WO2024025967A1

WO2024025967A1 - Determination of bcma level on plasma cells by flow cytometry

Info

Publication number: WO2024025967A1
Application number: PCT/US2023/028740
Authority: WO
Inventors: Todd Webster SHEARER; Rex WILLIAMS; Mark Johnson
Original assignee: SpringWorks Therapeutics Inc
Current assignee: SpringWorks Therapeutics Inc
Priority date: 2022-07-28
Filing date: 2023-07-26
Publication date: 2024-02-01
Anticipated expiration: 2025-01-28

Abstract

Methods, systems, and computer readable media for quantifying cells having expressed BCMA are provided. In aspects, a whole blood sample is mixed with a mixture of fluorophores to obtain a blood sample mixture, each fluorophore in the mixture of fluorophores configured to attach to a specific type of cell in the blood sample. The blood sample mixture is processed with a flow cytometer to obtain a computational dataset for each cell in the blood sample mixture. A first set of cells from the computational dataset are selected for further analysis by gating cells based upon physical dimensions. A second set of cells from the first set are selected for further analysis by further gating cells in the first set based on cell type. Cells in the second set of cells are then gated using a gating strategy to quantify the cells having expressed BCMA.

Description

DETERMINATION OF BCMA LEVEL ON PLASMA CELLS BY FLOW CYTOMETRY

[0001] The present application claims the benefit of U.S. Provisional Application No.

63/369,731, filed July 28, 2022, which is hereby incorporated by reference.

FIELD

[0002] Aspects of the present disclosure relate to determination of protein level on cells from whole blood, and in particular to determination of BCMA level on plasma cells.

BACKGROUND

[0003] Multiple myeloma is a bone marrow cancer that affects more than 30,000 patients each year in the United States. Multiple myeloma is currently considered an incurable disease, but overall survival has improved significantly with recent technological advancements in genetic research that have allowed researchers to identify novel targets of the disease. There has been specific interest in B-cells because of their role in modulating the immune response to cancer. B-cell maturation antigen (BCMA) plays an important role in B-cell proliferation and survival, and has been a focus of study and treatment for diseases like multiple myeloma. BCMA is expressed on the cell surface of both healthy and cancerous plasma cells and exhibits both intra- and extracellular functional components. The extracellular component of BCMA, membrane bound BCMA (mbBCMA) can be cleaved from the cell surface by y-secretase to generate soluble BCMA (sBCMA). sBCMA levels have been shown to be correlated with disease progression and prognosis.

[0004] Because of these findings, there has been interest in researching and testing BCMA expression levels and its effects on disease. It is standard procedure to analyze BCMA expression on plasma cells using bone marrow samples. However, collecting bone marrow is expensive, invasive, and painful for the subjects. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate aspects of the present disclosure and, together with the description, further serve to explain the principles of the disclosure and to enable a person skilled in the pertinent art to make and use the disclosure.

[0006] FIG. 1 illustrates a diagram of a method for obtaining cell data measurements from a sample using a flow cytometer, according to aspects of the present disclosure.

[0007] FIG. 2 illustrates a flowchart diagram for a method of quantifying cells having expressed BCMA, according to aspects of the present disclosure.

[0008] FIG. 3 illustrates a flowchart diagram for a gating strategy to quantify cells having expressed BCMA, according to aspects of the present disclosure.

[0009] FIG. 4 illustrates a flowchart diagram for another gating strategy to quantify cells having expressed BCMA, according to aspects of the present disclosure.

[0010] FIG. 5 illustrates an example of gates that may be used in a gating strategy to isolate and quantify cells having expressed BCMA, according to aspects of the present disclosure.

[0011] FIG. 6 illustrates an example of gates that may be used in a gating strategy to isolate and quantify cells having expressed BCMA, according to aspects of the present disclosure.

[0012] FIG. 7 illustrates another example of gates that may be used in a gating strategy to isolate and quantify cells having expressed BCMA, according to aspects of the present disclosure.

[0013] FIG. 8 illustrates a block diagram of example components of a computer system, according to aspects of the present disclosure.

[0014] Aspects of the present disclosure will be described with reference to the accompanying drawings.

DETAILED DESCRIPTION

[0015] BCMA is found on the surface of B-cells, which are produced in bone marrow. Sampling bone marrow is the most commonly practiced method to retrieve cells having expressed BCMA, because B-cells have a higher concentration in bone marrow than elsewhere in the body There is also a well-known process of isolating and quantifying the cells having expressed BCMA in bone marrow using flow cytometry. With the interest in BCMA for discovery and treatment of certain diseases, however, it may be necessary to find alternative strategies for collecting BCMA because of the burden it places on the subjects. The collection of bone marrow from a subject is expensive, invasive, and painful for the subject. Although it is known that flow cytometry can generally be completed on whole blood, there has been no innovation quantifying cells having expressed BCMA with a whole blood sample. There are challenges with this approach because B-cells are not as concentrated in whole blood, meaning there are lower concentrations of BCMA in the sample. This requires a new flow cytometry strategy for isolating cells having expressed BCMA in order to quantify their expression levels in a whole blood sample.

