WO2005085842A2 - Procede de detection simultanee de populations de plusieurs entites biologiques differentes par cytometrie de flux, dispositif et programme informatique a cet effet - Google Patents

Procede de detection simultanee de populations de plusieurs entites biologiques differentes par cytometrie de flux, dispositif et programme informatique a cet effet Download PDF

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WO2005085842A2
WO2005085842A2 PCT/EP2005/002492 EP2005002492W WO2005085842A2 WO 2005085842 A2 WO2005085842 A2 WO 2005085842A2 EP 2005002492 W EP2005002492 W EP 2005002492W WO 2005085842 A2 WO2005085842 A2 WO 2005085842A2
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populations
cells
regions
computer program
region
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PCT/EP2005/002492
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WO2005085842A3 (fr
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Olivier Pradier
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Universite Libre De Bruxelles
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1456—Optical investigation techniques, e.g. flow cytometry without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459—Optical investigation techniques, e.g. flow cytometry without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/01—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials specially adapted for biological cells, e.g. blood cells
    • G01N2015/012—Red blood cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1486—Counting the particles

Definitions

  • the present invention relates to a method, device and computer program for analyzing populations of biological components, using flow cytometry, and an analysis which allows a large number of populations to be simultaneously quantified.
  • the differential count of white blood cells and leukocytes is widely used to assess the hematological and immunological status of human patients.
  • hematological analyzers used by the pathologists throughout the world which provide physicians with hematological biological results.
  • These analyzers are, with different technologies, able to process about 100 to 150 patient samples per hour, and provide up 15 to 18 results per samples. They are able to analyze red blood cells, platelets and specific parameters relating thereto (Hemoglobin content, volume, distribution etc.), and they are also able to analyze leucocytes circulating in the blood.
  • the polymorphonuclears the polynuclears, eosinophils and basophils, the monocytes and the lymphocytes.
  • PMN polymorphonuclears
  • These cells are normally resident in the blood, and are matured (or near mature) cells. They are derived from precursors located in the bone marrow. When an individual has a pathologic condition these precursors, or their neoplastic counterparts sometimes appear in the blood.
  • Current analyzers are able to recognize them in a crude manner, but are not able to clearly quantify them.
  • Present analyzers rely on expression flag(s) for quantification.
  • one or more flags allows the pathologists or his technologists to analyze the morphology of the cells under a microscope, and to perform manually a short differential count.
  • the number cells per sample is limited to roughly 100. Should a cell count be especially low, it would require the analysis of several samples to obtain a statistically meaningful cell count. Thus, the microscopic analysis method is time consuming (from 10 to 20 minutes per slide when the leukocyte count is low) and very inefficient.
  • FCM flow cytometry
  • a FCM device might be set up such that FL1 is sensitive to emission wavelength of fluorescein (FITC blue green light), FL2 is sensitive to phycoerythrin (PE, orange), FL3 to pteridine, cyanine or derivatives and/or tandems thereof (Per-CP, Per-CP Cy 5.5, PC5, far red), and FL4 to cyanin (APC, blue).
  • FCM can be used to classify the blood lymphocytes into B, T and NK lymphocytes; to subdivide T cells into helpers (marker CD4 positive) and cytotoxic/suppresors (marker CD8 positive); to subdivide T cells according to their activation level using HLA-DR expression.
  • helpers marker CD4 positive
  • cytotoxic/suppresors marker CD8 positive
  • lymphocytes in T, B and NK cells are of great importance because B cell proliferations are the most frequent in lympho- proliferative diseases.
  • Quantitating CD8/HLA-DR positive cells allow the detection of virocytes (equivalent to the "atypical lymphocytes" flags of the analyzers) and are clinically relevant during AIDS follow up. Detecting bone marrow released precursors is important during inflammation/sepsis and myeloproliferative diseases or leukemias.
  • FCMs and/or devices attached thereto may, in a particular mode of operation, produce a two- dimensional intensity representation of data measured from a sample.
  • the two-dimensional representation may be marked by the user into a certain number of regions to establish populations of cells; the number of regions the device is able to compute is proportional to the number of populations that can be quantified. Because of the computation complexity required, the number of regions a FCM and/or device attached thereto can compute is limited, therefore, a limit is automatically placed on the number of populations a FCM can quantify.
