METHOD FOR DETECTING INFLAMMATION-RELATED PLATELET ACTIVATION

Abstract

The present invention relates to a method for detecting inflammation-related platelet activation, comprising measuring the quantity, concentration and/or the proportion of seven specific biomarkers representative of 47 intra-platelet, soluble and membrane molecules, in a biological sample. Said panel of seven biomarkers is particularly useful for implementing a method of diagnosing inflammation-related platelet activation in an individual, a method for monitoring the efficacy of a curative or preventive treatment of an inflammatory disease in an individual and/or a method for monitoring the development of an inflammatory disease associated with inflammation-related platelet activation in an individual.

The present invention also relates to a kit for detecting inflammation-related platelet activation, as well as the use thereof.

Claims

1. A method for detecting an inflammation-related platelet activation comprising measuring the quantity, concentration and/or the proportion of the biomarkers AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand in a biological sample comprising platelets.

2. A method of diagnosis for inflammation-related platelet activation in an individual, comprising: a) measuring the quantity, concentration and/or the proportion of the biomarkers AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand in a biological sample comprising platelets of said individual, b) comparing the results obtained during the step a) with a corresponding standard control value, and c) deducing from the above if the individual has inflammation-related platelet activation.

3. The method according to claim 2, characterized in that the step c) comprises deducing therefrom whether a specific intra-platelet signaling pathway is activated.

4. A method for monitoring the efficacy of a curative or preventive treatment for inflammatory disease in an individual, comprising: a) measuring the quantity, concentration and/or the proportion of the biomarkers AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand in a biological sample comprising platelets of said individual at a time t during said treatment, b) comparing the results obtained during the step a) with a corresponding standard control value and/or with a corresponding value obtained before the start of said treatment or at a time during the treatment, which is earlier than time t, c) deducing therefrom whether the treatment is effective, and d) optionally, repeating the steps a) to c).

5. A method of monitoring the evolution of inflammatory disease associated with inflammation-related platelet activation in an individual, comprising: a) measuring the quantity, concentration and/or the proportion of the biomarkers AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand in a biological sample comprising platelets of said individual at times t1 and t2, separated in time, b) comparing the results at time t1 and time t2 obtained during the step a), c) deducing therefrom whether the inflammatory disease evolves favorably, and d) optionally, repeating the steps a) to c).

6. A stratification method for an individual with or at risk of suffering from inflammatory disease in a class of individuals with inflammation-related platelet activation or in a class of individuals without any inflammation-related platelet activation, comprising: a) measuring the quantity, concentration and/or the proportion of the biomarkers AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand in a biological sample comprising platelets of said individual, b) comparing the results obtained during the step a) with a corresponding standard control value, and c) deducing therefrom whether the individual belongs to the class of individuals with inflammation-related platelet activation or to the class of individuals without inflammation-related platelet activation.

7. The method according to claim 4, characterized in that said inflammatory disease is selected from the group consisting of atherosclerosis, pulmonary inflammation, rheumatoid arthritis (RA), inflammatory bowel disease (IBD), sepsis, severe sepsis, septic shock, cancer and combinations thereof.

8. The method according to claim 1, characterized in that the biological sample is a platelet-rich plasma sample.

9. A kit suitable for detecting an inflammation-related platelet activation comprising means for detecting at least seven biomarkers, characterized in that said at least seven biomarkers are AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand.

10. A method for the detection of an inflammation-related platelet activation comprising the use of a kit according to claim 9.

11. A method for the detection of an inflammation-related platelet activation comprising the use of a biomarker panel including AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand.

12. The method according to claim 5, characterized in that said inflammatory disease is selected from the group consisting of atherosclerosis, pulmonary inflammation, rheumatoid arthritis (RA), inflammatory bowel disease (IBD), sepsis, severe sepsis, septic shock, cancer and combinations thereof.

13. The method according to claim 6, characterized in that said inflammatory disease is selected from the group consisting of atherosclerosis, pulmonary inflammation, rheumatoid arthritis (RA), inflammatory bowel disease (IBD), sepsis, severe sepsis, septic shock, cancer and combinations thereof.

14. The method according to claim 2, characterized in that the biological sample is a platelet-rich plasma sample.

15. The method according to claim 3, characterized in that the biological sample is a platelet-rich plasma sample.

16. The method according to claim 4, characterized in that the biological sample is a platelet-rich plasma sample.

17. The method according to claim 5, characterized in that the biological sample is a platelet-rich plasma sample.

18. The method according to claim 6, characterized in that the biological sample is a platelet-rich plasma sample.

19. The method according to claim 7, characterized in that the biological sample is a platelet-rich plasma sample.

Description

FIGURES

[0287] FIGS. 1 to 8 show the variables in the order of decreasing magnitude (as estimated by a criterion of mean decrease of precision) in every model, with the variable on the ordinate and the magnitude on the abscissa.

