Apparatus for recovering magnetically tagged target cells - Patent application

Abstract

Apparatus, systems and methods are provided for retrieving magnetically tagged target cells from a cell collection fluid. The apparatus includes a magnet plate having an array of micromagnets and a modular chip releasably coupled to the magnet plate. The modular chip has a flow chamber and a plurality of flow reduction structures. A magnetic field generated by the array of micromagnets cooperates with the flow reduction structures to define a capture zone in the vicinity of each structure. The magnetic field is sufficient to overcome drag forces on the target cells to facilitate capture of the target cells in the capture zone. Separation of the modular chip from the magnet plate allows for recovery of the captured target cells from the modular chip.

Description

[Technical field]

[0001] The present disclosure relates generally to an apparatus for recovering cells from a population of cells. In particular, the present disclosure relates to an apparatus that uses magnets to recover magnetically tagged target cells in a flow chamber. [Background technology]

[0002] Tumor-infiltrating lymphocytes (TILs) are a subset of leukocytes that leave the circulation and migrate to tumor tissue. 1 TILs are involved in the tumor killing process, and the presence of TILs in tumors is often associated with better clinical outcomes after treatment. 2 Due to their efficacy in killing tumors, TILs have been successfully used in adoptive cellular therapy (ACT) to treat cancer and have achieved remarkable success in the management of highly immunogenic tumors, especially melanoma.

[0003] Despite its success in the clinic, prolonged turnaround times significantly limit the application of TIL-based ACT. To date, typical lead times for TIL-based ACT vary from 6 to 14 weeks. 3 ,TIL growth and proliferation accounts for 80% of the lead time. 4~6 This approach to generate therapeutic doses of TILs dramatically increases the total cost of TIL-based ACT to >$85,000 per patient. 7 It is well accepted that more effective TIL isolation / expansion could greatly benefit their utility and clinical adoption. Moreover, approximately 20% of patients will clinically deteriorate before completion of TIL production. 9 A faster TIL manufacturing process could potentially provide better outcomes for these patients. Furthermore, some studies suggest that prolonged proliferation may alter the phenotype and efficacy of TILs. 10,11 TILs that underwent minimal culture and selection in vitro showed higher levels of antigen reactivity and activation when used in vivo. 12Taken together, it is highly desirable to establish a method to efficiently generate large numbers of highly potent TILs from the original source with minimal post-isolation processing.

[0004] The amount of TILs after expansion depends on two main factors: the rate of expansion and the initial amount of cells. Although considerable efforts have been made to optimize the expansion conditions of TILs, 13,14 However, very limited research has been done on increasing the initial amount of TILs isolated from tumors. + TILs are the primary driver of tumor rejection in patients, and therefore CD8 + Enrichment of TIL subpopulations such as 15 and specificity 16 can be improved 17 In the study, enrichment of TILs from digested tumor tissue was performed using fluorescence-activated cell sorting (FACS). 18~20 or magnetic activated cell sorting (MACS), but none of these approaches have been used to isolate TILs in clinical applications. 21,22 FACS often loses 50-70% of the cells due to poor droplet formation or scanning errors. 23,24 This low level of recovery may result in significant loss of TILs and impede downstream proliferation processes. Furthermore, although MACS has a better recovery rate than FACS, 24 This column-based approach captures dead cells and debris. 25 , leading to inadequate enrichment of small cells, including leukocytes 26,27 .

[0005] Microfluidic-based approaches have been used for cell sorting with high specificity and sensitivity 28,29 Circulating tumor cells 30,31 , antigen-specific T cells 32,33 , and contaminating tumorigenic cells 34These have been widely applied to the isolation, recovery, and analysis of various mammalian cells, such as TILs, TILs, and TILs. However, existing platforms are not suitable for TIL isolation, which requires volumetric, high-recovery, and high-purity cell sorting at a reasonable cost. Summary of the Invention

[0006] In some examples, the present disclosure describes an apparatus for magnetically retrieving tagged target cells from a cell collection fluid, the apparatus comprising: a magnet plate having an array of micromagnets disposed therein, the array of micromagnets generating a magnetic field along the magnet plate; and a modular chip releasably coupled overlying the magnet plate, the modular chip comprising a flow chamber having an inlet and an outlet, and a plurality of flow reduction structures within the flow chamber, each structure comprising a capture surface shaped to reduce flow near the capture surface, the magnetic field generated by the array of micromagnets cooperating with the flow reduction structures to define corresponding capture zones near each of the flow reduction structures, where the magnetic field is sufficiently high in the capture zones to overcome drag forces on the target cells to facilitate capture of the target cells from the cell collection, and where separation of the modular chip from the magnet plate enables separation and recovery of the captured target cells from the modular chip.

[0007] In some examples, the present disclosure describes a system for recovering magnetically tagged target cells from a cell collection, the system comprising: a magnet plate having an array of micromagnets disposed therein, the array of micromagnets generating a magnetic field along the magnet plate; one or more modular chips releasably coupled overlying the magnet plate, each of the one or more modular chips having a flow chamber having an inlet and an outlet, and a plurality of flow reduction structures within the flow chamber, each structure having a capture surface shaped to reduce flow in the vicinity of the capture surface, the magnetic field generated by the array of micromagnets cooperating with the flow reduction structures to define a corresponding capture zone in the vicinity of each of the flow reduction structures, where the magnetic field is sufficiently high in the capture zone to overcome a drag force on the target cells to facilitate capture of the target cells from the cell collection, and where separation of the modular chip from the magnet plate enables separation and recovery of the captured target cells from the modular chip; and a scaffold configured to hold the magnet plate.

[0008] In some examples, the present disclosure describes a method for magnetically recovering tagged target cells from a cell collection fluid, the method including the steps of: introducing the magnetically tagged cell collection fluid into an apparatus comprising a magnet plate having an array of micromagnets disposed therein, the array of micromagnets generating a magnetic field along the magnet plate, and a modular chip releasably coupled over the magnet plate, the modular chip having a flow chamber with a plurality of flow reduction structures, the magnetically tagged target cells being sensitive to magnetic attraction and being captured by the flow reduction structures as they move through the flow chamber; washing non-target cells from the apparatus; separating the modular chip from the magnet plate; and recovering the magnetically tagged target cells from the modular chip.

[0009] In some examples, the present disclosure describes a method for magnetically recovering tagged target cells from a cell collection fluid, the method comprising the steps of introducing a cell collection fluid containing magnetically tagged target cells into a system as described herein through an inlet of a first modular chip and directing the fluid sample from an outlet of the first modular chip into an inlet of a second modular chip, flushing non-target cells from the system, separating the first and second modular chips from a magnet plate, and recovering the magnetically tagged target cells from the first and second modular chips.

[0010] In some examples, the present disclosure describes a method for magnetically recovering tagged target cells from a cell collection fluid, the method comprising introducing a cell collection fluid containing magnetically tagged target cells into a system as described herein through an inlet of a first modular chip and an inlet of a second modular chip, flushing non-target cells from the system, separating the first modular chip and the second modular chip from a magnet plate, and recovering the magnetically tagged target cells from the first modular chip and the second modular chip.

[0011] The ability of the modular chip to separate from the magnet plate helps improve throughput in the disclosed devices, systems, and methods, and increases the ease of removing cells from the modular chip after sorting. The releasable coupling also allows the system to be field programmable, i.e., allows flexibility in changing and adapting the configuration for different sorting applications. For example, the releasable coupling of the modular chip to the magnet plate allows the system to be interchangeable between serial and parallel configurations by the end user. The fact that the modular chip and the magnet plate are separate components also allows the modular chip to be fabricated more quickly and cheaply using 3D printing and / or injection molding instead of using traditional lithography. This can also be beneficial in enabling a hygienic disposable system, and low-cost, high-volume 3D printing processes can be used to fabricate the disposable modular chip, which may be particularly desirable in a healthcare environment. [Brief description of the drawings]

[0012] Reference will now be made, by way of example, to the accompanying drawings which illustrate exemplary embodiments of the present application.