  • US Patent number 5,843,689 discloses a method for determining the immunoregulatory status of the mononuclear leukocyte immune system using FCM.
  • the method uses light scatter determine the leukocyte class and fluorcescence data to enumerate the cell subclass and amount of activation antigen expression.
  • the problem of measuring a large number of populations of components in the mononuclear leukocyte immune system is not encountered in the document and, therefore, is not addressed therein.
  • US Patent number 5,188,935 discloses a method for lysing and fixing cells for use in FCM; the method discloses specific reagent-based methodological procedures, however, the problem of enumerating a large number of populations in a sample is not touched on.
  • US Patent number 5,627,040 discloses a method for autoclustering of two-dimensional arrays derived from FCM. There is no disclosure therein of enumerating a large number of populations in a sample. There is a need for a method of easily analyzing the populations of biological entities in a sample which is capable of simultaneously measuring the size of the populations of at least two, and ideally more than five biological entities, such as blood components. There is a need for overcoming the limits placed on FCM devices, wherein the number of populations to be measured is greater than the number of different fluorescent markers that can be simultaneously detected. There is a need for overcoming the limits placed on FCM devices, wherein the number of populations to be measured is limited by the number of regions into which a two-dimensional intensity representation of the data therefrom can be demarked.
  • One embodiment of the present invention is a method suitable for quantifying a sample comprising populations of biological entitles, using a flow cytometer capable of measuring forward light, scattered light and fluorescence comprising: a) labelling populations of interest, optionally wherein two or more populations are labelled by the same fluorophore, b) taking a flow cytometry measurement of said sample, c) demarking one or more cluster regions, d) performing one or more Boolean operations upon said cluster regions, and e) obtaining quantitative data relating to the size of said populations.
  • Another embodiment of the present invention is a method as described above wherein two or more said regions overlap.
  • step a) is performed using population-specific antibodies.
  • labels of step a) are one or more of fluoresceine, phycoerythrin, pteridine, cyanine, Per-CP, Per- CP, Cy 5.5, PC5, cyanin, APC.
  • Another embodiment of the present invention is a computer program, stored on a computer readable medium, capable of performing a method as described above.
  • Another embodiment of the present invention is a computer storage medium comprising a computer program as described above.
  • One aim of the present invention is to provide a method suitable for quantifying a sample comprising populations of biological entitles, using a flow cytometer capable of measuring forward light, scattered light and fluorescence comprising:
  • the number of populations that can be detected is maximised. This is especially relevant when the number of fluorophores available for detection is less than the number of populations to be detected. This scenario occurs in the analysis of blood wherein the sizes of the populations of 6 or more blood components need to be measured, and flow cytometry devices may detect only 3 or 4 fluorescent labels simultaneously.
  • Another aim of the present invention is to provide said method, using non-covalent association to label populations of interest.
  • Another aim of the present invention is to provide said method, using demarcation of regions on two dimensional intensity plots wherein said two or more said regions overlap.
  • the demarcation of two dimensional intensity plots into overlapping regions allows the user artificially to overcome the limits set by FCMs and/or devices attached thereto regarding the maximum number of regions available for Boolean operations; this subsequently allows more components in a sample to be simultaneously analysed.
  • Another aim of the invention is to provide said method, making use of one or more sets of Boolean operations that are performed between demarked regions of two dimensional intensity plots.
  • Boolean logic in combination with a computing device, allows operations to be performed extremely quickly since Boolean logic is a fundamental operation of computers.
  • Another embodiment of the present invention is a computer program, stored on a computing device having a data storage means, which is capable of performing a method according to the invention.
  • the use of a computer program to perform certain steps of the invention allows the method to be transferred to any FCM device which comprises a computer and/or is capable of interfacing with a computer, so representing a considerable time saving, cost saving and convenience in performing the method of the invention.
  • One embodiment of the present invention is a method for quantifying a sample comprising populations of biological entitles, using a flow cytometer capable of measuring forward light, scattered light and fluorescence comprising: a) labelling populations of interest, optionally wherein two or more populations are labelled by the same fluorophore, b) taking a flow cytometry measurement of said sample, c) demarking a number (C) of cluster regions, d) performing one or more Boolean (gating) operations upon said cluster regions, and e) obtaining quantitative data relating to the size of said populations.