[0016] Isolating, quantifying, and/or measuring cells having expressed BCMA using whole blood samples can be useful in researching, studying, and testing the effects of disease therapies and/or treatment. Aspects described herein for quantifying cells having expressed BCMA can be used in many different applications of research and development, while also removing the need to collect bone marrow samples. For example, the method can be used in drug development, clinical studies and trials, testing for drug efficacy, and treatment plans for patients.

[0017] FIG. 1 illustrates a diagram of a system 100 for isolating and/or measuring, from whole blood, cells having a particular protein using a flow cytometer. In some aspects, system 100 is used to isolate, from whole blood, cells having surface BCMA, such that the BCMA levels on those cells can then be measured. System 100 includes one or more sample storage devices 102, a flow cytometer 104, and a computing device 106. Sample storage device 102 may be a physical storage device storing a biological sample, such as a sample tube, beaker, or pipette. The biological sample in the sample storage device may be, for example, a whole blood sample from a patient. In some aspects, the patient is a mammal, such as a human.

[0018] The biological sample in sample storage device 102 may be added to flow cytometer 104 for processing. Flow cytometer 104 uses light scattering and fluorescence on a liquid suspension containing cells to collect cell data on a cell-by-cell basis. The collected cell data may be used to classify each cell, count the cells, and/or make additional measurements pertaining to the cells.

[0019] Computer 106 may include, among other things, a memory 108 and a processor 110. Further details regarding computer 106 are provided with reference to FIG. 8, below. Cell data from flow cytometer 104 may be stored in memory 108 of computing device 106. Processor 110 is configured to execute instructions stored in a computer-readable memory, such as memory 108, to process the cell data from flow cytometer 104.

[0020] FIG. 2 illustrates a flowchart diagram of a method 200 for identifying, from whole blood, plasma cells having expressed BCMA. Method 200 begins with step 202, in which a whole blood sample is obtained. The whole blood sample may contain plasma cells having expressed BCMA, as well as other types of cells that would typically be found in whole blood. The whole blood sample may be obtained from a patient through any means of obtaining whole blood, such as a pin prick or blood draw. The whole blood sample may be contained in, for example, sample storage device 102.

[0021] In order to isolate cells using flow cytometry, fluorescently tagged molecules called fluorophores may be used to stain the surface of the cells in the whole blood sample. Fluorophores are microscopic molecules that absorb and emit fluorescent light. At step 204, the whole blood sample is mixed with a mixture of fluorophores that are configured to attach to a specific type of cell in the blood sample. In some aspects, the fluorophores may be used in conjunction with antibodies to create a fluorophore antibody reagent. Each antibody targets a specific type of cell or cell component, and the fluorophores attached to the antibody will stain the antibody’s target cell. When targeting cells in a heterogeneous sample of cells, the fluorophore antibody reagents are mixed together into a fluorophore mixture to stain the different types of cells or cell components.

[0022] In some aspects, the fluorophore mixture that may be used to quantify cells having expressed BCMA includes fluorophore antibody reagents that detect, for example and without limitation, B -lymphocytes, monocytes, T-cells, natural killer cells, plasma cells, and BCMA. For example, the fluorophore mixture may include CD19 PerCP-Cy™5.5, CD 14 FITC, CD3 FITC, CD56 FITC, CD 138 APC, CD38 BV421, and CD269 PE. A person of skill in the art will recognize that the mixture may contain additional or fewer fluorophore reagents depending on the use case. A person of skill in the art will further recognize that a fluorophore reagent for targeting a specific type of cell may be swapped for another flurophore reagent that is also known to target that same specific type of cell.

[0023] The fluorophore mixture and the whole blood sample may be mixed such that each fluorophore antibody reagent in the fluorophore mixture will stain the antibody’s targeted cell in the whole blood sample. This creates a whole blood sample mixture. The mixing may occur through any means of mixing two substances to obtain a whole blood sample mixture, such as a rotating mixer or a rolling mixer. The whole blood sample mixture may be held in sample storage device 102. In some aspects, the whole blood sample is mixed directly in sample storage device 102. In some other aspects, the whole blood sample is moved to an intermediate storage device (not shown) for mixing.