[0013] [Figure 1] FIG. 1 is an illustration of an exemplary exploded device having different channel thicknesses for magnetic recovery of target cells from a cell collection. [Diagram 2] 2a is an exemplary diagram of the assembled devices of FIG. 1 connected in parallel in a system for magnetic recovery of target cells from a cell collection according to one embodiment of the present disclosure, and FIG. 2b is an exemplary diagram of the assembled devices of FIG. 1 connected in series in a system according to another embodiment of the present disclosure. [Diagram 3] 2 is a photograph of the exemplary device of FIG. 1 disassembled. [Figure 4] 2b is a photograph of the assembled system of FIG. 2a. [Diagram 5]Figure 5a is a photograph of the assembled device of Figure 3 according to another embodiment of the present disclosure, and Figure 5b is an enlarged view of portion A of Figure 5a. [Figure 6] 5b is an enlarged perspective view of part X in each of the devices of FIG. 5a. FIG. [Figure 7] FIG. 1 is a schematic diagram of an exemplary method for the recovery of magnetically tagged target cells from a tumor sample for use in adoptive cell therapy. [Figure 8] 2c is a flow chart showing steps of an exemplary method for recovering target cells from a cell collection using the device of FIG. 2a or 2b. [Figure 9] Figures 5a and 6 show the simulated flow velocity distributions (units of color bar (mm·s-1)) in devices with different heights. [Figure 10] Quantification of the simulated flow velocities in FIG. [Figure 11] 1 is an illustration of how magnetically tagged target cells can be separated from non-target cells. [Figure 12] 2c is a flow chart showing steps of an exemplary method for recovering target cells from a cell collection using the system of FIG. 2a or 2b. [Figure 13] Figure 13a is a schematic of the system of Figure 2a used to recover magnetically tagged target TILs, and Figure 13b is a schematic of the system of Figure 2b used to recover a subset of the recovered TILs, CD8+ TILs, from Figure 13a. [Figure 14] Figures 14a, 14b, and 14c show a comparison between binary microfluidic cell sorting and commercial column-based magnetic cell sorting (MACS). (14a) Typical CD45 profiles of K562 and MDA-MB-231 cells used for positive and negative enrichment. (14b) Quantification of capture performance during positive enrichment. Legend indicates cell number used for each run. (14c) Quantification of capture performance during negative enrichment. Legend indicates cell number used for each run. [Figure 15]Figures 15a, 15b, and 15c show a comparison between quantitative microfluidic cell sorting and commercial column-based magnetic cell sorting (MACS). (15a) Typical CD326 profiles of PC-3M, MDA-MB-231, and U937 cells. (15b) Quantification of capture profiles of quantitative microfluidic cell sorting and estimated capture cutoffs. (15c) Quantification of capture profiles of binary MACS sorting and its estimated capture cutoffs. [Figure 16] Figures 16a, 16b, 16c, and 17 show the optimization of flow rates for sorting TILs based on CD4 or CD8, (16a) is a typical flow cytometry profile of pure human CD4 T cells, pure MDA-MB-231 cells, and 1% CD4 T cells spiked into MDA-MB-231 cells. CD4 was occupied by MNPs, so CD45 conjugated with APC was used to confirm purity. (16b) is a typical flow cytometry profile of purified spike-in samples under different flow rates. The optimal flow rate for human CD4 is 32 mL / hr. (16c) is a typical flow cytometry profile of purified spike-in samples under different flow rates. The optimal flow rate for mouse CD8 is 16 mL / hr. [Figure 17] Figures 16a, 16b, 16c, and 17 show optimization of flow rates for sorting TILs based on CD4 or CD8, and (17) is a quantitative comparison between the purity of FACS / MACS / MAGIC for isolating 0.1% and 1% spike-in samples (human CD4 in MDA-MB-231 and mouse CD8 in B16F10). [Figure 18] Figures 18 and 19 are representative cytometry histograms and quantification of recovery efficiency of T cell populations purified from 0.1% and 1% spike-in samples (human CD4 in MDA-MB-231 and mouse CD8 in B16F10). [Figure 19]Figures 18 and 19 are representative cytometry histograms and quantification of recovery efficiency of T cell populations purified from 0.1% and 1% spike-in samples (human CD4 in MDA-MB-231 and mouse CD8 in B16F10). [Figure 20] 1 is a pie chart comparing cellular stress induced by different sorting techniques. [Figure 21] Figure 1 shows the workflow of a mouse melanoma model for TIL isolation. [Figure 22] Figure 22 and Figure 23 are typical cytometry plots at D4 after isolation and quantification of TIL purity and recovery. TIL was defined as CD8+ / CD45+ population. Pure B16 cells and CD8+ splenocytes were used as negative and positive controls. Analysis was performed on day 4 to degrade CD8-MNPs and re-express CD8 epitopes for fluorescent labeling. [Diagram 23] Figure 22 and Figure 23 are typical cytometry plots at D4 after isolation and quantification of TIL purity and recovery. TIL was defined as CD8+ / CD45+ population. Pure B16 cells and CD8+ splenocytes were used as negative and positive controls. Analysis was performed on day 4 to degrade CD8-MNPs and re-express CD8 epitopes for fluorescent labeling. [Figure 24] Graph showing determination of unique clonotypes within TIL populations based on CDR3 expression using bulk TCR sequencing and Shannon diversity index. [Diagram 25] FIG. 13 is a graph showing quantification of FACS / MACS / FACS recovery for isolation of TILs from human NSCLC patients. [Figure 26] Graph showing the growth curves of TILs isolated by different methods from standard counts using a hemocytometer. [Figure 27] Typical CD45RA / CCR7 profile of MAGIC-TILs after 14 days of expansion is shown. [Figure 28]Quantification of relative mRNA expression of TILs compared to CD8 T cells in blood using TaqMan microarrays. Upregulation in proliferation, activation, cytotoxicity and immune response related pathways was observed (NFkB and JAK-STAT). MAGIC TILs have more significant upregulation of immune response core genes such as IFNG, GZMB, NFKB family and STAT family compared to MACS / FACS TILs. [Figure 29] Figure 1 shows pathway enrichment using gene sets with log2(FC)>1.5. Positive regulation is highly likely in T cell proliferation, activation, cytotoxicity, and NFkB, JAK-STAT, and TNF pathways. A higher (-log10(P) score means that the corresponding pathway is more likely to be involved. [Diagram 30] 1 is a graph showing the cytotoxicity of TILs against B16F10OVA-GFP cells in vitro. MAGIC TILs have higher killing efficacy in vitro. [Diagram 31] Cytokine profile of supernatants collected from in vitro killing assays. Compared to non-TIL controls, the presence of TILs promotes secretion of several cytokines / chemokines involved in antigen presentation, monocyte recruitment and anti-angiogenesis. Similar to RNA levels, a more significant secretion of IFN was observed in MAGIC TILs compared to MACS / FACS TILs. [Diagram 32] Figure 1 shows the workflow for Scenario 1 study comparing the therapeutic efficacy of TILs expanded for 14 days. The number of available TILs on D14 is 2x106, 5x105, and 5x104 for MAGIC, MACS, and FACS per mouse. [Diagram 33] Typical tumor sizes for each group on day 18 are shown. [Diagram 34] Graph showing quantification of tumor size and survival curves treated with TILs isolated by MAGIC, MACS, and FACS (n=5). (The maximum number of available TILs was injected into each group.) Statistical significance was determined using the log-rank test. [Diagram 35] Graph showing quantification of tumor size and survival curves treated with MAGIC-TIL under different doses (n=5). Statistical significance was determined using the log-rank test. [Diagram 36] 1 is a graph showing a comparison of the therapeutic efficacy of MAGIC and MACS TILs at the same dose (5×10 5 , n=5) with that of MAGIC and FACS TILs at the same dose (5×10 4 , n=5). [Figure 37] We present the workflow of the study for scenario 2, comparing the therapeutic efficacy of TILs isolated by different methods at the earliest time points (D5 for MAGIC, DIO for MACS, and D15 for FACS; for FACS, fewer (5 × 104) TILs were injected because the desired concentration was not reached before the mice developed large tumors), with an optimal dose of approximately 5 × 105. [Figure 38] Typical tumor sizes for each group on day 18 are shown. [Figure 39] Graph showing quantification of tumor size and survival curves treated with TILs isolated by MAGIC, MACS, and FACS (n=5, **p<0.01). Statistical significance was determined using the log-rank test. [Diagram 40] Representative images of infiltrating T cells in solid tumors (blue: nuclei, red: CD8a, brown: melanin) and quantification of the number / area coverage of CD8+ TILs in tumors treated by MAGIC, MACS, and FACS TIL (n=3, 5 slices per tumor). [Diagram 41] Figure 1 shows the workflow of the murine colon cancer model MC-38 for quantitative CD39-based sorting of CD8 TILs. [Diagram 42] A typical cytometric profile of CD39 expression in bulk CD8 TIL populations and characterization of sorted cells from CD39-mediated quantitative sorting are shown. [Diagram 43] Quantification of relative mRNA expression of different CD39 populations compared to bulk CD8 TILs is shown. [Diagram 44] Representative cytometric profiles and quantification of cell proliferation based on Ki67 expression. [Diagram 45] 1 is a graph showing the cytotoxicity of TILs against MC-38 cells in vitro. [Diagram 46] We present the workflow of an animal study comparing the therapeutic efficacy of different populations of TILs isolated by quantitative MAGIC based on CD39 expression. [Figure 47] Typical tumor sizes for each group on day 21 are shown. [Figure 48] Graph showing quantification of tumor size treated with TILs with different CD39 expression (n=5-10). Statistical significance was determined using the log-rank test. [Figure 49] Graph showing quantification of tumor size treated with TILs of different purification degrees (unsorted, CD8 sorted, CD8 and CD39 sorted, n=5-10). Statistical significance was determined using the log-rank test. [Figure 50] FIG. 50a shows the experimental validation of the proposed working principle of configurable microfluidic cell sorting, where the experiment was carried out using K562 cells labeled by anti-CD45 MNPs and stained by calcein AM. The images are typical microscopic images of the device with different trapping settings. Only the combination of magnetically labeled cells with a suitable external magnet led to efficient cell capture at the desired trapping pocket. FIG. 50b are typical microscopic images of the device at different operational stages. After removing the magnet, nearly 100% of the captured cells could be recovered from the chip, which provided excellent recovery efficiency during cell sorting. [Figure 51] Figures 51, 52, 53, and 54 illustrate the isolation and clonotyping of CD8+ TILs in the B16F10 melanoma model, where Figure 51 illustrates a representative gating strategy used for FACS isolation of CD8+ TILs. [Figure 52]Figures 51, 52, 53, and 54 illustrate the isolation and clonotyping of CD8+ TILs in the B16F10 melanoma model, where Figure 52 illustrates the use of V and J genes from isolated CD8+ TILs by different approaches. Similar enrichment of genes was seen in all approaches, indicating similar origin and phenotype of the isolated TILs. [Figure 53] Figures 51, 52, 53, and 54 illustrate the isolation and clonotyping of CD8+ TILs in the B16F10 melanoma model, where Figure 53 illustrates the VJ pairing status of CD8+ TILs isolated by different approaches. [Figure 54] Figures 51, 52, 53, and 54 illustrate the isolation and clonotyping of CD8+ TILs in the B16F10 melanoma model, and Figure 54 illustrates the quantification of the VJ pairing status. The high recovery approach was able to separate rare clones of TILs, better preserving their complexity and diversity. [Figure 55] Figures 55 and 56 show a comparison of different sorting techniques on human NSCLC samples, Figure 55 shows typical cytometric profiles before and after sorting and Figure 56 shows quantification of FACS / MACS / FACS purity. [Figure 56] Figures 55 and 56 show a comparison of different sorting techniques on human NSCLC samples, Figure 55 shows typical cytometric profiles before and after sorting and Figure 56 shows quantification of FACS / MACS / FACS purity. [Figure 57] Figure 57 shows the relative expression, with the top panel showing pathway enrichment and the bottom panel showing immune-related genes by specific pathways. Activated CD8+ T cells from spleen were used as an internal reference. [Figure 58]Figures 58a, 58b, 59a, and 59b show quantification of CD8+ TILs in tumors that received adoptive cell therapy, where Figure 58a shows that a random forest-based tumor classifier was trained with user-defined tumor / stroma / glass regions. The trained classifier was then applied to perform whole-slide segmentation to identify tumors. Stroma and glass regions were excluded in downstream analysis. Figure 58b shows that the overlaid brightfield images were decomposed by the CytoNuclear algorithm to reconstruct the hematoxylin (blue), warp red, and brown channels. The decomposed images were used to calculate the positive area of ​​each channel by thresholding. [Figure 59] Figures 58a, 58b, 59a, and 59b show quantification of CD8+ TILs in tumors that underwent adoptive cell therapy, where Figure 59a shows the cell count of CD8+ TILs, quantified by an automated cell counting algorithm using decomposed images. TILs were defined as hematoxylin+ / warp red+, and Figure 59b shows a typical decomposed image from a tumor that underwent adoptive cell therapy. [Figure 60] Figures 60a, 60b, and Figure 61 show flow cytometry analysis of TILs from different CD39 populations in the MC-38 mouse model, Figure 60a is an MC-38 model with approximately 1% CD8+ TILs in the tumor by CD8 / CD45 gating, and Figure 60b is a typical cytometry profile and quantification of exhaustion markers (PD-1, TIM3, TIGIT). [Figure 61] Figures 60a, 60b, and Figure 61 show flow cytometry analysis of TILs from different CD39 populations in the MC-38 mouse model, with Figure 61 being a typical cytometry profile and quantification of intracellular cytokines (IFN, TNF, IL-2). [Figure 62a]Figure 62a shows benchmarking of CD326 across different cancer cell lines. A mixture of these cell lines was generated with a fairly uniform and broad spectrum of CD326 expression as input. Figure 62b shows typical flow cytometry profiles and median fluorescence intensity (MFI) of the populations collected from each module running at a flow rate of 16 mL / hr. Figure 62c shows the MFI of the populations collected from each module running at a flow rate of 8 mL / hr. [Figure 62b] Figure 62a shows benchmarking of CD326 across different cancer cell lines. A mixture of these cell lines was generated with a fairly uniform and broad spectrum of CD326 expression as input. Figure 62b shows typical flow cytometry profiles and median fluorescence intensity (MFI) of the populations collected from each module running at a flow rate of 16 mL / hr. Figure 62c shows the MFI of the populations collected from each module running at a flow rate of 8 mL / hr. [Fig. 62c] Figure 62a shows benchmarking of CD326 across different cancer cell lines. A mixture of these cell lines was generated with a fairly uniform and broad spectrum of CD326 expression as input. Figure 62b shows typical flow cytometry profiles and median fluorescence intensity (MFI) of the populations collected from each module running at a flow rate of 16 mL / hr. Figure 62c shows the MFI of the populations collected from each module running at a flow rate of 8 mL / hr. [Figure 63] 1 shows the characterization of the capabilities of a 3D printer to print a mold for fabricating an example of the disclosed modular chip. The 3D printer has been shown to better support the shaping of positive structures (i.e., microposts) than negative structures (i.e., microwells). The printer can print fine features with widths of less than 200 μm in the positive shape. [Figure 64] Illustrates the direct generation of high aspect ratio and compound height structures using 3D printing. [Figure 65]Figure 1 shows the workflow of the double replica procedure for fabricating an example of the disclosed modular chip. From one 3D printed positive mold, multiple PDMS models carrying high-resolution negative patterns can be generated. After a debonding process, these negative molds can be used to generate positive channels and fabricate the final device. [Figure 66] An example of the disclosed system is used to demonstrate quantification of sorting performance when performing antibody-mediated negative selection and multimer-mediated positive selection for isolating HA-reactive T cells from peripheral blood cells.

