FIELD OF THE INVENTION:

The present invention relates to methods and kits for diagnosis and prognostic of sepsis. More specifically present invention relates to methods for diagnosis of sepsis through detection of a specific population of neutrophils.

BACKGROUND OF THE INVENTION:

Sepsis is defined as a widespread inflammation secondary to an infection (Cohen J. Nature 2002; Levy MM et al. Crit Care Med 2003). Sepsis strikes an estimated 30 million people worldwide, it’s the 10th cause of death in developed countries and its incidence rises every years (Angus DC et al. Crit Care Med 2001.). With an incidence of 377 cases per 100000 per year in the US, sepsis outnumbers the three major cancers (lung+breast+prostate=332/ 100000/year) or myocardial infarction (210/ 100000/year) (Hall MJ et al NCHS Data Brief 2011.). The total cost of sepsis is over 20 billion dollars per year in the US and was estimated to exceed 3 billion euros in France. With the late consequences of sepsis, this estimation is probably well below the real financial impact for our societies. Sepsis may evolve to severe sepsis and in its most severe form, septic shock, mortality can be up to 50% (Angus DC et al. Crit Care Med 2001). Despite adequate treatments, patients who suffered from sepsis have a poor outcome with an in-hospital mortality rate of 30 % and a one-year mortality rate up to 50-60% associated with a major loss of their quality of life, with physical and psychological disabilities (Iwashyna TJ et al. JAMA 2010;).

Sepsis is a dual disease. While inflammation is predominant in the early phase of the disease, patients present immunoparalysis features in the latter phase. A third of patients die few days after the initiation of the primary infection or from secondary infections within the first year after recovery. The cellular mechanisms underlying these phases and their different outcomes remain poorly understood and the exact process of the transition from the activation of inflammation to its hypo responsiveness is uncertain (Hotchkiss RS et al. Lancet Infect Dis 2013). Moreover, diagnosis of patients relies on scores based on clinical data (IGS2) rather than molecular or cellular variations specific to sepsis. The objective of this invention is to identify new cellular biomarkers of sepsis and help to improve individual patients’ diagnosis and follow-up. Accordingly, there remains an unmet need in the art for specific and more rapid diagnostic test for sepsis, reflecting directly the inactivation of immune process of neutrophils.

The inventors therefore set up a diagnostic method and monitoring of sepsis that allows to directly reflect the immunological status of the patient.

SUMMARY OF THE INVENTION:

Inventors work represents the first comprehensive evaluation of whole blood circulating immune cells in septic patients. During a non-interventional clinical study using mass cytometry (CyTOF), inventors defined a minimal markers set that identify two neutrophil subset specific of infectious inflammation highly enriched in sepsis patients but neither in other systemic inflammation from other aetiologies such as non-infected post car diothoracic surgery patients (NIC), nor in Healthy subject. This minimal marker set may be used as diagnose tool in combination with clinical scores. These results thus set-up the basis for the development of a rapid functional specific diagnostic test for sepsis.

Thus, the present invention relates to an in vitro method for diagnosing Sepsis disease in a subject, comprising the steps of i) determining in a sample obtained from the subject the level of neutrophil cells having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers, ii) comparing the level determined in step i) with a reference value and iii) concluding that the subject suffers from a sepsis when the level of neutrophil having cell surface expression of CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers determined at step i) is higher than the reference value.

An additional object of the invention relates to an in vitro method for monitoring a sepsis disease comprising the steps of i) determining the level of a population of neutrophils having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers in a sample obtained from the subject at a first specific time of the disease, ii) determining the level of a population of neutrophils having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10- CD64+PDL1+ markers in a sample obtained from the subject at a second specific time of the disease, iii) comparing the level determined at step i) with the level determined at step ii) and iv) concluding that the disease has evolved in worse manner when the level determined at step ii) is higher than the level determined at step i). An additional object of the invention relates to an in vitro method for monitoring the treatment of a sepsis disease comprising the steps of i) determining the level of a population of neutrophils having cell surface expression of CD66+CD10-CD16-CD64+CD123+ and/or CD66+CD10-CD64+PDL1+ in a sample obtained from the subject before the treatment, ii) determining the level of a population of neutrophils having cell surface expression of CD66b+CD 10-CD 16-CD64+CD 123+ markers and/or CD66b+CD10-CD64+PDLl+ markers in a sample obtained from the subject after the treatment”, iii) comparing the level determined at step i) with the level determined at step ii) and iv) concluding that the treatment is efficient when the level determined at step ii) is lower than the level determined at step i).