[0024] At step 206, the whole blood sample mixture is processed in the flow cytometer 104. Flow cytometry is a well-known process for acquiring specific information about individual cells, especially cells within a heterogeneous mixture. Flow cytometry can measure characteristics of cells in a sample, including size, count, and cell cycle. In some aspects, these measurements are taken by fluorescently labelling cell types or cell components in a sample and passing the cells in a single file through a laser. When the cell passes the laser, scattered light measurements and fluorescent light measurements are stored on a computing device in a computational dataset. The scattered light measurements can be used to measure, for example, size and granularity of a cell. The fluorescent light measurements are measurements of fluorescent labels on a cell that are excited and emit light at varying wavelengths when passed through the laser. In some aspects, a flow cytometer may include several detectors to measure different properties of the cell. A Forward Scatter (FSC) detector may be used to measure cell volume. A Side Scatter (SSC) detector may be used to measure granularity. Fluorescent detectors detect different cells or cell components based on the fluorescence they emit. In step 206, the whole blood sample mixture may be processed in the flow cytometer, and a computational dataset containing the whole blood sample’s cell measurements may be collected and stored in a computing device for further analysis. For example, each cell in the whole blood sample mixture from sample storage device 102 may be measured by flow cytometer 104. The resulting computational dataset may be stored in memory 108 of computing device 106. [0025] Once the scattered and fluorescent light measurements are collected and stored in the computational dataset in the computing device, they can be used to isolate and/or identify certain cells or cell components that are of interest. In some aspects of the present invention, a scatter plot may be used to compare two different light measurements of each cell in the computational dataset simultaneously. Certain areas of the scatter plot may signify a certain cell type. Selecting certain areas in the scatter plot to isolate a certain cell type is called gating. Gating sequentially selects areas on the scatter plot where the cells share similar measurements to determine which cells will be further analyzed and which cells will not be further analyzed. As referred to herein, a “positive” or “+” gate keeps those cells having the attribute being searched, while a “negative” or gate keeps those cells that do not have the attribute being searched. When seeking to isolate specific or rare cells, there may be a series of gates, called a gating strategy, applied to the computational dataset. The sequence in which these gates are applied plays a key role in isolating cells of interest. If data corresponding to a particular set of cells is removed from the gating strategy, that data may either be deleted completely from the computational dataset, or flagged or recategorized such that it is simply not considered for future steps in the gating strategy.

[0026] BCMA, for example, is found on a rare cell type in whole blood. Accordingly, searching every cell in the biological sample for BCMA would be computationally intensive and time consuming. In accordance with aspects of the present invention, computational identification of these rare, BCMA-containing plasma cells can be made feasible by the gating strategies described herein because they classify/sort the cells in manageable stages through which relevant cells can be targeted. This reduces the computational complexity and thus reduces the time needed to efficiently identify BCMA- containing plasma cells. Accordingly, the gating strategies described herein are vital to isolating and quantifying the plasma cells having expressed BCMA, as there are lesser quantities of the cell in the whole blood sample.

[0027] The computational dataset generated by the flow cytometer may be processed through a gating strategy 207. In some aspects, computing device 106 may include tools for data acquisition and data analysis from flow cytometer 104, and may use processor 110 to process the computational dataset to identify cells having expressed BCMA in the whole blood sample mixture. Tn the aspect shown in FIG 2, gating strategy 207 includes steps 208, 210, and 212, and one of step 214 and 216.

[0028] At step 208, the cells in the computational dataset may be gated by a mononuclear cell gate. A mononuclear cell gate included in the gating strategy may select cells that are mononuclear. Mononuclear cells refer to blood cells that have a single, round nucleus, including lymphocytes, which are the type of cells BCMA is found on. An example result from a mononuclear cell gate is illustrated in FIG. 5, plot 502. FIG. 5 is a graphical depiction of scatter plots from an example implementation of method 200 on a specific whole blood sample. As shown by plot 502, a mononuclear cell gate scatter plot may include FSC-area measurements and SSC-area measurements that measure size and granularity to select cells for further analysis. In this example, the mononuclear cell gate is a positive gate. The mononuclear cell gate may keep cells (that is, keep data corresponding to those cells) for further analysis that are within the range of size and shape of a mononuclear cell. Data for cells that do not present as mononuclear are removed from further analysis.

[0029] At step 210, the cells output from the mononuclear cell gate - the mononuclear cells - are gated by a single cell gate. A single cell gate included in the gating strategy may select cells that are single cells. A single cell gate is important because it removes cells that are stuck together, which may appear positive for antigens that would not be positive on a single cell, thus distorting the data. An example result from a single cell gate is illustrated in FIG. 5, plot 504. As shown by plot 504, a single cell gate scatter plot may include FSC- area measurements and FSC-height measurements that measure cell size to select cells for further analysis. In this example, the single cell gate is a positive gate. The single gate may keep cells that are within the range of size of a single cell. Data for cells that do not present as single cells are removed from further analysis.

[0030] A person of skill in the art will recognize that steps 208 and 210 may occur in any order. In some aspects, step 208 (mononuclear cell gate) occurs prior to step 210 (single cell gate), so that the cells remaining after the mononuclear cell gate are input into the single cell gate. In some other aspects, step 210 (single cell gate) occurs prior to step 208 (mononuclear cell gate), so that all cells are initially processed by the single cell gate, and the cells remaining after the single cell gate are input into the mononuclear cell gate. The cells remaining after passing through both the mononuclear gate and the single cell gate will be referred to herein as a first set of cells.