[0014] Similar reference numbers may be used in different figures to indicate similar components. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] In various examples, the present disclosure describes devices and methods for recovering target cells, particularly magnetically tagged target cells, from cell collections. The disclosed devices, systems, and methods may also be used to recover target cells from fluid sources (carrying collections of cells), such as peripheral blood, vascularized tumors, malignant pleural effusions, lymphatic fluids, fluid portions of bone marrow, and other cell-carrying fluids. In one example, the method is a tunable immunomagnetic cell sorting approach that can be used to enable rapid and efficient recovery of TILs from solid tumors.

[0016] What is referred to as Microfluidic Targeting of Infiltrating Cells (or MAGIC) can be used for the recovery and expansion of TILs from tumor tissues based on immunomagnetic selection. Although the present disclosure provides an example in which cell recovery is performed on TILs from tumor samples, the disclosed methods and devices can be suitable for magnetic profiling of other cells in various media, with modifications as necessary. In another example, the disclosed devices, systems, and methods can be used to collect tumor-reactive immune cells from peripheral blood.

[0017] MAGIC uses a series of modular microfluidic chips designed for configurable, quantitative, and volumetric cell separation. Referring to Figures 1-6, an apparatus (10) and system (100) for recovering magnetically tagged target cells from a cell collection fluid are shown according to an exemplary embodiment.

[0018] The device (10) generally comprises a magnet plate (12) and a modular tip (14) releasably coupled to and overlying the magnet plate (12).

[0019] As best seen in FIG. 3, each magnet plate (12) has an array of micro-magnets (16) disposed and arranged therein, which array of micro-magnets (16) generates a substantially constant magnetic field along the magnet plate (12). In the embodiment shown, all of the micro-magnets (16) are N52 NdFeB magnets. In other applications, magnets with different magnetic strengths may be used. In further applications, magnets with different magnetic strengths can be fixed to the same magnet plate (12) to generate a varying magnetic field along the magnet plate (12).

[0020] The modular chip (14) is comprised of a base and a chamber wall 20. In this embodiment, the modular chip (14) has a first end (22) and an opposing second end (24). The base may be a glass base (18) having a flow surface (26) and an opposing bonding surface for bonding with the magnetic plate (12). The flow surface (26) and the opposing bonding surface generally extend between the first end (22) and the second end (24). At least the flow surface (26) of the glass base (18) may also be coated with polydimethylsiloxane (PDMS) or another suitable coating to prevent non-specific capture by smoothing the surface, such as another silicone-based lubricant. This coating helps to lubricate the flow surface (26) of the glass base (18), thus trapping cells that may slide off during collection. The coating also helps to form a bond between the chamber wall 20 and the glass base (18) to prevent leakage.

[0021] The glass base (18) may have a thickness between 0.05 mm and 0.5 mm. Preferably, the glass base (18) has a thickness of 0.1 mm or less, which allows the magnetic field exerted by the micromagnets (16) to better extend beyond the glass base (18) when the magnet plate (12) and the modular chip (14) are bonded together. The dimensions of the glass base (18) may be 30 mm to 300 mm in length and / or 12.5 mm to 125 mm in width. In this embodiment, the glass base (18) is 75 mm in length and 50 mm in width.

[0022] The chamber walls 20 extend from a flow surface (26) of the glass base (18) and may be secured thereto, such as by using an adhesive. The chamber walls 20 and the glass base (18) collectively form a flow chamber (28) therebetween. The flow chamber (28) has an inlet (30) disposed at one end of the flow chamber (24), such as near the first end (22) of the modular chip (14). The flow chamber (28) also has an outlet (32) disposed at an opposite end of the flow chamber (24), such as near the second end (24). In the embodiment shown, each device (10) has one inlet (30), one outlet (32), and one flow chamber (24). However, in alternative applications, the device (10) may have multiple inlets (30), and / or multiple outlets (32), and / or multiple flow chambers (28).

[0023] Inlet (30) is configured to receive fluid into flow chamber (24) and outlet (32) is configured to expel fluid from flow chamber (24), although inlet (30) and outlet (32) may be used in reverse, such that inlet (30) becomes outlet (32) and outlet (32) becomes inlet (30).

[0024] The modular chip (14) further includes a plurality of flow reduction structures (34) disposed within the flow chamber (28). The flow reduction structures (34) may also extend from and be secured to the flow surface (26) of the glass base (18). In some implementations, the chamber walls 20 and the flow reduction structures (34) may be formed as a single unit, such as by 3D printing and injection molding, and then secured to the glass base (18). In alternative applications, the chamber walls 20 and the flow reduction structures (34), or the device (10) as a whole, may be formed through injection molding. Each structure (34) includes a capture surface (36) that is shaped to reduce the flow rate in the vicinity of the capture surface (36). In this embodiment, each flow reduction structure (34) is X-shaped, although other shapes, such as V-shaped or C-shaped geometries, may be used.

[0025] The magnetic field generated by the array of micromagnets (16) extends through the glass base (18) and cooperates with the flow reduction structures (34) to define respective capture zones in the vicinity of each of the flow reduction structures (34).

[0026] Depending on the desired filtration rate / type, the height of each flow reduction structure (34) may be between 50 microns and 800 microns. It has been found that if the height exceeds 800 microns, the mechanism of cell capture changes and the specificity of capture is lost. It has been found that if the flow reduction structure (34) height is less than 50 microns, clogging occurs due to cell size being around 20 microns.

[0027] In the embodiment shown in Figure 1, for example, all of the flow reduction structures in the top left modular chip (14) are 100 μm high (34a), all of the flow reduction structures in the middle left modular chip (14) are 400 μm high (34c), and all of the flow reduction structures in the bottom left modular chip (14) are 800 μm high (34d). In the embodiments depicted in Figures 5a, 5b, and 6, flow reduction structures (34a), (34b), (34c), and (34d) are shown in further detail having heights of 100 μm, 200 μm, 400 μm, and 800 μm, respectively.

[0028] In further applications, a modular chip (14) may have flow reduction structures (34) with different heights on the same glass base 18. For example, the modular chip (14) shown in Figure 9 includes flow reduction structures (34a), (34b), (34c), and (34d) arranged in order of height on the glass base 18.

[0029] To help determine or select the appropriate height of the flow reduction structures for a given modular chip flow, the cytometry profile may be used to help design a sorting setup to capture a specific target population.

[0030] In one application, a series of human cancer cell lines expressing CD326 were benchmarked by flow cytometry, including MCF-7, PC-3M, 22Rv1, PC-3, MDA-MB231, and HeLa, as shown in Figure 62a. These cells have significant differences in CD326 expression, as judged by median fluorescence intensity (MFI), over the range of 80 to 20,000. A quantitative sorting device was constructed with four modules, 100, 200, 400, and 800 μm, connected in series, and the cell mixture was sorted at a flow rate of 16 mL / hr. Figure 62b shows the MFI of the population captured in each module. Curve fitting was performed using the log 2 Thickness and log 2 The linear relationship between the MFI and 2 >0.998), with a slope of approximately -1.5. Thus, from the above observations, the MFI decreased by a factor of 3 (2 - 1.5 = 0.35) when the height of the capture module was doubled.

