Patient-derived micro organ spheres (mos) implementation of clinical precision oncology

Abstract

Provided herein are methods and materials for generating and using micro-organ spheres derived from a patient (e.g., micro-organ spheres derived from tumor tissue).

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application Serial No. 63 / 338,022, filed on May 3, 2022. The disclosure of the prior application is considered part of and incorporated by reference into the disclosure of the present application.

[0003] Sequence Listing

[0004] This application contains a sequence listing, which has been submitted electronically as an XML file named "53157-0008WO1.XML". This XML file was created on May 3, 2023 and is 6,345 bytes in size. The entire contents of the materials in this XML file are hereby incorporated by reference herein. Technical Field

[0005] This article relates to methods and materials for generating and using patient-derived micro-organ spheroids. Background Art

[0006] The success of precision oncology relies on models that capture the morphological, molecular, and functional characteristics of patient tumors to accurately predict drug response and resistance. The development of various patient-derived cancer models (PDMCs) has provided tools for this work. For example, drug sensitivity assays using PDMCs have summarized anti-tumor responses in the clinic, emphasizing their potential to guide personalized care (Barretina et al., Nature 483, 603-607, 2012; Gao et al., Nature Med 21, 1318-1325, 2015; Lu et al., PLoS One 12, e0169439, 2017; Vlachogiannis et al., Science 359, 920-926, 2018). Patient-derived xenografts (PDX) and organoids (PDO) have also been shown to mimic clinical responses to cancer treatments (Bruna et al., Cell 167, 260-274.e222, 2016; Gao et al., Nature Med 21, 1318-1325, 2015; Hidalgo et al., Cancer Discov 4, 998-1013, 2014; Jenkins et al., Cancer Discov 4, 998-1013, 2018; Neal et al., Cell 175, 1972-1988e1916, 2018; Yuki et al., Trends Immunol 41, 652-664, 2020). In addition, given the growing clinical importance of immuno-oncology (IO), reproducing physiological immune activity in organoid cultures has received great attention. For example, peripheral blood lymphocyte and tumor organoid co-culture models have been used to test tumor-reactive T cells (Dijkstra et al., Cell 174, 1586-1598, 2018). However, using PDX and PDO models to guide timely clinical decisions for cancer patients can be challenging. Summary of the invention

[0007] As described herein, droplet emulsion microfluidics with temperature control and dead volume minimization can be used to rapidly generate thousands of micro-organ spheroids (MOS) from small volumes of patient tissue; MOS can be very useful as a patient-derived model for clinical precision oncology. Clinical studies of newly diagnosed metastatic colorectal cancer (CRC) patients using a MOS-based precision oncology pipeline reliably predicted patient treatment outcomes within 14 days, a timeline suitable for guiding treatment decisions in the clinic. In addition, as described herein, MOS retains stromal cells of the original tumor tissue and allows T cell infiltration, providing a clinical assay for testing IO therapies such as PD-1 blockers, bispecific antibodies, and T cell therapies for patient tumors.

[0008] In a first aspect, the present invention features a method comprising or consisting essentially of: obtaining a plurality of cells derived from a tissue; forming a microorgan sphere (MOS) from the plurality of cells; culturing the MOS in a MOS culture; and introducing a virus into the MOS culture, thereby obtaining one or more cells infected with the virus in the MOS. The infected one or more cells may express one or more genes introduced by the virus after infection with the virus. The MOS may have an average diameter of about 50 μm to about 500 μm. In some cases, the plurality of cells include no more than 15,000 cells. The cells of the method may be derived from a biopsy. The cells may be derived from a tumor biopsy. The cells may be derived from one or more core needle biopsies, the one or more core needle biopsies including about 14-gauge core needle biopsies to about 20-gauge core needle biopsies. The cells may be derived from one or more 18-gauge core needle biopsies. The cells may be derived from a tumor biopsy of one or more cancers. The one or more cancers may include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof. The cells may be derived from one or more patients. The cell may include a xenograft (PDX) cell derived from a CRC patient. The MOS may contain a tumor spheroid. The MOS may be cultured in a droplet, wherein the nascent MOS includes a seeding density of about 1 to about 300 cells per droplet. The nascent MOS may have a seeding density configured to generate a desired number, size, or both of tumor spheroids in the MOS. The MOS may be cultured in a droplet, and the method may further include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. The method may further include treating the MOS with one or more therapeutic agents. The one or more therapeutic agents may include small molecules or antibodies. The cell may be from a patient, and the MOS may serve as a predictive model of the patient's sensitivity to one or more drug therapies for treating a disease. The MOS may serve as a predictive model of the patient's sensitivity to one or more chemotherapies.

[0009] In another aspect, the present invention is characterized in that a method comprises the following or is essentially composed of the following: obtaining a plurality of cells derived from tissue, mixing the plurality of cells with a fluid comprising a polymer, and intersecting the stream of cells and fluid with a stream of an immiscible material to generate a plurality of micro-organ spheres (MOS). The method may further include de-emulsifying and / or culturing the generated MOS. In some cases, the method may include culturing the generated MOS in the form of a suspension droplet. The polymer may be a polymer matrix (e.g., an extracellular matrix). The MOS may have an average diameter of about 10 μm to about 700 μm. The MOS may have an average diameter configured to provide a three-dimensional cell environment. In some cases, the plurality of cells may include no more than 15,000 cells, no more than 10,000 cells, no more than 5,000 cells, or no more than 1,000 cells. In some cases, the plurality of cells may include about 50 cells to about 20,000 cells (e.g., about 500 cells to about 10,000 cells). The cell may be derived from a biopsy (e.g., a tumor biopsy). The cell may be derived from one or more core needle biopsies (e.g., one or more biopsies with a core needle biopsy of about 14 to about 20). The cell may be derived from one or more core needle biopsies of 18. The cell may be derived from a tumor biopsy of one or more cancers. The one or more cancers may include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof. The cell may be derived from one or more patients. The cell may include a xenograft (PDX) cell derived from a CRC patient. In the presence of tumor-resident immune cells, the MOS may include tumor spheroids and / or tumor spheroid-like structures. Mixing may form a plurality of nascent MOSs that subsequently form MOSs. The nascent MOS may 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 may include a seeding density configured to generate a desired number, size, or both of tumor spheroids in the MOS. The method may further include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. The method may further include treating the MOS with one or more therapeutic agents. The one or more therapeutic agents may include a small molecule or an antibody. The therapeutic agent may be any chemotherapeutic agent. Treatment may include delivering one or more therapeutic agents at a concentration of about 1 μM to about 10 μM. The one or more therapeutic agents may include oxaliplatin, irinotecan, or a combination thereof. Treatment may be performed within 11 days after biopsy collection, within 5 days after biopsy collection, or within 3 days after biopsy collection. Each MOS may contain at least 30 tumor cells, at least 20 tumor cells, or at least 10 tumor cells.In some cases, each MOS may contain about 10 tumor cells to about 50 tumor cells. MOS can serve as a predictive model for the sensitivity of a patient to one or more drug therapies for treating a disease. MOS can serve as a predictive model for the sensitivity of a patient to one or more chemotherapies. MOS can serve as a predictive model for the sensitivity of a patient to one or more chemotherapies within 14 days of MOS preparation. The amount of fibroblasts contained in MOS may be less than the amount of fibroblasts found in a comparative large number of organoid cultures. For example, the amount of fibroblasts in MOS may be less than the amount of fibroblasts found in a comparative large number of organoid cultures after 2 days of culture, less than the amount of fibroblasts found in a comparative large number of organoid cultures after 5 days of culture, or less than the amount of fibroblasts found in a comparative large number of organoid cultures after 7 days of culture. MOS may contain functional immune cells. MOS may contain immune cells that respond to immunotherapy. MOS may contain natural killer cell markers (e.g., CD4+, CD8+, CD56+, or a combination thereof).

[0010] In another aspect, the present invention is characterized by a method for predicting a patient's response to therapeutic treatment. The method may include or consist essentially of: co-culturing a microorgan sphere (MOS) derived from a patient and an agent associated with immunotherapy; and determining the MOS to determine the efficacy of immunotherapy. Immunotherapy may be immuno-oncology (IO) therapy. The agent may include an immune checkpoint inhibitor, a T cell activator, a tumor infiltrating lymphocyte (TIL), an IO therapy molecule, or a combination thereof. An immune checkpoint inhibitor may be an anti-PD1 therapy (e.g., nivolumab, pembrolizumab, cemiplimab, atezolizumab, dostarlimab, durvalumab, or avelumab). IO therapy molecules may include PD-1 blockers, T cell bispecific antibodies (TCBs), or both. Immunotherapy may target human leukocyte antigens (HLA), antigens associated with HLA, or both. The agent may include a T cell receptor mimetic antibody (e.g., ESK1, DP47, or both). The agent may 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 may include determining the amount of apoptosis that occurs in tumor spheroids present within the MOS after initiation of immunotherapy. The MOS may serve as a predictive model for at least 12 months, at least 6 months, or at least 3 months.

[0011] In another aspect, the present invention features a method of treating a patient. The method may include or consist essentially of: (a) predicting a patient's response to a therapeutic treatment described herein; and (b) selecting a therapy based on the predicted patient response.

[0012] In another aspect, the present invention is characterized by a method for predicting a patient's response to therapy. The method may include or consist essentially of the following: (a) co-culturing a microorgan sphere (MOS) derived from a patient with an effector immune cell; and (b) determining the MOS to determine the efficacy of a therapy using an effector immune cell. Immune cells may be selected from the group consisting of: chimeric antigen receptor (CAR) T cells, tumor infiltrating lymphocytes (TILs), peripheral blood mononuclear cells (PBMCs), T cells separated from PBMCs, T cells separated and amplified from tumor cells, and combinations thereof. MOS can be formed by the methods described herein.

[0013] In yet another aspect, the present disclosure features a micro-organ spheroid composition. The composition can include, consist essentially of, or consist of a plurality of micro-organ spheroids, wherein each micro-organ spheroid includes a base material and at least one tumor spheroid, wherein the plurality of micro-organ spheroids contain 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 spheroid can be responsive to the one or more drug therapies.

[0014] Unless otherwise defined, the meaning of all technical terms and scientific terms used herein is the same as the meaning generally understood by those of ordinary skill in the field to which the present invention relates. Although methods and materials similar or equivalent to the methods and materials described herein can be used to implement the present invention, suitable methods and materials are described below. All publications, patent applications, patents and other references mentioned herein are incorporated herein by reference in their entirety. In the event of a conflict, this specification (including definitions) shall prevail. In addition, materials, methods and examples are only illustrative and are not intended to be limiting.

