data, Euclidean distance, and Ward clustering is shown.

[0496] FIG. 47C Principal Component Analysis (PCA) plot using 95% confidence intervals is shown.

[0497] FIG. 48A Enrichment analysis using SMPDB library set using all metabolites produced in the experiments of the present disclosure (3 replicates each of two samples) is shown. The top 25 enriched metabolite sets are shown. Methylornithine metabolism was the top metabolic pathway (enrichment ratio > 12) of detected metabolites in tumor cells (CHLA01) cultured for 24 hours in secretome and standard media.

[0498] FIG. 48B Pathway analysis using SMPDB library set using all metabolites produced in the experiments of the present disclosure (3 replicates each of two samples) is shown. Methylornithine metabolism was the top metabolic pathway of detected metabolites in tumor cells (CHLA01) cultured for 24 hours in secretome and standard media.

[0499] FIG. 48CPathway analysis using the SMPDB library set using all metabolites produced in the experiments of the present disclosure (3 replicates each of two samples) is shown. In tumor cells (CHLA01) cultured in the secretome for 24 hours, methionine metabolism was the most upregulated metabolic pathway among the detected metabolites.

[0500] FIG. 48D Enrichment analysis using the SMPDB library set using upregulated metabolites detected in tumor cells (CHLA01) cultured in the secretome for 24 hours produced in the experiments of the present disclosure (3 replicates each of two samples) is shown (compared to tumor cells cultured in standard media for 24 hours). The top 25 enriched metabolite sets are shown. In tumor cells (CHLA01) cultured in the secretome, biotin metabolism was the most upregulated metabolic pathway among the detected metabolites (enrichment ratio of 25), followed by taurine and hypotaurine metabolism (enrichment ratio > 15), and the ammonia cycle pathway (enrichment ratio > 10).

[0501] FIG. 48E Pathway analysis using the SMPDB library set using upregulated metabolites produced in the experiments of the present disclosure (3 replicates each of two samples) is shown. In tumor cells (CHLA01) cultured in the secretome for 24 hours, biotin metabolism was the most upregulated metabolic pathway among the detected metabolites, followed by taurine and hypotaurine metabolism, and the ammonia cycle pathway.

[0502] FIG. 48F Pathway analysis using the SMPDB library set using upregulated metabolites produced in the experiments of the present disclosure (3 replicates each of two samples) is shown. In tumor cells (CHLA01) cultured in the secretome for 24 hours, biotin metabolism was the most upregulated metabolic pathway among the detected metabolites, followed by taurine and hypotaurine metabolism, and the ammonia cycle pathway.

[0503] FIG. 48G Enrichment analysis using the SMPDB library set using downregulated metabolites detected in tumor cells (CHLA01) cultured in the secretome for 24 hours produced in the experiments of the present disclosure (3 replicates each of two samples) is shown (compared to tumor cells cultured in standard media for 24 hours). The top 25 enriched metabolite sets are shown. In tumor cells (CHLA01) cultured in the secretome for 24 hours, methionine metabolism was the most downregulated metabolic pathway among the detected metabolites (enrichment ratio > 12).

[0504] FIG. 48HPathway analysis using the SMPDB library set using down-regulated metabolites generated in the disclosed experiments (two samples, three replicates each) is shown. In the secretome of tumor cells (CHLA01) cultured for 24 hours, methylhistidine metabolism became the most down-regulated metabolic pathway among the metabolites detected.

[0505] FIG. 48I The following pathway analysis was performed using the SMPDB library set using down-regulated metabolites generated in the disclosed experiments (two samples and three replicates each) as shown below. In the secretome of tumor cells (CHLA01) cultured for 24 hours, methylhistidine metabolism became the most down-regulated metabolic pathway among the metabolites detected.

[0506] FIG. 48J Shown is a table of down-regulated metabolites generated using the SMPDB library set.

[0507] FIG. 49A Figure 2 shows an enrichment analysis of upregulated metabolites detected in tumor cells (CHLA01) cultured in the secretome for 24 hours (two samples, three replicates each) using a KEGG library set generated in the disclosed experiments (compared to tumor cells cultured in standard medium for 24 hours). The top 25 enriched metabolite sets are shown. In tumor cells (CHLA01) cultured in the secretome, taurine and hypotaurine metabolism (enrichment ratio > 25) became the most upregulated metabolic pathway among the detected metabolites, followed by biotin metabolism (enrichment ratio > 20).