[0031] Based on the CD39 flow cytometry data shown in FIG. high Populations and CD39 low The difference in MFI between the populations was found to be about 27-fold (18615 vs. 688). Thus, the populations were found to be well separated by the 100 μm and 800 μm modules. med The population was found to have an MFI of 5768 and was CD39 low This resulted in a fold change of 8.38 compared to the 100-μm module. This provides the rationale for using the 200 μm module for capture. In summary, the setup of serially connecting 100, 200, and 800 μm modules may be chosen for quantitative sorting of CD39.

[0032] Of course, in alternative applications, the modular chip (14) may have flow reduction structures (34) with different heights than those illustrated and discussed herein.

[0033] As a further possible variation, the embodiment of the device (10) shown in Figure 9 includes two magnet plates (12) with a modular chip (14) sandwiched between them. The magnets in this embodiment generate a magnetic field that has a constant magnetization along all of the flow reduction structures (34a, 34b, 34c, and 34d).

[0034] According to an exemplary embodiment, a method (800) for recovering magnetically tagged target cells from a cell collection fluid using the device (10) is shown in Figures 7-11.

[0035] At (802), the method (800) may optionally include obtaining a cell collection fluid. The obtaining may include lysing a tumor sample from the patient into single cells to form a cell collection fluid. The lysis may further include enzymatically dissociating the tumor sample into a single cell suspension.

[0036] Alternatively, or in addition, rather than lysing a tumor sample to form a cell collection fluid, the cell collection fluid may be derived from peripheral blood, vascularized tumors, malignant pleural effusion, lymphatic fluid, the fluid portion of bone marrow, or other cell-carrying fluid that holds single cells in suspension.

[0037] Then, in (804), the single cells can be labeled with magnetic particles, such as by immunomagnetic labeling. For example, the single cell mixture can be labeled with an antibody conjugated to a magnetic nanoparticle (MNP) that is specific for a surface marker (e.g., CD4, CD8, or CD45) expressed on the immune cells of interest but not on tumor cells. Due to the attachment of the MNPs on their surface, the immune cells of interest (i.e., TILs) will gain strong magnetization within the microfluidic device. The magnetically tagged target cells are thus made susceptible to magnetic attraction.

[0038] The cell collection fluid containing the magnetically tagged or labeled target cells is then introduced into device 10 at 806. In particular, the cell collection fluid may be introduced into flow chamber 28 of device 10 through inlet 30 using a syringe (not shown).

[0039] When introduced into the device (10), the cell collection fluid experiences two main forces: the magnetic force generated by the interaction between MNPs, the magnetic field generated by the micromagnets (16), and the fluid drag force determined by the fluid velocity in a particular region. When the magnetic force overcomes the fluid drag force, the cells gain enough force to remain in the particular region. TILs experience a higher magnetic force compared to tumor cells and other non-target cells because they are labeled with a higher number of MNPs.

[0040] Thus, the magnetic field from the micromagnets (16) in the capture zone is sufficiently high to cooperate with the flow reduction structures (34) to overcome the drag forces on the target cells and promote capture of the magnetized target cells from the cell collection in the capture zone, such that cells with higher magnetization are captured by the flow reduction structures (34).

[0041] As mentioned above, the flow reduction structures (34) may have different heights / thicknesses selected for different purposes. After selection of the appropriate / desired configuration, the flow rate may also be adjusted for better sorting performance. The difference in thickness / height of the modular chip (14) may itself contribute to different flow rates. Devices (10) with lower flow reduction structures (34) may tend to have lower volumes in their flow chambers (28) and therefore higher flow rates through the chambers. Conversely, devices (10) with higher flow reduction structures (34) may tend to have higher volumes in their flow chambers (28) and therefore lower flow rates through them.

[0042] The flow rate itself may also be adjusted as the cell collection fluid is injected into the harvester (10). Returning to the cancer cell line setup described above, the MFI from each module sorted at a flow rate of 8 mL / hr (Figure 62c) was compared to 16 mL / hr (Figure 62b). Overall, the MFI was approximately linearly proportional to the flow rate, with k ≈ 1. This resulted in a direct translation to achieve a desired MFI by adjusting the existing flow rate.

[0043] For the above setup for quantitative sorting of CD39 (with 100, 200, and 800 μm modules connected in series), it is recommended to perform presorting under a flow rate of 8mb / hr for weak markers (i.e., CD39 / PD-1) or 32mL / hr for strong markers (i.e., CD45). After sorting, the populations from each module can be collected to determine the MFI by flow cytometry. By comparing the existing MFI with the desired MFI, the user can estimate the optimal flow rate. Alternatively, the MFI by flow cytometry can be estimated by counting the percentage of cells in each module and subsequently mapping these percentages to the flow cytometry data obtained above to infer the corresponding MFI.

[0044] For example, CD39 was sorted at a flow rate of 8 mL / hr and the MFI from the 200 μm module was found to be 7620. The ideal MFI is 5768 (see cancer cell line settings above). Therefore, the optimal flow rate in that case would be 8 x 5768 ÷ 7620 = 6.05 mL / hr.

[0045] The difference in flow rate allows the capture of cells with different expression of the protein marker (i.e., cells with different degrees of magnetization). A certain amount of MNPs is conjugated to an antibody targeting CD39. The CD39 antibody specifically binds to the CD39 protein. Thus, a high expression of CD39 on the cell surface results in a higher number of bound CD39 antibodies, which is proportional to the amount of MNPs. In this way, the expression level of CD39 correlates with the level of magnetic labeling. Thus, a modular chip (14) with a lower thickness (and therefore a higher flow rate) captures cells with higher expression. A modular chip (14) with a higher thickness (and therefore a lower flow rate) captures cells with lower expression.

[0046] FIG. 9 shows simulated flow velocity distributions within an apparatus (10) having flow reduction structures (34) of different heights, with the units of the color bar being mm s -1 ) is displayed. Figure 10 shows the quantification of the simulated flow velocities. The flow rates near the pockets of the "X" shaped structures (34) were low, forming a low velocity zone, i.e., a trapping zone, favorable for cell capture.

[0047] FIG. 11 is an illustration of how the embodiment of the device (10) shown can capture magnetically tagged target cells for collection. When immunomagnetically labeled cells are introduced into this device (10), regions that vary in height between 100-800 μm result in a decrease in fluid velocity and a decrease in fluid drag. A particular cell is captured in the capture pocket of the "X" structure once its resulting magnetic force overcomes the fluid drag force.

[0048] At (808), the method (800) further includes flushing non-target cells from the device (10). The flushing may be performed by introducing a flushing fluid into the device (10) to flush away non-target cells, or cells that were not captured within the capture zone. The flushing fluid may be injected into the flow chamber (28) through the inlet (30) using a syringe.

[0049] At (810), the modular chip (14) is separated from the magnet plate (12). The ability of the modular chip (14) to separate from the magnet plate (12) helps improve throughput and increases the ease of removing cells from the modular chip (14) after sorting. Separating the modular chip (14) from the magnet plate (12) removes the magnetic force generated by the micromagnets (16) from the magnetically labeled target cells. This allows for the separation and recovery of the captured magnetically tagged target cells from the modular chip (14) at 812.

[0050] If the cell collection is derived from a tumor sample, the target cells recovered are CD8 + These recovered TILs may be TILs. These recovered TILs may undergo an in vitro expansion protocol using CD3 / CD28 microparticle stimulation in an antigen-independent manner. Once the expanded TILs reach a desired level, they can be transplanted back into an in vivo environment (i.e., the patient) for adoptive cell therapy.

[0051] 1-6 also show a system (100) for sorting and recovering magnetically tagged target cells from a cell collection fluid, according to an exemplary embodiment. The system (100) generally comprises a first apparatus (10a) as described above, a second apparatus (10b) as described above, and a scaffold (102) configured to hold the magnetic plates (12) of the first and second apparatus (10a), (10b).

[0052] As depicted, the magnetic plates (12) of the first and second devices (10a), (10b) are assembled to the scaffold (102) positioned parallel to one another. Alternatively, the magnetic plates (12) of the first and second devices (10a), (10b) may be releasably securable to the scaffold. In that regard, the magnetic plates (12) may be coupled to the scaffold (102) in any manner known in the art, such as via a sliding or snap-fit ​​coupling mechanism. Magnetic plates (12) having magnets of different magnetic strengths or configurations may thus be interchangeably assembled to the scaffold (102). In other alternative embodiments, the first and second devices (10a), (10b) may be arranged on the scaffold (102) in series or at a non-perpendicular angle to one another.

[0053] When the system (100) includes multiple devices (10), the flow reduction structures in each device may be the same or different from one another.

[0054] The system (100) is further shown to include a first connector (104) positioned proximate an end of each of the first and second devices (10a), (10b) and a second connector (106) positioned proximate the other end of each of the first and second devices (10a), (10b). For example, as shown in Figures 2a and 4, the first connector (104) may be positioned proximate a first end (22) of the modular chip (14) and the second connector (106) may be positioned proximate a second end (24) of the modular chip (14). Thus, the first connector (104) may be fluidly connectable to a corresponding inlet (30) of each of the first devices (10a) or second devices (10b), and the second connector (106) may be fluidly connectable to a corresponding outlet (32) of each of the first devices (10a) or second devices (10b).

[0055] This embodiment uses flexible tubing (108) to fluidly couple the first connector (104) with the corresponding inlet (30), the second connector (106) with the corresponding outlet (32), and / or to fluidly couple the inlet (30) of one device with the outlet (32) of another device. The flexibility of the tubing (108) allows for reconfigurability or reconnectability between the inlets (30) and outlets (32) of the first connector (104) and second connector (106). Alternative coupling mechanisms may be used in place of the tubing (108) to fluidly couple the first connector (104) with the corresponding inlet (30) and the second connector (106) with the corresponding outlet (32).