[0015] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will become apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figures 1A to 1J : Establishment of CRC MOS for drug screening and clinical validation. Figure 1A The scheme of CRC MOS generation and drug screening is depicted. Figure 1B Included is an image of a microfluidic MOS chip. Figure 1CIncluded are bright-field microscopy images of CRC MOS generated using different numbers of cells per MOS. Figure 1D Included are representative images of generated MOS from patient CRC tumor tissue and hematoxylin and eosin (H&E) staining of primary CRC tumor tissue and derived MOS. Figure 1E Included are images showing H&E staining of CRC MOS established from different patient tumor tissues. Figure 1F Figure 2 is a heat map of high-throughput drug screening using MOS derived from CRC tumors, indicating sensitivity to oxaliplatin and resistance to irinotecan. Figure 1G Included are images showing a patient's response to oxaliplatin after 6 months of treatment in the clinic. Figure 1H is a schematic diagram of the clinical study design for drug testing using MOS established from CRC biopsies. Fig. 1I Representative images of patient-derived MOS are included. Figure 1J is a Kaplan Meier plot of the survival results, which shows that the survival of eight CRC patients is associated with MOS drug sensitivity. Scale bar: 100 μm.

[0017] FIG. 2A to FIG. 2H :CRC clinical research. Figure 2A is an image of a MOS production machine and associated microfluidic system (100). A 15 mL conical tube (110) containing an immiscible fluid (e.g., oil) and a sample containing cells / A 1.5 mL Eppendorf tube (120) of sample mixture is pressurized to drive flow through a microfluidic chip set inside a chip holder (130). The device is placed in a refrigerator with the tube connected to an external pump (140). FIG. 2B to FIG. 2H Included are graphs plotting the results of in vitro CRC MOS drug responses as well as images showing clinical validation from seven different CRC patients. For each drug concentration, n=3.

[0018] FIG. 3A to FIG. 3F : Oxaliplatin-based treatment of CRC MOS and phenotypic characterization of MOS derived from cancer patients. Figure 3A Included are representative images of CRC MOS from two patients (designated CRC1282 and CRC1297) treated with oxaliplatin. Figure 3B Included is a scatter plot of caspase 3 / 7 fluorescence signal in CRC MOS normalized by the surface area of ​​individual tumor spheroids inside the MOS. Figure 3C Included are white light images of MOS generated from patient breast tumor tissue and H&E stained images showing primary breast tumor tissue and derived MOS. Scale bar: 100 um. Figure 3DIncluded are white light images of MOS generated from patient renal tumor tissue and H&E stained images showing primary renal tumor tissue and derived MOS. Scale bar: 100 um. Figure 3E Includes plotted data to compare tumor spheroid growth in MOS relative to bulk Figure 2. Figure 3F Includes 7th day MOS compared to traditional Representative images showing that fibroblasts in MOS grow less than Fibroblast growth in .

[0019] FIG. 4A to FIG. 4E : Genomic and transcriptomic characterization of MOS generated from patient lung tumors. Figure 4A Included are representative images showing MOS generated from patient lung tumor tissue, as well as images showing H&E staining of primary lung tumor tissue and derived MOS. Figure 4B Included are copy number variation (CNV) profiles showing the association of lung tumor tissue and derived MOS. Figure 4C Included are UMAPs of cells from primary lung tumor tissue and derived MOS by cell type marker. Figure 4D Included are graphs plotting comparisons of the three lung tumor samples and the log-transformed relative abundance of each cell type from which MOS were derived. Figure 4E are graphs plotting the relative abundance of cell types represented in tissue (n=3) or MOS (n=3) samples as indicated. Abundance is reported as log1p (percent in 1).

[0020] FIG. 5A to FIG. 5E : Characterization of MOS derived from cancer patients. Figure 5A Includes flow cytometry graph showing MOS support ratio Few vimentin (+) fibroblasts. Figure 5B Copy number variation (CNV) profiles with associations of breast, kidney, and ovarian tumor tissues and MOS derived therefrom are shown. Figure 5C Cluster plot including the Jacquard similarity scores between the mutation profiles of each sample and disease state. Figure 5D Included is a Venn diagram showing the fraction of shared mutations between tumor (T) and matched MOS (M). Figure 5E is a graph plotting the analysis of driver mutations in tumors and their derived MOSs.

[0021] 6A to 6F : Single-cell RNA-seq analysis of patient tissues and derived MOS. Fig. 6A Results of the quality assessment metrics are shown plotted as UMAP for all cells. Figure 6Bis a pair of violin plots of the quality assessment of cells analyzed using Drop-seq. nCount_RNA and nFeature_RNA describe the distribution of the number of sequencing reads or observed genes associated with the cells profiled in each sample, respectively. Cells with more than 2,500 observed genes were removed from downstream analysis. Figure 6C Shown are cells from three lung tumor tissue samples and their derived MOS samples, plotted as UMAP by cell type marker. Fig.6D Included are graphs showing cells from primary renal tumor tissue and MOS samples plotted as UMAP labeled by cell type (top left) and preparation (top right), and the log-transformed relative abundance of cell types in renal samples and derived MOS (bottom). Fig. 6E Included are graphs showing cells from primary ovarian tumor tissue and MOS samples plotted as UMAP labeled by cell type (top left) and preparation (top right), as well as log-transformed relative abundance of cell types in kidney samples and derived MOS (bottom). Fig. 6F Included are graphs showing cells from CRC tissue and MOS samples plotted as UMAP labeled by cell type (top left) and preparation (top right), and a graph plotting the relative abundance of the four major cell types in CRC tissue and derived MOS at day 7 (bottom).

[0022] FIG. 7A to FIG. 7D : Gene expression analysis in tumor tissue relative to derived MOS. Fig. 7A Included are flow cytometry plots showing characterization of the CRC MOS stroma and demonstrating that key immune cell populations are conserved in MOS. Figure 7B is a graph comparing the log fold changes in gene expression in tumor cells, fibroblasts, lymphocytes, and myeloid cells from a renal cancer sample (n=1). Genes with an absolute log fold change > 1.5 are labeled. Figure 7C is a graph comparing the log fold changes in gene expression in tumor cells, fibroblasts, lymphocytes, and myeloid cells from an ovarian cancer sample (n=1). Genes with an absolute log fold change > 1.5 are labeled. Fig.7D Included are a series of UMAPs that plot the expression of broad cell type marker genes for each of the broad cell types in lung samples and derived MOS. Tumor cell markers include EPCAM and CDH1. Myeloid cell markers include FCER1A and LYZ. Lymphocyte markers include CD3E and IL7R. Fibroblast markers include FAP and PDGFRA.

[0023] FIG. 8A to FIG. 8D : Differential gene analysis of lung cancer tissue relative to derived MOS. Fig. 8AThis is a bulk differential expression analysis comparing lung cancer primary tissues and derived MOS datasets (n=3). Genes with absolute log fold changes > 1.5 are marked. Figure 8B Volcano plot of differentially expressed genes including epithelial cells, lymphocytes, myeloid cells, and fibroblasts from lung cancer samples. Figure 8C Included are UMAPs plotting the expression of cancer-associated marker genes CD274 (PD-L1), PDCD1 (PD-1), and TGFB1 (TGF-β). Cells are plotted on separate UMAPs based on their origin: primary tissue (left) or MOS (right). Fig.8D is a graph plotting the top five identified conserved markers for each cell type labeled by cell of origin.

[0024] FIG. 9A to FIG. 9M : MOS response to immunotherapy. Fig.9A Included are representative images and flow cytometry plots showing that resident immune cells encapsulated in MOS are viable and responsive to immune stimulation. Fig. 9B are images showing established renal tumor MOS on day 3. Fig. 9C is a graph showing that nivolumab (10 μg / mL) induces MOS killing (indicated by phospholipin V) of renal tumors. Fig.9D Included are representative images from Incucyte showing death of tumor spheroids within MOS responding to nivolumab treatment relative to control. Fig.9E is a graph showing that ESK1* (10 μg / mL) induced more death than 1 μg / mL ESK1* in lung tumor MOS. Fig.9F Included are representative images from Incucyte showing that higher doses of ESK1* induced more killing (higher PI3K signal). Figure 9G Figure 2 is a graph plotting the level of cell death showing that CRC tumor spheroids in MOS respond to ESK1* treatment. Phospholipin V fluorescence signal from each organoid was measured 3 days after drug administration. Each dot represents an individual organoid. Figure 9H is a graph that plots the level of cell death, showing CRC organoids in the dome do not respond to ESK1* drug treatment. Phospholipin V fluorescence signal from each organoid was measured 3 days after drug administration. Each dot represents an individual organoid. Fig.9I Including on day 3 after ESK1* treatment Representative images of MOS in domes and tumor spheroids in organoids. Figure 9J is a graph showing that ESK1* induces lung tumor MOS killing (indicated by phospholipin V) compared to DP47 (CD3-only TCB). Figure 9KFigure 2 is UMAP of cells from primary lung tumor tissue and three MOS samples treated with ESK1*, negative TCB, or drugs. Figure 9L is a UMAP with cells indicated by sample origin. Figure 9M Included were UMAPs of cells from primary lung tumor tissue and derived MOS with or without treatment.

[0025] FIG. 10A to FIG. 10I : Immune cells stored in MOS respond to immunotherapy. Fig. 10A is a graph showing that nivolumab induces significant cytotoxicity in tumor spheroids within MOS. Incucyte images were taken every 2 hours for 4 days, and phospholipin V green dye was added to indicate apoptosis. Fig. 10B Included are representative Incucyte images demonstrating that nivolumab induces apoptosis within MOS. Fig. 10C are images of established MOS (day 4) derived from lung tumor tissue. Fig. 10D is a schematic diagram depicting how ESK1*TCB drugs induce CTL-mediated killing in MOS. Fig. 10E is a graph plotting HLA-A2 gene expression levels in lung tumor tissue. Fig.10F are flow cytometric graphs showing HLA-A2 expression in established MOS from lung tumor tissue. Figure 10G is a graph showing that ESK1* induces a higher apoptosis signal (indicated by phospholipin V signal) in MOS than in DP47. Fig. 10H Included are representative images showing apoptosis induced by ESK1* treatment of MOS. Fig.10I is a graph showing that ESK1* induced killing lung cancer MOS in all eight lung cases (p<0.005).

