Clinical Precision Oncology Enabled by Patient-Derived Micro-Organospheres (MOS)

Abstract

Methods and materials are provided herein for generating and using patient-derived micro-organospheres (e.g., micro-organospheres derived from tumor tissue).

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims priority based on U.S. Provisional Application No. 63 / 338,022, filed on May 3, 2022. The disclosure of the prior application is considered to be part of (and incorporated by reference into) the disclosure of this application.

[0002] Sequence Listing This application includes a sequence listing that was electronically submitted as an XML file named "53157 - 0008WO1.XML". The XML file was created on May 3, 2023 and is 6,345 bytes in size. Accordingly, the materials within the XML file are hereby incorporated by reference in their entirety into this specification.

[0003] This document relates to methods and materials for generating and using patient - derived micro - organospheres.

Background Art

[0004] The success of precision oncology depends on models that capture the morphological, molecular, and functional characteristics of patient tumors to accurately predict drug response and drug resistance. The development of various patient - derived cancer models (PDMCs) has provided tools for this endeavor. For example, drug sensitivity assays using PDMCs have reproduced anti - tumor responses in the clinic and highlight the potential to guide personalized care (Non - Patent Documents 1 - 4). Patient - derived xenografts (PDXs) and organoids (PDOs) have also been shown to model clinical responses to cancer therapies (Non - Patent Documents 2, 5 - 9). Furthermore, given the growing clinical importance of cancer immunology (IO), there is great interest in reproducing physiological immune activity in organoid culture. For example, co - culture models of peripheral blood lymphocytes and tumor organoids have been used to test tumor - reactive T cells (Non - Patent Document 10). However, it can be difficult to use PDX and PDO models to guide timely clinical decisions for cancer patients.

Prior Art Documents

Non-Patent Literature

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Non-Patent Literature 1

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Summary of the Invention

Problems to be Solved by the Invention

[0006] As described herein, droplet emulsion microfluidics with temperature control and minimization of dead volume can be used to rapidly generate thousands of micro-organospheres (MOS) from small amounts of patient tissue, and the MOS may be very useful as patient-derived models for clinical precision oncology. In a clinical study of patients diagnosed with colorectal cancer (CRC) with newly developed distant metastases using a MOS-based precision oncology pipeline, the treatment outcome of the patients was reliably predicted within 14 days, a timeline suitable for guiding clinical treatment decisions. Further, as described herein, the MOS preserves the stromal cells of the original tumor tissue, enables infiltration of T cells, and provides a clinical assay for testing IO therapies such as PD-1 inhibitors, bispecific antibodies, and T cell therapies against patient tumors.

Means for Solving the Problems

[0007] In a first aspect, this document features a method that includes, or consists essentially of, obtaining a plurality of cells from an organism, forming micro - organospheres (MOS) from the plurality of cells, culturing the MOS in a MOS culture, introducing a virus into the MOS culture to obtain one or more cells infected with the virus in the MOS. The one or more infected cells can express one or more genes introduced by the virus after being infected with the virus. The MOS can have an average diameter of about 50 μm to about 500 μm. Optionally, the plurality of cells can include 15,000 cells or less. In this method, the cells can be derived from a biopsy. The cells can be derived from a tumor biopsy. The cells can be derived from one or more core biopsies including a core biopsy from about 14 - gauge to about 20 - gauge. The cells can be derived from one or more 18 - gauge core biopsies. The cells can be derived from one or more cancer tumor biopsies. The one or more cancers can include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof. The cells can be derived from one or more patients. The cells can include patient - derived xenograft (PDX) cells from CRC patients. The MOS can include tumor - like masses. The MOS can be cultured in droplets, and the nascent MOS can have a seeding density of about 1 to about 300 cells per droplet. The nascent MOS can have a seeding density configured to generate tumor - like masses of a desired quantity, size, or both within the MOS. The MOS can be cultured in droplets, and this method can further include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. This method can further include treating the MOS with one or more therapeutic agents. The one or more therapeutic agents can include small molecules or antibodies. The cells can be patient - derived, and the MOS can function as a predictive model of a patient's sensitivity to one or more drug therapies for treating a disease. The MOS can function as a predictive model of a patient's sensitivity to one or more chemotherapies.

[0008] In another aspect, this document features a method that includes obtaining a plurality of cells from an organization, mixing the plurality of cells with a fluid containing a polymer, and crossing the flow of the cells and the fluid with the flow of an immiscible material to generate a plurality of micro-organospheres (MOS), or consisting essentially of these steps. This method can further include demulsifying the generated MOS and / or culturing the generated MOS. Optionally, this method can include culturing the generated MOS as suspension droplets. The polymer can be a polymer matrix (e.g., an extracellular matrix). The MOS can have an average diameter of about 10 μm to about 700 μm. The MOS can have an average diameter configured to provide a three-dimensional cell environment. Optionally, the plurality of cells can include 15,000 cells or fewer, 10,000 cells or fewer, 5,000 cells or fewer, or 1,000 cells or fewer. Optionally, the plurality of cells can include from about 50 cells to about 20,000 cells (e.g., from about 500 cells to about 10,000 cells). The cells can be derived from a biopsy (e.g., a tumor biopsy). The cells can be derived from one or more core biopsies (e.g., one or more biopsies having a core from about 14 gauge to about 20 gauge core biopsies). The cells can be derived from one or more 18 gauge core biopsies. The cells can be derived from one or more cancer tumor biopsies. The one or more cancers can include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof. The cells can be derived from one or more patients. The cells can include patient-derived xenograft (PDX) cells from CRC patients. The MOS can include tumor-like masses and / or tumor-like mass-like structures in the presence of tumor-resident immune cells. By mixing, a plurality of nascent MOS can be formed, which then form MOS. The nascent MOS can include a seeding density of about 20 to about 100 cells per droplet, about 20 to about 50 cells per droplet, about 30 to about 70 cells per droplet, about 40 to about 60 cells per droplet, or about 50 to about 100 cells per droplet.The nascent MOS can include a seeding density configured to generate tumor-like masses of a desired quantity, size, or both within the MOS. This method can further include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. This method can further include treating the MOS with one or more therapeutic agents. The one or more therapeutic agents can include small molecules or antibodies. The therapeutic agent can be any chemotherapeutic agent. Treatment can include delivering one or more therapeutic agents at a concentration of about 1 μM to about 10 μM. The one or more therapeutic agents can include oxaliplatin, irinotecan, or a combination thereof. Treatment can be performed within 11 days after biopsy acquisition, within 5 days after biopsy acquisition, or within 3 days after biopsy acquisition. Each MOS can include at least 30 tumor cells, at least 20 tumor cells, or at least 10 tumor cells. Optionally, each MOS can include from about 10 to about 50 tumor cells. The MOS can function as a predictive model of a patient's sensitivity to one or more drug therapies for treating a disease. The MOS can function as a predictive model of a patient's sensitivity to one or more chemotherapies. The MOS can function as a predictive model of a patient's sensitivity to one or more chemotherapies within 14 days after MOS preparation. The MOS can include a lesser amount of fibroblasts than that seen in relatively bulk organoid cultures. For example, the amount of fibroblasts in the MOS can be less than that seen in relatively bulk organoid cultures after 2 days of culture, less than that seen in relatively bulk organoid cultures after 5 days of culture, or less than that seen in relatively bulk organoid cultures after 7 days of culture. The MOS can include functional immune cells. The MOS can include immune cells that respond to immunotherapy. The MOS can include natural killer cell markers (e.g., CD4+, CD8+, CD56+, or a combination thereof).

[0009] In another aspect, this document features a method for predicting a patient's response to a therapeutic treatment. This method can include, or can consist essentially of, co-culturing patient-derived micro-organospheres (MOS) with a drug related to immunotherapy and analyzing the MOS to determine the efficacy of the immunotherapy. The immunotherapy can be a cancer immunology (IO) therapy. The drug can include an immune checkpoint inhibitor, a T cell activator, tumor-infiltrating lymphocytes (TIL), an IO therapy molecule, or a combination thereof. The immune checkpoint inhibitor can be an anti-PD1 therapy (e.g., nivolumab, pembrolizumab, cemiplimab, atezolizumab, dostarlimab, durvalumab, or avelumab). The IO therapy molecule can include a PD-1 inhibitor, a T cell bispecific antibody (TCB), or both. The immunotherapy can target human leukocyte antigen (HLA), an antigen related to HLA, or both. The drug can include a T cell receptor mimicking antibody (e.g., ESK1, DP47, or both). The drug can be present in an amount of about 0.1 μg / mL to about 10 μg / mL, about 0.5 μg / mL to about 5 μg / mL, or about 1 μg / mL to about 3 μg / mL. This method can include determining the amount of cell apoptosis that occurred in tumor-like masses present within the MOS after the initiation of the immunotherapy. The MOS can function as a predictive model for at least 12 months, at least 6 months, or at least 3 months.

[0010] In another aspect, this document features a method for treating a patient. This method can include, or can consist essentially of, (a) predicting the patient's response to a therapeutic treatment described herein and (b) selecting a therapy based on the predicted patient response.

[0011] In another aspect, this document features a method for predicting a patient's response to a therapy. This method can include, or consist essentially of, or consist of: (a) co-culturing patient-derived micro-organospheres (MOS) with effector immune cells; and (b) analyzing the MOS to determine the efficacy of the therapy by the effector immune cells. The immune cells can be selected from the group consisting of chimeric antigen receptor (CAR) T cells, tumor-infiltrating lymphocytes (TIL), peripheral blood mononuclear cells (PBMC), T cells isolated from PBMC, T cells isolated and expanded from tumor cells, and combinations thereof. The MOS can be formed by the methods described herein.