[0031] At step 212, cells that are not a certain cell type in the first set of cells are gated by a dump gate. A dump gate included in the gating strategy may select (keep) cells in the first set of cells that are not of a certain cell type. For example, the dump gate may select (keep) cells that are not monocytes, T-cells, or natural killer cells. Monocytes, T-cells, and natural killer cells are removed because BCMA is not found on those types of cells. The monocytes may be fluorescently marked (and thus identified by the dump gate) by, for example, CD14 fluorophores. The T-cells may be fluorescently marked by, for example, CD3 fluorophores. The natural killer cells may be fluorescently marked by, for example, CD56 fluorophores. Because each of these types of cells are marked, they can be removed from the data set by the dump gate. One of skill in the art will recognize that other fluorophores that identify monocytes, T-cells, and/or natural killer cells may alternatively or additionally be used. An example result from a dump gate is illustrated in FIG. 5, plot 506. As shown by plot 506, a dump gate scatter plot may include SSC-area measurements and fluorescent emissions of cells. In this example, the dump gate is a negative dump gate. The dump gate may keep all cells in the first set of cells that are not fluorescently marked by CD 14 fluorophores, CD3 fluorophores, or CD56 fluorophores. The cells from the first set of cells that remain after the dump gate will be referred to herein as a second set of cells.

[0032] After step 212, the second set of cells may be processed through either gating strategy 214 or gating strategy 216 to further narrow down the cells to identify plasma cells having surface BCMA. Gating strategy 214 is described below with respect to FIG. 3, while gating strategy 216 is described below with respect to FIG. 4.

[0033] Gating Strategy 1

[0034] FIG. 3 illustrates a flowchart diagram of a method 300 for the gating strategy 214. At step 302, the second set of cells are separated into two subsets of cells by a B- lymphocyte gate. One subset of cells includes B-lymphocytes and the other subset of cells includes non-B -lymphocytes. B-lymphocytes are selected because BCMA is found on B- lymphocytes. The B-lymphocytes may be fluorescently marked by, for example, CD19 fluorophores One of skill in the art will recognize that a different fluorophore that identifies B-lymphocytes may alternatively or additionally be used.

[0035] An example result from a B-lymphocyte gate is illustrated in FIG. 6, plot 601. As shown by plot 601, a scatter plot may include SSC-area measurements and CD19 fluorescence emissions. In this example, the B-lymphocyte gate is both a positive and a negative gate. Cells processed through the B-lymphocyte gate may be placed in a subset depending on whether the cell emits CD19 fluorescence (e.g., CD19+ gate 602) or does not emit CD 19 fluorescence (e.g., CD 19- gate 604). The B-lymphocyte gate may generate a B-lymphocyte cell subset and a non-B-lymphocyte cell subset.

[0036] Returning to FIG. 3, at step 304, cells in the B-lymphocyte cell subset are gated by a plasma cell gate. A plasma cell gate included in the gating strategy may select cells that are plasma cells. Plasma cells are selected because plasma cells develop from B- lymphocytes that have been activated, and BCMA is found on these activated B- lymphocytes. Plasma cells may be identified based on a co-expression of CD138 and CD38. Cells expressing CD38 may be fluorescently marked by CD38 fluorophores. Cells expressing CD138 may be fluorescently marked by CD138 fluorophores. Cells having the appropriate fluorescence emissions for CD138 fluorophores and CD38 fluorophores may be identified as plasma cells. The plasma cell gate may keep cells for further analysis that are identified as plasma cells. An example result from a plasma cell gate is illustrated in FIG. 6, plot 606. As shown by plot 606, a scatter plot may include fluorescence emissions for CD38 fluorophores and CD138 fluorophores so as to select an area of plasma cells. The plasma cell gate may be used to select cells that are plasma cells in the B-lymphocyte cell subset to generate a B-lymphocyte plasma cell subset.

[0037] At step 306, cells in the B-lymphocyte plasma cell subset are gated by a BCMA gate. A BCMA gate included in the gating strategy may identify cells left in the B- lymphocyte plasma cell subset that express BCMA, in order to isolate and/or quantify the cells having expressed BCMA. The cells having expressed BCMA may be fluorescently marked by, for example, CD269 fluorophores. An example result from a BCMA gate is illustrated in FIG. 6, plot 610. As shown by plot 610, a scatter plot may include SSC-area and fluorescence emissions for cells having expressed BCMA. The gate may be used to isolate and/or quantify the cells having expressed BCMA in the B-lymphocyte plasma cell subset.

[0038] Returning to FIG. 3, at step 308, cells in the non-B -lymphocyte cell subset are gated by a plasma cell gate. The plasma cell gate in step 308 may operate in a manner similar to that described for step 304. Cells expressing CD38 may be fluorescently marked by CD38 fluorophores. Cells expressing CD138 may be fluorescently marked by CD138 fluorophores. Cells having the appropriate fluorescence emissions for CD38 fluorophores and CD138 fluorophores may be identified as plasma cells in the non-B -lymphocyte cell subset to generate a non-B -lymphocyte plasma cell subset. An example result from a plasma cell gate acting on non-B -lymphocyte cells is illustrated in FIG. 6, plot 612. As shown by plot 612, a scatter plot may include fluorescence emissions for CD38 fluorophores and CD138 fluorophores so as to select an area of plasma cells.