[0026] FIG. 11A to FIG. 11O : MOS potency assay for T cell therapy. Fig.11A Is to show TIL and traditional An image showing that TIL cannot penetrate conventional Immune cells were stained with Cytolight red dye before capturing images using the Incucyte. Fig. 11B Included is an image showing that TILs can penetrate MOS and adhere to tumor cells. Immune cells were stained with Cytolight red dye before the image was taken with Incucyte. Fig. 11C is a graph showing that increased killing (indicated by phospholipin V) was observed in MOS treated with autologous TILs. Fig.11D Included are representative images showing MOS killing of TILs (indicated by phospholipin V stain). Fig.11E is a graph showing that activated PBMCs induce MOS killing (indicated by phospholipin V green dye). Fig.11F Included are representative images showing MOS killing of PBMCs. Fig.11G Included are representative images illustrating the imaging analysis pipeline that identifies droplet regions to minimize background noise from external immune cells. Fig.11H Figure 2 is a graph of a quantitative analysis showing that PBMC induced MOS killing (indicated by apoptosis proteinase 3 / 7 dye). Fig.11I is a graph showing that ESK1* enhanced PBMC-induced tumor cell killing compared to DP47 (CD3-only TCB). Fig.11J Included are representative images showing death induced by ESK1* treated MOS in combination with PBMCs. White arrows indicate lung cancer tumor spheroids within MOS. Compared to ESK1*, the negative control TCB, DP47, did not induce significant apoptosis of tumor spheroids within MOS. Figure 11K is a dot plot showing that ESK1* induced PBMC-mediated lung tumor MOS death in 7 patient cases (p<0.005). Fig.11L are representative images showing lung tumor-derived MOS infected with a dsRed expression vector (shown 3 days after infection). Fig.11M is a graph plotting HLA-A2 expression in virus-treated samples, which shows that significantly higher HLA-A2 gene expression was observed in HLA-A2 infected MOS. Fig.11N Included is a flow chart showing that significantly higher antigen expression was observed in HLA-A2 infected MOS. Fig.11O is a graph showing that HLA-A2 infected MOS undergo higher cell death than matched uninfected MOS in the presence of ESK1* and activated PBMCs as indicated by phospholipin V dye.

[0027] FIG. 12A to FIG. 12M : MOS-based T cell potency assay against lung, renal, and colorectal cancers. Fig. 12A Including display MOS Representative images of PBMC infiltration. Immune cells were stained with Cytolight Fast Red. Images were taken every 2 hours for 3 days by Incucyte. Fig. 12B Included are representative images showing activated PBMC-induced killing of MOS. Tumor spheroids inside MOS were stained with Cytolight red dye to indicate cell viability. Fig. 12C Included are representative images showing that activated PBMCs induce MOS death indicated by caspase 3 / 7 green dye. Fig.12DIncluded are representative images showing activated PBMCs inducing MOS death indicated by Cytotox green dye. Fig.12E is a graph showing that pre-activated allogeneic PBMCs induce CRC MOS death (E:T=5:1) as indicated by caspase 3 / 7 green dye. Fig.12F Included are representative Incucyte images indicating significant killing in CRC MOS combined with activated PBMCs (E:T=5:1). Figure 12G is a graph showing that pre-activated allogeneic PBMCs induce renal tumor MOS death as indicated by caspase 3 / 7 signaling.

[0028] Fig.12H Included are representative Incucyte images demonstrating that the level of death in renal tumor MOS combined with pre-activated PBMCs was higher at an effector:target ratio of 10:1 than at a ratio of 5:1. Fig.12I Figure 2 is a graph plotting the effect of nivolumab (PD-1 blockade) treatment on lung tumor MOS with and without matched patient TIL and MHC blockade. Fig.12J Included are representative images showing that ESK1* enhanced TIL-induced killing of lung tumor MOS compared to DP47 (CD3-only TCBs). Figure 12K Included are representative images showing heterogeneity of cell death (killing indicated by circles) at different times in ESK1* / TIL-treated MOS. Figure 12L is a graph plotting ESK1*-induced tumor sphere death in each lung tumor MOS. Figure 12M is a pictorial representation of the HLA-A2 vector map. DETAILED DESCRIPTION

[0029] This document provides methods and materials that can be used to generate and use MOS. For example, as described herein, droplet emulsion microfluidics with temperature control and dead volume minimization can be used to rapidly generate thousands of MOS from a small volume of patient tissue (e.g., a tumor biopsy). MOS can serve as a patient-derived model for clinical precision oncology, thereby predicting the patient's response to a specific therapeutic agent and predicting the treatment outcome within 14 days, a timeline suitable for guiding clinical treatment decisions. In addition, since it has now been determined that MOS contains stromal cells derived from the original tumor that allow T cells to infiltrate, and as described herein, it has been shown that immune cells derived from tumors are contained in an environment that effectively simulates the environment of the original tumor, MOS provides a clinical assay for testing IO therapies such as checkpoint inhibitors (e.g., PD-1 blockers), bispecific antibodies, and T cell therapies on patient tumors.

[0030] In some cases, the present invention provides a method for generating MOS. In some variants, MOS is formed by forming a droplet of an unpolymerized mixture of a dissociated tissue sample and a fluid matrix material in an immiscible material (such as a fluid hydrophobic material (e.g., oil)). For example, a MOS can be formed by combining a stream of an unpolymerized material containing cells of a dissociated tissue sample with one or more streams of an immiscible material to form a droplet. In some cases, MOS can be formed according to one or more methods described in U.S. Patent No. 11,555,180, the entire contents of which are incorporated herein by reference. See, for example, the 5th row of the 7th column of the 5th row of the 3rd column and the 54th row of the 21st column to the 57th row of the 22nd column. In some cases, the method may also include de-emulsifying and / or cultivating the generated MOS to the generated MOS. For example, MOS can be cultivated in the form of a droplet. In some cases, MOS can be cultivated in the form of a suspension droplet.

[0031] Any suitable polymer and immiscible fluid (e.g., oil) can be used. In some cases, for example, the polymer can be a polymer matrix (e.g., an extracellular matrix such as matrix).

[0032] MOS may have any suitable diameter. For example, MOS may have an average diameter of about 10 μm to about 700 μm (e.g., about 10 μm to about 50 μm, about 50 μm to about 100 μm, about 100 μm to about 150 μm, about 150 μm to about 200 μm, about 200 μm to about 250 μm, about 250 μm to about 300 μm, about 300 μm to about 350 μm, about 350 μm to about 400 μm, about 400 μm to about 450 μm, about 450 μm to about 500 μm, about 500 μm to about 550 μm, about 550 μm to about 600 μm, about 600 μm to about 650 μm, or about 650 μm to about 700 μm). In some cases, MOS in a population may have an average diameter configured to provide a three-dimensional cell environment. In some cases, the plurality of cells may include no more than 15,000 cells (e.g., no more than 10,000 cells, no more than 5,000 cells, or no more than 1,000 cells). In some cases, the plurality of cells may include 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 about 5000 cells, about 5000 to about 10,000 cells, about 500 cells to about 10,000 cells, or about 10,000 to about 20,000 cells).

[0033] The cells may be derived from a biopsy (e.g., a tumor biopsy). In some cases, the cells may be derived from one or more core needle biopsies (e.g., one or more biopsies with about a 14-gauge core needle biopsy to about a 20-gauge core needle biopsy). For example, the cells may be derived from one or more 18-gauge core needle biopsies or from one or more 16-gauge core needle biopsies.

[0034] The cells may be derived from a tumor biopsy. The tumor may be associated with any type of cancer, including but not limited to colorectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or any combination thereof. The cells may be derived from a single patient or from more than one patient. In some cases, the cells may include CRC PDX cells.

[0035] When MOS is prepared by mixing cells with an immiscible material (e.g., oil) and a polymer, the mixing may form a plurality of nascent MOS that subsequently form MOS. The nascent MOS may include 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). In some cases, the nascent MOS may have a seeding density configured to generate a desired number, size, or both of tumor spheroids in the MOS. Thus, in some cases, the MOS may include tumor spheroids, or may include tumor spheroid-like structures (e.g., in the presence of tumor-resident immune cells). The number and size of tumor spheroids may be related to the seeding density.

[0036] In some cases, the method for generating MOS may further include determining the number of MOS (NMOS) by dividing the number of viable cells by the number of cells per droplet. The MOS generated according to the methods described herein may each contain at least 10 tumor cells (e.g., at least 20 tumor cells or at least 30 tumor cells). In some cases, each MOS may contain about 10 tumor cells to about 50 tumor cells.

[0037] In some cases, methods for imaging MOS are provided herein. For example, MOS (e.g., large quantities of MOS) can be obtained using a microscope (e.g., bright field microscopy, confocal microscopy, or fluorescence microscopy) or using any other suitable technique (e.g., liquid lenses, holography, sonar, bright field and / or dark field imaging, laser imaging, planar laser sheets, or high throughput methods including image-based analysis). In some cases, any suitable software (e.g., ImageJ software; imagej.nih.gov / ij) can be used to determine the surface area of ​​MOS.

[0038] In addition, in some cases, the methods provided herein may include treating MOS with one or more therapeutic agents. Such treatment, followed by an assessment of whether the therapeutic agent affects the survival rate of the MOS, may indicate whether the therapeutic agent is likely to effectively treat a tumor in a subject in which the MOS is prepared. The one or more therapeutic agents may include, for example, a small molecule or an antibody. The one or more therapeutic agents may be applied to the MOS at any suitable concentration (e.g., from about 1 μM to about 10 μM). In addition, the one or more therapeutic agents may include any suitable agent. One or more of the therapeutic agents may be a chemotherapeutic agent. Non-limiting examples of therapeutic agents that can be used in the methods provided herein include oxaliplatin, irinotecan, or a combination thereof. Treatment may be performed within 11 days after biopsy collection (e.g., within 5 days after biopsy collection, or within 3 days after biopsy collection).

[0039] As described herein, MOS can encapsulate various cell types (e.g., tumor cells, stromal cells, and immune cells) residing in the tissue (e.g., tumor tissue) from which it is derived. In addition, MOS also captures the genomic profile of the tissue from which it is derived to a large extent. Therefore, without being constrained by a specific mechanism, MOS can serve as a predictive model for the sensitivity of a patient to one or more drug therapies for treating a disease. For example, MOS can serve as a predictive model for the sensitivity of a patient to one or more chemotherapies. In some cases, MOS can serve as a predictive model for the sensitivity of a patient to one or more chemotherapies within 14 days of MOS preparation.

[0040] In some cases, the amount of fibroblasts contained in the MOS may be less than the amount of fibroblasts found in a comparative bulk organoid culture. For example, the amount of fibroblasts encapsulated in the MOS may be less than the amount of fibroblasts found in a comparative bulk organoid culture after 2 days of culture, less than the amount of fibroblasts found in a comparative bulk organoid culture after 5 days of culture, or less than the amount of fibroblasts found in a comparative bulk organoid culture after 7 days of culture. The MOS may also contain functional immune cells. For example, the MOS may contain immune cells that respond to immunotherapy. In some cases, the MOS may contain natural killer cell markers (e.g., CD4+, CD8+, CD56+, or a combination thereof).