[0012] In yet another aspect, this document features a micro-organosphere composition. The composition can include, consist essentially of, or consist of a plurality of micro-organospheres, each micro-organosphere including a substrate and at least one tumor-like mass, and the plurality of micro-organospheres including a predetermined number of cells per droplet, a predetermined number of droplets in the composition, and / or a predetermined droplet size. The composition can further include one or more drug therapies. The at least one tumor-like mass can be capable of responding to one or more drug therapies.

[0013] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Although methods and materials similar or equivalent to those described herein can be used to practice the invention, the preferred methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, this specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

[0014] Details of one or more embodiments of the present invention are set forth in the accompanying drawings and the following description. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

Brief Description of the Drawings

[0015]

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Mode for Carrying Out the Invention

[0016] This document provides methods and materials that can be used to generate and use MOS. For example, as described herein, using droplet emulsion microfluidics with temperature control and minimization of dead volume enables the rapid generation of thousands of MOS from a small amount of patient tissue (e.g., tumor biopsy). MOS can function as a patient-derived model in clinical precision oncology, predicting a patient's response to specific therapeutic agents and predicting treatment outcomes within 14 days, a timeline suitable for guiding treatment decisions in the clinic. Furthermore, MOS has been found to contain stromal cells from the original tumor that enable T cell infiltration, and as demonstrated herein, to contain tumor-derived immune cells in an environment that effectively mimics the environment of the original tumor, MOS provides a clinical assay for testing IO therapies such as checkpoint inhibitors (e.g., PD-1 inhibitors), bispecific antibodies, and T cell therapies against a patient's tumor.

[0017] Optionally, this document provides a method for generating MOS. In some variations, MOS is formed by forming droplets of an unpolymerized mixture of dissociated tissue samples and a fluid matrix material in an immiscible material such as a fluid hydrophobic material (e.g., oil). For example, MOS can be formed by combining a stream of unpolymerized material containing cells of a dissociated tissue sample with one or more streams of an immiscible material to form droplets. Optionally, MOS can be formed according to one or more of the methods described in U.S. Patent No. 11,555,180, which is hereby incorporated by reference in its entirety. See, for example, columns 3, lines 5 through 7, lines 5, and columns 21, lines 54 through 22, line 57. Optionally, this method can also include demulsifying and / or culturing the generated MOS. For example, MOS can be cultured as droplets. Optionally, MOS can be cultured as suspended droplets.

[0018] Any suitable polymer and immiscible fluid (e.g., oil) can be used. Optionally, for example, the polymer can be a polymer matrix (e.g., an extracellular matrix such as a MATRIGEL® matrix).

[0019] The MOS can have any suitable diameter. For example, the MOS can have an average diameter of about 10 μm to about 700 μm (e.g., about 10 to about 50 μm, about 50 to about 100 μm, about 100 to about 150 μm, about 150 to about 200 μm, about 200 to about 250 μm, about 250 to about 300 μm, about 300 to about 350 μm, about 350 to about 400 μm, about 400 to about 450 μm, about 450 to about 500 μm, about 500 to about 550 μm, about 550 to about 600 μm, about 600 to about 650 μm, or about 650 to about 700 μm). Optionally, the MOS within the population can have an average diameter configured to provide a three-dimensional cell environment. Optionally, the plurality of cells can contain 15,000 cells or fewer (e.g., 10,000 cells or fewer, 5,000 cells or fewer, or 1,000 cells or fewer). Optionally, the plurality of cells can contain from about 100 cells to about 20,000 cells (e.g., about 100 to about 500 cells, about 500 to about 1000 cells, about 1000 to about 2500 cells, about 2500 to 5000 cells, about 5000 cells to about 10,000 cells, about 500 cells to about 10,000 cells, or about 10,000 cells to about 20,000 cells).

[0020] The cells can be derived from a biopsy (e.g., a tumor biopsy). Optionally, the cells can be derived from one or more core biopsies (e.g., one or more biopsies having a core biopsy from about a 14-gauge core to about a 20-gauge core). For example, the cells can be derived from one or more 18-gauge core biopsies, or one or more 16-gauge core biopsies.

[0021] The cells can be derived from a tumor biopsy. The tumor can be associated with any type of cancer, including but not limited to rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or any combination thereof. The cells can be derived from one patient or multiple patients. Optionally, the cells can include CRC PDX cells.

[0022] When preparing MOS by mixing the cells with an immiscible material (e.g., oil) and a polymer, multiple nascent MOS can be formed by the mixing, and then MOS are formed. The nascent MOS can have a seeding density of about 20 to about 100 cells per droplet (e.g., about 20 to about 50 cells per droplet, about 30 to about 70 cells per droplet, about 40 to about 60 cells per droplet, or about 50 to about 100 cells per droplet). Optionally, the nascent MOS can have a seeding density configured to generate tumor-like masses of a desired quantity, a desired size, or both within the MOS. Thus, optionally, the MOS can contain tumor-like masses or can contain tumor-like mass-like structures (e.g., in the presence of tumor-resident immune cells). The number and size of the tumor-like masses can potentially be correlated with the seeding density.

[0023] Optionally, the method of generating MOS can also include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. MOS generated according to the methods described herein can each contain at least 10 tumor cells (e.g., at least 20 tumor cells, or at least 30 tumor cells). Optionally, each MOS can contain about 10 to about 50 tumor cells.

[0024] In some cases, this document provides a method for imaging MOS. For example, an image of MOS (e.g., MOS in bulk MATRIGEL® or MOS cultured in any suitable medium) can be obtained using a microscope (e.g., brightfield microscope, confocal microscope, or fluorescence microscope), or any other suitable technique (e.g., liquid lens, holography, sonar, brightfield and / or darkfield imaging, laser imaging, planar laser sheet, or high-throughput methods including image-based analysis). Optionally, the surface area of MOS can be determined using any suitable software (e.g., ImageJ software; imagej.nih.gov / ij).

[0025] Furthermore, optionally, the methods provided herein can include treating MOS with one or more therapeutic agents. After such treatment, by evaluating whether the therapeutic agent(s) affect the survival rate of MOS, it can be shown whether the therapeutic agent(s) are likely to be effective in treating tumors in the subject from which the MOS was prepared. The one or more therapeutic agents can include, for example, small molecules or antibodies. The one or more therapeutic agents can be applied to MOS at any suitable concentration (e.g., from about 1 μM to about 10 μM). Additionally, the one or more therapeutic agents can include any suitable drug. The one or more therapeutic agents can be chemotherapeutic agents. Non-limiting examples of therapeutic agents that can be used in the methods provided herein include oxaliplatin, irinotecan, or combinations thereof. The treatment can be performed within 11 days after biopsy acquisition (e.g., within 5 days after biopsy acquisition, or within 3 days after biopsy acquisition).

[0026] As described herein, MOS can encapsulate various cell types (e.g., tumor cells, stromal cells, and immune cells) that are resident in the tissue from which they are derived (e.g., tumor tissue). Further, MOS also substantially captures the genomic profile of the tissue from which they are derived. Thus, without being bound by a particular mechanism, MOS can function as a predictive model of a patient's sensitivity to one or more drug therapies for treating a disease. For example, MOS can function as a predictive model of a patient's sensitivity to one or more chemotherapies. Optionally, MOS can function as a predictive model of a patient's sensitivity to one or more chemotherapies within 14 days after MOS preparation.

[0027] Optionally, MOS can contain a lower amount of fibroblasts than the amount of fibroblasts found in a relatively bulk organoid culture. For example, the amount of fibroblasts encapsulated in MOS can be less than the amount of fibroblasts found in a relatively bulk organoid culture after 2 days of culture, less than the amount of fibroblasts found in a relatively bulk organoid culture after 5 days of culture, or less than the amount of fibroblasts found in a relatively bulk organoid culture after 7 days of culture. MOS can also contain functional immune cells. For example, MOS can contain immune cells that respond to immunotherapy. Optionally, MOS can contain natural killer cell markers (CD4+, CD8+, CD56+, or a combination thereof).

[0028] This document also provides a method for predicting a patient's response to a therapeutic treatment. As described herein, immune cells resident in a tissue sample (e.g., immune cells resident in a tumor tissue sample) can be encapsulated in MOS derived from the tissue sample. Since MOS can capture the immune microenvironment of a tumor, the effect of a drug that affects immune cells and / or a drug that affects the interaction between immune cells and cancer cells (e.g., a checkpoint inhibitor) can be evaluated with MOS. As demonstrated herein, immune cells encapsulated within MOS are viable and can respond to immune stimulation, so immunotherapy can be tested on the resident immune cells encapsulated within MOS. Optionally, the method provided herein can include co-culturing MOS with one or more drugs related to immunotherapy and analyzing MOS to determine the efficacy of the immunotherapy.