[0056] Each first connector (104) may also be in fluid communication with a source of cell collection (not shown), and each second connector (106) may also be in fluid communication with a retentate container (not shown). Figures 1-4 further illustrate that the scaffold (102) may be configured to hold more than two devices (10), such that in addition to the first and second devices (10a), (10b), additional devices (such as a third device (10c)) may be added to the system (100) as desired.

[0057] The reconfigurability of the components of the system 100 allows the system 100 to be adapted to multiple modes or configurations. Two exemplary configurations include a parallel configuration / system 100a, examples of which are shown in Figures 2a and 4, and a series configuration / system 100b, examples of which are shown in Figure 2b.

[0058] In the embodiment of Figure 2a, an example of a parallel system (100a) is shown, where a flexible tube 108 fluidly connects each first connector (104) with the inlet (30) of its corresponding device (10), and another flexible tube fluidly connects each second connector (106) with the outlet (32) of its corresponding device (10). In such case, each first connector (104) is also fluidly connected to a collection source of cells, and each second connector (106) is also fluidly connected to a retentate container (not shown).

[0059] Similarly, the height of the flow reduction structures (34) in each of the first, second and third devices (10a), (10b) and (10c) of FIG. 2a are the same. In particular, the first, second and third devices (10a), (10b) and (10c) include flow reduction structures (34a) having a height of 100 microns. In this manner, the first, second and third devices (10a), (10b) and (10c) of FIG. 2a are structurally the same. In alternative applications, the devices of FIG. 2a may instead include flow reduction structures having heights between 50 microns and 800 microns.

[0060] In the embodiment of Figure 4, another example of a parallel system (100a) is shown, where the flexible tubes 108 are arranged in parallel in the same manner as shown in Figure 2a. However, the height of the flow reduction structures (34) in each of the first, second, and third devices (10a), (10b), and (10c) are different. In particular, the first, second, and third devices (10a), (10b), and (10c) of Figure 4 include flow reduction structures (34a), (34c), and (34d) having heights of 100, 400, and 800 microns, respectively.

[0061] FIG. 2b illustrates an example of a series system (100b) in which first and second devices (10a), (10b) are arranged in series and fluidly connected in series with a third device (10c).

[0062] In the series system (100b), similar to the parallel system (100a), the connector (104) adjacent to the first device (10a) is fluidly connected to the inlet (30) of the first device (10a) using a flexible tube (108). However, as described above, in each modular chip (14), the functions of the inlet (30) and outlet (32) can be reversed. Thus, unlike the parallel system (100a), the outlet (32) of the first device (10a) is fluidly connected to the inlet (30) of the second device (10b) rather than the second connector (106). Furthermore, the outlet (32) of the second device (10b) is fluidly connected to the inlet (30) of the third device (10c) rather than the first connector (104). The outlet (32) of the third device (10c) is then fluidly connected to a second connector (106) adjacent the device (10c).

[0063] The height of the plurality of flow reduction structures (34) in the first device (10a) of the series system (100b) is also different (lower or higher) than the height of the flow reduction structures (34) in the second device (10b) and the third device (10c). In the particular embodiment shown in Figure 2b, the first device (10a) has flow reduction structures (34a) (100 μm), the second device (10b) has flow reduction structures (34c) (400 μm), and the third device (10c) has flow reduction structures (34d) (800 μm).

[0064] The modularity and configurability of the system (100) allows the system (100) to be field programmable, i.e., allowing flexibility in changing the configuration for different sorting applications to make the system (100) fit for purpose. For example, depending on the needs of the end user, the system (100) may be configured into a parallel system (100a) and then reconfigured into a series system (100b), or a system having both parallel and series components, and / or a system with a different combination of components.

[0065] In some examples, instead of a system (100) including a first and second device (10a), (10b), each with its own magnet plate (12), the system (100) may include a single large magnet plate that can be used with a first and second modular chip (14). The first modular chip (14) may be coupled to a scaffold such that the first modular chip (14) covers a first portion of the magnet plate (12), and the second modular chip (14) may also be coupled to a scaffold such that the second modular chip (14) covers a second portion of the magnet plate (12). And a parallel system (100a) or a serial system (100b) may be similarly achieved by connecting the inlets (30) and outlets (32) of the first and second modular chips (14) as described above. That is, modularity and configurability of the system (100) can be achieved using modular chips (14) that can be freely arranged on a single large magnetic plate (12) (which may be integrated into the scaffold (102) or releasably coupled to the scaffold (102)), or can be achieved using devices (100) that each include a modular chip (14) with its own magnetic plate (12).

[0066] A method (1200) for recovering magnetically tagged target cells from a cell collection fluid using the system (100) according to an exemplary embodiment is shown in Figures 12, 13a, and 13b. Optionally, the method (1200) may include lysis (802) of the tumor sample and magnetic labeling (804) of the target cells, as described above.

[0067] Then, at 1202, the method (1200) includes introducing a cell collection fluid containing the magnetically tagged target cells into the system (100), specifically into the first device (10a) through the inlet (30) of the first device (10a). Then, at 1204, the fluid sample is directed into the second device (10b), i.e., from the outlet (32) of the first device (10a) into the inlet (30) of the second device (10b). The method (1200) may also optionally include, at (1206), directing the fluid sample into the third device (10c), i.e., from the outlet (32) of the second device (10b) into the inlet (30) of the third device (10c).

[0068] The non-target cells are then flushed from the system (100) at (1208). The flushing step may be performed by introducing a flushing fluid into the system (100) to flush away the non-target cells, or cells that were not captured in the capture zone. The flushing fluid may be injected into the flow chamber (28) of the first device (10a) through the inlet (30) using a syringe. The flushing fluid will then pass through the second device (10b) and the third device (10c) as described above.

[0069] At 1210, the modular chips 14 of the first, second and third devices 10a, 10b, 10c are separated from their corresponding magnet plates 12. Then, at 1212, the magnetically tagged target cells from the modular chips 14 of the first and second devices 10a, 10b are retrieved.

[0070] 13a and 13b show how the method (1200) can be implemented when using the system (100) in parallel and in series.

[0071] FIG. 13a includes a parallel system (100a) in which first, second, and third devices (10a), (10b), and (10c) are connected in parallel, each with a 100 micron flow reduction structure (34a). Given their structural identity, the method (1200) can be implemented for ultra-high throughput binary sorting of tumor cells into CD8+ TILs and their recovery. This binary sorting, also referred to herein as "Binary MAGIC," allows for the isolation of T cell populations for generating bulk TILs.

[0072] However, TILs can be further classified into subpopulations based on their degree of activation. In particular, subpopulations of cells with more potent phenotypes can be targeted by honing in to specific proteins in TILs.

[0073] To that end, FIG. 13b illustrates a series system (100b) in which first, second, and third devices (10a), (10b), and (10c) are connected in series with different flow reduction structures (34a), (34c), and (34d) (100, 400, and 800 microns, respectively). Given their structural differences, the method (1200) is advantageously suited for high-throughput quantitative sorting and sorting of tumor cells (or general CD8 + A method for sorting TILs can be performed to recover TILs into subpopulations based on CD39 expression, such as bystander TILs, reactive TILs, and exhausted TILs. This type of sorting is also referred to herein as "quantitative MAGIC."

[0074] As mentioned above, flow reduction structures (34) with different heights can result in different flow rates through the flow chamber (28). The labeled cell collection fluid may also be injected at different flow rates. This difference in flow rates allows for the capture of cells with different expression of the CD39 protein marker. Thus, a first device (10a) with a 100 micron flow reduction structure (34a) can capture cells with higher expression, such as exhausted TILs. A second device (10b) with a 400 micron flow reduction structure (34c) can capture cells with medium expression, such as reactive TILs. A third device (10c) with an 800 micron flow reduction structure (34d) can capture cells with lower expression, such as bystander TILs.

[0075] Thus, when the modular chips (14) of the first, second and third devices (10a), (10b), (10c) are separated from their corresponding magnetic plates (12), the target cells recovered from the first modular plate are mostly exhausted TILs, the target cells recovered from the second modular plate are mostly reactive TILs, and the target cells recovered from the third modular plate are mostly bystander TILs.

[0076] Method 1200 may be performed following the performance of method 800, where magnetically tagged target cells recovered from method 800 are introduced into inline system 100b. Method 1200 may alternatively be performed independently of method 800, where a cell collection fluid (such as a lysed tumor sample) with magnetically tagged target cells is introduced directly into inline system 100b.

[0077] The separability of the modular chips (14) from the magnet plate (12) in the device (10) and the modular construction of the system (100) serve to increase the ease of cell removal from the modular chips and allow for tunable resolution. Any one compartment containing cells of interest can be simply removed separately from the other modules, allowing easy recovery of specific subpopulations of cells. This modular design also allows end users to assemble a sorting system that meets their requirements in terms of resolution (number of populations sorted), throughput, and system complexity.

[0078] Another advantage of using the system (100a) in series is that up to 30-fold higher recovery efficiency and 100-fold better throughput can be achieved compared to commercially available sorting techniques without sacrificing purity. The high recovery and purity achieved can improve the initial quantity and diversity of TIL clonotypes and accelerate the expansion process. TILs isolated using this approach require minimal expansion, which maximizes their in vivo cytotoxic phenotype. Using in vivo adoptive cell therapy in mouse tumor models, it was demonstrated that TILs isolated and expanded through the MAGIC platform are highly potent and can extend the median survival of xenografted animals by 50%.

[0079] In addition, quantitative sorting set up for high throughput (serial system (100a)) and fine profiling of TIL subpopulations based on CD39 (parallel system (100b)) can be obtained. In the examples below, it is demonstrated that moderate levels of expression of CD39 define a progenitor population of TILs that are antigen-specific, capable of self-renewal, and capable of rapid differentiation into a highly cytotoxic phenotype. med The population is characterized by CD39 high , CD39 lowor provide superior antitumor efficacy in vivo compared to bulk TILs. Collectively, the examples described herein demonstrate that the disclosed devices, systems, and methods enable cost-effective and efficient adoptive cell therapy with rapid turnaround. EXAMPLES

[0080] Exemplary Manufacturing Methods Here, an exemplary manufacturing method of one example of the disclosed device is described. The separability of the modular chip and the magnet plate as separate components allows at least the modular chip to be fabricated more quickly and cheaply using 3D printing and / or injection modeling, rather than using traditional lithography. Furthermore, by enabling a low-cost, high-volume manufacturing process for the modular chip (e.g., using 3D printing), the modular chip can be a disposable part of the system. The disposability of the modular chip can be beneficial for hygienic reasons and / or use in a healthcare environment, since the modular chip is the component that comes into most direct contact with the cell collection fluid (which can be biological fluids such as blood, lymph, etc.).