[0041] Also provided herein is a method for predicting a patient's response to treatment. As described herein, immune cells resident in a tissue sample (e.g., immune cells resident in a tumor tissue sample) may be encapsulated in a MOS derived from a tissue sample. Since MOS can capture the immune microenvironment of a tumor, the effect of drugs (e.g., checkpoint inhibitors) that affect immune cells and / or affect the interaction between immune cells and cancer cells can be evaluated in MOS. As indicated herein, the immune cells encapsulated in MOS may be alive and responsive to immune stimulation, so that immunotherapy can be tested on resident immune cells encapsulated in MOS. In some cases, the method provided herein may include co-culturing MOS with one or more reagents associated with immunotherapy, and determining MOS to determine the effectiveness of immunotherapy.

[0042] Any suitable immunotherapy can be tested with a population MOS preparation. For example, immunotherapy can be immuno-oncology (IO) therapy, checkpoint inhibitors, T cell activators, tumor infiltrating lymphocytes (TIL), IO therapy molecules, MAPK inhibitors, or combinations thereof. In some cases, immune checkpoint inhibitors such as anti-PD1 therapy (e.g., nivolumab, pembrolizumab, cemiplimab, atezolizumab, dostalimab, durvalumab, or avelumab) or another checkpoint inhibitor (e.g., T cell targeted immunomodulators), ipilimumab, TSR-022, MGB453, BMS-986016, or LAG525) can be used. In some cases, IO therapy molecules can be used, wherein IO therapy molecules include PD-1 blockers, TCBs, or both. Immunotherapy can target human leukocyte antigens (HLA), antigens associated with HLA, or both. Reagents can include T cell receptor mimetic antibodies (e.g., ESK1, DP47, or both). In some cases, the immunotherapy may be a MAPK inhibitor (e.g., vemurafenib, dabrafenib, PLX8349, cobimetinib, trametinib, selumetinib, or BVD-523). Other immunotherapies that may be used include, but are not limited to, immunomodulators (e.g., anti-CD47 antibodies and antibody-dependent cell-mediated cytotoxicity (ADCC) therapy), apoptosis inhibitors (e.g., ABT-737, WEHI-539, ABT-199), agents targeting components of potential contributing pathways (e.g., afotibin, idarucizumab, and infliximab), chemotherapeutic agents (e.g., cytarabine), cell therapy, cancer vaccines, oncolytic viruses, and bispecific antibodies. The agent may 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 may include determining the amount of apoptosis that occurs in tumor spheroids present in MOS after initiation of immunotherapy. MOS may serve as a predictive model for at least 12 months, at least 6 months, or at least 3 months.

[0043] In some cases, the methods provided herein may include infecting MOS with one or more viruses. For example, a virus can be used to deliver a therapeutic agent (e.g., immunotherapy) to a MOS. Examples of viruses that can be used to infect MOS include, but are not limited to, lentiviruses, adeno-associated viruses, and influenza viruses. In some cases, a virus containing a nucleic acid encoding a polypeptide (e.g., a marker, a therapeutic polypeptide, or a DNA editing polypeptide, such as a CRISPR-associated (Cas) nuclease) can be used to infect a MOS.

[0044] On the other hand, the present invention is characterized in that it is used to treat a mammal (e.g., a human, such as a human patient). The method may include, for example, using the method provided herein to predict the patient's response to therapeutic treatment, and selecting therapy based on the patient's predicted response. In some cases, the method may include co-culturing MOS with effector immune cells, and then determining MOS to determine the efficacy of a therapy with effector immune cells. Immune cells may be, for example, chimeric antigen receptor (CAR) T cells, tumor infiltrating lymphocytes (TILs), peripheral blood mononuclear cells (PBMCs), T cells separated from PBMCs, T cells separated and amplified from tumor cells, or any combination thereof.

[0045] Also provided herein is a MOS composition, wherein the composition comprises a plurality of MOS, each micro-organ sphere comprising a base material and at least one tumor sphere comprising a cell aggregate. The plurality of MOS may comprise a predetermined number of cells per droplet, a predetermined number of droplets in the composition, and / or a predetermined droplet size. In some cases, the composition may also comprise one or more therapeutic agents (e.g., one or more drug therapies to which the tumor sphere is responsive).

[0046] As described herein, MOS and the original tumor from which MOS is generated may have similar gene profiles. In addition, the entire exome sequence of MOS may be related to the exome sequence of the original tumor. In some cases, MOS and the original tumor may have similar immunosuppressive marker expression patterns.

[0047] Exemplary Embodiments

[0048] Example 1 is a method comprising obtaining a plurality of cells derived from a tissue; mixing the plurality of cells with a fluid comprising a polymer to obtain a mixture; and intersecting the flow of the mixture with an immiscible material (eg, oil) to generate a micro-organ spheroid (MOS).

[0049] Embodiment 2 is the method of embodiment 1, which includes de-emulsifying the generated MOS.

[0050] Embodiment 3 is the method of any one of the preceding embodiments, comprising culturing the generated MOS.

[0051] Embodiment 4 is the method of any one of the preceding embodiments, comprising culturing the generated MOS in the form of suspension droplets.

[0052] Embodiment 5 is the method of any of the preceding embodiments, wherein the polymer is a polymer matrix.

[0053] Embodiment 6 is the method of embodiment 5, wherein the polymer matrix is ​​derived from an extracellular matrix.

[0054] Embodiment 7 is the method of any of the preceding embodiments, wherein the MOS has an average diameter of about 250 μm to about 450 μm.

[0055] Embodiment 8 is the method of any of the preceding embodiments, wherein the MOS has an average diameter configured to provide a three-dimensional cellular environment.

[0056] Embodiment 9 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises no more than 15,000 cells.

[0057] Embodiment 10 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises no more than 10,000 cells.

[0058] Embodiment 11 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises no more than 5,000 cells.

[0059] Embodiment 12 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises no more than 1,000 cells.

[0060] Embodiment 13 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises about 100 cells to about 20,000 cells.

[0061] Embodiment 14 is the method of any one of the preceding embodiments, wherein the plurality of cells comprises about 500 cells to about 10,000 cells.

[0062] Embodiment 15 is the method of any one of the preceding embodiments, wherein the cells are derived from a biopsy.

[0063] Embodiment 16 is the method of any one of the preceding embodiments, wherein the cells are derived from a tumor biopsy.

[0064] Embodiment 17 is the method of any one of the preceding embodiments, wherein the cells are derived from one or more core needle biopsies comprising about a 14 gauge core needle biopsy to about a 20 gauge core needle biopsy.

[0065] Embodiment 18 is the method of any one of the preceding embodiments, wherein the cells are derived from one or more 18-gauge core needle biopsies.

[0066] Embodiment 19 is the method of any one of the preceding embodiments, wherein the cells are derived from a tumor biopsy of one or more cancers.

[0067] Embodiment 20 is the method of embodiment 19, wherein the one or more cancers may include rectal cancer, lung cancer, breast cancer, colorectal cancer (CRC), kidney cancer, ovarian cancer, or a combination thereof.

[0068] Embodiment 21 is the method of any one of the preceding embodiments, wherein the cells are derived from one or more patients.

[0069] Embodiment 22 is the method of any one of the preceding embodiments, wherein the cells comprise CRC patient-derived xenograft (PDX) cells.

[0070] Embodiment 23 is the method of any one of the preceding embodiments, wherein the MOS comprises a tumor spheroid.

[0071] Embodiment 24 is the method of any one of the preceding embodiments, wherein the MOS comprises tumor body-like structures in the presence of tumor-resident immune cells.

[0072] Embodiment 25 is the method of any of the preceding embodiments, wherein the mixing forms a plurality of nascent MOSs that subsequently form MOSs.

[0073] Embodiment 26 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density of about 20 to about 100 cells per droplet.

[0074] Embodiment 27 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density of about 20 to about 50 cells per droplet.

[0075] Embodiment 28 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density of about 30 to about 70 cells per droplet.

[0076] Embodiment 29 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density of about 40 to about 60 cells per droplet.

[0077] Embodiment 30 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density of about 50 to about 100 cells per droplet.

[0078] Embodiment 31 is the method of any of the preceding embodiments, wherein the nascent MOS comprises a seeding density configured to generate a desired number, size, or both of tumor spheres in the MOS.

[0079] Embodiment 32 is the method of any 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.

[0080] Embodiment 33 is the method of any of the preceding embodiments, further comprising treating MOS with one or more therapeutic agents.

[0081] Embodiment 34 is the method of embodiment 33, wherein the one or more therapeutic agents comprise a small molecule or an antibody.

[0082] Embodiment 35 is the method of any one of the preceding embodiments, wherein treating comprises delivering one or more therapeutic agents at a concentration of about 1 μM to about 10 μM.

[0083] Embodiment 36 is the method of any one of embodiments 32 to 34, wherein the one or more therapeutic agents comprises oxaliplatin, irinotecan, or a combination thereof.

[0084] Embodiment 37 is the method of any one of the preceding embodiments, wherein the treatment is performed within 11 days after biopsy collection.

[0085] Embodiment 38 is the method of any one of the preceding embodiments, wherein the treatment is performed within 5 days of biopsy collection.

[0086] Embodiment 39 is the method of any one of the preceding embodiments, wherein the treatment is performed within 3 days of biopsy collection.

[0087] Embodiment 40 is the method of any one of the preceding embodiments, wherein each MOS comprises at least 30 tumor cells.

[0088] Embodiment 41 is the method of any of the preceding embodiments, wherein each MOS comprises at least 20 tumor cells.

[0089] Embodiment 42 is the method of any of the preceding embodiments, wherein each MOS comprises at least 10 tumor cells.

[0090] Embodiment 43 is the method of any of the preceding embodiments, wherein each MOS comprises about 10 tumor cells to about 50 tumor cells.

[0091] Embodiment 44 is the method of any one of the preceding embodiments, wherein the MOS serves as a predictive model for the patient's sensitivity to one or more drug therapies used to treat the disease.

[0092] Embodiment 45 is the method of any one of the preceding embodiments, wherein the MOS serves as a predictive model for the patient's sensitivity to one or more chemotherapies.

[0093] Embodiment 46 is the method of any one of the preceding embodiments, wherein the MOS serves as a predictive model for the patient's sensitivity to one or more chemotherapies within 14 days.

[0094] Embodiment 47 is the method of any of the preceding embodiments, wherein the MOS comprises an amount of fibroblasts that is less than the amount of fibroblasts found in a comparable bulk organoid culture.

[0095] Embodiment 48 is the method of embodiment 47, wherein the amount of fibroblasts in the MOS after 2 days in culture is less than the amount of fibroblasts found in a comparable bulk organoid culture.