[0288] FIG. 1 shows the variables in order of decreasing magnitude in the overall class.

[0289] FIG. 2 shows the variables in order of decreasing magnitude in the overall class corresponding to the absence of stimulation.

[0290] FIG. 3 shows the variables in decreasing order of magnitude in the class corresponding to ADP stimulation.

[0291] FIG. 4 presents the variables in order of decreasing magnitude in the class corresponding to collagen stimulation.

[0292] FIG. 5 presents the variables in decreasing order of magnitude in the class corresponding to fibrinogen stimulation.

[0293] FIG. 6 shows the variables in decreasing order of magnitude in the class corresponding to PAR-1 agonist stimulation.

[0294] FIG. 7 shows the variables in decreasing order of magnitude in the class corresponding to PAR-4 agonist stimulation.

[0295] FIG. 8 presents the variables in order of decreasing magnitude in the class corresponding to soluble CD40 stimulation.

EXAMPLES

[0296] Equipment and Method

[0297] (i) Platelet-Rich Plasma

[0298] Peripheral blood samples from healthy individuals (n=10) were collected and placed in endotoxin-free tubes containing 3.2% sodium citrate (Vacutainer®, Becton Dickinson, San Jose, Calif.). Informed consent of blood donors was obtained prior to blood collection in a regional blood establishment, in accordance with French legislation. The blood samples were centrifuged at 192 g for 10 minutes at room temperature so as to obtain a platelet-rich plasma.

[0299] (ii) Stimulation of Platelets

[0300] The platelet response tests were carried out using a PAR-1 agonist (TRAP for Thrombin Receptor Activating Peptide SEQ ID NO: 1 SFLLRN, 6 μM) (Sigma-Aldrich, Saint Quentin-Fallavier, France), a PAR-4 agonist (AYPGKF, 200 μM) (Sigma-Aldrich, Saint Quentin-Fallavier, France), ADP (10 μM), collagen (50 μg/ml), sCD40L (50 ng/ml) or fibrinogen (50 μg/ml).

[0301] To this end, platelets from 10 donors were subject to each of the seven conditions (non-stimulated, PAR-1 agonist, PAR-4 agonist, ADP, collagen or sCD40L) and the response of 47 biological parameters was measured, namely: [0302] the activation of membrane biomarkers: CD62P-%, CD62P-MFI, CD63-%, CD63-MFI, [0303] the activation of soluble biomarkers: BCA-1, 6Ckine, TSLP, IL-33, GRO alpha, IFNgamma, MDC, CD40 ligand, CXCL9/MIG, CCL19/MIP-3b, CCL20/MIP-3a, serotonin, RANTES, soluble CD62, and [0304] the activation of intracellular biomarkers: IKBa, IKKa, NFKB1, PKC, AKT, SYK(pY629/30), Axl(pY859), Lyn Total, Lyn Y937, PI3K110, SYK Py323, SYK total, ERK1/2 pY204/187, Gab1pY285/307/317, Gab2 pY614, PLCg1 pY1253, PLCg2 pY1197/1217, SHC pY349/350, STAT3 pY705, CBL pY700/731/774, WASH pY291, TEC pY206, RAP GEF1 GRF2 pY504, JAK3 pY785, Gab2 pY584, Gab2pY266, PTEN total, and Axl(pY772).

[0305] (iii) Quantification of Membrane Biomarkers

[0306] Platelet suspensions were incubated with a suitable monoclonal antibody, recognizing membrane proteins expressed on the surface of platelets, for 30 minutes at room temperature in the dark and then washed once with a phosphate saline buffer (X1).

[0307] Since all platelets constitutively express CD41a, said marker (recognized by a specific antibody conjugated to a fluorochrome—such e.g. as fluorescein isothiocyanate) was used for defining the window corresponding to platelets in flow cytometry analyzes.

[0308] Activated platelets are characterized by the expression of CD62P and CD63, among other markers. Monoclonal (or polyclonal) antibodies conjugated to a fluorochrome—such as e.g. allophycocyanin or phycoerythrin—directed against human CD62P and CD63 were then used for defining the windows of the cell population to be characterized as a function of the activation thereof.

[0309] The flow cytometry analyzes were performed using a FACSVantage SE apparatus equipped with CellQuestS-Pro software (BD Biosciences, Le Pont de Claix, France).

[0310] The results were given in MFI (Mean Fluorescence Intensity) or in percentage (%). The CD62P and CD63 immunolabeling makes it possible to specify the percentage of activated cells among the cells comprised in the window of analysis.