[0081] In this example, the mold for manufacturing the MAGIC / modular chip (14) was 3D printed by a stereolithography 3D printer (Microfluidics Edition 3D Printer, Creative CADworks, Toronto, Canada) using "CCW Master Mold for PDMS" resin (Resinworks 3D, Toronto, Canada) with a layer thickness of 25 μm. Other known 3D printing resins may be used in this process, optionally with UV or heat treatment. 49MAGIC chips were fabricated by casting PDMS (Sylgard 184, 182 or 186 Dow Chemical, Midland, MI) onto a printing mold, followed by incubation at 50–100 °C for 30 min–4 h. The cured PDMS replica was peeled off, punched out, and plasma bonded to a thickness number 1 glass coverslip (260462, Ted Pella, Redding, CA) to finish the chip. Prior to use, MAGIC chips were treated with 0.01–1% Pluronic F68 (24040032, Thermo Fisher Scientific, Waltham, MA) in phosphate-buffered saline (Wisent Bio Products, Montreal, Canada) for 30 min–24 h to reduce nonspecific binding between cells and the chip. During the experiment, each device was sandwiched between an array of N52 NdFeB magnets (D14-N52, K&J Magnetics, Pipersville, PA) and connected to a digital syringe pump (Fusion 100, Chemyx, Stafford, TX) for fluid handling.

[0082] The fabricated tips were sputter coated with 15 nm of Au (Denton Desk II, Leica) for imaging under a field emission scanning electron microscope (SU5000, Hitachi, Tokyo, Japan) using 5 kV accelerating voltage and high vacuum mode. In other applications, the fabricated tips may not be sputter coated when used as described above.

[0083] With regard to 3D printing, the ability of the 3D printer to print positive (e.g., microposts) and negative (e.g., microwells) structures (see FIG. 63) was first quantified. The 3D printer in this example (i.e., the Microfluidics Edition 3D Printer referenced above) was found to have better resolution in printing the positive structures compared to the negative structures. The lower resolution of the negative structures may be due to the resin residues that get lodged therein due to surface tension or high viscosity of the resin. In that regard, the 3D printer can print high resolution patterns on the positive structures, such as "X" shaped cell capture pockets. The 3D printer was found to support microstructures with heights of at least up to 1 mm, which is hardly supported by standard lithography (see FIG. 64). In addition, the 3D printer was found to be able to generate structures of multiple depths in one shot, whereas standard lithography methods require multiple rounds since lithography can only generate one thickness per round.

[0084] The challenge of limited resolution in 3D printing of negative structures can be addressed by the use of a specially designed double replica procedure for casting PDMS (see Figure 65). This double replica procedure first generates a PDMS mold carrying the negative structure. The negative mold was then treated with saturated detergent in a 70% ethanol solution for 20 min to 72 h. This detergent treatment allows the newly cured PDMS to be separated from the treated PDMS, allowing its use as a mold for generating the positive channels of the negative PDMS structure during device fabrication.

[0085] The use of this protocol has at least three major advantages. First, it allows any structure to be fabricated with a sufficiently high resolution. It is important to use this protocol to have the ability to create both positive and negative structures for channel fabrication, since 3D printers were found to have a higher resolution than printing positive structures. Second, this protocol can generate multiple negative molds from one 3D printed piece, allowing for scaling up of the manufacturing. At the same time, batch-to-batch variations during 3D printing / standard lithography are also minimized, since all molds are formed from the exact same piece. Third, it is relatively cost-effective and straightforward, since it does not involve the use of other types of resins and the handling process is simple.

[0086] Research example The exemplary device constructed as described above was used in several exemplary studies.

[0087] The overall design of the device was verified by sorting cells with and without MNPs and an external magnet using a binary sorting setup (Figure 50a). As expected, cells were captured only when both MNPs and an external magnet were present. It is noteworthy that the majority of cells were captured in the low-velocity pockets near the "X"-shaped structures. This result proved the fidelity of our sorting principle and demonstrated the specificity of our modular chip. Furthermore, the feasibility of retrieving the captured cells from the chip by flushing the chip without an external magnet was investigated (Figure 50b). Nearly 100% of the captured cells were successfully removed from the chip, facilitating efficient cell recovery.

[0088] The sorting performance of MAGIC / apparatus (10) and system (100) was compared to a commercially available magnetic sorting platform - magnetic activated cell sorting (MACS). Binary sorting using the in-line system (100a) involved CD45-based positive and negative sorting using K562 and MDA-MB-231 cells (see FIG. 14). During positive sorting, it was found that binary MAGIC provides consistent capture of up to 50 million cells per chip, while the MACS column was saturated at 10 million cells and failed to capture the majority of positive cells at 50 million. This demonstrates that MAGIC is more suitable for applications involving volumetric capture of positive cells, such as purifying TILs from an excessive background of tumor cells.

[0089] For quantitative sorting with a parallel system (100b), CD326 was tested using PC-3M, MDA-MB-231, and U937 cells, which have high, medium, and low expression of CD326, respectively (see Figure 15). Quantitative MAGIC was able to adequately enrich all cell lines, while MACS only showed a small amount of CD326 in the positive fraction. med It was observed that MACS failed to capture MDA-MB-231 cells, indicating that MACS has limited ability to discriminate between moderate and low expressing cells. Quantitative MAGIC sorting offers finer sorting resolution under high throughput, which may better resolve biological information that is not accessible by MACS.

[0090] Cytotoxic CD8 using Binary MAGIC + Isolation of TILs

[0091] CD4 and CD8 are definitive markers of different anti-tumor T cell populations within the tumor and are widely accepted for TIL isolation. A binary MAGIC setup (Parallel System (100a)) was configured to isolate TILs via CD4 or CD8. T cells were spiked into the tumor cell sample to optimize the flow rate favorable for the isolation of TILs. Pure human CD4 + T cells and pure mouse CD8+ OT-1 T cells were used. Human CD4 + and mouse CD8 + The optimal flow rates for capturing CD4 T cells were found to be 32 mL / h and 16 mL / h, respectively (see Figures 16a-17). This corresponds to a throughput of 320 million human cells and 160 million mouse cells / hour / device. + and CD8 + TILs typically represent less than 10% of all TILs. 37 Such a capacity of the MAGIC is deemed sufficient to handle 500 million dissociated tumor cells per chip. The performance of the MAGIC, FACS, and MACS was evaluated using human CD4+ cells spiked into MDA-MB-231 human breast cancer cells. + CD4-mediated capture of T cells and mouse CD8 spiked onto B16F10 murine melanoma cells + A comparison was made using small spike-in samples (~10 million / run) from two separate setups of CD8-mediated capture of OT-1 T cells (see Figures 18 and 19). It was found that MAGIC, thanks to its droplet-free principle of action and ultra-high throughput, achieved consistent enrichment of T cells compared to FACS / MACS, with the best recovery over FACS / MACS over stress on sorted cells (see Figure 20).

[0092] MAGIC, FACS, and MACS were challenged with TILs from a B16F10 mouse melanoma model (see FIG. 21). Mice were sacrificed on day 14 and TILs were isolated from the endothelial tumor using different isolation techniques based on CD8 expression. Interestingly, CD8 + The percentage of TILs represents only 0.2% of the total cell population within solid tumors (Figure 51), and therefore, it was found necessary to process the entire digested tumor in order to maximize the amount of these rare populations. A single gram of tumor tissue typically contains 100-1 billion cells. 38Such high cell numbers make sorting of rare and live TILs from real tumor samples very challenging. Processing undiluted samples with MACS or FACS is difficult due to clogging issues, and we have found that the number of cells is as high as 5 × 10 for MACS and FACS, respectively. 6 cells / mL and 2 x 10 6 This required diluting the samples to a concentration of 20 × 10 cells / mL, which dramatically increased the processing time to 4 and 20 hours. However, the MAGIC was able to perform 20 × 10 6 Concentrated samples with cell numbers up to 10 ...

[0093] [Table 1]

[0094] Isolated CD8 + The purity and quantity of TILs was determined by CD8 / CD45 co-staining after 4 days of culture in medium prepared for T cell expansion (see FIG. 22), at which point >97% of the MNPs had detached from the surface. 34, re-expressed the CD8a epitope for labeling. MAGIC achieved the best purity (98.0%) on day 4 and was more efficient than FACS (88.3%). This trend may be explained by the time required for FACS-based sorting as well as the high level of cell stress that caused significant cell apoptosis / death. As shown in Figure 23, MAGIC has a 5-fold and 30-fold higher recovery rate than MACS and FACS, respectively. This trend is in good agreement with the spike-in characterization. A very limited number and percentage of TILs (2.65%) were recovered from unsorted digested tumor samples. This suggests that an efficient and gentle microfluidic sorting process results in a better growth curve of TILs. TIL recovery was also tested with tumor specimens from non-small cell lung cancer (NSCLC) patients (see Figures 24, 55, and 56), and a similar trend was observed - MAGIC retained the highest cell recovery, 5-20 times better than MACS and FACS.

[0095] The clonotypes of isolated TILs were analyzed using bulk TCR sequencing. The number of unique clones observed (based on CDR3) was 684, 20468, and 64165 for TILs isolated by FACS, MACS, and MAGIC, respectively (Figure 25). This trend suggests that the high recovery rate of MAGIC also helps to maximally preserve the heterogeneity and diversity of the original TIL population. Interestingly, the different isolation techniques did not significantly change the V and J gene usage (Figure 50), indicating similar antigen specificity of isolated TILs. However, mapping of V(D)J recombination (Figure 51) revealed that TILs isolated by MAGIC (referred to as MAGIC-TILs) had a significantly higher complexity of VJ pairing and a higher Shannon diversity index (Figure 52), highlighting the better diversity of TILs isolated by MAGIC.