[0096] Embodiment 49 is the method of embodiment 47, wherein the amount of fibroblasts in the MOS after 5 days in culture is less than the amount of fibroblasts found in a comparable bulk organoid culture.

[0097] Embodiment 50 is the method of embodiment 47, wherein the amount of fibroblasts in the MOS after 7 days in culture is less than the amount of fibroblasts found in a comparable bulk organoid culture.

[0098] Embodiment 51 is the method of any of the preceding embodiments, wherein the MOS comprises functional immune cells.

[0099] Embodiment 52 is the method of any of the preceding embodiments, wherein the MOS comprises immune cells responsive to immunotherapy.

[0100] Embodiment 53 is the method of any one of the preceding embodiments, wherein the MOS comprises a natural killer cell marker.

[0101] 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.

[0102] Example 55 is a method of predicting a patient's response to a therapeutic treatment, the method comprising co-culturing a micro-organ spheroid (MOS) derived from the patient with an agent associated with an immunotherapy; and measuring the MOS to determine the efficacy of the immunotherapy.

[0103] Embodiment 56 is the method of embodiment 55, wherein the immunotherapy is immuno-oncology (IO) therapy.

[0104] Embodiment 57 is the method of embodiment 55 or embodiment 56, wherein the agent comprises an immune checkpoint inhibitor, a T cell activator, a tumor infiltrating lymphocyte (TIL), an IO therapy molecule, or a combination thereof.

[0105] Embodiment 58 is the method of embodiment 57, wherein the immune checkpoint inhibitor comprises an anti-PD1 therapy (e.g., nivolumab).

[0106] Embodiment 59 is the method of embodiment 57, wherein the IO therapy molecule comprises a PD-1 blocker, a T cell bispecific antibody (TCB), or both.

[0107] Embodiment 60 is the method of embodiment 55, wherein the immunotherapy targets human leukocyte antigen (HLA), antigens associated with HLA, or both.

[0108] Embodiment 61 is the method of embodiment 55, wherein the reagent comprises a T cell receptor mimetic antibody.

[0109] Embodiment 62 is the method of embodiment 55, wherein the T cell receptor mimetic antibody comprises ESK1, DP47, or both.

[0110] Embodiment 63 is the method of any one of embodiments 55 to 62, wherein the agent is present in an amount of about 0.1 μg / mL to about 10 μg / mL.

[0111] Embodiment 64 is the method of any one of embodiments 55 to 63, wherein the agent is present in an amount of about 0.5 μg / mL to about 5 μg / mL.

[0112] Embodiment 65 is the method of any one of embodiments 55 to 64, wherein the agent is present in an amount of about 1 μg / mL to about 3 μg / mL.

[0113] Embodiment 66 is the method of any one of embodiments 55 to 65, comprising determining the amount of apoptosis occurring in tumor spheroids present within the MOS after initiation of immunotherapy.

[0114] Embodiment 67 is the method of any one of embodiments 55 to 66, wherein the method provides a predictive model for at least 12 months.

[0115] Embodiment 68 is the method of any one of embodiments 55 to 67, wherein the method provides a predictive model for at least 6 months.

[0116] Embodiment 69 is the method of any one of embodiments 55 to 68, wherein the method provides a predictive model for at least 3 months.

[0117] Example 70 is a method of treating a patient, the method comprising: (a) predicting the patient's response to a therapeutic treatment as described in Example 55; and (b) selecting a therapy based on the predicted patient response.

[0118] Example 71 is a method for predicting a patient's response to a therapy, the method comprising: (a) co-culturing a patient-derived micro-organ spheroid (MOS) with effector immune cells; and (b) measuring the MOS to determine the efficacy of a therapy utilizing the effector immune cells.

[0119] 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 (TILs), peripheral blood mononuclear cells (PBMCs), T cells isolated from PBMCs, T cells isolated and expanded from tumor cells, and combinations thereof.

[0120] Embodiment 73 is the method of any one of embodiments 55 to 72, wherein the MOS is formed by the method of any one of embodiments 1 to 54.

[0121] Embodiment 74 is a micro-organ spheroid composition comprising a plurality of MOS, wherein each MOS comprises a base material and at least one tumor spheroid, wherein the plurality of MOS comprises a predetermined number of cells per droplet, a predetermined number of droplets in the composition, and / or a predetermined droplet size.

[0122] Embodiment 75 is the composition of embodiment 74, comprising one or more drug therapies.

[0123] Embodiment 76 is the composition of embodiment 74, wherein the at least one tumor spheroid is responsive to one or more drug therapies.

[0124] The present invention will be further described in the following examples, which do not limit the scope of the invention described in the claims.

[0125] Examples

[0126] Patient-derived MOS enables clinical precision oncology

[0127] Methods and Materials

[0128] Microfluidic chip fabrication and design: Microfluidic chips were fabricated from silicon wafers (Wafer Pro, Santa Clara, CA). Details of fabricating microfluidic features in silicon are described elsewhere (Rius et al., "Introduction to Micro- / Nanofabrication", in: Bhushan B. (ed.) Springer Handbook of Nanotechnology). Springer Handbooks. Springer, Berlin, Heidelberg, 2017). Briefly, the design was imprinted onto a 6" silicon wafer using standard photolithography techniques, and the features were etched using deep reactive ion etching (DRIE) in a cleanroom facility. Once cleaned, a borofloat glass coverslip (PG&O; Santa Ana, CA) was bonded to the silicon chip using anodic bonding. After bonding, the microfluidic channels were coated with Aquapel (Aquapel Glass; Cranberry Twp, PA) to create a hydrophobic surface. After coating, the channels were rinsed with 3 mL of Novec 7500 Engineered Fluid (3M; St. Paul, MN) and then baked at 60°C for 20 minutes.

[0129] MOS generator assembly: MOS generation occurs inside a 1.7 cubic foot internal micro refrigerator to prevent temperature sensitive gels from polymerizing during generation. A Fluigent FlowEZ (Fluigent; La Kremlin-Bicetre, France) pressure source is attached to the top of the refrigerator. Air lines are connected to the reagent and sample reservoir PCap (Fluigent) through the top of the refrigerator via two drilled holes. The pump is manually operated according to the manufacturer's recommendations. The chip is assembled inside a custom manifold that contains ports for connecting reagent and sample reservoirs to the chip. All components are placed inside the refrigerator. When handling temperature sensitive materials, the door is kept closed. MOS generation is imaged by assembling the camera and lens components listed in Table 3 and placing the camera directly above the chip.

[0130] Patient samples: Tissue sections (approximately 1 cm) of metastatic colorectal cancer, lung cancer, ovarian cancer, renal cancer, breast cancer, and non-tumor tissues were obtained from surgically resected specimens provided by the Duke Biorepository and Precision Pathology Center (BRPC) with patient consent. 3 Up to 2cm 3 The entire experimental protocol was performed in accordance with the institutional guidelines. The samples were confirmed to be tumor or normal tissue by histopathological evaluation. IRB approval (IRB#Pro00089222) and the study protocol were approved by the relevant institutional IRB.

[0131] Tumor tissue processing and MOS generation: All tumor and non-tumor tissues were stored in transfer medium and stored on ice after dissection. Ten percent of the tissue samples were immediately frozen in 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) (STEMCelltechnology catalog number 07900), Y-27632 (10 μM) (STEMCell technology catalog number 72302) and pramoxine (100 ug / mL) (Fisher Scientific catalog number NC9141851). Before the first cell quality check, the minced tissue samples were gently stirred in the enzyme solution at 37°C for 30 minutes to dissociate them. If large cell clumps were observed, digestion was performed for another 15 to 20 minutes until the tissue was mostly dissociated into single cells. After digestion, cells are filtered through a 70 μM cell strainer and yield and cell viability are determined using the Trypan blue method described previously by a Countess II cell counter. The initial number of cells inserted into the MOS depends on the intended application. For example, a single tumor cell per MOS is used for clonal diversity studies, while 20 tumor cells per MOS are typically used to test chemotherapies because this number provides the best trade-off between speed of tumor sphere establishment and the number of MOS used to test different conditions. Thirty (30) to 50 tumor cells per MOS (and a proportion of immune cells from the same digested sample) are more suitable for IO assays. Using traditional Methods The same cell density was seeded for comparison. De-emulsified MOS were layered with tumor culture medium and seeded in 6-well low binding plates. Cells were plated in 24-well plates and grown in tumor culture medium. The culture medium was changed every 3 days.

[0132] H&E staining of primary tumors and MOS: Tissues and MOS were processed for paraffin sections. Embedded MOS. The supernatant was removed and the MOS was fixed in 2% paraformaldehyde (PFA) containing 0.1% glutaraldehyde for 30 minutes at room temperature, then washed in 1X PBS and embedded in Histogel. After formalin fixation, fresh cancer tissues were embedded in paraffin. After dewaxing, 5-μm sections were stained with hematoxylin-eosin (H&E). The morphological characteristics of MOS and primary tumor sections were evaluated by a pathologist.

[0133] MOS and organoid imaging: Images of MOS and organoids were acquired using a Leica microscope (Leica, USA) on days 1, 3, 5, and 7 after initial plating. The organoid surface area was quantified using ImageJ software (Wayne Rasband, NIHR, USA; imagej.nih.gov / ij). To calculate the average size (area) of the organoids, more than 40 tumor spheres or Organoids in the PCR products were manually quantified and statistical analysis was performed using Prism 8.

[0134] Genomic and transcriptomic analysis of tumor tissue samples and matched MOS

[0135] DNA extraction and WES sequencing: MOS from day 7 of development were collected for DNA extraction. DNA was extracted using the Zymo Quick-DNA microprep kit (Zymo Research No. D2030) according to the manufacturer's protocol. DNA was quantified using NanoDrop. Tumor samples and MOS derived from matched tumors were analyzed using whole exome sequencing (WES) using an Illumina Novaseq 6000 sequencer by Novagene.

[0136] Mutational profiling of tumors and matched MOS: A total of >0.4 μg DNA per sample was used as input. The effective sequencing depth of each sample exceeded 50× (6G). Before alignment, TrimGalore was used to trim adapters from the raw sequencing data. The resulting fastq files were then aligned to the human reference genome (hg38) using BWA. Duplicate BAM files from matched samples were merged and filtered to remove duplicate and non-chromosomal reads. Sequence variants were then called using the HaplotypeCaller pipeline of GATK (version 4.2.0). Variants were filtered based on depth quality (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 variants.