  • population herein means a collection of one or more of the same entity.
  • entity herein means any biological molecule detectable using a fluorescent label and a FCM.
  • entities include, but are not limited to any blood component, any whole blood component, any immune system-related blood component, blood leukocytes, lymphocytes, platelets, polymorphonuclears, immature myeloids, eosinophils, basophils, T lymphocytes, non T non B lymphocytes, CD4+ T lymphocytes, Non CD4+ T lymphocytes, CD4+ DR+ T lymphocytes, CD8+ T lymphocytes, Non CD8+ T lymphocytes, CD8+ DR+ T lymphocytes, atypical lymphocytes, nucleated red blood cells, blasts.
  • Entities include any cell from any organism, including, but limited to eukaryotic cell, prokaryotic cell, viruses, fungi, plant cells. Entities include any biological macromolecule, including, but not limited to proteins, nucleic acids, glycoproteins, protein-nucleic acid associations, bacteria, protozoa, protoplasts, zooplankton etc.
  • flow cytometer can be readily understood by a skilled person and encompasses flow cytometers of any kind, as well as any analyzers, in particular hematological analyzers, which employ the same or similar technological platform.
  • a number (P) of populations can be labelled by the same fluorophore.
  • the number of populations labeled by the same fluorophore can be two or more. It may be, for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10 or more.
  • the value of P can depend of many factors including the number of regions the cytometer or device attached thereto is capable of performing Boolean operations thereon, and the number of different fluorophores said cytometer is capable of simultaneously detecting.
  • the labelling of populations of interest may be performed by any means known in the art. It may, for example, be performed by using a protein that interacts with a macromolecule on the surface of the population of entities, said protein being tagged with a fluorophore. It may be performed using an antibody directed against an antigen belonging to a population of entities; said antibody being tagged with a fluorophore.
  • a non-covalent means of labelling a population which takes advantage of a unique aspect of the surface of the population, provides a non-invasive, sensitive and simple means for identifying entities using flow cytometry according to the invention.
  • monoclonal antibodies are used labeled with the same fluorphore, it is an aspect of the invention that they do not recognise antigens common to different populations of cells.
  • one fluorescence channel dedicated to the fluorescent tag of an antibody separating clearly the lymphoid cells, the myeloid cells and the blast cells. This role is generally devoted to the marker CD45.in association with the physical parameters ⁇ i.e. side scatter and forward scatter).
  • the flow cytometer measures side scatter, forward scatter, and the fluorescence of one or more fluorescent labels.
  • the data may be presented as two dimensional intensity plots wherein the two axis are any combination of the aforementioned measurements. For example, side scatter vs. forward scatter, side scatter vs. fluorescence due to chromophore 1 , fluorescence due to chromophore 1 vs. fluorescence due to chromophore 2, etc.
  • Providing two dimensional data plots of combinations of the data available allows the cluster regions to be readily identified and allows Boolean operations to be performed thereon quickly.
  • the use of two dimensional analysis allows the method of the invention to be performed on the basic flow cytometers, and does not require extensive multidimensional array handling capabilities.
  • the data may be processed as a multidimensional intensity plot wherein the axes are any combination of the aforementioned measurements.
  • Manipulating multidimensional data allows fast and integrated calculations to proceed, without the need to analyse separate two dimensional data. It further allows easy compression of data, so saving storage space, time and expenditure on storage.
  • regions are identified in the two- or multi-dimensional representations of the aforementioned parameters.
  • the regions are delimited according to the clustering of data points. Identification of regions is performed by methods of the art, and may be automated and/or manual.
  • the number of regions that may be indicated and made available for Boolean (gating) operations can be any number. Alternatively, it may be limited by the flow cytometer and/or the processing device attached thereto; the mathematical complexity and the size of the data sets sometimes means the number or regions a device can perform Boolean operations on is set at a limit. Often this limit is below that required to quantify populations of entities in a sample. For example, if a user has to identify 15 components of blood, 30 regions would need to be defined and operated on in a gating strategy. This number is beyond the level set by some devices. Therefore, the inventors have provided another aspect of the invention which is to demark two dimensional intensity plots into bi-lobed regions and overlapping regions to increase artificially the number of regions.