[0029] Any suitable immunotherapy can be tested using the population MOS formulation. For example, the immunotherapy can be a cancer immunology (IO) therapy, a checkpoint inhibitor, a T cell activator, tumor infiltrating lymphocytes (TlL), an IO therapy molecule, a MAPK inhibitor, or a combination thereof. Optionally, an immune checkpoint inhibitor such as an anti-PD1 therapy (e.g., nivolumab, pembrolizumab, cemiplimab, atezolizumab, dostarlimab, durvalumab, or avelumab) or another checkpoint inhibitor (e.g., a T cell-targeted immunomodulator, TSR-022, MGB453, BMS-986016, or LAG525) can be used. Optionally, an IO therapy molecule can be used, where the IO therapy molecule includes a PD-1 inhibitor, a TCB, or both. The immunotherapy can target a human leukocyte antigen (HLA), an antigen related to HLA, or both. The drug can include a T cell receptor mimicking antibody (e.g., ESK1, DP47, or both). Optionally, the immunotherapy can be a MAPK inhibitor (e.g., vemurafenib, dabrafenib, PLX8349, cobimetinib, trametinib, selumetinib, or BVD-523). Other immunotherapies that can be used include immunomodulators (e.g., anti-CD47 antibody and antibody-dependent cell cytotoxicity (ADCC) therapy), apoptosis inhibitors (e.g., ABT-737, WEHI-539, ABT-199), drugs that target components of potentially contributing pathways (e.g., afuresertib, idasanutlin, and infliximab), chemotherapeutic agents (e.g., cytarabine), cell therapy, cancer vaccines, oncolytic viruses, and bispecific antibodies, but are not limited thereto. The drug can be present in an amount of about 0.1 μg / mL to about 10 μg / mL, about 0.5 μg / mL to about 5 μg / mL, or about 1 μg / mL to about 3 μg / mL. The method can include determining the amount of cell apoptosis that occurs in tumor-like masses present within the MOS after initiation of the immunotherapy. The MOS can function as a predictive model for at least 12 months, at least 6 months, or at least 3 months.

[0030] Optionally, the methods provided herein can include infecting the MOS with one or more viruses. For example, the viruses can be used to deliver therapeutic agents (e.g., immunotherapies) to the MOS. Examples of viruses that can be used to infect the MOS include, but are not limited to, lentiviruses, adeno-associated viruses, and influenza viruses. Optionally, viruses containing nucleic acids encoding polypeptides (markers, therapeutic polypeptides, or DNA editing polypeptides such as CRISPR-associated (Cas) nucleases) can be used to infect the MOS.

[0031] In another aspect, the present document features a method for treating a mammal (e.g., a human such as a human patient). The method can include, for example, predicting a patient's response to a therapeutic treatment using the methods provided herein, and selecting a therapy based on the patient's predicted response. Optionally, the method can include co-culturing the MOS with effector immune cells and then analyzing the MOS to determine the efficacy of treatment by the effector immune cells. The immune cells can be, for example, chimeric antigen receptor (CAR) T cells, tumor-infiltrating lymphocytes (TIL), peripheral blood mononuclear cells (PBMC), T cells isolated from PBMC, T cells isolated and expanded from tumor cells, or any combination thereof.

[0032] This document also provides a MOS composition in which the composition includes a plurality of MOS, and each micro-organosphere includes at least one tumor-like mass including an aggregate of a substrate and cells. The plurality of MOS can include a predetermined number of cells per droplet, a predetermined number of droplets in the composition, and / or a predetermined droplet size. Optionally, the composition can also include one or more therapeutic agents (e.g., one or more drug therapies to which the tumor-like mass responds).

[0033] As described herein, the MOS and the original tumor from which the MOS was generated can have a similar genomic profile. Further, the whole exome sequence of the MOS can correlate with the whole exome sequence of the original tumor. Optionally, the MOS and the original tumor can have a similar expression pattern of immunosuppressive markers.

[0034] Exemplary embodiments Embodiment 1 is a method comprising obtaining a plurality of cells derived from a tissue, obtaining a mixture by mixing the plurality of cells with a fluid containing a polymer, and generating micro - organospheres (MOS) by crossing the flow of the mixture with an immiscible material (e.g., oil).

[0035] Embodiment 2 is the method of Embodiment 1, further comprising demulsifying the generated MOS.

[0036] Embodiment 3 is the method of any one of the preceding embodiments, further comprising culturing the generated MOS.

[0037] Embodiment 4 is the method of any one of the preceding embodiments, further comprising culturing the generated MOS as suspension droplets.

[0038] Embodiment 5 is the method of any one of the preceding embodiments, wherein the polymer is a polymer matrix.

[0039] Embodiment 6 is the method of Embodiment 5, wherein the polymer matrix is derived from the extracellular matrix.

[0040] Embodiment 7 is the method of any one of the preceding embodiments, wherein the MOS has an average diameter of about 250 μm to about 450 μm.

[0041] Embodiment 8 is the method of any one of the preceding embodiments, wherein the MOS has an average diameter configured to provide a three - dimensional cell environment.

[0042] Embodiment 9 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises 15,000 cells or less.

[0043] Embodiment 10 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises 10,000 cells or less.

[0044] Embodiment 11 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises 5,000 cells or less.

[0045] Embodiment 12 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises 1,000 cells or less.

[0046] Embodiment 13 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises from about 100 cells to about 20,000 cells.

[0047] Embodiment 14 is any one of the methods of the preceding embodiments, wherein the plurality of cells comprises from about 500 cells to about 10,000 cells.

[0048] Embodiment 15 is any one of the methods of the preceding embodiments, wherein the cells are derived from a biopsy.

[0049] Embodiment 16 is any one of the methods of the preceding embodiments, wherein the cells are derived from a tumor biopsy.

[0050] Embodiment 17 is any one of the methods of the preceding embodiments, wherein the cells are derived from one or more core biopsies including a core biopsy from about a 14-gauge core to about a 20-gauge core.

[0051] Embodiment 18 is any one of the methods of the preceding embodiments, wherein the cells are derived from one or more 18-gauge core biopsies.

[0052] Embodiment 19 is any one of the methods of the preceding embodiments, wherein the cells are derived from one or more cancer tumor biopsies.

[0053] Embodiment 20 is the method of Embodiment 19, wherein one or more cancers include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof.

[0054] Embodiment 21 is the method of any one of the preceding embodiments, wherein the cells are derived from one or more patients.

[0055] Embodiment 22 is the method of any one of the preceding embodiments, wherein the cells include CRC patient-derived xenograft (PDX) cells.

[0056] Embodiment 23 is the method of any one of the preceding embodiments, wherein the MOS includes tumor-like masses.

[0057] Embodiment 24 is the method of any one of the preceding embodiments, wherein the MOS includes tumor-like mass-like structures in the presence of tumor-resident immune cells.

[0058] Embodiment 25 is the method of any one of the preceding embodiments, wherein a plurality of nascent MOS are formed by mixing, and then MOS are formed.

[0059] Embodiment 26 is the method of any one of the preceding embodiments, wherein the nascent MOS includes a seeding density of about 20 to about 100 cells per droplet.

[0060] Embodiment 27 is the method of any one of the preceding embodiments, wherein the nascent MOS includes a seeding density of about 20 to about 50 cells per droplet.

[0061] Embodiment 28 is the method of any one of the preceding embodiments, wherein the nascent MOS includes a seeding density of about 30 to about 70 cells per droplet.

[0062] Embodiment 29 is the method of any one of the preceding embodiments, wherein the nascent MOS includes a seeding density of about 40 to about 60 cells per droplet.

[0063] Embodiment 30 is any one of the methods of the preceding embodiments, wherein the nascent MOS includes a seeding density of about 50 to about 100 cells per droplet.

[0064] Embodiment 31 is any one of the methods of the preceding embodiments, wherein the nascent MOS includes a seeding density configured to generate tumor-like masses of a desired quantity, size, or both within the MOS.

[0065] Embodiment 32 is any one of the methods of the preceding embodiments, further comprising determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet.

[0066] Embodiment 33 is any one of the methods of the preceding embodiments, further comprising treating the MOS with one or more therapeutic agents.

[0067] Embodiment 34 is the method of Embodiment 33, wherein the one or more therapeutic agents include small molecules or antibodies.

[0068] Embodiment 35 is any one of the methods of the preceding embodiments, wherein the treatment includes delivering one or more therapeutic agents at a concentration of about 1 μM to about 10 μM.

[0069] Embodiment 36 is any one of the methods of Embodiments 32 - 34, wherein the one or more therapeutic agents include oxaliplatin, irinotecan, or a combination thereof.

[0070] Embodiment 37 is any one of the methods of the preceding embodiments, wherein the treatment is performed within 11 days after biopsy acquisition.

[0071] Embodiment 38 is any one of the methods of the preceding embodiments, wherein the treatment is performed within 5 days after biopsy acquisition.

[0072] Embodiment 39 is any one of the methods of the preceding embodiments, wherein the treatment is performed within 3 days after biopsy acquisition.

[0073] Embodiment 40 is any one of the methods of the preceding embodiments, wherein each MOS contains at least 30 tumor cells.

[0074] Embodiment 41 is any one of the methods of the preceding embodiments, wherein each MOS contains at least 20 tumor cells.

[0075] Embodiment 42 is any one of the methods of the preceding embodiments, wherein each MOS contains at least 10 tumor cells.

[0076] Embodiment 43 is any one of the methods of the preceding embodiments, wherein each MOS contains from about 10 to about 50 tumor cells.

[0077] Embodiment 44 is any one of the methods of the preceding embodiments, wherein the MOS functions as a predictive model of a patient's sensitivity to one or more drug therapies for treating a disease.

[0078] Embodiment 45 is any one of the methods of the preceding embodiments, wherein the MOS functions as a predictive model of a patient's sensitivity to one or more chemotherapy regimens.

[0079] Embodiment 46 is any one of the methods of the preceding embodiments, wherein the MOS functions as a predictive model of a patient's sensitivity to one or more chemotherapy regimens within 14 days.

[0080] Embodiment 47 is any one of the methods of the preceding embodiments, wherein the MOS contains a lower amount of fibroblasts than that found in a relatively bulk organoid culture.

[0081] Embodiment 48 is the method of Embodiment 47, wherein the amount of fibroblasts in the MOS is lower than that found in a relatively bulk organoid culture after 2 days of culture.