[0137] 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. Binarization was performed for each unique mutation (classified as a specific position-base-alternating combination) for each sample based on presence-absence. The resulting binary vectors were used to calculate the Jacquard similarity score and generate Venn diagrams and presence-absence tables. According to the Cancer Genome Atlas (TCGA), the genes represented in the presence-absence table (not shown) were limited to the 25 most commonly mutated genes by cancer type.

[0138] Drop-seq gene expression library preparation and data analysis: Frozen PBMCs were thawed, and counts and cell viability were measured by CountessII. For single-cell RNA-seq, 200K cells were aliquoted, centrifuged, resuspended in 30μl PBS+0.04% BSA+0.2U / μl RNase inhibitor, and counted using Countess II. scRNA Drop-seq libraries were generated using a Dolomite Nadia machine according to the manufacturer's protocol. The libraries were pooled and sequenced using the Illumina NovaSeq platform, with the goal of reaching saturation or an average of 20,000 unique reads per cell. Sequencing data was used as input to the Drop-seq pipeline published by the Broad Institute (github.com / broadinstitute / Drop-seq). The gene count matrix was generated using the top 4,000 cell barcodes, each with the maximum number of reads associated with each index.

[0139] 10x Next GEM 3′ Single Cell Library Preparation and Data Analysis: For single cell RNA sequencing of ESK1* drug treated MOS and original tissue tumor cells, MOS were first generated from lung tumor tissue (Case No. 805). ESK1* drug (1 μg / mL) was added to the culture medium for 24 hours at day 5 MOS, and then the cells were collected to perform scRNA seq library preparation. During library preparation, 200K cells were aliquoted, centrifuged, resuspended in 30 μl PBS + 0.04% BSA + 0.2U / μl inhibitor, and counted using Countess II. GEM generation, GEMRT post-cleanup, cDNA amplification, and library construction were performed according to 10X Genomics Single Cell 3'v3.1 chemistry. Quality was assessed using the Agilent DNA band screening assay. Libraries were then pooled and sequenced using the Illumina NovaSeq platform, with a goal of reaching saturation or an average of 20,000 unique reads per cell. The sequencing data was used as input to the 10xGenomics Cell Ranger pipeline to demultiplex the BCL files, generate FASTQs, and generate feature counts for each library.

[0140] Dimensionality reduction and cell type annotation: Unless otherwise stated, Seurat 3 with default parameters was used to analyze the gene barcode matrix generated using the DigitalExpression script from the Broad Drop-seq pipeline. Cells with >2,500 genes detected were removed from the analysis. The counts were log-normalized and the top 2,000 variable features were determined. 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 at resolution = 1. Cell types were inferred by using the HumanPrimaryCellAtlasData (rdrr.io / github / LTLA / celldex / man / HumanPrimaryCellAtlasData.html) function in the SingleR package. Labels were confirmed by using the FindAllMarkers function of Seurat (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / FindAllMarkers) to identify differentially expressed genes and visualizing marker genes plotted as nuclear density on UMAP using the Nebulosa package. For differential expression analysis, cell type labels were divided into four groups: tumor cells, fibroblasts, lymphocytes, and myeloid cells.

[0141] Pseudo-bulk differential expression analysis: Three biological replicates from lung cancer patients were used for pseudo-bulk differential expression analysis. Specifically, the dataset generated from primary tissue was compared with the dataset generated from MOS to determine the changes in gene expression between the two platforms. Gene count values ​​from cells with the same cell type label were aggregated into a single matrix. The model design formula included terms indicating which samples were generated from primary tissue or MOS. Significance testing was performed using the glmQLFit function from the EdgeR package (www.rdocumentation.org / packages / edgeR / versions / 3.14.0 / topics / glmQLFit), and false discovery rate adjustment was performed on the p-value. Genes with an absolute log-fold change >1 and an adjusted p-value <0.05 were considered to be significantly differentially expressed between the two conditions. The intersections in the differentially expressed gene lists for each cell type were visualized as UpSet plots using the UpSetR package. Volcano plots were generated for the pseudo-bulk results for each cell type using the EnhancedVolcano package and the same significance threshold.

[0142] The remaining two samples were collected from patients with renal cancer (n=1) or ovarian cancer (n=1). For these samples, the logarithmic fold changes of gene expression in the libraries produced by primary tissue or MOS were compared, and no p value was reported. The gene counts of each cell type were averaged using the AverageExpression function of Seurat (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / AverageExpression), and logarithmic conversion values ​​were plotted to compare sample tissues and MOS produced from primary tissues. Genes with logarithmic fold changes>1 are marked in red, and genes with average logarithmic expression>1.5 are marked in black to provide background for genes highly expressed in each cell type.

[0143] Identification of conserved gene expression: The FindConservedMarkers (www.rdocumentation.org / packages / Seurat / versions / 4.1.0 / topics / FindConservedMarkers) function from Seurat was applied to cells of each cell type and genes with conserved expression and log fold change enrichment > 0.5 were identified. The top 5 markers with the highest log fold change enrichment for each cell type were visualized using the DotPlot (ssatijalab.org / seurat / reference / dotplot) function from Seurat. Important cancer gene expression markers CD274 (PD-L1), PDCD1 (PD-1), and TGFB1 (TGF-β) were also specifically visualized to compare expression in tumor cells, lymphocytes, and fibroblasts, respectively. The expression of these markers was plotted as UMAP using the Nebulosa package and marked on the corresponding volcano plots.

[0144] Flow cytometry analysis: MOS and a large number of cells established on days 7 to 9 were treated with TrypLE. Dissociate into single cells and incubate at 37°C for 5 minutes. Wash the dissociated cells with PBS+0.04% BSA and stain with anti-human vimentin antibody (CST catalog number, 1:100) in combination with PE or anti-human EpCAM (Biolegend catalog number 324205, 1:250) for 20 minutes at room temperature. Wash the cells again with PBS+0.04% BSA and then stain with goat anti-mouse AlexaFluro 488 secondary antibody (Invitrogen catalog number A32723) at room temperature for 15 minutes. Before flow analysis, wash the cells again with PBS+0.04% BSA. Add Sytox blue dead cell stain (A34857) diluted 1:1000 to exclude dead cells in the detection. All flow determinations were performed using a Sony SH800 FACS sorter, and flow data were analyzed using FlowJo.

[0145] Drug high-throughput screening: Automated liquid handling was provided by Echo Acoustic Dispenser (Labcyte) for drug administration, or by Well mate (Thermo Fisher) for cell plating, and the Clarioscan plate reader (BMG Labtech) was used for determination. Before cell plating, 119 FDA-approved drug compounds were printed on 384-well plates at a final concentration of 1 μM. The compound library (approved oncology group VI) was provided by the NCI Development Therapeutics Program (https: / / dtp.cancer.gov / ). MOS were spread on these drug pre-coated plates at 100 MOS / well, each MOS containing 30 cells / droplet. Cell viability was assessed via the CellTiter-Glo luminescent cell viability assay (Promega, USA) 72 hours after cell plating. The following formula is used to quantify the percentage of cytotoxicity: 100*[1-(average CellTiterGlo 药物 / averageCellTiterGlo 对照 )].

[0146] HLAA2 plasmid, lentiviral packaging and MOS infection: HLA-A2 (insert) was amplified from a cDNA library prepared from RNA from NCI-H1755 (ATTC, CRL-5892) using the sense primer GGTCGCCACCATGGCCGTCATGGCTCCCCG (SEQ ID NO: 1) and the antisense primer GGCCGCTTTACACTTTACAAGCTGTGAGAG (SEQ ID NO: 2). The linearized plasmid (receptor) 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 a gel DNA recovery kit (Zymo, D4007). The insert fragment was then cloned into the vector by Gibson assembly (NEB, E2611S). HEK 293T cells were co-transfected using Lipofectamine 2000 transfection to produce lentiviral particles. In brief, HEK293T cells were co-transfected with 10 μg of transgenic plasmid, 10 μg of packaging plasmid pCMVR8.74 (Addgene: 22036) and 5 μg of envelope plasmid pMD2.G (Addgene: 12259). The transfection medium was replaced after 12 hours. Recombinant lentivirus was collected at 24 hours and 48 hours. The supernatant containing the virions was then concentrated using a Lenti-X concentrator kit (Takara, 631232). The concentrated lentiviral particles were then aliquoted and stored at -80°C until use.

[0147] MOS infection with lentivirus expressing HLA-A2: When MOS was established, lentivirus expressing HLA-A2 and DsRed was added to lung tumor MOS cultures (MOI = 5-6). After 3 days of incubation, infection efficiency was assessed by observing DsRed expression under a microscope. Flow cytometry was used to assess HLA-A2 gene expression and HLA-A2 antigen expression.

[0148] 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 IVVilo MasterMix and 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).

[0149] Immuno-Oncology Potency Assays

[0150] Human peripheral blood mononuclear cells (PBMC) and patient TIL expansion: Human PBMCs were purchased from STEMCell Technologies (Cat. No. 70025.1). Tumor TILs were generated from dissociated tumor tissue cells. Dissociated cells (0.5x10 6 ) for TIL expansion. The cells were resuspended in IMMUNOCULT supplemented with 6000 IU / mL recombinant human IL-2 (Miltenyi Biotec catalog number 130-097-743). TM TILs were maintained for 1 week before splitting and the medium was changed to medium containing CD3 / CD28 / CD2 T cell activator (STEMCell Technologies, catalog number 10971) for further expansion.

[0151] ESK1* drug preparation: ESK1* TCB and negative TCB (DP47) were supplied by Roche. Drugs were aliquoted immediately upon receipt to avoid multiple freeze-thaw cycles. Drugs were used at a concentration of 1 μg / mL or 10 μg / mL in all potency assays.

[0152] IO assays and Incucyte live cell imaging: MOS generated from primary tumor tissue were seeded into 96-well plates at a density of 30 to 50 MOS per well and provided with medium without Y compound. Day 3 or day 4 MOS were treated with ESK1*, DP47, or nivolumab for at least 3 days and imaged in Incucyte during treatment. When performing immune cell potency assays, pre-activated PBMCs or matched TILs were stained with Cytolight fast red dye according to the manufacturer's instructions. Briefly, Cytolight fast red dye in one bottle was diluted with 20 μl of DMSO and further diluted 10 times in PBS. PBMCs or TILs were incubated with 5 μl of diluted Cytolight red dye (500X) in PBS for 25 minutes at 37°C. After washing once with PBS, PBMCs or TILs were counted and resuspended in wells containing MOS and medium at an effector: target ratio of 5:1 or 10:1. Phospholipin V green dye, caspase 3 / 7 green dye, or Cytotox green dye was added to each well according to the manufacturer's instructions. The plate was loaded into the Incucyte S3 and images were taken every 2 hours for 4 to 5 days.