  • bi-lobed regions and overlapping regions overcome the limits placed on the number of region numbers by some flow cytometers.
  • Another aspect of the invention is the demarcation of regions on a two dimensional intensity plot, wherein the two axis are any combination of the aforementioned measurements, and two or more regions overlap.
  • the regions may be of any shape including, but not limited to circular, trapezoidal, concave, polygonal, and bi-lobed, tri-lobed, multi-lobed etc.
  • the demarcation is performed using any method of the art. According to another aspect of the invention, the demarcation is performed using a scheme depicted in Figure 1. According to another aspect of the invention, the demarcation is performed using a scheme depicted in Figure 2-1 and 2-2. According to another aspect of the invention, the demarcation is performed using a set of rules described below. The demarcation of two dimensional intensity plots into overlapping regions allows a user artificially to overcome the limits set by flow cytometers and/or devices attached thereto regarding the maximum number of regions available for gating operations; this subsequently allows more components in a sample to be simultaneously analysed.
  • the rules to design Regions, Gates and the Boolean take in account the following: - To define a cluster (literally a cell population), at least two regions defined in dot plots and three or more different parameters (fluorescence or physical) are frequently required. Considering that, a minimum of fifteen clusters may be defined in the present invention, it requires defining a minimum of 24 regions.
  • a cluster volumeally a cell population
  • three or more different parameters fluorescence or physical
  • the gating strategy (Boolean operations) is performed between regions demarked.
  • Said operations may be performed by methods known in the art. Alternatively, they may be performed according to a set of rules calculated according to a method of the invention. Alternatively, they may be performed according to Table 1.
  • R3 is bi-lobed, surrounding the eosinophiles and the basophiles.
  • R5 overlaps R4 and R6 (surrounding lymphocytes and eosinophiles);
  • R6 overlaps R4 surrounding the non T lymphocytes.
  • R8 is bi-lobed surrounding CD4 and non CD4 T lymphocytes.
  • R7 overlapped the left side of R8.
  • R9 overlapped R10 to surround the CD4 T cells.
  • Region 1-1 and 1-2 Exemplary demarcations of regions (R1 to R16) for use in the strategy (or algorithm) of Table 1 are illustrated in Figure 1-1 and 1-2 (A to H) and explained below.
  • SSC side scatter; y-axis
  • FSC forward scatter; x-axis
  • region 1 (R1) surrounds mononuclear cells including the blasts area.
  • Region 2 (R2) surrounds the myeloid cells (PMN and immature granulocytes).
  • the overlap between R1 and R2 is not intended to create a new region but is due to the necessity to increase the surface of the regions to contain the inter individual variability.
  • R3 is a bi-lobed region surrounding the basophiles (low SSC) and the eosinophiles (high SSC).
  • R4 is approximately rectangular on the left and surround lymphocytes and NRBC
  • R6 is oblique and rectangular in the bottom and surrounds eosinophiles (combination of R5 and R6), Immature granulocytes (R6 and not (R5 or R4)) and non T lymphocytes (R6 and R4).
  • R5 is rectangular with two extensions, one in the left in the middle of R4 surround the T lymphocytes (R4 and R5) and one in the bottom right overlapping with R6 creating a new region surrounding eosinophiles (R5 and R6).
  • R5 surrounds mature polymorphonuclear (R5 and not (R6 or R4)).
  • dot plot R7 in Figure 1-1C is an "L"-shape and R8 is bi-lobed region, with the left lobe of R8 overlapping with R7 detremining a new region surrounding non CD4 T cells.
  • R9 is a "dog leg right" and R10 is trapezoidal; together they overlap and surround the CD4+ region as indicated with an arrow. R9 is designed to improve eosinophiles definition and R10 the B cells definition.
  • FIG. 1-1 E where R11 surrounds the HLA-DR positive cells (blastes, B cells monocytes and virocytes), Figure 1-1 F where R12 is to increase the definition of blastes and Figure 1-2G and H with y- and x-axis labeled to identify the measured signals and R13 improving the T cell definition, R16 and R14 the monocytes definition, and R16 the NRBCs.
  • R11 surrounds the HLA-DR positive cells (blastes, B cells monocytes and virocytes)
  • Figure 1-1 F where R12 is to increase the definition of blastes and Figure 1-2G and H with y- and x-axis labeled to identify the measured signals and R13 improving the T cell definition, R16 and R14 the monocytes definition, and R16 the NRBCs.