Another object of the invention relates to an in vitro method for monitoring the immunological status of patient with sepsis disease comprising the steps of i) determining the level of neutrophil cells having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers in a sample obtained from the subject, ii) comparing the level determined at step i) with the with a reference value and iv) concluding that:

- when the level of neutrophil having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers determined at step i) is higher than the reference value, then said patient is at risk of having an unresponsive profile; or

- when the level of neutrophil having cell surface expression of CD 10-CD 16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers determined at step i) is lower or equal than the reference value, then said patient is at risk of having a responsive profile.

DETAILED DESCRIPTION OF THE INVENTION:

Diagnostic methods according to the invention

The present invention relates to an in vitro method for diagnosing Sepsis disease in a subject, comprising the steps of i) determining in a sample obtained from the subject the level of neutrophil cells having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers, ii) comparing the level determined in step i) with a reference value and iii) concluding that the subject suffers from a sepsis when the level of neutrophil having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers determined at step i) is higher than the reference value.

The term“subject” as used herein refers to a mammalian, such as a rodent (e.g. a mouse or a rat), a feline, a canine or a primate. In a preferred embodiment, said subject is a human subject.

The subject according to the invention can be a healthy subject or a subject suffering from a given disease such as sepsis.

As used herein the term "Sepsis" means morbid condition induced by a toxin, the introduction or accumulation of which is caused by infection or trauma, and includes the early stage of sepsis, severe sepsis and the acute phase of septic shock.

The term“early stage sepsis” refers to the stage of the disease with the onset of clinical symptoms of severe infectious disease that typically include chills, profuse sweat, irregularly remittent fever, prostration and the like.

The term“severe sepsis” refers to the stage of the disease with the clinical symptoms of early stage sepsis in addition to persistent fever, lymphopenia, disseminated intravascular coagulation, respiratory distress syndrome, multiple organ failure and hypotension leading to shock.

The term“acute phase of septic shock” refers to peripheral circulatory collapse, resulting in hemodynamic, metabolic and visceral disorders that almost invariably lead to death.

As used herein the term "infectious disease" means disorders caused by organisms such as bacteria, viruses, fungi or parasites.

The complexity of sepsis comes from its Janus double faces (Hotchkiss RS et al. Nat Med 2009). In the early phase of sepsis, inflammation is predominant and leads to shock, organ dysfunctions and death. After few days, patients present signs of immunodysfunctions. The“immunosuppressed” patients are particularly susceptible to nosocomial infections and especially healthcare-associated infections. Several patients will also develop organ dysfunction, infections or even cancer or acute cardiovascular events after their intensive care unit stay. Several immunomodulatory approaches have been tested with no clinical success, as the process is complex and multifactorial (Abraham E et al. JAMA 1995; Annane D et al. JAMA 2010; Sprung CL et al. N Engl J Med 2008; Stephens DP et al. Crit Care Med 2008; Tidswell M et al. Crit Care Med 2010). Antibiotics administration and intravenous fluids are the current symptomatic treatment for sepsis patients admitted in a medical unit. Early recognition and focused management may improve the outcomes in sepsis. Current professional recommendations include a number of actions to be followed as soon as possible after the diagnosis

As used herein, the term“sample“ or "biological sample" as used herein refers to any biological sample of a subject and can include, by way of example and not limitation, bodily fluids and/or tissue extracts such as homogenates or solubilized tissue obtained from a subject. Tissue extracts are obtained routinely from tissue biopsy. In a particular embodiment regarding the diagnostic method according to the invention, the biological sample is a body fluid sample (such blood or immune primary cell) or tissue biopsy of said subject.