[0082] Embodiment 49 is the method of Embodiment 47, wherein the amount of fibroblasts in the MOS is lower than that found in a relatively bulk organoid culture after 5 days of culture.

[0083] Embodiment 50 is the method of Embodiment 47, wherein the amount of fibroblasts in the MOS is less than the amount found in a relatively bulky organoid culture after 7 days of culture.

[0084] Embodiment 51 is the method of any one of the preceding embodiments, wherein the MOS contains functional immune cells.

[0085] Embodiment 52 is the method of any one of the preceding embodiments, wherein the MOS contains immune cells that respond to immunotherapy.

[0086] Embodiment 53 is the method of any one of the preceding embodiments, wherein the MOS contains natural killer cell markers.

[0087] Embodiment 54 is the method of any one of the preceding embodiments, wherein the natural killer cell markers include CD4+, CD8+, CD56+, and combinations thereof.

[0088] Embodiment 55 is a method for predicting a patient's response to a therapeutic treatment, the method comprising co-culturing patient-derived micro-organospheres (MOS) with a drug related to immunotherapy and analyzing the MOS to determine the efficacy of the immunotherapy.

[0089] Embodiment 56 is the method of Embodiment 55, wherein the immunotherapy is cancer immunology (IO) therapy.

[0090] Embodiment 57 is the method of Embodiment 55 or 56, wherein the drug includes an immune checkpoint inhibitor, a T cell activator, tumor infiltrating lymphocytes (TIL), an IO therapy molecule, or a combination thereof.

[0091] Embodiment 58 is the method of Embodiment 57, wherein the immune checkpoint inhibitor includes anti-PD1 therapy (e.g., nivolumab).

[0092] Embodiment 59 is the method of Embodiment 57, wherein the IO therapy molecule comprises a PD-1 inhibitor, a T cell bispecific antibody (TCB), or both.

[0093] Embodiment 60 is the method of Embodiment 55, wherein the immunotherapy targets human leukocyte antigen (HLA), an antigen related to HLA, or both.

[0094] Embodiment 61 is the method of Embodiment 55, wherein the drug comprises a T cell receptor mimetic antibody.

[0095] Embodiment 62 is the method of Embodiment 55, wherein the T cell receptor mimetic antibody comprises ESK1, DP47, or both.

[0096] Embodiment 63 is any one of the methods of Embodiments 55 - 62, wherein the drug is present in an amount of about 0.1 μg / mL to about 10 μg / mL.

[0097] Embodiment 64 is any one of the methods of Embodiments 55 - 63, wherein the drug is present in an amount of about 0.5 μg / mL to about 5 μg / mL.

[0098] Embodiment 65 is any one of the methods of Embodiments 55 - 64, wherein the drug is present in an amount of about 1 μg / mL to about 3 μg / mL.

[0099] Embodiment 66 is any one of the methods of Embodiments 55 - 65, and includes determining the amount of cell apoptosis that occurred within the tumor-like mass present within the MOS after the initiation of immunotherapy.

[0100] Embodiment 67 is any one of the methods of Embodiments 55 - 66, and this method provides a predictive model over at least 12 months.

[0101] Embodiment 68 is any one of the methods of Embodiments 55 - 67, and this method provides a predictive model over at least 6 months.

[0102] Embodiment 69 is any one of Embodiments 55 to 68, and this method is a method that provides a prediction model over at least three months.

[0103] Embodiment 70 is a method for treating a patient, and this method includes (a) predicting the patient's response to the therapeutic treatment described in Embodiment 55, and (b) selecting a therapy based on the predicted patient response.

[0104] Embodiment 71 is a method for predicting a patient's response to a therapy, and this method includes (a) co-culturing patient-derived micro-organospheres (MOS) with effector immune cells, and (b) analyzing the MOS to determine the efficacy of the therapy by the effector immune cells.

[0105] Embodiment 72 is the method of Embodiment 71, wherein the effector immune cells are selected from the group consisting of chimeric antigen receptor (CAR) T cells, tumor-infiltrating lymphocytes (TIL), peripheral blood mononuclear cells (PBMC), T cells isolated from PBMC, T cells isolated and expanded from tumor cells, and combinations thereof.

[0106] Embodiment 73 is any one of Embodiments 55 to 72, wherein the MOS is formed by any one of the methods of Embodiments 1 to 54.

[0107] Embodiment 74 is a micro-organosphere composition comprising a plurality of MOS, each MOS comprising a substrate and at least one tumor-like mass, and the plurality of MOS comprising a predetermined number of cells per droplet, a predetermined number of droplets in the composition, and / or a predetermined droplet size.

[0108] Embodiment 75 is the composition of Embodiment 74 comprising one or more drug therapies.

[0109] Embodiment 76 is the composition of Embodiment 74, wherein at least one tumor-like mass responds to one or more drug therapies.

[0110] The present invention is further described in the following examples, which do not limit the scope of the present invention described in the claims.

Example

[0111] Realization of clinical precision oncology by patient-derived MOS Methods and Materials Manufacture and design of the microfluidic chip: The microfluidic chip was manufactured from a silicon wafer (Wafer Pro, Santa Clara, CA). Details of the manufacture of microfluidic features in silicon are described elsewhere (Rius et al., "Introduction to Micro- / Nanofabrication," In: Bhushan B. (eds) Springer Handbook of Nanotechnology. Springer Handbooks. Springer, Berlin, Heidelberg, 2017). Briefly, the design was imprinted onto a 6-inch silicon wafer using standard photolithography techniques, and the features were etched using deep reactive ion etching (DRIE) in a cleanroom facility. After washing, a borofloat glass coverslip (PG&O; Santa Ana, CA) was bonded to the silicon chip using anodic bonding. After bonding, the microfluidic channels were made hydrophobic using Aquapel (Aquapel glass; Cranberry Twp, PA). After coating, the channels were rinsed with 3 mL of Novec 7500 engineering fluid (3M; Saint Paul, MN) and then baked at 60°C for 20 minutes.

[0112] MOS Generator Assembly: MOS generation was carried out inside a 1.7 cubic feet mini-refrigerator so that the temperature-sensitive gel would not polymerize during generation. A pressure source of Fluigent FlowEZ (Fluigent; La Kremlin-Bicetre, France) was attached to the top of the refrigerator. An air tube was connected through two drilled holes through the top of the refrigerator to the reagent and sample reservoir PCaps (Fluigent). The pump was manually operated according to the manufacturer's recommendations. The chip was assembled inside a custom-made manifold containing ports for connecting the reagent and sample reservoir to the chip. All components were placed inside the refrigerator. The door was kept closed when processing temperature-sensitive materials. MOS generation was imaged by assembling the camera and lens components listed in Table 3 and placing the camera directly above the chip.

[0113] Patient Specimens: Tissue sections (approximately 1 - 2 cm3) of colorectal cancer, lung cancer, ovarian cancer, kidney cancer, breast cancer, and non-tumor tissue with distant metastases were obtained from surgically resected specimens provided by the Duke BioRepository&Precision Pathology Center (BRPC) with patient consent. The entire experimental protocol was carried out in accordance with the facility's guidelines. The samples were confirmed to be tumor or normal tissue by histopathological evaluation. The IRB approval (IRB#Pro00089222) and research protocol were approved by the IRB of the relevant facility.

[0114] Treatment of tumor tissues and generation of MOS: All tumor and non-tumor tissues were stored on ice in transfer medium after dissection. 10% of the tissue samples were immediately frozen with OCT, and the rest were minced and then mixed with 10 mL of enzyme solution. The enzyme solution consisted of a collagenase-based digestion solution containing CaCl2 (3 mM), collagenase (1 mg / mL) (Sigma catalog number 11088858001), DNase I (0.1 mg / mL) (STEMCell technology catalog number 07900), Y-27632 (10 μM) (STEMCell technology catalog number 72302), and primocin (100 μg / mL) (Fisher Scientific catalog number NC9141851). The minced tissue samples were dissociated by gently stirring in the enzyme solution at 37 °C for 30 minutes before the first cell quality check. If large cell clumps were observed, digestion was continued for an additional 15 - 20 minutes until the tissue was mostly dissociated into single cells. After digestion, the cells were filtered through a 70 μM cell strainer, and the yield and cell viability were measured with a Countess II cell counter using the trypan blue method described above. The initial number of cells inserted into the MOS varied depending on the intended use. For example, in clonal diversity studies, 1 tumor cell per MOS was used, but usually, in chemotherapy tests, 20 tumor cells per MOS were used, which provides an optimal trade-off between the rate of establishment of tumor-like masses and the number of MOSs for testing various conditions. For the IO assay, 30(30) - 50 tumor cells per MOS (and a proportional number of immune cells from the same digested sample) were more suitable. As a comparison, the same cell density was seeded using the conventional MATRIGEL® method. The emulsified MOS was layered with tumor medium and seeded into 6-well low-binding plates. The cells in MATRIGEL® were loaded into 24-well plates and grown in tumor medium. The medium was changed every 3 days.

[0115] H&E staining of the original tumor and MOS: Tissues and MOS were processed for paraffin sections. MOS embedded in MATRIGEL® was collected after centrifugation at 100 g for 3 minutes in a 15 mL tube. The supernatant was removed, and MOS was fixed in 2% paraformaldehyde (PFA) containing 0.1% glutaraldehyde at room temperature for 30 minutes, then washed with 1X PBS and embedded in histogel. After formalin fixation, fresh cancer tissues were embedded in paraffin. After deparaffinization, 5-μm sections were stained with hematoxylin and eosin (H&E). MOS and primary tumor sections were evaluated by a pathologist for morphological characterization.