[0153] IO assay for immunotherapy and MHC blockade: Lung tumor MOS at a concentration of 20 μg / mL were incubated with anti-MHC I / II antibody (W6 / 32; Tu39, catalog number 361702, Biolegend) for 45 minutes at 37°C and then seeded into 96-well plates at a density of 30 to 50 MOS per well and supplied with lung tumor medium without Y-27632. Non-MHC blocked MOS were used as controls. Matched TILs were added to each well at a 5:1 effector:target ratio. Nivolumab was added to the wells at a working concentration of 10 μg / mL. CD2 / CD3 / CD28 T cell activator reagent was added at a working concentration of 25 μl / mL. Phospholipid binding protein V was added to each well according to the manufacturer's instructions.

[0154] Incucyte imaging data analysis: Raw images of the phase bar green and red fluorescence channels were exported, and MOS were manually drawn using the "Labelme" image annotation software. The fluorescence images and labels were then input into a Python script that binarized the images using a constant threshold, counting all pixels above the threshold in the red image as "red", all pixels above the threshold in the green image as "green", and all pixels above the threshold in both the red and green images as "yellow". These pixels were then grouped according to the MOS they belonged to (if any), and the script then exported a CSV file containing the counts of yellow, red, and green pixels contained in the MOS at that time for each well, each time, for each MOS marked in the associated image.

[0155] Quantification and statistical analysis: T-tests were performed using Prism 8.0. p < 0.05 was considered significant.

[0156] MOS generation and establishment

[0157] To establish a precision medicine pipeline that can be used to guide patient care, droplet-based microfluidics technology has been developed to rapidly generate patient-derived cancer models in a reliable manner. Figure 1A The thick needle principle involves adding suspended cells from primary tissue to a 3D extracellular matrix The MOS was then mixed with a two-phase liquid (oil) to generate a microfluidics-based droplet MOS. The generated MOS was de-emulsified to remove excess oil and then cultured in the form of a suspension droplet.

[0158] The basis of the pipeline is a desktop machine for generating MOS ( Figure 1B and Figure 2A ; Table 3). Important design features of the device include reservoirs for loading the oil and sample phases directly onto the custom microfluidic chip, and then positioning the sample outlet on the back of the chip for direct dispensing into the MOS recovery container. An additional pressure source (e.g., Fluigent FlowEZ) is used to control the flow of oil and sample fluids into the custom microfluidic chip through lines connected via a clamping manifold. The 15 mL conical tubes (110) containing oil and the 15 mL conical tubes (110) containing cells / A 1.5 mL Eppendorf tube (120) of sample mixture is pressurized to drive flow through a microfluidic chip set inside a chip holder (130). The device is placed in a refrigerator with the tube connected to an external pump (140). The sample and oil meet at a "T" junction ( Figure 1B ), the sample is “squeezed” into droplets by the oil phase when entering the collection channel. This system is temperature-sensitive Both the 4°C sample and 37°C collection blocks are integrated into this, which allows Flows through microfluidic channels and then rapidly solidifies at higher temperatures. Channel and chamber heights are carefully designed to generate MOS with average diameters of 250 μm to 450 μm, as these dimensions provide a 3D environment well suited to a variety of cell numbers and sizes. The MOS can be generated from as few as 15,000 cells in an 18-gauge needle biopsy, a sample size that is typically too small to reliably generate traditional organoids for therapeutic profiling within clinical time constraints.

[0159] This method was first used to generate MOS from CRC PDX cells. Monitoring the growth of CRC MOS at different seeding densities (20 to 100 cells per droplet) showed that MOS established tumor spheroid-like structures ( Figure 1C ). The number and size of tumor spheroids increased with the seeding density per droplet. MOS were then generated from clinical CRC biopsies ( Figure 1D ) and shows that it has various forms ( Figure 1E ). The number of MOS was determined by dividing the number of viable cells by the number of cells per droplet.

[0160] MOS predicts patient drug response in prospective clinical studies

[0161] Since clinical treatment decisions are typically made within 10 to 14 days of diagnosis, an ideal diagnostic assay would give results within 14 days and use minimal tissue (e.g., core needle biopsy) to predict clinical outcomes. In preliminary studies, biopsies were obtained from patients with metastatic rectal cancer, and MOS (30 tumor cells per MOS) were established within 8 days of biopsy. In vitro high-throughput drug screening was performed by treating 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. MOS was sensitive to oxaliplatin (% killing > 50%) and resistant to irinotecan (% killing < 50%) ( Figure 1F The entire procedure was performed within 11 days of biopsy collection. Consistent with MOS predictions, the patient's tumor continued to respond to oxaliplatin-based therapy after 6 months ( Figure 1G ).

[0162] A prospective clinical study was then designed and conducted. Core needle biopsies (18 gauge) were obtained from seven additional patients presenting with metastatic CRC, MOS were generated, and drug testing was performed ( Figure 1H and Fig. 1I). Patient demographics and mutation status are shown in Table 1. MOS were generated (30 tumor cells per MOS), and all eight biopsy samples were tested for response to oxaliplatin within 13 days (average 9.9 days) after biopsy, with a success rate of 100% (8 / 8) (Table 2). Given the limited tissue volume, doses of 1 μM and 10 μM were selected based on studies published 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 value as measured via Cell Titer Glo was used. Of the eight patients, four had oxaliplatin-sensitive MOS and four had oxaliplatin-resistant MOS ( Figure 1J ).

[0163] All eight patients received oxaliplatin-based therapy according to conventional treatment guidelines. CT scans were then used to evaluate the patient's outcomes before and after oxaliplatin treatment ( FIG. 2B to FIG. 2H ), and the duration of treatment was compared with MOS oxaliplatin sensitivity. All four patients with MOS oxaliplatin sensitivity had a clinical response and continued treatment past 20 weeks (three out of four patients were still receiving treatment at nearly 40 weeks), while three out of four MOS resistant patients did not respond to oxaliplatin treatment and stopped treatment within 10 weeks ( Figure 1J ). The initial CT scan showed a variable response to treatment in the remaining patient in the resistant MOS group, but given the clinical benefit, the patient continued on treatment. Subsequent CT scans showed a response to treatment, and the patient continued on treatment until week 28, when hepatectomy was performed to remove the metastatic lesions ( Figure 2B and Table 2 ).

[0164] This proof-of-concept clinical study demonstrated that MOS can be reliably generated from 18-well biopsies of metastatic CRC tumors and then used to test sensitivity to first-line chemotherapy within 14 days. Our preliminary results suggest that this workflow can predict patient outcomes to a large extent, but larger trials are needed to further validate clinical applicability.

[0165] Cell death was measured per MOS by imaging the caspase 3 / 7 fluorescence signal and normalizing it by the cell surface area within each MOS. Treatment of two available CRC MOS lines resistant to oxaliplatin (20 cells per MOS) showed that only the highest dose induced significant cell killing, with heterogeneity between different MOS ( Figure 3A and Figure 3B ).

[0166] Tumor stromal cells and immune cells in MOS

[0167] Because the tumor microenvironment, and in particular the immune component, may impact cancer therapy, studies have been conducted to characterize the stromal components of patient-derived MOS. The focus has been on lung tumors because they are responsive to immunotherapy, but renal tumors, breast cancer, CRC, and ovarian tumors have also been characterized to a lesser extent. MOS were generated at a density of 30 tumor cells per MOS, and a large number of organoids were established simultaneously using cells of the same density for comparison. Representative images of MOS generated from each tumor type and H&E staining from each tumor tissue and MOS are shown in Figure 3C , Figure 3D and Figure 4A The formation and growth of MOS and bulk organoids were comparable on days 2, 5, and 7 ( Figure 3E ).

[0168] Overgrowth of fibroblasts is often a challenge in establishing organoids from clinical samples of certain cancer types. Comparison of the number of fibroblasts in MOS and bulk organoid cultures between days 7 and 9. Fewer fibroblasts ( Figure 3F ), as confirmed by flow cytometric analysis of vimentin expression ( Figure 5A ). MOS generated from patients with lung, ovarian, and kidney cancers were then subjected to rapid, high-throughput chemotherapeutic drug screening and measured for sensitivity to commonly used drugs used to treat these cancers.

[0169] Whole exome sequencing of MOS was compared with matched primary tumor samples to determine whether genomic alterations were maintained (Table 4). First, copy number variations (CNVs) were characterized. Figure 4B ) and other cancer types ( Figure 5B ) and the original tissue. Second, somatic mutations in the genomes of matched MOS and original tumor samples were characterized. For each cancer type, the mutation profiles of matched tissue samples and MOS were highly correlated, but not unmatched samples ( Figure 5C). Variability between tissue samples and matching MOS is common ( Figure 5D For each cancer type, driver mutations in commonly affected genes were largely consistent between tissue samples and MOS, 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 also not present in MOS) of 95% ± 0.003 ( Figure 5E ). These findings suggest that MOS largely capture the genomic profile of the patient tumor from which it was derived.

[0170] To compare tumor and stromal cell types between tissue and derived MOS, single-cell RNA sequencing was performed on six pairs of matched patient tumor samples (three lung cancers, one kidney cancer, one ovarian cancer, and one CRC) and derived MOS (7 to 9 days) (Macosko et al., Cell 161, 1202-1214, 2015). QC is summarized in Fig. 6A and Figure 6B Using UMAP reduction, cells from all three lung cancer samples were clustered into four groups labeled as tumor cells, cancer-associated fibroblasts, and lymphoid or myeloid immune cells, which were consistent between tissues and MOS ( Figure 4C ), with comparable relative abundance levels ( Figure 4D and Figure 6C ). Similar single-cell RNA sequencing analyses were performed on renal cancer, ovarian cancer, and CRC ( FIG. 6D to FIG. 6F Flow cytometry analysis confirmed the presence of major immune cell populations in CRC MOS ( Fig. 7A ). Pseudo-bulk analysis showed that overall gene expression levels per cell population were comparable between primary tissue and MOS ( Figure 4E ), and relatively few differentially expressed genes ( Figure 7B , Figure 7C and Fig. 8A ). Analysis of each cell type in the lung cancer pairs showed that lymphocytes had more differentially expressed genes than other cell types ( Figure 8B ).

[0171] In addition, the expression patterns of immunosuppressive markers were basically consistent between lung cancer tumor tissues and MOS. After automatic cell type labeling using the SingleR package, UMAP was used to visualize the expression of cell type-specific gene markers. CD274 (PD-L1) was mainly expressed in tumor and myeloid cell clusters, while PDCD1 (PD-1) and TGFB1 (TGF-β) were expressed at elevated levels in lymphocytes ( Figure 8C The top five genes with the highest log-fold change enrichment in each cell type were visualized to confirm consistent expression across each cell type and sample preparation ( Fig.8D These conserved markers, including the key cell type-specific markers EPCAM, PDGFRA, LYZ, and CD3E for tumor cells, fibroblasts, myeloid cells, and lymphocytes, respectively, were largely consistent between tissues and derived MOS ( Fig.7D ).