In preferred embodiments, the fluid sample is a blood sample. The term“blood sample” means a whole blood sample obtained from a subject (e.g. an individual for which it is interesting to determine whether a population of neutrophils cells can be identified).

The term“immune primary cell” has its general meaning in the art and is intended to describe a population of white blood cells directly obtained from a subject.

In the context of the present invention immune primary cell is selected from the group consisting of PBMC, WBC, neutrophil.

The term “PBMC” or “peripheral blood mononuclear cells” or “unfractionated PBMC”, as used herein, refers to whole PBMC, i.e. to a population of white blood cells having a round nucleus, which has not been enriched for a given sub-population (which contain neutrophils, T cells, B cells, natural killer (NK) cells, NK T cells and DC precursors). A PBMC sample according to the invention therefore contains lymphocytes (B cells, T cells, NK cells, NKT cells) and neutrophils. Typically, these cells can be extracted from whole blood using Ficoll, a hydrophilic polysaccharide that separates layers of blood, with the PBMC forming a cell ring under a layer of plasma. Additionally, PBMC can be extracted from whole blood using a hypotonic lysis buffer, which will preferentially lyse red blood cells. Such procedures are known to the expert in the art.

The term“WBC” or“White Blood Cells”, as used herein, also refers to leukocytes population, are the cells of the immune system. All white blood cells are produced and derived from multipotent cells in the bone marrow known as hematopoietic stem cells. Leukocytes are found throughout the body, including the blood and lymphatic system. Typically, WBC or some cells among WBC can be extracted from whole blood by using i) immunomagnetic separation procedures, ii) percoll or ficoll density gradient centrifugation, iii) cell sorting using flow cytometer (FACS). Additionally, WBC can be extracted from whole blood using a hypotonic lysis buffer, which will preferentially lyse red blood cells. Such procedures are known to the expert in the art.

In some embodiments, the fluid sample is a sample of purified neutrophil in suspension. Typically, the sample of neutrophil is prepared by immunomagnetic separation methods preformed on a PBMC or WBC sample. For example, neutrophils cells are isolated by using antibodies for neutrophils -associated cell surface markers, such as CD66b (or CD66+/CRTH2-),. Commercial kits, e.g. Direct Human Neutrophil Isolation Kit kits (Immunomagnetic negative selection from whole blood kit) using CD66b labelled antibodies (#19666 from Stem cells technologies) are available.

The term“diagnosis” means the identification of the condition or the assessment of the severity of the disease.

In the context of the present invention the“diagnosis” is associated with level of neutrophils having cell surface expression of CD66b+CDI0-CDI6-CD64+CDI23+markers and/or the level of neutrophils having cell surface expression of CD66b+CDI0- CD64+PDLI+ markers which in turn may be a risk for developing a sepsis.

As used herein, the term "CDIO", also known as cluster of differentiation 10 (or Neprilysin, membrane metallo-endopeptidase (MME), neutral endopeptidase (NEP), and common acute lymphoblastic leukemia antigen (CALLA)) has its general meaning in the art refers to an enzyme that in humans is encoded by the MME gene (gene ID 4311).

CD66b (Cluster of Differentiation 66b) also known as Carcinoembryonic antigen- related cell adhesion molecule 8 (CEACAM8) refers to a member of the carcinoembryonic antigen (CEA) gene family (CD66b / human gene (gene ID 1088)). Its main function is cell adhesion, cell migration, and pathogen binding. CD66b is expressed exclusively on neutrophils (granulocytes) and used as neutrophils marker (Eades-Perner AM et al. (1998) Blood. ;91(2):663-72).

CDIO refers to a cell-surface marker in the diagnosis of human acute lymphocytic leukemia (ALL). CDIO is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. Hematopoetic progenitors expressing CDIO are considered "common lymphoid progenitors", which means they can differentiate into T, B or natural killer cells.

In the context of the method of the invention“CD10-“ means that the cell surface marker is not expressed on neutrophil.