[0116] Imaging of MOS and organoids: Images of MOS and organoids in bulk MATRIGEL® were acquired using a Leica microscope (Leica, USA) on days 1, 3, 5, and 7 after the first plating, and the organoid surface area was quantified using ImageJ software (Wayne Rasband, NIH, USA; imagej.nih.gov / ij). To calculate the average size (area) of the organoids, more than 40 tumor-like masses of MOS or organoids in MATRIGEL® from each tumor sample were manually quantified, and statistical analysis was performed using Prism8.

[0117] Genomic and transcriptomic analysis of MOS matching tumor tissue samples DNA extraction and WES sequencing: MOS developed on day 7 was collected for DNA extraction. DNA was extracted using the Zymo Quick-DNA Microprep kit (Zymo Research #D2030) according to the manufacturer's protocol. DNA was quantified using NanoDrop. Tumor-derived MOS matching the tumor samples was analyzed using whole-genome sequencing (WES) by Novagene using an Illumina Novaseq6000 sequencer.

[0118] Analysis of the MOS mutation profile consistent with tumors: A total of more than 0.4 μg of DNA per sample was used as input. The effective sequencing depth exceeded 50-fold (6G) per sample. Before alignment, adapters were trimmed from the raw sequence data using TrimGalore. Subsequently, the resulting fastq files were aligned to the human reference genome (hg38) using BWA. Duplicate BAM files from the matching samples were merged and filtered to remove duplicates and non-chromosomal reads. Then, sequence variants were called using the GATK HaplotypeCaller pipeline (version 4.2.0). Variants were filtered based on quality by depth (QD < 2.0), mapping quality (MQ < 40.0), Fisher strand (FS > 60.0), strand odds ratio (SOR > 4.0), mapping quality rank sum (MQRankSum < -12.5), and read position rank sum (ReadPosRankSum < -8.0). Finally, snpEff was used to annotate the mutations.

[0119] Disruptive variants (e.g., missense, stop gain, disruptive in-frame indels, 3 / 5’UTR, splice acceptor, and splice donor variants) were selected for downstream analysis. Each unique mutation (classified as a specific position-base-alternative combination) was binarized for each sample according to presence and absence. The resulting binary vectors were used to calculate the Jaccard similarity score and generate Venn diagrams and presence-absence tables. Genes represented in the presence-absence table (not shown) were limited to the 25 most commonly mutated genes for each cancer type according to The Cancer Genome Atlas (TCGA).

[0120] Preparation and data analysis of Drop-seq gene expression libraries: Frozen PBMCs were thawed, and counted and cell viability was measured using a Countess II. For single-cell RNA-seq, 200K cells were aliquoted, centrifuged, resuspended in 30 μl of PBS + 0.04% BSA + 0.2 U / μl of RNase inhibitor, and counted using a Countess II. scRNA Drop-seq libraries were generated using a Dolomite Nadia machine according to the manufacturer's protocol. Libraries were pooled and sequenced using an Illumina NovaSeq platform targeting to reach saturation or an average of 20,000 unique reads per cell. Sequence data were used as input to the Drop-seq pipeline published by the Broad Institute (github.com / broadinstitute / Drop-seq). Gene count matrices were created using the first 4,000 cell barcodes with the maximum number of reads associated with each index.

[0121] Preparation and data analysis of 10x Next GEM 3' single-cell library: For single-cell RNA-seq of MOS and original tissue tumor cells treated with ESK1* drug, MOS was first generated from lung tumor tissue (case #805). After adding ESK1* drug (1 μg / mL) to the medium for 24 hours on the 5th day of MOS, the cells were collected and the scRNA seq library was prepared. During library preparation, 200K cells were aliquoted, centrifuged, resuspended in 30 μl of PBS + 0.04% BSA + 0.2 U / μl of RNase inhibitor, and counted using CountessII. Generation of GEM, cleanup after GEMRT, amplification of cDNA, and construction of the library were performed according to the 10XGenomics single-cell 3' v3.1 chemistry. Quality was evaluated using the Agilent DNA TapeStation screening assay. Next, the libraries were pooled aiming to reach saturation or an average of 20,000 unique reads per cell, and sequenced using the Illumina NovaSeq platform. The sequence data was used as input to the 10x Genomics Cell Ranger pipeline to demultiplex the BCL files, generate FASTQ, and generate feature counts for each library.

[0122] Dimensionality reduction and cell type annotation: The gene barcode matrix generated using the DigitalExpression script of the Broad Drop-seq pipeline was analyzed using Seurat3 with default parameters unless otherwise specified. Cells with more than 2,500 detected genes were excluded from the analysis. Counts were log-normalized, and the top 2,000 variable features were identified. Principal component analysis was performed using these variable genes, and the top 30 principal components were used for downstream analysis. UMAP dimensionality reduction was performed using the top 20 principal components identified using the Harmony package. Graph-based clustering was performed with a resolution = 1. Cell types were inferred using the HumanPrimaryCellAtlasData(rdrr.io / github / LTLA / celldex / man / HumanPrimaryCellAtlasData.html) function of the SingleR package. Labels were confirmed by identifying differentially expressed genes using the Seurat's FindAllMarkers function (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / FindAllMarkers) and visualizing marker genes plotted as kernel density on UMAP using the Nebulosa package. To perform differential expression analysis, cell type labels were classified into four groups: tumor cells, fibroblasts, lymphoid cells, and myeloid cells.

[0123] Pseudo-bulk differential expression analysis: Three biological replicates from lung cancer patients were used for pseudo-bulk differential expression analysis. Specifically, the gene expression changes between the two platforms were determined by comparing the dataset generated from the primary tissue with the dataset generated from MOS. Gene values from cells with the same cell type label were aggregated into a single matrix. The model design formula included a term indicating whether the sample was generated from the primary tissue or MOS. The significance test was performed using the glmQLFit function of the EdgeR package (www.rdocumentation.org / packages / edgeR / versions / 3.14.0 / topics / glmQLFit), and false discovery rate adjustment was performed on the p-values. Genes with an absolute log-fold change greater than 1 and an adjusted p-value less than 0.05 were considered to be significantly differentially expressed between the two conditions. The intersection of the lists of differentially expressed genes for each cell type was visualized as an UpSet plot using the UpSetR package. Volcano plots were generated for the pseudo-bulk results of each cell type using the EnhancedVolcano package and the same significance threshold.

[0124] The remaining two samples were collected from patients with renal cancer (n = 1) or ovarian cancer (n = 1). For these samples, the log-fold changes in gene expression of the libraries generated from the primary tissue or MOS were compared, but no p-values were reported. The gene counts for each cell type were averaged using the AverageExpression function of Seurat (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / AverageExpression), and the log-transformed values were plotted to compare the samples generated from the primary tissue and MOS. To provide the context of genes highly expressed in each cell type, genes with a log-fold change greater than 1 were labeled in red, and genes with an average log-expression greater than 1.5 were labeled in black.

[0125] Identification of conserved gene expression: The Seurat FindConservedMarkers function (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / FindConservedMarkers) was applied to cells of each cell type to identify genes with conserved expression and log-fold change enrichment greater than 0.5. The top 5 markers with the highest log-fold change enrichment for each cell type were visualized using the Seurat DotPlot function (satijalab.org / seurat / reference / dotplot). The important cancer gene expression markers CD274 (PD-L1), PDCD1 (PD-1), and TGFB1 (TGF-beta) were also specifically visualized to compare their expression in tumor cells, lymphoid cells, and fibroblasts, respectively. The expression of these markers was plotted as a UMAP using the Nebulosa package and labeled on each volcano plot.

[0126] Flow cytometry analysis: MOS and bulk MATRIGEL® established by day 7–9 were dissociated into single cells using TrypLE treatment and incubated at 37°C for 5 minutes. The dissociated cells were washed with PBS + 0.04% BSA and stained with either anti-human vimentin antibody conjugated to PE (CST catalog number, 1:100) or anti-human EpCAM (Biolegend catalog number 324205, 1:250) at room temperature for 20 minutes. After washing the cells again with PBS + 0.04% BSA, they were stained with goat anti-mouse Alexa Fluro 488 secondary antibody (Invitrogen catalog number A32723) at room temperature for 15 minutes. Prior to the flow assay, the cells were washed once more with PBS + 0.04% BSA. To exclude dead cells in the assay, Sytox blue dead cell stain (A34857) was added at a 1:1000 dilution. All flow assays were performed using a Sony SH800 FACS sorter, and the flow data were analyzed using FlowJo.

[0127] Drug high-throughput screening: Automated liquid handling was provided by an Echo Acoustic Dispenser (Labcyte) for drug administration and a Well mate (Thermo Fisher) for cell plating. The assay was performed using a Clarioscan plate reader (BMG Labtech). Immediately before plating the cells, 119 FDA-approved drug compounds were stamped onto 384-well plates at a final concentration of 1 μM. The compound library (approved oncology set VI) was provided by the NCI Developmental Therapeutics Program (https: / / dtp.cancer.gov / ). MOS were plated at 100 MOS / well onto these pre-coated drug plates, and each MOS contained 30 cells / droplet. Cell viability was evaluated by the CellTiter-Glo luminescent cell viability assay (Promega, USA) 72 hours after cell plating. The percentage of cytotoxicity was quantified using the following formula: 100 * [1 - (average CellTiterGlo 薬物 / average CellTiterGlo 対照 )].