[0172] Immune cells preserved in MOS respond to immunotherapy

[0173] The purpose of the study was to examine whether patient immune cells in MOS were functional and responsive to IO therapy. Addition of anti-CD3 and anti-CD28 antibodies to MOS culture media increased CD4+, CD8+, and CD56+ (natural killer cell markers) populations and had a modest effect on the CD11b+ (dendritic cell marker) population ( Fig.9A ), indicating that immune cells resident in MOS encapsulated are viable and responsive to immune stimulation.

[0174] Immune checkpoint inhibitors, particularly 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, there is still an urgent need for an in vitro assay to better guide IO therapy in patients with advanced NSCLC, as PD-L1 expression and tumor mutation burden do not fully predict patient response. MOS generated from NSCLC patient samples, at a density of 30 tumor cells per MOS, formed tumor sphere-like structures in the presence of tumor-resident immune cells. MOS were then treated with 10 μg / mL of the anti-PD1 therapy nivolumab (day 4), and apoptosis was assessed using phospholipid-binding protein V. Nivolumab induced tumor sphere death within MOS ( Fig. 10A and Fig. 10B The Incucyte measurement also contains background signal outside the tumor spheroids from cellular debris in the MOS microenvironment, resulting in an elevated curve in the control. In MOS derived from patients with renal cancer (day 3), treatment with nivolumab alone did not enhance killing of tumor spheroids within the MOS, whereas the combination of nivolumab and a T cell activator enhanced killing of tumor spheroids ( FIG. 9B to FIG. 9D ).

[0175] T cell-based therapies have been directed against intracellular antigens presented on the cell surface by human leukocyte antigen (HLA) molecules. Studies were conducted to test whether the non-selective HLA-A*02 / WT1-targeting antibody ESK1* (ESK-1 Tumor Binder, Roche Proprietary CD3), a T cell receptor mimetic monoclonal antibody (mAb) that binds human leukocyte antigens HLA-A2 / WT1 and CD3, could induce cytotoxic T cell (CTL)-mediated killing in MOS derived from patient lung tumors ( Fig. 10C and Fig. 10D ) (Dao et al., Nature Biotechnol 33, 1079-1086, 2015). Fig. 10E ) and flow cytometry ( Fig.10F ) to verify HLA-A2 genotype. ESK1* was compared with a negative control DP47, which is a non-tumor-targeted 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 (indicated by phospholipid binding protein V signal) ( Figure 10G Although DP47 was also able to activate T cells through CD3 and cause cell death, ESK1* induced more killing in all eight lung cancer patient cases ( Fig. 10H and Fig.10I ).

[0176] CRC MOS (HLAA2+) were then treated with ESK1*. MOS were generated at a density of 30 tumor cells per MOS. A higher dose of ESK1* (10 μg / mL) induced more tumor sphere death in MOS than a lower dose of ESK1* (1 μg / mL) ( Fig.9E and Fig.9F Quantification of phospholipin V fluorescence signals from individual tumor spheroids confirmed ESK1-mediated killing in MOS, but not in MOS embedded in conventional This was not the case in organoids in the dome ( FIG. 9G to FIG. 9I ).

[0177] To further understand how MOS responds to ESK1*, 10X single-cell RNA sequencing was performed on primary lung tumor tissue cells at day 0 and MOS treated with ESK1*, negative TCB (DP47) without any added treatment at day 5 ( Figure 9J The clusters analyzed from tissue samples and MOS undergoing treatment were consistent ( Figure 9K and Figure 9LThe abundance of each cell type from MOS treated with DP47 or without treatment was similar to that of the original tissue cells, but was dramatically decreased in MOS treated with ESK1* ( Figure 9M ). Collectively, these results suggest that the MOS assay can be used to rapidly assess the effects of IO therapy molecules, such as PD-1 blockers and TCBs, on patient tumor and stromal cells.

[0178] MOS potency assay for T cell therapy

[0179] Adoptive T cell therapy (ACT), such as chimeric antigen receptor T cell (CAR-T) therapy and TIL therapy, has the potential to transform 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 the determination of the efficacy of manufactured T cells against patient tumors, which is required by regulatory agencies 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 assess the effects of TILs on patient tumors, but at least four studies have shown that it is not associated 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). For ACT using TILs, patient tumor models must be quickly established from a small portion of the biopsy (because a large portion of the biopsy must be used to extract and expand TILs), which makes it particularly challenging.

[0180] To explore whether MOS could be used as a potential efficacy assay, patient-derived autologous TILs were infiltrated with MOS (20 cells per MOS) into a large population of Most T cells remain in a large number of In contrast, T cells easily penetrated into the MOS (due to their smaller size and larger surface area to volume ratio) and adhered to tumor cells ( Fig.11A and Fig. 11B The infiltration of peripheral blood mononuclear cells (PBMCs) into Compared with the situation of MOS (20 cells per MOS), it is revealed that immune cells can easily infiltrate MOS ( Fig. 12A ). Time-lapse fluorescence imaging was used to measure the immune cytotoxicity of TILs and PBMCs against targeted tumor cells. For TIL potency assays, MOS generated at a density of 30 tumor cells per MOS were grown simultaneously with TILs from the same lung tumor tissue. Increased killing (indicated by phospholipid binding protein V) was observed in MOS treated with autologous TILs ( Fig. 11C and Fig.11D ). This assay confirmed the efficacy of Rapid Expansion Protocol (REP) TILs against matched lung tumor MOS, providing promising preliminary data for TIL efficacy assays.

[0181] The efficacy of PBMCs against lung tumor MOS was then evaluated to demonstrate that MOS can be used as an in vitro platform for cell therapy. MOS were derived from lung cancer patients, and allogeneic PBMCs from different normal patients were added. After 96 hours of co-culture with PBMCs, tumor spheroids within MOS were still viable, as indicated by Cytolight Fast Red labeling, which appeared orange. However, when PBMCs were activated with anti-CD3 and anti-CD28 antibodies, tumor spheroids showed increased cell death, as shown by phospholipid binding protein V staining ( Fig. 12B ).

[0182] Phospholipid binding protein V (early cell surface apoptosis), caspase 3 / 7 (enzyme-mediated apoptosis), and Cytotox (cell membrane integrity) were used to characterize the response of lung cancer MOS (20 cells per MOS) to activated PBMC. PBMC were prestained with the live cell marker Cytolight red dye. Both phospholipid binding protein V and caspase 3 / 7 can detect MOS apoptosis, with caspase 3 / 7 being more specific ( Fig.11E , Fig.11F , Fig. 12C and Fig.12D ). An imaging analysis pipeline was developed to identify MOS regions to screen out background noise from external immune cells ( Fig.11G ), which confirmed PBMC-induced apoptosis of MOS cells with less background signal from outside the MOS ( Fig.11H PBMCs also induced tumor spheroid death in CRC MOS (20 cells per MOS), which was enhanced by cytokine activation ( Fig.12E and Fig.12F), and renal cancer MOS (20 cells per MOS), which was enhanced by a higher effector cell:target cell ratio ( Figure 12G and Fig.12H ).

[0183] Adjuvant therapy was first explored by combining PD-1 blockade (nivolumab) with autologous TILs against matched lung tumor MOS. PD-1 blockade enhanced TIL-mediated killing within MOS, which was eliminated by blocking MHC ( Fig.12I ). TCB was then combined with autologous TIL or allogeneic PBMC to treat HLA-A2-expressing lung cancer MOS (20 cells per MOS). Compared with DP47, ESK1* enhanced TIL- and PBMC-induced tumor cell death ( Fig.11I , Fig.11J , Fig.12J and Figure 12K In all seven lung cancer samples, the phospholipid binding protein V signal was higher in MOS treated with ESK1* than in MOS treated with DP47 ( Figure 11K ). As a negative control, ESK1* did not enhance the killing effect on HLA-A2(-) lung cancer MOS, as indicated by the red arrow. The heterogeneity of drug response between MOS from the same patient was observed and quantified ( Figure 12K and Figure 12L ).

[0184] Traditional large-scale organoids are re-embedded Previously, single cells needed to be isolated for viral gene delivery. Due to the small size and large specific surface area of ​​MOS, lentivirus can be directly added to the culture medium to infect MOS without dissociation. This provides a convenient method to edit MOS at passage 0. Lung cancer MOS from HLA-A2(-) patients (20 cells per MOS) were infected with lentiviral HLA-A2 expression vector for 3 days and dsRed was used as a control ( Fig.11L and Figure 12M MOS infected with HLA-A2 showed high expression ( Fig.11M and Fig.11N ). HLA-A2-infected MOS were then treated with a combination of ESK1* and activated PBMCs. In the presence of ESK1* and activated PBMCs, HLA-A2-infected MOS experienced more cell death than matched uninfected MOS, thus verifying that HLA-A2 expression levels mediate the efficacy of ESK1*+PBMC treatment ( Fig.11O ).

[0185]

[0186]

[0187]

[0188]

[0189] Other embodiments

[0190] It should be understood that although the invention has been described in conjunction with the specific description of the invention, the foregoing description is intended to illustrate rather than limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages and modifications are within the scope of the following claims.

Claims

1. A method comprising: obtaining multiple cells derived from tissue; forming a micro-organ spheroid (MOS) from the plurality of cells; culturing the MOS in a MOS culture; as well as The virus is introduced into the MOS culture, thereby obtaining one or more cells in the MOS infected with the virus.

2. The method of claim 1, wherein the infected cell or cells express one or more genes introduced by the virus after infection with the virus.

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

4. The method of any one of claims 1 to 3, wherein the plurality of cells comprises no more than 15,000 cells.

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 of any one of claims 1 to 6, wherein the cells are derived from one or more core needle biopsies, the one or more core needle biopsies comprising about a 14 gauge core needle biopsy to about a 20 gauge core needle biopsy.

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

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

10. The method of claim 9, wherein the one or more cancers comprise 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 of any one of claims 1 to 11, wherein the cells comprise patient-derived xenograft (PDX) cells from a CRC patient.

13. The method of any one of claims 1 to 12, wherein the MOS comprises a tumor spheroid.

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

15. The method of any one of claims 1 to 13, wherein the nascent MOS comprises a seeding density configured to generate a desired number, size, or both of tumor spheroids in the MOS.

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

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

18. The method of claim 17, wherein the one or more therapeutic agents comprise a small molecule or an antibody.

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

20. The method of claim 19, wherein the MOS serves as a predictive model for the patient's sensitivity to one or more chemotherapies.

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