As used herein, the term "CD 16" also known as FcyRIII, has its general meaning in the art and refers to a cluster of differentiation molecule found on the surface of natural killer cells, neutrophils, monocytes, and macrophages CD16 has been identified as Fc receptors FcyRIIIa (CD 16a / human gene (gene ID 2214)) and FcyRIIIb (CD 16b / human gene (gene ID 2214)), which participate in signal transduction. The most well-researched membrane receptor implicated in triggering lysis by NK cells, CD 16 is a molecule of the immunoglobulin superfamily (IgSF) involved in antibody-dependent cellular cytotoxicity (ADCC). It can be used to isolate populations of specific immune cells through fluorescent-activated cell sorting (FACS) or magnetic-activated cell sorting, using antibodies directed towards CD 16.

In the context of the method of the invention“CD16-“ means that the cell surface marker is not expressed on neutrophil.

As used herein, the term "CD64" also knows as Cluster of Differentiation 64 or Fc- gamma receptor 1 (FcyRI) refers to a membrane glycoprotein known as an Fc receptor that binds monomeric IgG-type antibodies with high affinity (Hulett M, et al (1998). Mol Immunol. 35 (14-15): 989-96). After binding IgG, CD64 interacts with an accessory chain known as the common g chain (g chain), which possesses an IT AM motif that is necessary for triggering cellular activation (Nimmeijahn F, et al (2006). Immunity. 24 (1): 19-28). Structurally CD64 is composed of a signal peptide that allows its transport to the surface of a cell, three extracellular immunoglobulin domains of the C2-type that it uses to bind antibody, a hydrophobic transmembrane domain, and a short cytoplasmic tail (Ernst L, et al (1998). Mol Immunol. 35 (14-15): 943-54). CD64 is constitutively found on only macrophages and neutrophils, but treatment of polymorphonuclear leukocytes with cytokines like IFNy and G- CSF can induce CD64 expression on these cells. There are three distinct (but highly similar) genes in humans for CD64 called FcyRIA (CD64A / human gene (gene ID 2209)), FcyRIB (CD64B/ human gene (gene ID 2210)), and FcyRIC (CD64C / human gene (gene ID 2211)) that are located on chromosome 1 (Ernst L, et al (1992). J Biol Chem. 267 (22): 15692-700). These three genes produce six different mRNA transcripts; two from CD64A, three from CD64B, and one from CD64C; by alternate splicing of the genes (Ernst L, et al (1998). Mol Immunol. 35 (14-15): 943-54).

As used herein, the term "CD 123" also knows as Cluster of Differentiation 64 or alpha-chain of the interleukin-3 receptor (IL-3RA) refers to receptor found on cells which helps transmit the signal of interleukin-3, a soluble cytokine important in the immune system. The human gene coding for the receptor is located in the pseudoautosomal region of the X and Y chromosomes (human gene (gene ID 3553). The receptor belongs to the type I cytokine receptor family and is a heterodimer with a unique alpha chain paired with the common beta (beta c or CD131) subunit. CD123 found on pluripotent progenitor cells, induces tyrosine phosphorylation within the cell and promotes proliferation and differentiation within the hematopoietic cell lines. It can be found on basophils and pDCs as well as some cDCs among peripheral blood mononuclear cells. CD123 is expressed across acute myeloid leukemia (AML) subtypes, including leukemic stem cells. An experimental antibody-drug conjugate SGN-CD123A targets CD123 as a possible treatment for AML (www.businesswire. com/news/home/20160919005140/en/Seattle-Genetics-Initiates-P hase- 1 - Trial-SGN-CD123A /Sept 2016)

As use herein, the term“PD-L1” also known as“Programmed death-ligand 1” or cluster of differentiation 274 (CD274) or B7 homolog 1 (B7-H1) is a protein that in humans is encoded by the CD274 gene (human gene : Gene ID: 29126).