[0128] HLAA2 plasmid, lentivirus packaging, and MOS infection: HLA-A2 (insert) was amplified from a cDNA library prepared from RNA from NCI-H1755 (ATCC, CRL-5892) using the sense primer GGTCGCCACCATGGCCGTCATGGCTCCCCG (SEQ ID NO: 1) and the antisense primer GGCCGCTTTACACTTTACAAGCTGTGAGAG (SEQ ID NO: 2). The linear plasmid (recipient) was amplified from the pLenti CMV GFP Puro plasmid (Addgene: 17748) using the sense primer TTGTAAAGTGTAAAGCGGCCGCGTCGACAA (SEQ ID NO: 3) and the antisense primer TGACGGCCATGGTGGCGACCGGTGGATCCT (SEQ ID NO: 4). The PCR products (both insert and vector) were purified using Gel DNA Recovery Kits (Zymo, D4007). Subsequently, the insert was cloned into the vector by Gibson assembly (NEB, E2611S). Lentivirus particles were generated by co-transfecting HEK293T cells using Lipofectamine2000 transfection. Briefly, HEK293T cells were co-transfected with 10 μg of the transgene plasmid, 10 μg of the packaging plasmid pCMVR8.74 (Addgene: 22036), and 5 μg of the envelope plasmid pMD2.G (Addgene: 12259). After 12 hours, the transfection medium was replaced. Recombinant lentivirus was harvested at 24 hours and 48 hours. Subsequently, the supernatant containing virus particles was concentrated using the Lenti-X Concentrator Kit (Takara, 631232). Then, the concentrated lentivirus particles were aliquoted and stored at -80 °C until use.

[0129] MOS infection by HLA-A2-expressing lentivirus: When MOS was established, HLA-A2- and DsRed-expressing lentiviruses were added to the MOS cultures of lung tumors (MOI = 5 - 6). After 3 days of incubation, the infection efficiency was evaluated by observing the expression of DsRed under a microscope. HLA-A2 gene expression and HLA-A2 antigen expression were evaluated using flow cytometry.

[0130] RNA extraction and qRT-PCR: To quantify HLA-A2 gene expression in lung tumor samples, RNA was extracted using the Norgen Single Cell RNA Purification Kit (Norgen Biotek catalog number 51800). cDNA reverse transcription was performed using SuperScript IV Vilo MasterMix with ezDNase (Thermo Fisher catalog number 11756050). The HLA-A2 gene was amplified using the forward primer TGAAGGCCCACTCACAGACTC (SEQ ID NO: 5) and the reverse primer CCCACGTCGCAGCCATACATC (SEQ ID NO: 6).

[0131] Cancer immunology potency assay Human peripheral blood mononuclear cells (PBMC) and patient TIL expansion: Human PBMC were purchased from STEMCell technology (catalog number 70025.1). Tumor TIL were generated from dissociated tumor tissue cells. Dissociated cells (0.5×10 6 ) were collected for TIL expansion. The cells were resuspended in IMMUNOCULT™-XF T Cell Expansion Medium supplemented with 6000 IU / mL of recombinant human IL-2 (Miltenyi Biotec catalog number 130 - 097 - 743). TIL were maintained for 1 week before splitting and the medium was changed to medium containing CD3 / CD28 / CD2 T cell activator (STEMCell technology, catalog number 10971) for further expansion.

[0132] ESK1* Drug Preparation: ESK1* TCB and negative TCB (DP47) were provided by Roche. To avoid multiple freeze-thaw cycles, the drugs were aliquoted immediately upon receipt. In all potency assays, the drugs were used at 1 μg / mL or 10 μg / mL.

[0133] IO Assay and Incucyte Live Cell Imaging: MOS generated from primary tumor tissue were plated at a density of 30 - 50 MOS per well in 96-well plates supplied with medium without Y compound. On day 3 or 4, MOS were treated with ESK1*, DP47, or nivolumab for at least 3 days and imaged with Incucyte during treatment. When performing the immune cell potency assay, pre-activated PBMC or matched TIL were stained with Cytolight Rapid Red dye according to the manufacturer's instructions. Briefly, the Cytolight Rapid Red dye in one vial was diluted with 20 μl of DMSO and further diluted 10-fold with PBS. PBMC or TIL were incubated with 5 μl of Cytolight Red dye (500X) diluted in PBS at 37°C for 25 minutes. After washing once with PBS, PBMC or TIL were counted and resuspended in wells containing MOS and medium at an effector:target ratio of 5:1 or 10:1. According to the manufacturer's instructions, annexin V green dye, caspase 3 / 7 green dye, or Cytotox green dye was added to each well. The plates were loaded onto an Incucyte S3 and imaged every 2 hours for 4 - 5 days.

[0134] Immunotherapy and IO assay with MHC block: MOS of lung tumors were incubated at 37°C for 45 minutes with anti-MHCI / II antibody (W6 / 32; Tu39, catalog number 361702, Biolegend) at a concentration of 20 μg / mL, and then plated at a density of 30 - 50 MOS per well in a 96-well plate supplied with lung tumor medium without Y-27632. MOS not blocked by MHC were used as a control. Matched TIL were added to each well at an effector:target ratio of 5:1. Nivolumab was added to the wells at a working concentration of 10 μg / mL. CD2 / CD3 / CD28 T cell activation reagent was added at a working concentration of 25 μl / mL. Annexin V was added to each well according to the manufacturer's instructions.

[0135] Incucyte imaging data analysis: Raw images from the green and red fluorescence channels of the phase wand were exported, and MOS were manually drawn using "Labelme" image annotation software. Next, the fluorescence images and labels were input into a Python script, the images were binarized using a certain threshold, all pixels of the red image exceeding the threshold were counted as "red", all pixels of the green image exceeding the threshold were counted as "green", and all pixels exceeding the threshold in both the red and green images were counted as "yellow". Next, these pixels were grouped according to which MOS (if any) they belonged to, and the script exported a CSV file containing the number of red, green, and yellow pixels contained within that MOS at that time point for each well, each time, and each MOS labeled in the associated images.

[0136] Quantification and statistical analysis: A t-test was performed using Prism 8.0. p < 0.05 was considered significant.

[0137] Generation and establishment of MOS To establish a precision medicine pipeline that can be used as a guide for patient care, droplet-based microfluidic technology has been developed to rapidly generate patient-derived cancer models in a reliable manner (Figure 1A). The basic principle is to generate microfluidic-based droplet MOS by mixing cells suspended from primary tissue with a three-dimensional extracellular matrix (MATRIGEL®) and then with a biphasic liquid (oil). The generated MOS was demulsified to remove excess oil and then cultured as a suspension droplet.

[0138] The basis of the pipeline is a benchtop machine for generating MOS (Figures 1B and 2A, Table 3). Important design features of this device include reservoirs for directly loading both the oil phase and the sample phase into a custom microfluidic chip, and a reservoir for subsequently placing a sample outlet on the back of the chip for direct dispensing into a MOS collection container. An attached pressure source (e.g., Fluigent FlowEZ) was used to control the flow of oil and sample fluids into the custom microfluidic chip through tubes connected via a clamped manifold. A 15 mL conical tube (110) containing oil and a 1.5 mL Eppendorf tube (120) containing a cell / MATRIGEL® sample mixture stored on ice were pressurized to drive the flow through the microfluidic chip seen within the chip holder (130). The device was placed in a refrigerator together with tubes connected to an external pump (140). The sample and oil contacted at a "T"-shaped junction (Figure 1B), where the sample was "pinched" into droplets by the oil phase as it entered the collection channel. This system was compatible with temperature-sensitive MATRIGEL®. Since both a 4°C sample block and a 37°C collection block were integrated into the device, MATRIGEL® was able to pass through the microfluidic channels and rapidly solidify at high temperatures. The height of the channels and chambers was designed to generate MOS with an average diameter of 250 μm to 450 μm, and these dimensions provided a 3D environment suitable for various cell numbers and sizes. This device can generate MOS from as few as 15,000 cells from an 18-gauge core biopsy, but generally the sample size is too small to reliably generate conventional organoids for therapeutic profiling within clinical time constraints.

[0139] This device was first used to generate MOS from CRC PDX cells. The growth of CRC MOS was monitored at different seeding densities (20 - 100 cells per droplet), demonstrating that MOS established tumor-like mass-like structures (Figure 1C). The number and size of the tumor-like masses increased with the seeding density per droplet. Subsequently, MOS was generated from clinical CRC biopsies (Figure 1D) and shown to have various morphologies (Figure 1E). The number of MOS was determined by dividing the number of viable cells by the number of cells per droplet.

[0140] Prediction of patient drug response in a prospective clinical study by MOS Since clinical treatment decisions are often made within 10 - 14 days after diagnosis, an ideal diagnostic assay would provide results within 14 days and predict clinical outcomes using minimal tissue (e.g., core biopsy). In an initial study, biopsies were taken from patients presenting with metastatic rectal cancer, and MOS (30 tumor cells per MOS) were established within 8 days from the biopsies. In vitro high-throughput drug screening was performed by treating the MOS with an Approved Oncology Set VI panel (provided by the NCI Developmental Therapeutics Program) containing 119 different FDA-approved small molecule inhibitors at a concentration of 1 μM and then analyzing the treatment response. The MOS were sensitive to oxaliplatin (% kill rate > 50%) and resistant to irinotecan (% kill rate < 50%) (Figure 1F). The entire process was completed within 11 days from biopsy acquisition. Consistent with the prediction by MOS, the patient's tumor responded to oxaliplatin-based treatment even 6 months later (Figure 1G).