  • the gating strategy (Boolean operations) may be performed according to Table 2.
  • Region 16' is included in R1' and surrounds the NRBC (i.e., CD71 positive CD45 low or negative) myeloid cells (PMN and immature granulocytes).
  • the overlap between R1' and R16' is intended to include the percentage of NRBC in the differential count.
  • SSC y-axis
  • CD45 Per-CP dot plot in Figure 2-1 B each region surrounds a big family of cells, which is common in pivotal dot plots such as this one.
  • R2' surrounds the lymphocytes, R3' the monocytes, R6' the myeloid family, and R15' the CD45 low represented by blasts, plamatocytes and basophiles.
  • R2' and R15' overlap to create a new region which surrounds the basophile area.
  • R4' covers all FITC positive cells (i.e., in the SSC low area the CD3 positive T cells and in the SSC medium or high the CD16b mature polymorphonuclears) and R5' surrounds more immature myeloid cells (from band cells to myeloblasts).
  • R4' and R5' overlap to create a new region surrounding the eosinophiles CD16b intermediate and high SSC.
  • the limit separates the HLA-DR positive non T lymphocytes cells (CD3 FITC negative).
  • CD3 FITC negative cells belong to the B cells population.
  • the NK cells are indirectly determined by this gating because they are CD3 (and CD16b which is a strictly polymorphonuclear marker in contrast to CD16 and CD16a which are mainly expressed by NK cells) negative and HLA-DR negative.
  • the basophile are located because they are CD123 positive (the separation of the basophiles PE stained by CD123 and B lymphocytes PE stained by HLA-DR is made using differential expression of CD45; an overlap might occur between basophiles and blasts and basophiles and CLL B cells, such cells having frequently a low CD45 expression).
  • the right part (FITC positive) of the R10' region is dedicated to the T cells positively stained for HLA-DR, and particularly the CD8 positive T cells, useful marker of viral infection (activated T cytotoxic cells, virocytes).
  • F R8' is a redundancy of R10' and R11' surrounds the plasmatocytes region (CD19 intermediate and CD38 extremely bright).
  • SSC (y-axis) / FSC (x-axis) dot plot in Figure 2-1 G the classical physical cells parameters (size and complexity) are used to better define eosinophiles (SSC high and FSC intermediate) and basophiles FSC low and SSC low (inside the lymphocytes area).
  • the bi-lobed shape of the R12' region serves to create artificially two regions because basophiles and eosinophiles are different in their phenotypes and it is easy to split R12' using Boolean logic.
  • R12' is bi-lobed and surrounds the eosinophiles and the basophiles.
  • R13' is dedicated to surround blasts and plasmatocytes. It is not a mononuclear cells gate. Blasts location is generally under the monocytes (lower SSC) and partially overlaps the lymphocyte region.
  • Figures 3-1 and 3-2 show exemplary gating using regions R1' to R16' as above in a sample from a patient with a Myeloproliferative syndrome in acutisation, showing the blasts location (arrows) in all the dot graphs and the immature granulocytes.
  • Another embodiment of the present invention is a device capable of performing the method of the present invention.
  • the device is a FCM capable of performing the method of the present invention.
  • the device interfaces with a FCM and enables the FCM to perform the method of the invention.
  • Another embodiment of the present invention is a device capable of performing steps c) and/or d) and/or e) according to the invention.
  • the device may be connected directly to the FCM and/or it receives data from the FCM without direct connection to the FCM.
  • Data may be received by any means known in the art, including, but not limited to, storage media such as floppy disk, optical disk (e.g. MO, CD, DVD), DAT; across a network; wireless communication; IR communication.
  • Another embodiment of the present invention is a computer program, stored on a computing device having a data storage means, which is capable of performing steps c) and/or d) and/or e) according to the invention.
  • the computer program is written according to methods known in the art.
  • the computer program has a user interface which allows the operation of the FCM and/or the method of the invention; said user interface presenting options, displays, dialogue boxes in accordance to methods known in the art.
  • the computer program interacts with a computer program installed on the FCM, so allowing the method of the invention to be performed by the FCM computer program.