[0508] FIG. 49B to FIG. 49D Pathway analysis of up-regulated metabolites using KEGG pathways is shown.

[0509] FIG. 49E Figure 2 shows an enrichment analysis of downregulated metabolites detected in the secretome of tumor cells (CHLA01) cultured for 24 hours (two samples, three replicates each) using a KEGG library set generated in the disclosed experiments (compared to tumor cells cultured in standard medium for 24 hours). The top 25 enriched metabolite sets are shown. Valine, leucine, and isoleucine biosynthesis (enrichment ratio > 25), as well as phenylalanine, tyrosine, and tryptophan biosynthesis (enrichment ratio > 25).

[0510] FIG. 49F and FIG. 49G Pathway analysis of down-regulated metabolites using KEGG pathway generation is shown.

[0511] FIG. 49H A table of down-regulated metabolites generated using KEGG pathways is shown.

[0512] FIG. 50A to 50CPathway analysis of upregulated metabolites generated using drug-associated libraries is shown.

[0513] FIG. 50D Table of upregulated metabolites generated using drug-associated libraries is shown.

[0514] FIG. 50E to FIG. 50G Pathway analysis of downregulated metabolites generated using drug-associated libraries is shown.

[0515] FIG. 50H Table of downregulated metabolites generated using drug-associated libraries is shown.

[0516] FIG. 51A Microscopy images of CHLA01R cells taken after 65 hours of cryopreservation in the secretome-based cryomedia are shown (on an automated cell counter). White circles highlight mostly live cells.

[0517] FIG. 51B Microscopy images of CHLA01R cells taken after 188 hours of cryopreservation in the secretome-based cryomedia are shown (on an automated cell counter). White circles highlight mostly live cells. Cell number and viability of vials taken after 188 hours. Cell number (at time of taking) is even higher at 3 million compared to 2.49 million at the time of freezing. Viability has dropped by about 15% from the day of freezing, which is comparable / better than the standard media-based cryomedia.

[0518] Applications

[0519] The embodiments disclosed herein provide a composition comprising a secretome obtained by culturing cells in the presence of an agent to produce immune cells.

[0520] Advantageously, the present disclosure is scalable. The secretome of the present disclosure can be harvested in large quantities after 48 hours of culturing of immune progenitor cells with an agent and packaged in cryovials, which can be stably stored for 3 years or more under storage conditions of -80°C.

[0521] More advantageously, the present disclosure allows screening of patient tumors to customize precision medicine and select patients with immune-rich tumors for clinical trials. The secretome product of the present disclosure enables testing of new drug / drug libraries in vitro under immune-rich conditions of cancer cells for high-throughput drug discovery. This can be performed in a laboratory setting prior to application to patients during clinical trials and is very useful to the pharmaceutical industry.

[0522] Even more advantageously, the present disclosure demonstrates that the secretome of the present disclosure is able to sustain cells during nutritional stress and is of significant importance in the relapse subtype of aggressive childhood brain tumor (ATRT). The secretome product of the present disclosure is also present in other adult cancer cell types and can be applied to other non-cancer human diseases that can share this secretome, such as chronic inflammation, ulcerative colitis, Crohn’s disease, Alzheimer’s disease, dementia, coronavirus disease, and HIV disease.

[0523] Even more advantageously, the secretome of the present disclosure can be used for cryopreservation of cells, such as cancer cells, healthy cells. The secretome of the present disclosure can preserve cells such as ova, sperm, umbilical cord blood, etc.

[0524] Even more advantageously, the secretome of the present disclosure can be used as a cell culture medium and for biomarker discovery in cell research. The secretome of the present disclosure provides a rich immune condition for laboratory testing of diseased cells in an immune-rich in vitro culture, testing of new drugs on cancer cells, or screening of compounds to identify drugs effective against diseased / cancer cells, mimicking the microenvironmental conditions within a patient’s tumor.