[0141] Subsequently, a prospective clinical study was designed and conducted. Core biopsies (18-gauge) were taken from an additional seven patients presenting with CRC with distant metastases, MOS were generated, and drug tests were performed (Figures 1H and 1I). Patient demographics and mutation status are shown in Table 1. MOS (30 tumor cells per MOS) were generated, and the response to oxaliplatin was examined within 13 days (mean 9.9 days) from biopsy for all eight biopsy samples, with a success rate of 100% (8 / 8) (Table 2). Considering the limited amount of tissue, doses of 1 μM and 10 μM were selected based on studies disclosed elsewhere (Vlachogiannis et al., Science 359, 920-926, 2018, Ooft et al., Science Translational Med 11, 2019; Ganesh et al., Nat Med 25, 1607-1614, 2019; and Yao et al., Trends Immunol 41, 652-664, 2020). The same cutoff as measured by Cell Titer Glo was used. Of the eight patients, four had oxaliplatin-sensitive MOS and four had oxaliplatin-resistant MOS (Figure 1J).

[0142] All eight patients received oxaliplatin-based treatment according to normal treatment guidelines. Subsequently, the patient outcomes were evaluated by CT scans before and after oxaliplatin treatment (Figures 2B-2H), and the treatment duration was compared with MOS oxaliplatin sensitivity. All four patients with MOS sensitive to oxaliplatin responded clinically and continued treatment for over 20 weeks (three of the four continued treatment for nearly 40 weeks), while three of the four patients with resistant MOS did not respond to oxaliplatin treatment and discontinued treatment within 10 weeks (Figure 1J). The remaining patient in the resistant MOS group showed various responses to treatment on the first CT scan, but considering the clinical benefit, the patient continued treatment. Subsequent CT scans showed a response to treatment, and the patient continued treatment until 28 weeks, after which a liver resection was performed to remove metastatic lesions (Figure 2B and Table 2).

[0143] This proof-of-concept clinical study suggests that MOS can be reliably generated from 18-gauge biopsies of CRC tumors with distant metastases and used to test sensitivity to frontline chemotherapy within 14 days. Our initial results indicate that this workflow can almost predict patient outcomes, but larger-scale studies are needed to further validate its clinical applicability.

[0144] Cell death in each MOS was measured by imaging the caspase 3 / 7 fluorescence signal and normalizing it by the cell surface area within each MOS. Treating two available CRC MOS strains (20 cells per MOS) resistant to oxaliplatin showed heterogeneity among different MOSs, with only the highest dose inducing significant cell death (Figures 3A and 3B).

[0145] Tumor stromal cells and immune cells in MOS Since the tumor microenvironment, especially the immune component, can affect cancer treatment, studies were conducted to characterize the stromal components of patient-derived MOSs. Focusing on lung tumors due to their response to immunotherapy, although to a lesser extent, tumors of the kidney, breast, CRC, and ovary were also characterized. MOSs were generated at a density of 30 tumor cells per MOS with 70% MATRIGEL® diluted in medium, and bulk organoids were simultaneously established using cells at the same density for comparison. Representative photos of MOSs generated from each tumor type, as well as H&E staining from each tumor tissue and MOS, are shown in Figures 3C, 3D, and 4A. The formation and growth of MOSs and bulk organoids were comparable on days 2, 5, and 7 (Figure 3E).

[0146] Fibroblast overgrowth often poses a challenge in establishing organoids from clinical samples of specific cancer types. The number of fibroblasts in MOS cultures and bulk organoid cultures between days 7 and 9 was compared. As confirmed by flow cytometry analysis of vimentin expression (Figure 5A), fewer fibroblasts were observed in MOS compared to bulk organoid cultures (Figure 3F). Next, rapid and high-throughput chemotherapeutic drug screening was performed on MOS generated from patients with lung cancer, ovarian cancer, and kidney cancer, and the sensitivity to drugs commonly used in the treatment of these cancers was measured.

[0147] The whole exome sequence of MOS was compared with the matching original tumor specimen to determine whether genomic changes were maintained (Table 4). First, copy number variations (CNVs) were characterized. Similar amplification and loss patterns were seen in MOS and original tissues from lung cancer (Figure 4B) and other cancer types (Figure 5B). Second, somatic mutations in the genomes of matching MOS and original tumor samples were characterized. For each cancer type, the mutation profiles of the matching tissue specimens and MOS were highly correlated, while non-matching samples were not (Figure 5C). Mutants were common between the MOS that matched the tissue specimens (Figure 5D). Driver mutations were generally consistent between tissue specimens and MOS among the genes commonly affected in each cancer type, with a sensitivity (mutations detected in tumor tissue were also detected in MOS) of 85% ± 0.007 and a specificity (mutations not present in tumor tissue were not present in MOS) of 95% ± 0.003 (Figure 5E). These results suggest that MOS mainly captures the genomic profile of the tumors of the patients from whom they are derived.

[0148] To compare the types of tumor and stromal cells between the tissue and the derived MOS, single-cell RNA sequencing (Macosko et al., Cell 161, 1202-1214, 2015) was performed on six pairs of matching patient tumor specimens (three lung cancers, one kidney, one ovarian cancer, one CRC) and the derived MOS (7-9 days). The overview of QC is shown in Figures 6A and 6B. Cells from all three lung tumor samples were clustered into four groups marked as either tumor cells, cancer-associated fibroblasts, or lymphoid or myeloid immune cells using UMAP reduction, and these cells were consistent between the tissue and the MOS (Figure 4C), and the relative abundances were also equivalent (Figures 4D and 6C). Similar single-cell RNA-seq analyses were performed on the kidney cancer, ovarian cancer, and CRC pairs (Figures 6D-6F). The presence of the major immune cell populations in the CRC MOS was confirmed by flow cytometry analysis (Figure 7A). In the pseudo-bulk analysis, it was shown that the overall gene expression levels were equivalent between the primary tissue and the MOS in each of these cell populations (Figure 4E), and there were relatively few differentially expressed genes (Figures 7B, 7C, and 8A). Analysis of each cell type in the lung tumor pairs revealed that lymphoid cells had differentially expressed genes compared to the other cell types (Figure 8B).

[0149] Furthermore, the expression patterns of immunosuppressive markers were almost identical between the lung tumor tissue and the MOS. The expression of cell type-specific gene markers was visualized using UMAP after automated cell type labeling by the SingleR package. CD274 (PD-L1) was mainly expressed in the tumor and myeloid cell clusters, while PDCD1 (PD-1) and TGFB1 (TGF-β) had increased expression in lymphoid cells (Figure 8C). The top five genes with the highest log-fold change enrichment in each cell type were visualized, and consistent expression in each cell type and sample preparation was confirmed (Figure 8D). These conserved markers, including the major cell type-specific markers EPCAM, PDGFRA, LYZ, and CD3E for tumor cells, fibroblasts, myeloid cells, and lymphoid cells, respectively, were almost identical between the tissue and the derived MOS (Figure 7D).

[0150] Immune cells stored in MOS that respond to immunotherapy A study was conducted to examine whether the patient's immune cells in MOS function and respond to IO therapy. When anti-CD3 antibody and anti-CD28 antibody were added to the MOS medium, it increased the CD4+, CD8+, and CD56+ (natural killer cell marker) populations and had a moderate effect on the CD11b+ (dendritic cell marker) population (Figure 9A), suggesting that the resident immune cells encapsulated in MOS survived and responded to immune stimulation.

[0151] Immune checkpoint inhibitors, especially those targeting the programmed cell death-1 (PD-1) / programmed cell death ligand-1 (PD-L1) axis, have shown promising activity in non-small cell lung cancer (NSCLC) (Han et al., Am J Cancer Res 10, 727-742, 2020). However, since PD-L1 expression and the amount of tumor mutations cannot fully predict the patient's response, there is still a very important need for in vitro assays to more appropriately guide IO therapy for patients with advanced NSCLC. MOS generated at a density of 30 tumor cells per MOS from samples of NSCLC patients formed tumor-like mass-like structures in the presence of tumor resident immune cells. Subsequently, MOS (day 4) was treated with nivolumab at 10 μg / mL of anti-PD1 therapy, and annexin V was used to evaluate cell apoptosis. Nivolumab induced the death of tumor-like masses in MOS (Figures 10A and 10B). The Incucyte measurement also included the background signal outside the tumor-like masses from cell debris in the MOS microenvironment, which caused an ascending curve in the control. In MOS (day 3) derived from renal cancer patients, nivolumab monotherapy did not enhance the death of tumor-like masses in MOS, but the combination of nivolumab and T cell activator enhanced the death of tumor-like masses (Figures 9B-9D).

[0152] Intracellular antigens presented on the cell surface by human leukocyte antigen (HLA) molecules are targets for T cell-based therapies. A study was conducted to test whether the non-selective HLA-A*02 / WT1-targeting antibody ESK1* (ESK-1 tumor binder, Roche's proprietary CD3), a T cell receptor-mimicking monoclonal antibody (mAb) that binds to both human leukocyte antigen HLA-A2 / WT1 and CD3, can induce cytotoxic T lymphocyte (CTL)-mediated killing in MOS derived from a patient's lung tumor (Figures 10C and 10D) (Dao et al., Nature Biotechnol 33, 1079-1086, 2015). The HLA-A2 genotype was verified by qRT-PCR (Figure 10E) and flow cytometry (Figure 10F). ESK1* was compared with the negative control DP47, a non-tumor-targeting T cell bispecific (CD3 arm only) antibody (TCB). ESK1* or DP47 was added to MOS medium (without Y compound) on day 5. ESK1* induced apoptosis in MOS (shown by annexin V signal) (Figure 10G). DP47 also activated T cells via CD3 and could cause cell death, but ESK1* induced more killing in all 8 lung cancer patients (Figures 10H and 10I).