  • Another embodiment of the invention is a data media, such as a floppy disk, CD-ROM, DVD, comprising the computer program according to the invention.
  • Figure 1-1 and Figure 1-2, (A) to (H), show various dot plots, wherein regions have been demarked. Regions R1 to R16 in the figures are exemplary for use in the strategy (or algorithm) as detailed in Table 1.
  • Region 1 surrounds mononuclear cells including the blasts area
  • Region 2 surrounds the myeloid cells (PMN and Immature granulocytes).
  • the overlap between Region 1 and Region 2 is not intended to create a new region but is due to the necessity to increase the surface of the regions to contain the inter individual variability.
  • Region 3 is a bi-lobed region surrounding the basophiles and the eosinophiles.
  • R4 is approximately rectangular on the left; R6 is oblique and rectangular in the bottom and R5 is rectangular with two extensions, one in the left in the middle of R4 and one in the bottom right overlapping with R6.
  • R4 and R5 surround the T lymphocytes and R6 and R5 surround eosinophiles.
  • R9 is a "dog leg right” and R10 is trapezoidal. They overlap surrounding the CD4 + region (indicated).
  • Figure 2-1 and 2-2 (A to L), show various dot plots, wherein regions have been demarked. Regions R1' to R16' in these figures are exemplary for use in the strategy (or algorithm) as detailed in Table 2.
  • NRBC CD71 positive CD45 low or negative myeloid cells
  • R2' surrounds the lymphocytes
  • R3' the monocytes
  • R6' the myeloid family
  • R15' the CD45 low represented by blasts, plamatocytes and basophiles.
  • R2' and R15' overlap to create a new region which surrounds the basophile area.
  • CD8 positive cells and B cells are stained with FITC and distinguished by another staining, here CD3.
  • CD8 positive cells belonging to the T cells family are also CD3 positive.
  • B cells are CD3 negative.
  • CD8 positive cells are surrounded by a new region created by the overlap of R7' and R9'.
  • the B cells (FITC positive but negative for CD16b, CD71 and CD3) are surrounded by the lower part of R9' (R9' and not R7').
  • the basophile are located because they are CD123 positive (the separation of the basophiles PE stained by CD123 and B lymphocytes PE stained by HLA-DR is made using differential expression of CD45; an overlap might occur between basophiles and blasts and basophiles and CLL B cells, such cells having frequently a low CD45 expression).
  • the right part (FITC positive) of the R10' region is dedicated to the T cells positively stained for HLA-DR, and particularly the CD8 positive T cells, useful marker of viral infection (activated T cytotoxic cells, virocytes).
  • R8' is a redundancy of R10' and R11' surrounds the plasmatocytes region (CD19 intermediate and CD38 extremely bright).
  • the classical physical cells parameters are used to better define eosinophiles (SSC high and FSC intermediate) and basophiles FSC low and SSC low (inside the lymphocytes area).
  • the bi-lobed shape of the R12' region serves to create artificially two regions because basophiles and eosinophiles are different in their phenotypes and it is easy to split R12' using Boolean logic.
  • R13' is dedicated to surround blasts and plasmatocytes. It is not a mononuclear cells gate. Blasts location is generally under the monocytes (lower SSC) and partially overlaps the lymphocyte region.
  • Plot H shows only the "lymphocytes CD8" gated events and is a control of the presence of CD8 T lymphocytes expressing HLA-DR (namely virocytes). These cells are easily visually separated from CD8 positive HLA-DR negative cells.
  • Plot I is a visual control of the lymphocytes populations (plot expressed events fitting the lymphocytes gate Boolean logic) CD8 positive T lymphocytes; B cells; CD8 negative T cells (indirectly the CD4) and non T non B cells (indirectly the NK cells).
  • Figure 3-1 and 3-2 are an example of gating using the regions depicted and explained in Figure 2-1 and 2-2 and in relation to Table 2 in a patient with a Myeloproliferative syndrome in acutisation showing the blasts location (arrows) in all the dot graphs and the immature granulocytes.
  • Figure 4-1 , 4-2, and 4-3 schematically illustrates regions and gates.
  • the regions R1 , R2 and R3 are only schematic representations and are not the same as in Figures 1-1 and 1-2 and Table 1.
  • Figure 4-1 shows a combination of two regions R1 and R2 which overlap to create three gates A, B and C.