[0096] Since significant improvements in quantity, purity, and diversity were observed with the MAGIC isolation process, we investigated whether enhanced proliferation rate and intrinsic cytotoxicity could also be observed.6 Isolated TILs were cultured using the different methods in well plates for 14 days using a common CD3 / CD28-based expansion protocol that subcultured cells at a density of 1×10 / mL. Cell numbers were recorded twice a week per well and the total number of TILs isolated from each method was calculated (Figure 26). The proliferation rate of MAGIC-TILs was found to be faster than MACS / FACS-TILs. MAGIC and MACS TILs expanded at 1×10 for each replicate. 6 FACS-TILs require 7 and 14 days to reach a quantity of 1 × 10 within 14 days, likely due to their extremely low initial quantity, as cell density is a key regulator of T cell activation and proliferation. 6 could not supply the amount 39 The high yield provided by MAGIC results in a more enriched initial TIL population that is favorable for expansion. At the end of expansion, the phenotype of the TILs was characterized by staining with CCR7 / CD45RA (Figure 27). Approximately 95% of the TILs were CCR7 - / CD45RA - , indicating that an adequate effector number of TILs is advantageous for rapid in vitro expansion.

[0097] We then characterized the cytotoxicity and reactivity of the expanded TILs at the RNA and phenotypic levels. First, we assessed the relative expression of key immune pathways by qPCR, with activated CD8 T cells as a control. + Using splenocytes, evaluation was performed (Figures 28 and 57). The majority of immune response pathways and genes are upregulated, including NFkB, JAK-STAT, proliferation markers, and cytotoxic cytokines (Figure 57). Log-regulation of genes in the GO and KEGG databases was significantly increased in the 14.1% and 15.2% of the genes ... 2 Pathway enrichment was further performed using gene sets with (FC)>1.5 (Figure 29). MAGIC-TIL had the highest-log 10(P), suggesting improved immune reactivity of MAGIC-TILs at the RNA level. An in vitro killing assay was constructed by co-culturing TILs with a monolayer of B16F10-OVA cells (Figure 30). Consistent with the data collected at the RNA level, MAGIC-sorted TILs showed higher immune reactivity measured by the percentage of cell death at 24 and 48 hours. ELISA analysis of the supernatants during co-culture revealed that all types of TILs were functional. All types of TILs were able to produce a cocktail of cytokines that promoted antigen presentation, cytotoxicity, T cell proliferation, monocyte recruitment, and anti-angiogenesis. Notably, MAGIC-TILs secreted significantly higher levels of IFNγ, which may explain their improved cytotoxicity over other TILs.

[0098] To further investigate the efficacy of TILs isolated by different approaches, two scenarios of animal studies were designed to systematically test their therapeutic efficacy (see Figures 32-40). Scenario 1 has a fixed time point of injection (day 7 after tumor introduction) with varying cell numbers as a result of the different proliferation curves of TILs (Figure 32). It was observed that all TILs suppressed tumor growth compared to untreated controls (Figures 33 and 34). Microfluidic sorted TILs achieved the best therapeutic efficacy, probably due to the high dosing times enabled by the rapid expansion, as well as a better cytotoxicity phenotype as a result of the high diversity. The effect of the dosage was also investigated for MAGIC-TILs. Interestingly, at 5 × 10 5 The dose is 2 x 10 6 This provides a statistically better median survival than the previous dose (32 vs. 28 days, p=0.049). It is expected that the high dose of TILs in one shot may have some adverse effects on the treatment. 40 Therefore, 5 × 10 5 The dose close to that of cells is the optimal dose in the B16F10 model. Furthermore, the therapeutic outcome of MAGIC / MACS-TIL was improved by 5 × 10 5 Comparing cell doses (Figure 36), the therapeutic outcome of MAGIC / FACS-TIL was 5x10 4The cell doses were compared (FIG. 36). The results highlighted that MAGIC-TIL was essentially more potent than MACS / FACS-TIL under the same dose.

[0099] We next evaluated the therapeutic outcome of TILs when isolation of TILs and introduction of new tumors were performed on the same day (Figure 37), in order to mimic the situation in which patients have rapidly growing metastatic tumors and rapidly deteriorate, which represents 20% of patients in clinical practice. 9 TILs were injected once their quantity reached an optimal dose (5 × 10 5 MAGIC / MACS / FACS-TIL was used to isolate TILs at optimal doses on days 5, 10, and 15 (except for FACS, which did not reach the target concentration). In this situation, MAGIC-TIL still provides the best therapeutic outcome as a result of high potency and early injection, likely due to high initial recovery and rapid expansion in vitro (Figure 38 and Figure 39). Median survival times are 18, 20, 21, and 32 days for untreated, FACS, MACS, and MAGIC-TIL, respectively. Interestingly, two out of five mice in the MAGIC-TIL group were in complete remission on day 40, such that no visible tumor tissue was found subcutaneously. Such findings indicate that MAGIC-TIL that underwent minimal in vitro expansion (for 5 days) may have better in vivo therapeutic efficacy. The results indicate that "young TILs" - minimally cultured TILs (referred to as young TILs) - have higher levels of antigen reactivity compared to standard TILs that have undergone extended expansion. 12 , which is consistent with the idea that it can effectively mediate regression of metastatic melanoma. 10 Recent studies have highlighted that oligoclonal TILs are often expanded by low-frequency clonotypes with greater proliferative potential. 41 As a result, the clonal composition and tumor reactivity of TILs may change during in vitro expansion. 42 This highlights the sophisticated nature of TIL expansion, where enrichment for the “right” clonotype is preferable over bulk TIL expansion. 41Finally, infiltrating CD8 in tumors from scenario 2 + The number of T cells was compared to directly benchmark the infiltration capacity (Figures 40a, 58-59b). The number and area of ​​infiltrating CD8+ T cells (Figure 40b) were upregulated 5-10 fold higher in the MAGIC group, which is in good agreement with its positive therapeutic outcome. Taken together, these findings clarify the importance of minimizing in vitro culture of TILs and directly demonstrate the importance of starting with more initial TILs through efficient cell sorting.

[0100] Isolation of high titer TILs using quantitative MAGIC

[0101] Despite the great success of ACT, its objective response rate varies between 40% and 70%. 8 Currently, it is unclear which phenotype of TILs has the best therapeutic efficacy in vivo. Identification of a highly tumor-reactive population of TILs may lead to better clinical success of ACT. Recent studies have highlighted that CD39 expression may define highly potent TILs. On the other hand, CD39 pos The group is alone 43,44 or in combination with other markers 45 reported that CD39 expression accurately determines the tumor-reactive population of TILs and leads to improved clinical outcomes, whereas CD39 expression was highly associated with T cell exhaustion. 46 Instead, CD39 neg It is suggested that the group promoted long-term tumor management 47 Thus, there is a lack of consensus regarding the role of CD39 expression in therapeutic outcomes. Interestingly, TILs with moderate expression of CD39 (CD39 med ) retains an inexhaustible phenotype in vitro. 46 CD39 neg defines the bystander population 43 , CD39 pos In the context of defining the exhausted population 47 , ignored by binary selection, often subjectively positive 47 or negative 43CD39, the population assigned to the fraction med It is hypothesized that such a treatment may have improved therapeutic outcomes.

[0102] The experiment began with the isolation of CD8+ T cells from the MC-38-bearing mouse model. Secondary quantitative (Serial System 100b) sorting based on CD39 was performed 5-7 days after CD8 isolation, followed by in vitro characterization (Figure 41). Expression of CD39 in CD8 T cells was not bimodal, with approximately 25% of the cells expressing CD39. med (Figure 42), which was initially identified as sharing a similar profile to existing literature. 46 The flow rate of the quantitative MAGIC (qMAGIC) was fine-tuned to 6 mL / hr, and a clear separation between the three CD39 populations was achieved (Figure 42). qPCR was then performed to analyze the phenotype of the various CD39 populations, including common markers of cytotoxicity, stemness, and exhaustion (Figure 43). low The population retained low expression of cytotoxicity and exhaustion markers, such as PRF1, GZMB, PD-1, CTLA-4, and 2B4, and high expression of stemness markers, including CD27, TCF7, and IL7R, defining a non-differentiated stem-like phenotype, which is in good agreement with previous reports. 47 In contrast, CD39 high The population defined a highly exhausted yet cytotoxic phenotype that correlated well with existing literature 43,44 Interestingly, CD39 med The population had balanced expression of cytotoxicity, stemness, and exhaustion markers. med It is noteworthy that HA-1 had the highest expression of TCF7, a memory stem-like T cell marker.

[0103] To validate the phenotype at the protein level, intracellular flow cytometry was performed (Figure 44 and Figure 60a-Figure 61). Similar trends for each population were observed within a panel of exhaustion markers (PD-1, TIM3, and TIGIT) and stemness markers (CD27 and TCF7). In particular, CD39 highThe population was found to have significantly lower intracellular expression of TNF and IL-2, which is indicative of their exhausted and dysfunctional phenotype. The dramatic reduction in IL-2 was also consistent with such CD39 high The results showed that the memory stem-like T cells in each population had reduced proliferative capacity. This hypothesis is confirmed by Ki67 staining (Figure 5F). The percentage of memory stem-like T cells was examined in each population through CCR7 / CD45 staining (Figure 45), and the majority of stem-like T cells were CD39 low and CD39 med We also found that CD39 med The population had the highest proportion of PD-1 + / TCF7 + These populations have been reported as stem-like T cell precursors with defined tumor specificity. 48 , CD39 med It was concluded that the population was a distinct population that contained mostly stem-like T cell progenitor populations.

[0104] Next, an in vitro co-culture killing assay was performed as a direct measure of cytotoxicity at a functional level (Figure 46). high It was found that the CD39 population exhibited the highest tumor killing activity 24 hours after inoculation. med The CD39 population had slightly lower efficacy in the first 24 hours, but at 48 hours, it out-activated its killing activity with CD39 high Therefore, PD-1 + / TCF7 + / CD39 med The CD39 population could rapidly generate a highly cytotoxic population for effective tumor killing. low The CD39 population retained significantly lower killing activity at 24 and 48 hours. low This means that the cells may lack tumor reactivity or have limited capacity to generate cytotoxic populations. This finding supports the notion that such populations lack PD-1 expression. 46 This is in good agreement with previous studies that reported the inclusion of nonspecific bystander cells. 43 .