[0153] Subsequently, CRC MOS (HLA A2+) was treated with ESK1*. MOS was generated at a density of 30 tumor cells per MOS. High-dose ESK1* (10 μg / mL) induced more tumor-like mass death in MOS than low-dose ESK1* (1 μg / mL) (Figures 9E and 9F). Quantification of annexin V fluorescence signal from individual tumor-like masses confirmed ESK1-mediated killing in MOS but not in organoids embedded in conventional MATRIGEL® domes (Figures 9G-9I).

[0154] To further understand how MOS reacts to ESK1*, 10x single cell RNA-seq was performed on the original lung tumor tissue cells, ESK1*, MOS treated with negative TCB (DP47) on day 0, and MOS untreated on day 5 (Figure 9J). The clusters profiled from the tissue samples and treated MOS were consistent (Figures 9K and 9L). The abundance of each cell type from DP47-treated or untreated MOS was similar to that of the original tissue cells, but dramatically decreased in ESK1*-treated MOS (Figure 9M). Collectively, these results suggest that the MOS assay can rapidly evaluate the effects of IO therapy molecules such as PD-1 inhibitors and TCBs on a patient's tumor and stromal cells.

[0155] MOS Potency Assay for T Cell Therapy Adoptive T cell therapies (ACTs), such as chimeric antigen receptor T cell (CAR-T) therapy and tumor infiltrating lymphocyte (TIL) therapy, have the potential to revolutionize cancer treatment (June et al., Science 359, 1361-1365, 2018; Waldman et al., Nat Rev Immunol 20, 651-668, 2020). However, an area of unmet need is an assay to evaluate the potency of the manufactured T cells against a patient's tumor, which is required by regulatory authorities such as the FDA to approve cell therapies (HHS and FDA, www.fda.gov / files / vaccines,%20blood%20&%20biologics / published / Final-Guidancefor- Industry--Potency-Tests-for-Cellular-and-Gene-Therapy-Products.pdf, 2011). Interferon gamma release has been used to evaluate TILs against a patient's tumor, but in at least four studies it has been shown not to correlate with clinical response (Besser et al., J Immunother 32, 415-423, 2009; Dudley et al., Clin Cancer Res 16, 6122-6131, 2010; Nguyen et al., Cancer Immunol Immunother 68, 773-785, 2019; Radvanyi et al., Clin Cancer Res 18, 6758-6770, 2012). In the case of ACT using TILs, it is necessary to rapidly establish a patient's tumor model from a portion of the biopsy (as most is needed for TIL extraction and expansion), which has been particularly challenging.

[0156] To investigate whether MOS can be used as a potential efficacy assay, the infiltration of autologous patient-derived TILs into bulk MATRIGEL® and MOS (20 cells per MOS) was evaluated. Most T cells remained around the bulk MATRIGEL® gel. In contrast, T cells readily infiltrated MOS (due to its small size and large surface area to volume ratio) and adhered to tumor cells (Figures 11A and 11B). The infiltration of peripheral blood mononuclear cells (PBMCs) into MATRIGEL® versus MOS (20 cells per MOS) was also compared using an Incucyte live imaging system, and it was revealed that immune cells could readily infiltrate MOS (Figure 12A). Time-lapse fluorescence imaging was used to measure the immunocytotoxicity of TILs and PBMCs against target tumor cells. In the TIL efficacy assay, MOS generated at a density of 30 tumor cells per MOS was grown simultaneously with TILs from the same lung tumor tissue. An increase in cell death (indicated by annexin V) was observed in MOS treated with autologous TILs (Figures 11C and 11D). This assay confirmed the efficacy of rapid expansion protocol (REP) TILs against MOS of the matching lung tumor and provided promising preliminary data as a TIL efficacy assay.

[0157] Next, the efficacy of PBMCs against MOS of lung tumors was evaluated, demonstrating that MOS can be used as an in vitro platform for cell therapy. MOS was derived from lung cancer patients and allogeneic PBMCs from another normal patient were added. Tumor-like masses within MOS survived even after 96 hours of co-culture with PBMCs and appeared orange when labeled with Cytolight Rapid Red. However, when PBMCs were activated with anti-CD3 and anti-CD28 antibodies, the tumor-like masses showed an increase in cell death as indicated by annexin V staining (Figure 12B).

[0158] The response of lung cancer MOS (20 cells per MOS) to activated PBMC was characterized using Annexin V (early-stage cell surface apoptosis), Caspase 3 / 7 (enzyme-mediated cell apoptosis), and Cytotox (cell membrane integrity). PBMC were pre-stained with the live cell marker Cytolight Red dye. Both Annexin V and Caspase 3 / 7 were able to detect MOS apoptosis, but Caspase 3 / 7 was more specific (Figures 11E, 11F, 12C, and 12D). An image analysis pipeline was developed to identify the MOS region to mask background noise from external immune cells (Figure 11G), which confirmed PBMC-induced MOS apoptosis with low background signal from outside the MOS (Figure 11H). PBMC also induced tumor mass death in CRC MOS (20 cells per MOS), which was enhanced by cytokine activation (Figures 12E and 12F), and induced tumor mass death in renal cancer MOS (20 cells per MOS), which was enhanced by a higher effector:target cell ratio (Figures 12G and 12H).

[0159] Adjuvant therapy was investigated by first combining the PD-1 inhibitor (nivolumab) with autologous TILs against the matching lung tumor MOS. The PD-1 inhibitor promoted MOS-internal TIL-mediated killing, which was suppressed by blocking MHC (Figure 12I). Next, TCB was combined with autologous TILs or allogeneic PBMCs to treat lung cancer MOS (20 cells per MOS) expressing HLA-A2. ESK1* enhanced both TIL- and PBMC-induced tumor cell death compared to DP47 (Figures 11I, 11J, 12J, and 12K). The Annexin V signal was higher in MOS treated with ESK1* compared to DP47 in all seven lung cancer samples (Figure 11K). As a negative control, ESK1* did not promote the killing of HLA-A2(−) lung cancer MOS, as indicated by the red arrow. Drug response heterogeneity among MOS from the same patient was observed and quantified (Figures 12K and 12L).

[0160] Conventional bulk organoids need to dissociate single cells to deliver viral genes before re-embedding in MATRIGEL (registered trademark). Since MOS are small in size and have a large surface area to volume ratio, they can be infected by directly adding lentivirus to the culture medium without dissociation. This provides an easy-to-use method for editing MOS at passage 0. Lung cancer MOS (20 cells per MOS) derived from HLA-A2(-) patients were infected with a lentiviral HLA-A2 expression vector together with dsRed as a control for 3 days (Figs. 11L and 12M). The infected MOS showed high expression of HLA-A2 (Figs. 11M and 11N). Next, combination therapy using ESK1* and activated PBMC was performed on HLA-A2-infected MOS. HLA-A2-infected MOS underwent more cell death in the presence of ESK1* and activated PBMC than the corresponding non-infected MOS, thus verifying that the expression level of HLA-A2 mediates the efficacy of ESK1*+PBMC treatment (Fig. 11O). [Table 1] [Table 2] [Table 3] [Table 4]

[0161] Other embodiments The present invention has been described in conjunction with its detailed description, but it is understood that the above description is intended to illustrate, and not limit, the scope of the present invention as defined by the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

1. obtaining a plurality of cells derived from a tissue; forming micro - organospheres (MOS) from the plurality of cells; culturing the MOS in a MOS culture; obtaining one or more cells infected with the virus within the MOS by introducing a virus into the MOS culture. A method comprising the steps of

2. The method according to claim 1, wherein the one or more infected cells express one or more genes introduced by the virus after being infected with the virus.

3. The method according to claim 1 or claim 2, wherein the MOS has an average diameter of about 50 μm to about 500 μm.

4. The method according to any one of claims 1 to 3, wherein the plurality of cells comprises 15,000 cells or less.

5. The method according to any one of claims 1 to 4, wherein the cells are derived from a biopsy.

6. The method according to any one of claims 1 to 5, wherein the cells are derived from a tumor biopsy.

7. The method according to any one of claims 1 to 6, wherein the cells are derived from one or more core biopsies including a core biopsy from about a 14 - gauge core to about a 20 - gauge core.

8. The method according to any one of claims 1 to 7, wherein the cells are derived from one or more 18 - gauge core biopsies.

9. The method according to any one of claims 1 to 8, wherein the cells are derived from one or more cancer tumor biopsies.

10. The method according to claim 9, wherein the one or more cancers include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof.

11. The method according to any one of claims 1 to 10, wherein the cells are derived from one or more patients.

12. The method according to any one of claims 1 to 11, wherein the cells include patient - derived xenograft (PDX) cells from CRC patients.

13. The method according to any one of claims 1 to 12, wherein the MOS includes tumor - like masses.

14. The method according to any one of claims 1 to 13, wherein the MOS is cultured in droplets, and the nascent MOS includes a seeding density of about 1 to about 300 cells per droplet.

15. The method according to any one of claims 1 to 13, wherein the nascent MOS includes a seeding density configured to generate tumor - like masses of a desired quantity, size, or both within the MOS.

16. The MOS is cultured in droplets, and the method further includes determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet, according to any one of claims 1 to 15.

17. The method according to any one of claims 1 to 16, further comprising treating the MOS with one or more therapeutic agents.

18. The method according to claim 17, wherein the one or more therapeutic agents include small molecules or antibodies.

19. The method according to any one of claims 1 to 18, wherein the cells are derived from a patient, and the MOS functions as a predictive model of the patient's sensitivity to one or more drug therapies for treating a disease.

20. The method according to claim 19, wherein the MOS functions as a predictive model of the patient's sensitivity to one or more chemotherapy treatments.

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