  • Figure 4-2 shows (i) a combination of one bi-lobed region (R2) and a single region R1 which overlap to create three gates A, B and C, and (ii) a combination of two bi-lobed regions (R1 and R2 which overlap to create three gates A, B and C.
  • Figure 4-3 shows (i) a combination of three regions (R1 , R2, and R3) which overlap to create five gates A, B, C, D and E.

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Abstract

La présente invention concerne un procédé qui convient pour quantifier un échantillon comprenant des populations d'entités biologiques, au moyen d'un cytomètre de flux ou de tout autre dispositif d'analyse hématologique utilisant une plate-forme technologique capable de mesurer une lumière dirigée vers l'avant, une lumière diffusée et une fluorescence comprenant des populations de marquage d'intérêt, éventuellement, au moins deux populations sont marquées par le même fluorophore, prenant une mesure de cytométrie de flux de cet échantillon, démarquant une ou plusieurs régions de groupes, réalisant une ou plusieurs opérations booléennes sur ces régions de groupes et, obtenant des données quantitatives relatives à la taille de ces populations. Cette invention concerne aussi un programme informatique à cet effet.
PCT/EP2005/002492 2004-03-09 2005-03-09 Procede de detection simultanee de populations de plusieurs entites biologiques differentes par cytometrie de flux, dispositif et programme informatique a cet effet WO2005085842A2 (fr)

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EP2004002410 2004-03-09

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EP1840571A3 (fr) * 2006-03-29 2009-09-09 Sysmex Corporation Procédé et appareil pour la mesure d'un échantillon hématologique
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EP1785899A3 (fr) * 2005-11-10 2007-05-23 IDEXX Laboratories Inc Procédés d'identification de populations discrètes (par exemple des grappes) de données au sein d'un jeu de données multidimensionnelles d'un cytomètre en flux
US7299135B2 (en) 2005-11-10 2007-11-20 Idexx Laboratories, Inc. Methods for identifying discrete populations (e.g., clusters) of data within a flow cytometer multi-dimensional data set
EP1785899A2 (fr) * 2005-11-10 2007-05-16 IDEXX Laboratories Inc Procédés d'identification de populations discrètes (par exemple des grappes) de données au sein d'un jeu de données multidimensionnelles d'un cytomètre en flux
EP1840571A3 (fr) * 2006-03-29 2009-09-09 Sysmex Corporation Procédé et appareil pour la mesure d'un échantillon hématologique
US7892841B2 (en) 2006-03-29 2011-02-22 Sysmex Corporation Method and apparatus for measuring hematological sample
WO2007131507A2 (fr) * 2006-05-13 2007-11-22 Dako Denmark A/S Procédés destinés à des analyses de cytométrie de flux de cellules non lysées issues de fluides biologiques
WO2007131507A3 (fr) * 2006-05-13 2008-01-10 Dako Denmark As Procédés destinés à des analyses de cytométrie de flux de cellules non lysées issues de fluides biologiques
US8163471B2 (en) 2006-06-08 2012-04-24 Sysmex Corporation Reagent for sample analysis, kit for sample analysis and method for sample analysis
EP1865318A1 (fr) * 2006-06-08 2007-12-12 Sysmex Corporation Réactif pour analyse d'échantillon, kit d'analyse d'échantillon et procédé d'analyse d'échantillon
US8101414B2 (en) 2006-06-26 2012-01-24 Sysmex Corporation Reagent for sample analysis, reagent kit for sample analysis and method for sample analysis
WO2011154605A1 (fr) * 2010-06-07 2011-12-15 Environics Oy Procédé et dispositif de détection de matériau biologique
CN102933952A (zh) * 2010-06-07 2013-02-13 环境学有限公司 用于检测生物材料的方法及装置
AU2011263615B2 (en) * 2010-06-07 2013-07-25 Environics Oy Method and device for detecting biological material
US8717550B2 (en) 2010-06-07 2014-05-06 Environics Oy Method and device for detecting biological material
EP2577255A4 (fr) * 2010-06-07 2017-12-27 Environics OY Procédé et dispositif de détection de matériau biologique
CN113188981A (zh) * 2021-04-30 2021-07-30 天津深析智能科技发展有限公司 一种多因子细胞因子自动分析方法

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