[0039] At step 310, cells in the non-B -lymphocyte plasma cell subset are gated by a BCMA gate. The BCMA gate in step 310 may operate in a manner similar to that described for step 306. A BCMA gate included in the gating strategy may identify cells left in the non- B-lymphocyte plasma cell subset that express BCMA, in order to isolate and/or quantify the cells having expressed BCMA. An example result from a BCMA gate is illustrated in FIG. 6, plot 616. As shown by plot 616, the cell measurements analyzed in a scatter plot may include SSC-area and fluorescence emissions for cells having expressed BCMA. The cells having expressed BCMA may be fluorescently marked by, for example, CD269 fluorophores.

[0040] Once the cells having expressed BCMA (referred to herein as “BCMA cells”) are identified, various measurements can be made regarding the cells. For example, the quantity and/or percentage of the BCMA cells in the whole blood sample may be determined. In another example, the level of BCMA expression in the BCMA cells may be determined.

[0041] In some aspects, an isotype control may also be processed through the gating strategy in order to determine the accuracy of the gating strategy for quantifying cells having expressed BCMA. An isotype control may be mixed with the fluorophore mixture into an isotype sample mixture and processed in the flow cytometer to create an isotype computational dataset. The isotype computational dataset may be gated by the mononuclear gate, the single cell gate, the dump gate, the B-lymphocyte gate, the plasma cell gate, and the BCMA gate. The quantity of cells having expressed BCMA after applying the gating strategy may conclude that the gating strategy was accurately able to isolate cells having expressed BCMA in the whole blood sample mixture.

[0042] For example, in one aspect, an isotype sample mixture may be processed through the same steps of the gating strategy described above in order to determine the accuracy of the gating strategy for quantifying cells having expressed BCMA in the whole blood sample mixture. The isotype sample mixture may include a control isotype-PE and the fluorophore mixture. The isotype sample mixture may be processed by the flow cytometer 104 to produce an isotype computational dataset. The isotype computational dataset containing cell characterizations and measurements may be stored, for example, in memory 108 of computing device 106.

[0043] The isotype computational dataset may then be processed through the gating strategy of method 200 and method 300. Example results of processing the isotype computational dataset through the gating strategy of methods 200 and 300 are illustrated in FIG. 6, plots 608 and 614. Plot 608 illustrates a scatter plot from which the quantity of cells having expressed BCMA in a set of isotype B-lymphocyte plasma cells can be determined. Plot 614 illustrates a scatter plot from which the quantity of cells having expressed BCMA in a set of isotype non-B -lymphocyte plasma cells may be determined.

[0044] Gating Strategy 2

[0045] As discussed above with respect to FIG. 2, after step 212, the second set of cells may be processed through either gating strategy 214 or gating strategy 216 to further narrow down the cells to identify plasma cells having surface BCMA.

[0046] FIG. 4 illustrates a flowchart diagram of a method 400 for the gating strategy 216. At step 402, cells in the second set of cells are gated by a BCMA cell gate. A BCMA gate included in the gating strategy may select cells having expressed BCMA (referred to herein as “BCMA cells”) from the second set of cells. The cells having expressed BCMA may be fluorescently marked by, for example, CD269 fluorophores. An example result from a BCMA gate acting on the second set of cells is illustrated in FIG. 7, plot 702. As shown by plot 702, a BCMA gate scatter plot may include SSC-area measurements and fluorescence emissions for cells having expressed BCMA. Tn this example, the BCMA gate is a positive gate. The BCMA gate may be used to select (keep) cells that are fluorescently labelled as having expressed BCMA to generate a BCMA-positive cell subset. Data for cells in the second set of cells that do not present as expressing BCMA are removed from further analysis.

[0047] Cells in the BCMA-positive cell subset may be further processed by multiple additional gates to further classify the BCMA cells, as illustrated by steps 404, 406, and 408. Steps 404, 406, and 408 may be performed in parallel, or may be performed in any order.

[0048] At step 404, cells in the BCMA-positive cell subset are separated into two further subsets of cells by a B-lymphocyte gate. One subset of cells includes B-lymphocytes and the other subset of cells includes non-B-lymphocytes. The B-lymphocytes may be fluorescently marked by, for example, CD 19 fluorophores. One of skill in the art will recognize that a different fluorophore that identifies B-lymphocytes may alternatively or additionally be used.

[0049] An example result from a B-lymphocyte gate is illustrated in FIG. 7, plot 704. As shown by plot 704, a scatter plot may include SSC-area measurements and CD19 fluorescence emissions. In this example, the B-lymphocyte gate is both a positive and a negative gate. BCMA cells processed through the B-lymphocyte gate may be placed in a subset depending on whether the cell emits CD 19 fluorescence or does not emit CD 19 fluorescence. The BCMA cells within each subset may then be identified, quantified, and/or measured.