[0525] Even more advantageously, the secretome of the present disclosure can be used as a cryopreservation medium. Cells cryopreserved using the secretome cryopreservation medium (90% secretome and 10% DMSO) are able to maintain or even restore viability compared to standard cryopreservation medium (standard medium and 10% DMSO).

[0526] Even more advantageously, the secretome of the present disclosure can be used for therapeutic applications, such as tissue regeneration (such as skin regeneration / skin graft manufacturing, nerve / brain regeneration / anti-aging, liver regeneration, vascular regeneration, tissue / organ regeneration for transplantation), wound healing, angiogenesis, osteogenesis, treatment of inflammatory responses, and / or drug discovery.

[0527] Even more advantageously, the present disclosure shows the screening capability to identify the secretome phenotype for each cancer type, thereby developing personalized therapy for precision medicine.

[0528] Even more advantageously, the present disclosure provides a pan-cancer secretome atlas comprising a database of multiple secretome phenotypes for multiple diseases, including cancer, acute / chronic inflammatory diseases. The secretome atlas of the present disclosure can be used to select a specific cancer type for testing of new drugs / chemical agents using the secretome product of the present disclosure for screening.

[0529] Those skilled in the art will appreciate that other alterations and / or modifications of the embodiments disclosed herein can be employed without departing from the spirit or scope of the disclosure broadly described above. For example, features of different exemplary embodiments described herein can be mixed, combined, interchanged, merged, adopted, modified, included, etc. among different exemplary embodiments. Accordingly, the present embodiments are to be considered as illustrative and not restrictive, and the disclosure is not to be limited to the details given herein, but can be implemented in alternative embodiments within the scope of the appended claims.

Claims

1. A composition comprising a secretome obtained by culturing immune progenitor cells in the presence of an agent that activates the immune progenitor cells into activated immune cells.

2. The composition of claim 1, wherein the secretome comprises proteins including cytokines, hormones, antibodies, growth factors, extracellular matrix proteins, shed receptors, coagulation factors, adhesion molecules, proteases, kinases and / or glycoproteins.

3. The composition of any of the preceding claims, wherein the secretome comprises one or more factors selected from the group consisting of CCL2 / MCP-1, MIP-1α / MIP-1β, CCL5 / RANTES, MIF, IL-1ra / IL-IF3, IL-8, and serine protease inhibitor E1 / PAI-1.

4. The composition of any one of the preceding claims, wherein the immune cells comprise myeloid cells, lymphoid cells and / or innate immune cells.

5. The composition of any one of the preceding claims, wherein the immune progenitor cells are myeloid progenitor cells.

6. The composition according to any one of the preceding claims, wherein the immune cells are macrophages expressing CD11b and / or CD163.

7. The composition of any one of the preceding claims, wherein the secretome is a macrophage-derived secretome.

8. The composition of any preceding claim, wherein the agent comprises a stimulator or an inhibitor.

9. The composition of any preceding claim, wherein the agent is a myeloid stimulator.

10. The composition of any preceding claim, wherein the agent is PMA and / or IL-4.

11. The composition of any one of the preceding claims, wherein the secretome maintains cell growth, cell proliferation, cryopreserves cells, extends telomere length in cancer cells, participates in metabolic reprogramming, identifies drug resistance, and / or prevents cancer cell death under nutritional stress conditions.

12. A composition according to any one of the preceding claims for use in tissue regeneration.

13. A method for generating a macrophage-derived secretome, the method comprising: Immune progenitor cells are cultured in the presence of a stimulatory agent to generate an activated immune cell population, and the secretome is harvested from the generated activated immune cell population.

14. The method of claim 13, further comprising culturing the activated immune cells in the presence of diseased cells.

15. The method of claim 13 or 14, wherein the diseased cells are cells from a proliferative disease.

16. The method of claims 13 to 15, wherein the diseased cells are brain tumors, atypical teratoid rhabdoid tumors (ATRT) and / or medulloblastomas.

17. A method for screening a drug, the method comprising culturing the drug with diseased cells in the presence of the composition of claims 1 to 11.

18. A method of culturing proliferating cells, the method comprising culturing the proliferating cells in a composition according to claims 1 to 11.

Images