[0105] The anti-tumor efficacy of different CD39 populations in vivo was examined by reintroducing sorted TILs into MC-38-bearing mice (Figures 46 and 47). med TILs showed the best long-term antitumor activity among all CD39 populations, prolonging median survival by 60% compared to the untreated group (Figure 48). high Although TILs were initially very effective, they were found to be unable to control tumor growth one week after injection, likely due to their non-renewable termination phenotype. med Side-by-side comparisons of TILs were performed between bulk CD8 TILs that underwent minimal in vitro culture ("young TILs") and bulk CD8 TILs that underwent longer in vitro culture ("old TILs"), as well as other TIL types, including unsorted TILs that infiltrated from segmented tumor fractions. As judged by tumor volume and median survival, CD39 TILs were significantly more abundant than TILs that underwent longer in vitro culture ("old TILs"). med TILs provided the best therapeutic efficacy among all TIL types (Figure 49).

[0106] Sorting of circulating TILs

[0107] The disclosed systems and methods are applicable to other cell types in different body fluids, such as rare tumor-reactive T cells in peripheral blood. In addition, the disclosed systems and methods can also sort cells based on the expression levels of specific proteins as well as T cell receptor (TCR) reactivity.

[0108] The disclosed system and method are also applicable to various types of sorting applications, such as positive, negative, or quantitative sorting. In the examples described below, a protocol was developed to sort circulating tumor-reactive T cells from peripheral blood by a two-step procedure. First, negative selection of CD8 cells from RBC lysed blood was performed, followed by the use of multimer-based positive to isolate highly purified T cells with reactivity against specific antigens (also called tumor / antigen-specific T cells) from peripheral blood.

[0109] An animal model was first established with two defined highly immunogenic epitopes, chicken ovalbumin (OVA257-264, SIINFEKL) in a C57BL6 model and influenza A hemagglutinin (HA533-541, IYSTVASSL) in a Balb / c model. Tumor cells carrying expression of the epitopes were injected subcutaneously. The immunogenicity of these epitopes led to the generation of OVA / HA-reactive T cells in the blood. These rare reactive T cells can be recognized via MHC (major histocompatibility complex) or HLA (human leukocyte antigen)-specific multimers. The multimers can be further magnetically labeled with MNPs to allow capture of tumor / epitope-reactive T cells.

[0110] It is noteworthy that before isolation, the abundance of HA-reactive T cells was only 0.063% of the mononuclear cell population (see Figure 66, pre-sorting panel). During isolation, mouse whole blood was collected at the intermediate stage of tumor development. Red blood cells (RBCs) were lysed by RBC lysis buffer. Lysed cells were labeled by cocktails targeting other parts of blood cells, including CD19 for B cells and CD11b for monocytes. Such cocktails can be prepared in-house or purchased directly from commercial resources (e.g., untouched mouse CD8 cell kit, catalog number 11417D, Thermo Fisher). The cocktail-labeled cells were subsequently labeled with MNPs and sorted by the proposed system at flow rates of 8–32 mL / h (specifically, for the above-mentioned untouched mouse CD8 cell kit, 16 mL / h was used). After CD8 negative selection, the purity of CD8+ cells improved from 3.7% to 90.8% (Figure 66, CD8 post panel) and the rarity of HA-reactive T cells was promoted from 0.063% to 0.44% (Figure 66, CD8 post panel).

[0111] Multimer-based positive selection was then performed to purify HA-reactive T cells from the bulk CD8+ population. +T cells were labeled by the corresponding PE-conjugated multimer (pentamer in this particular case) and the corresponding anti-PE MNPs. The conjugation of fluorophores on the multimers is flexible, and FITC (fluorescein isothiocyanate), PE (phycoerythrin), APC (allophycocyanin), cyanine family, and biotin will all work, using the corresponding MNPs (e.g., anti-biotin MNPs) for labeling. Multimer-labeled cells were sorted with the proposed system at flow rates of 2-8 mL / h (4 mL / h in this particular case). After positive selection, the purity of HA-reactive T cells improved from 0.44% to 83.6% (Figure 66, post-multimer panel).

[0112] Although the present disclosure describes the disclosed methods and devices for TIL sorting and recovery, the disclosed methods and devices may be used for magnetic profiling of other particles, including other cells, for other cell therapy purposes. For example, the disclosed devices, systems, and methods may also be used to recover target cells from other fluid sources, such as peripheral blood, neovascular tumors, malignant pleural effusions, lymphatic fluid, fluid portions of bone marrow, and other cell-carrying fluids.

[0113] The embodiments of the present disclosure described above are intended to be examples only. The present disclosure may be embodied in other specific forms. Changes, modifications, and variations to the present disclosure may be made without departing from the intended scope of the present disclosure. Although the systems, devices, and processes disclosed and illustrated herein may comprise a particular number of elements / components, the systems, devices, and assemblies may be modified to include additional or fewer such elements / components. For example, although any of the disclosed elements / components may be referred to as singular, the embodiments disclosed herein may be modified to include a plurality of such elements / components. Selected features from one or more of the above embodiments may be combined to create alternative embodiments not expressly described. All values ​​and subranges within the disclosed ranges are also disclosed. The subject matter described herein is intended to encompass and encompass all suitable modifications in technology. All references cited are incorporated herein by reference in their entirety.

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Claims

1. 1. An apparatus for recovering magnetically tagged target cells from a cell collection fluid, comprising: a magnet plate having an array of micro-magnets disposed therein, wherein the array of micro-magnets generates a magnetic field along the magnet plate; a modular chip releasably coupled overly to the magnet plate, the modular chip comprising: a flow chamber having an inlet and an outlet; and a plurality of flow reduction structures within the flow chamber, each of the plurality of flow reduction structures comprising a capture surface shaped to reduce flow adjacent the capture surface, wherein the magnetic field generated by the array of micromagnets cooperates with the plurality of flow reduction structures to define a corresponding capture zone adjacent each of the flow reduction structures in the plurality of flow reduction structures; the magnetic field is sufficiently high to overcome a drag force on the magnetically tagged target cells in the capture zone to facilitate capture of the magnetically tagged target cells from the cell collection fluid in the capture zone; and Separating the modular chip from the magnet plate allows for the separation and recovery of the magnetically tagged target cells from the modular chip. Modular chips and An apparatus comprising:

2. 2. The apparatus of claim 1, wherein the modular chip comprises a glass base and a chamber wall, wherein the chamber wall and glass base collectively form the flow chamber, and wherein the chamber wall and the plurality of flow reduction structures extend from the glass base.

3. The apparatus of claim 2 , wherein the chamber walls and the plurality of flow reduction structures are made of polydimethylsiloxane (PDMS).

4. The device of claim 2, wherein the glass base is between 0.05 and 0.5 mm thick.

5. The apparatus of claim 1 , wherein the height of the flow reduction structures in the plurality of flow reduction structures is between 50 microns and 800 microns.

6. The apparatus of claim 1, wherein the height of the flow reduction structures in the plurality of flow reduction structures is up to approximately 800 microns when laminar flow is maintained.

7. A system for recovering magnetically tagged target cells from a cell collection, comprising: a magnet plate having an array of micro-magnets disposed therein, wherein the array of micro-magnets generates a magnetic field along the magnet plate; one or more modular chips releasably coupled overly to the magnet plate, wherein each of the one or more modular chips comprises: a flow chamber having an inlet and an outlet; and a plurality of flow reduction structures within the flow chamber, wherein a flow reduction structure in the plurality of flow reduction structures comprises a capture surface shaped to reduce flow adjacent a capture surface, and wherein the magnetic field generated by the array of micromagnets cooperates with the plurality of flow reduction structures to define a corresponding capture zone adjacent a flow reduction structure in the plurality of flow reduction structures; the magnetic field is sufficiently high to overcome a drag force on the magnetically tagged target cells in the capture zone to facilitate capture of the magnetically tagged target cells from the cell collection in the capture zone; and one or more modular chips, wherein separation of the one or more modular chips from the magnet plate enables separation and recovery of the magnetically tagged target cells from the one or more modular chips; a scaffold configured to hold the magnetic plate; A system comprising:

8. The system described in claim 7, wherein the magnetic plate is incorporated into the scaffold.

9. The system of claim 7, wherein the one or more modular chips comprise a first modular chip and a second modular chip.

10. The system described in claim 9, wherein the first modular chip is releasably coupled to cover a first portion of the magnetic plate, and the second modular chip is releasably coupled to cover a second portion of the magnetic plate.

11. The system described in claim 9, wherein the magnetic plate comprises a first magnetic plate and a second magnetic plate, the first modular chip is releasably coupled to cover the first magnetic plate, and the second modular chip is releasably coupled to cover the second magnetic plate.

12. The system of claim 11, wherein the first magnet plate and the second magnet plate are arranged in parallel within the scaffold.

13. The system of claim 9, wherein the scaffold further comprises a first connector disposed near a first end of each of the first and second modular chips, and a second connector disposed near a second end of each of the first and second modular chips, wherein the first connector is fluidly coupled to a corresponding inlet of the first modular chip or a corresponding inlet of the second modular chip, and wherein the second connector is fluidly connected to a corresponding outlet of the first modular chip or a corresponding outlet of the second modular chip.

14. The system of claim 9, wherein the first modular chip and the second modular chip are fluidly connected in parallel to a source of the cell collection.

15. The system described in claim 9, wherein the first modular chip and the second modular chip are fluidly connected in series and the outlet of the first modular chip is in direct fluid communication with the inlet of the second modular chip.

16. The system of claim 9, wherein the heights of the multiple flow reduction structures in each of the first modular chip and the second modular chip are the same.

17. The system described in claim 16, wherein the height of the plurality of flow reduction structures in each of the first modular chip and the second modular chip is 100 microns.

18. The system described in claim 9, wherein a height of a first subset of the plurality of flow reduction structures in the first modular chip is different from a height of a second subset of the plurality of flow reduction structures in the second modular chip.

19. The system described in claim 18, wherein the height of the first subset of the plurality of flow reduction structures in the first modular chip is less than the height of the second subset of the plurality of flow reduction structures in the second modular chip.

20. The system of claim 9, wherein the one or more modular chips further include a third modular chip, wherein the third modular chip is releasably coupled to cover a third portion of the magnetic plate.

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