[0311] (iv) Quantification of Soluble Biomarkers

[0312] For every condition, the protein content of the a granules of the platelet supernatants was quantified using the Luminex® technology comprising magnetic beads specific for various human cytokines and chemokines (reference test HCYTOMAG-60K, HCYP2MAG-62K and HTek MAG-63K, Millipore, Molsheim, France). A molecule of canonical δ granule, namely serotonin, was quantified by ELISA (Enzyme-Linked Immunosorbent Assay) (IBL International, Hamburg, Germany). The absorbance at 450 nm (or 405 nm for serotonin) was measured using an ELISA plate reader (Magellan Software, Sunrise™, Tecan Group Ltd., Lyon, France). The results were normalized to pg/109 platelets/ml.

[0313] (v) Quantifications of Intracellular Biomarkers

[0314] For every condition, intracellular platelet proteins were extracted using the MILLIPLEX MAP EpiQuant sample preparation kit at a rate of 3×10.sup.7 platelets/ml lysis buffer, as per the manufacturer's instructions. Phosphorylated proteins were quantified using the MILLIPLEX MAP EpiQuant technology with the following five panels: MPEQMAG-100K, 102K, 103K, 104K and 110K (MILLIPORE). The results were expressed in pM per 3×10.sup.7 platelets/ml.

[0315] Results

[0316] (i) Identification of a Panel of Biomarkers for Detecting an Inflammation-Related Platelet Activation

[0317] FIGS. 1 to 8 show the variables in order of decreasing magnitude (as estimated by a criterion of decrease of the mean precision) for the overall multi-class model (cf. FIG. 1) and for each individual class (cf. FIGS. 2 to 8).

[0318] Repeated cross-validations were performed for each of the 1023 sets of variables, based on the 10 most significant variables identified in FIG. 1. The results are shown in the Table 1 below.

TABLE-US-00001 TABLE 1 The best biomarker panels in terms of overall precision N P AKT sCD40L CD62P-MFI CD62P-% CD63-MFI CD63-% GROα PKC RANTES TSLP 8 87.9 x x x x x x x x 8 87.6 x x x x x x x x 7 86.8 x x x x x x x 8 86.5 x x x x x x x x 7 86.4 x x x x x x x 7 86.4 x x x x x x x 8 86.4 x x x x x x x x 8 86.3 x x x x x x x x 8 86.3 x x x x x x x x 7 86.3 x x x x x x x N: Number of variables in the biomarker subset P: precision in %

[0319] From the results presented in Table 1, a panel of biomarkers was defined comprising AKT, PKC, CD62P, CD63, RANTES, TSLP and CD40 ligand which allow the presence of an inflammation-related platelet activation to be determined with very high precision.

[0320] (ii) Identification of Specific Biomarkers for Activation of an Intra-Platelet Signaling Pathway

[0321] The biomathematical analysis has also identified specific biomarkers for the activation of an intra-platelet signaling pathway, such as: [0322] NFKB1 and SHC pY349/350, associated with a stimulation by the PAR-1 agonist; [0323] SYK (pY629/30), associated with a stimulation by the PAR-4 agonist; [0324] BCA-1, CD63-%, Gab2 pY614, IFNγ and MDC, associated with a stimulation by the PAR-1 agonist and the PAR-4 agonist; [0325] PKC, associated with a stimulation by the PAR-4 agonist and ADP; [0326] CD63-MFI, associated with a stimulation by the PAR-1 agonist, the PAR-4 agonist and collagen; [0327] soluble CD62 and CD62P-MFI, associated with a stimulation by the PAR-1 agonist, the PAR-4 agonist, collagen and ADP; [0328] CD62P-%, GROα and RANTES, associated with a stimulation by the PAR-1 agonist, the PAR-4 agonist, collagen, ADP and sCD40L; [0329] TSLP, associated with a stimulation by fibrinogen, the PAR-4 agonist, collagen, sCD40L, [0330] AKT, associated with a stimulation by sCD40L, the PAR-1 agonist, the PAR-4 agonist, fibrinogen, collagen and ADP, and [0331] CDL40, associated with a stimulation by the PAR-1 agonist, the PAR-4 agonist, fibrinogen, collagen and ADP. [0332] (cf. table 2 below).

TABLE-US-00002 TABLE 2 Biomarkers for which a specific activation was achieved by at least one activator fibrin- col- sCD40L PAR-1 PAR-4 ogen lagen ADP AKT *** *** *** *** *** *** BCA-1 *** ** CD40L *** *** *** *** *** Soluble CD62 *** *** *** * CD62P-% ** *** *** *** *** CD62P-MFI *** *** *** *** CD63-% *** *** CD63-MFI *** *** *** Gab2 pY614 * * GROα ** *** *** *** *** INFγ *** *** MDC *** *** NKFB1 * PKC *** * RANTES * *** *** *** *** Shc pY349/350 * SYK(pY629/30) ** TSLP ** *** *** ***