[0050] At step 406, cells in the BCMA-positive cell subset are gated by a CD38 gate. Plasma cells that express CD38 may be fluorescently marked by CD38 fluorophores. An example result from a CD38 gate is illustrated in FIG. 7, plot 706. As shown by plot 706, a CD38 scatter plot may include SSC-area measurement and CD38 fluorescence emissions. Cells having expressed BCMA, as determined by their CD38 expression may be identified, quantified, and/or measured.

[0051] At step 408, cells in the BCMA-positive cell subset are gated by a CD138 gate. Plasma cells that express CD 138 may be fluorescently marked by CD 138 fluorophores. An example result from a CD138 gate is illustrated in FIG. 7, plot 708. As shown by plot 708, a CD138 scatter plot may include SSC-area measurement and CD138 fluorescence emissions. Cells having expressed BCMA, as determined by their CD138 expression may be identified, quantified, and/or measured.

[0052] Example Computer System

[0053] FIG. 8 is a block diagram of example components of computer system 800. One or more computer systems 800 may be used, for example, to implement any of the aspects discussed herein, such as computing device 106 discussed with reference to FIG. 1, as well as combinations and sub-combinations thereof. In some aspects, one or more computer systems 800 may be used to perform data acquisition, data analysis, and data processing, such as for the computational dataset obtained by flow cytometer 104 as described herein. Computer system 800 may include one or more processors (also called central processing units, or CPUs), such as a processor 804. Processor 804 may be connected to a communication infrastructure or bus 806.

[0054] Computer system 800 may also include user input/output interface(s) 802, such as monitors, keyboards, pointing devices, etc., which may communicate with communication infrastructure 806 through user input/output device(s) 803.

[0055] One or more of processors 804 may be a graphics processing unit (GPU). In an aspect, a GPU may be a processor that is a specialized electronic circuit designed to process mathematically intensive applications. The GPU may have a parallel structure that is efficient for parallel processing of large blocks of data, such as mathematically intensive data common to computer graphics applications, images, videos, etc.

[0056] Computer system 800 may also include a main or primary memory 808, such as random access memory (RAM). Main memory 808 may include one or more levels of cache. Main memory 808 may have stored therein control logic (i.e., computer software) and/or data.

[0057] Computer system 800 may also include one or more secondary storage devices or memory 810. Secondary memory 810 may include, for example, a hard disk drive 812 and/or a removable storage drive 814.

[0058] Removable storage drive 814 may interact with a removable storage unit 818. Removable storage unit 818 may include a computer usable or readable storage device having stored thereon computer software (control logic) and/or data. Removable storage unit 818 may be a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM or PROM) and associated socket, a memory stick and USB port, a memory card and associated memory card slot, and/or any other removable storage unit and associated interface. Removable storage drive 814 may read from and/or write to removable storage unit 818.

[0059] Secondary memory 810 may include other means, devices, components, instrumentalities or other approaches for allowing computer programs and/or other instructions and/or data to be accessed by computer system 800. Such means, devices, components, instrumentalities or other approaches may include, for example, a removable storage unit 822 and an interface 820. Examples of the removable storage unit 822 and the interface 820 may include a program cartridge and cartridge interface (such as that found in video game devices), a removable memory chip (such as an EPROM or PROM) and associated socket, a memory stick and USB port, a memory card and associated memory card slot, and/or any other removable storage unit and associated interface.

[0060] Computer system 800 may further include a communication or network interface 824. Communication interface 824 may enable computer system 800 to communicate and interact with any combination of external devices, external networks, external entities, etc. (individually and collectively referenced by reference number 828). For example, communication interface 824 may allow computer system 800 to communicate with external or remote devices 828 over communications path 826, which may be wired and/or wireless (or a combination thereof), and which may include any combination of LANs, WANs, the Internet, etc. Control logic and/or data may be transmitted to and from computer system 800 via communication path 826.

[0061] Computer system 800 may also be any of a personal digital assistant (PDA), desktop workstation, laptop or notebook computer, netbook, tablet, smartphone, smartwatch or other wearables, appliance, part of the Internet-of-Things, and/or embedded system, to name a few non-limiting examples, or any combination thereof.

[0062] In some aspects, a tangible, non-transitory apparatus or article of manufacture comprising a tangible, non-transitory computer useable or readable medium having control logic (software) stored thereon may also be referred to herein as a computer program product or program storage device. This includes, but is not limited to, computer system 800, main memory 808, secondary memory 810, and removable storage units 818 and 822, as well as tangible articles of manufacture embodying any combination of the foregoing. Such control logic, when executed by one or more data processing devices (such as computer system 800), may cause such data processing devices to operate as described herein.

[0063] Based on the teachings contained in this disclosure, it will be apparent to persons skilled in the relevant art(s) how to make and use aspects of this disclosure using data processing devices, computer systems and/or computer architectures other than that shown in FIG. 8. In particular, aspects can operate with software, hardware, and/or operating system implementations other than those described herein.

[0064] It is to be appreciated that the Detailed Description section, and not the Summary and Abstract sections, is intended to be used to interpret the claims. The Summary and Abstract sections may set forth one or more but not all exemplary aspects of the present disclosure as contemplated by the inventor(s), and thus, are not intended to limit the present disclosure and the appended claims in any way.

[0065] Aspects of the present disclosure have been described above with the aid of functional building blocks illustrating the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed.

[0066] The foregoing description of the specific aspects will so fully reveal the general nature of the disclosure that others can, by applying knowledge within the skill of the art, readily modify and/or adapt for various applications such specific aspects, without undue experimentation, without departing from the general concept of the present disclosure. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed aspects, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance. [0067] The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary aspects, but should be defined only in accordance with the following claims and their equivalents.

Claims

WHAT TS CLAIMED IS:

1. A method for quantifying cells having expressed BCMA, comprising: obtaining a whole blood sample containing the cells having expressed BCMA and other types of cells; mixing the whole blood sample with a mixture of fluorophores to obtain a blood sample mixture, each fluorophore in the mixture of fluorophores configured to attach to a specific type of cell in the blood sample; processing the blood sample mixture with a flow cytometer to obtain a computational dataset comprising scattered and fluorescent light measurements for each cell in the blood sample mixture; selecting cells from the computational dataset for further analysis by gating cells based upon physical dimensions to generate a first set of cells; selecting cells from the first set of cells for further analysis by further gating cells in the first set of cells based on cell type to generate a second set of cells; and gating cells in the second set of cells using a gating strategy to quantify the cells having expressed BCMA.

2. The method of claim 1, the gating strategy to quantify the cells having expressed BCMA comprising: generating two subsets of cells from the second set of cells by gating B- lymphocyte cells into a B-lymphocyte cell subset and a non-B-lymphocyte cell subset; selecting cells from the B-lymphocyte cell subset for further analysis by gating cells that are plasma cells to generate a B-lymphocyte plasma cell subset; quantifying the cells having expressed BCMA in the B-lymphocyte plasma cell subset; selecting cells from the non -B-lymphocyte cell subset for further analysis by gating cells that are plasma cells to generate a non-B -lymphocyte plasma cell subset; and quantifying the cells having expressed BCMA in the non-B-lymphocyte plasma cell subset. The method of claim 2, wherein the B-lymphocyte cells are fluorescently marked by CD 19 antibodies in the fluorophore mixture. The method of claim 2, wherein the plasma cells are fluorescently marked by at least one of: CD38 antibodies in the fluorophore mixture or CD138 antibodies in the fluorophore mixture. The method of claim 2, wherein the cells having expressed BCMA are fluorescently marked by CD269 antibodies in the fluorophore mixture. The method of claim 2, further comprising; analyzing isotypes in the B-lymphocyte plasma cell subset for the cells having expressed BCMA; and determining an accuracy of the gating cells that are plasma cells based on a number of cells in the B-lymphocyte plasma cell subset having expressed BCMA. The method of claim 2, further comprising; analyzing isotypes in the non-B-lymphocyte plasma cell subset for expressed

BCMA; and determining an accuracy of gating the cells that are plasma cells based on a number of cells in the non -B -lymphocyte plasma cell subset having expressed BCMA. The method of claim 1, the gating strategy to quantify the cells having expressed BCMA further comprising: selecting cells from the second set of cells for further analysis by gating cells having expressed BCMA to generate a BCMA-positive cell subset; quantifying the cells having expressed BCMA in the BCMA-positive cell subset in a B-lymphocyte gate and a non-B -lymphocyte gate; quantifying the cells having expressed BCMA in the BCMA-positive cell subset in a monoclonal plasma cell gate; quantifying the cells having expressed BCMA in the BCMA-positive cell subset in a CD 138 positive cells plasma cell gate; The method of claim 8, wherein the cells having expressed BCMA are fluorescently marked by CD269 antibodies in the fluorophore mixture. The method of claim 8, wherein the B-lymphocytes are fluorescently marked by CD 19 antibodies in the fluorophore mixture. The method of claim 8, wherein the monoclonal plasma cells are fluorescently marked by CD38 antibodies in the fluorophore mixture. The method of claim 8, wherein the CD138 positive plasma cells are fluorescently marked by CD138 antibodies in the fluorophore mixture. The method of claim 1, wherein the physical dimensions includes at least one of: a size of cells or a granularity of cells. The method of claim 1, wherein the gating for the physical dimensions removes cells that are not mononuclear cells from the computational dataset. The method of claim 1 , wherein the gating for the physical dimensions removes cells that are not single cells from the computational dataset. The method of claim 1, wherein the gating for the cell types removes monocytes from the first set of cells. The method of claim 16, wherein the monocytes that are removed are fluorescently marked by CD14 antibodies in the fluorophore mixture. The method of claim 1, wherein the gating for the cell types removes T-cells from the first set of cells. The method of claim 18, wherein the T-cells that are removed are fluorescently marked by CD3 antibodies in the fluorophore mixture. The method of claim 1, wherein the gating for the cell types removes natural killer cells from the first set of cells. The method of claim 20, wherein the natural killer cells that are removed are fluorescently marked by CD56 antibodies in the fluorophore mixture. The method of claim 1, wherein the fluorophore mixture includes at least one of: CD19 antibodies, CD14 antibodies, CD3 antibodies, CD56 antibodies, CD138 antibodies, CD38 antibodies, or CD269 antibodies. A system for quantifying cells having expressed BCMA, comprising: a mixer configured to mix a blood sample with a mixture of fluorophores to obtain a blood sample mixture, the blood sample containing the cells having expressed BCMA and other types of cells and each fluorophore in the mixture of fluorophores configured to attach to a specific type of cell in the blood sample; a flow cytometer configured to process the blood sample mixture to obtain a computational dataset comprising scattered and fluorescent light measurements for each cell in the blood sample mixture; a computing device having a processor and a memory, the memory storing instructions that, when executed by the processor, cause the processor to: select cells from the computational dataset for further analysis by gating cells based upon physical dimensions to generate a first set of cells; select cells from the first set of cells for further analysis by further gating cells in the first set of cells based on cell type to generate a second set of cells; and gate cells in the second set of cells using a gating strategy to quantify the cells having expressed BCMA. The system of claim 23, the gating strategy to quantify the cells having expressed BCMA comprising instructions that, when executed by the processor, cause the processor to: generate two subsets of cells from the second set of cells by gating B- lymphocyte cells into a B-lymphocyte cell subset and a non-B-lymphocyte cell subset; select cells from the B-lymphocyte cell subset for further analysis by gating cells that are plasma cells to generate a B-lymphocyte plasma cell subset; quantify the cells having expressed BCMA in the B-lymphocyte plasma cell subset; select cells from the non-B-lymphocyte cell subset for further analysis by gating cells that are plasma cells to generate a non-B-lymphocyte plasma cell subset; and quantify the cells having expressed BCMA in the non-B-lymphocyte plasma cell subset. The system of claim 24, wherein the B-lymphocyte cells are fluorescently marked by CD 19 antibodies in the fluorophore mixture. The system of claim 24, wherein the plasma cells are fluorescently marked by at least one of: CD38 antibodies in the fluorophore mixture or CD138 antibodies in the fluorophore mixture. The system of claim 24, wherein the cells having expressed BCMA are fluorescently marked by CD269 antibodies in the fluorophore mixture. The system of claim 24, further comprising instructions that, when executed by the processor, cause the processor to: analyze isotypes in the B-lymphocyte plasma cell subset for the cells having expressed BCMA; and determine an accuracy of the gating cells that are plasma cells based on a number of cells in the B-lymphocyte plasma cell subset having expressed BCMA. The system of claim 24, further comprising instructions that, when executed by the processor, cause the processor to: analyze isotypes in the non-B-lymphocyte plasma cell subset for expressed BCMA; and determine an accuracy of the gating cells that are plasma cells based on a number of cells in the non-B-lymphocyte plasma cell subset having expressed BCMA. The system of claim 23, the gating strategy to quantify the cells having expressed BCMA comprising instructions that, when executed by the processor, cause the processor to: select cells from the second set of cells for further analysis by gating cells having expressed BCMA to generate a BCMA-positive cell subset; quantify the cells having expressed BCMA in the BCMA-positive cell subset by gating between B-lymphocytes and non-B-lymphocytes; quantify the cells having expressed BCMA in the BCMA-positive cell subset by gating monoclonal plasma cells; quantify the cells having expressed BCMA in the BCMA-positive cell subset by gating CD138 positive cells plasma cells; The system of claim 30, wherein the cells having expressed BCMA are fluorescently marked by CD269 antibodies in the fluorophore mixture. The system of claim 30, wherein the B-lymphocytes are fluorescently marked by CD 19 antibodies in the fluorophore mixture. The system of claim 30, wherein the monoclonal plasma cells are fluorescently marked by CD38 antibodies in the fluorophore mixture. The system of claim 30, wherein the CD138 positive plasma cells are fluorescently marked by CD138 antibodies in the fluorophore mixture. The system of claim 23, wherein the physical dimensions includes at least one of: a size of cells or a granularity of cells. The system of claim 23, wherein the gating for the physical dimensions removes cells that are not mononuclear cells from the computational dataset. The system of claim 23, wherein the gating for the physical dimensions removes cells that are not single cells from the computational dataset. The system of claim 23, wherein the gating for the cell types removes monocytes from the first set of cells. The system of claim 38, wherein the monocytes that are removed are fluorescently marked by CD14 antibodies in the fluorophore mixture. The system of claim 23, wherein the gating for the cell types removes T-cells from the first set of cells. The system of claim 40, wherein the T-cells that are removed are fluorescently marked by CD3 antibodies in the fluorophore mixture. The system of claim 23, wherein the gating for the cell types removes natural killer cells from the first set of cells. The system of claim 42, wherein the natural killer cells that are removed are fluorescently marked by CD56 antibodies in the fluorophore mixture. The system of claim 23, wherein the fluorophore mixture includes at least one of: CD19 antibodies, CD14 antibodies, CD3 antibodies, CD56 antibodies, CD138 antibodies, CD38 antibodies, or CD269 antibodies.