PD-L1 is a 40kDa type 1 transmembrane protein that has been speculated to play a major role in suppressing the adaptive arm of immune system during particular events such as pregnancy, tissue allografts, autoimmune disease and other disease states such as hepatitis. Normally the adaptive immune system reacts to antigens that are associated with immune system activation by exogenous or endogenous danger signals. In turn, clonal expansion of antigen-specific CD8+ T cells and/or CD4+ helper cells is propagated. The binding of PD-L1 to the inhibitory checkpoint molecule PD-1 transmits an inhibitory signal based on interaction with phosphatases (SHP-1 or SHP-2) via Immunoreceptor Tyrosine-Based Switch Motif (ITSM) motif. This reduces the proliferation of antigen-specific T-cells in lymph nodes, while simultaneously reducing apoptosis in regulatory T cells (anti-inflammatory, suppressive T cells) - further mediated by a lower regulation of the gene Bcl-2.

Standard methods for detecting the expression of a specific surface marker such as CD64 or CD123 at cell surface (e.g. neutrophil surface) are well known in the art. Typically, the step consisting of detecting the surface expression of a surface marker (e;g. CD64 or CD123) or detecting the absence of the surface expression of a surface marker ((e;g. CD10 or CD 16) may consist in using at least one differential binding partner directed against the surface marker, wherein said cells are bound by said binding partners to said surface marker.

As used herein, the term“binding partner directed against the surface marker” refers to any molecule (natural or not) that is able to bind the surface marker with high affinity. The binding partners may be antibodies that may be polyclonal or monoclonal, preferably monoclonal antibodies. In another embodiment, the binding partners may be a set of aptamers.

Polyclonal antibodies of the invention or a fragment thereof can be raised according to known methods by administering the appropriate antigen or epitope to a host animal selected, e.g., from pigs, cows, horses, rabbits, goats, sheep, and mice, among others. Various adjuvants known in the art can be used to enhance antibody production. Although antibodies useful in practicing the invention can be polyclonal, monoclonal antibodies are preferred.

Monoclonal antibodies of the invention or a fragment thereof can be prepared and isolated using any technique that provides for the production of antibody molecules by continuous cell lines in culture. Techniques for production and isolation include but are not limited to the hybridoma technique originally; the human B-cell hybridoma technique; and the EBV-hybridoma technique.

For example, the binding partner of CD64 of the invention is the anti-human CD64 antibody available from Biolegend (CD64 (Fc gamma Receptor 1) Monoclonal Antibody (10.1), # 305029)

For example, the binding partner of CD123 of the invention is the anti-human CD123 antibody available from Biolegend (CD 123 Monoclonal Antibody (6H6), 306006) or from Fluidigm (Anti-IL3RA/CD123 antibody (6H6) (#3151001).

For example, the binding partner of CD66b of the invention is the anti-human CD66b antibody available from Biolegend (CD66b Monoclonal Antibody (G10F5), # 355005) or from Fluidigm (Anti-Human CD66b (80H3) (#3162023).

For example, the binding partner of CD274 (PD-L1) of the invention is the anti-human (CD274 antibody available from Biolegend (APC anti-human CD274 (B7-H1, PD-L1) Antibody (29E.2A3), 306006) or from Fluidigm (Anti-Human CD274/PD-Ll-148Nd antibody (29E.2A3) ).

The binding partners of the invention such as antibodies or aptamers may be labelled with a detectable molecule or substance, such as preferentially a fluorescent molecule, or a radioactive molecule or any others labels known in the art. Labels are known in the art that generally provide (either directly or indirectly) a signal.

As used herein, the term "labelled", with regard to the antibody or aptamer, is intended to encompass direct labelling of the antibody or aptamer by coupling (i.e., physically linking) a detectable substance, such as a fluorophore [e.g. fluorescein isothiocyanate (FITC) or phycoerythrin (PE) or Indocyanine (Cy5)]) or radioactive molecule or a non-radioactive heavy metals isotopes to the antibody or aptamer, as well as indirect labelling of the probe or antibody by reactivity with a detectable substance. An antibody or aptamer of the invention may be labelled with a radioactive molecule by any method known in the art. More particularly, the antibodies are already conjugated to a fluorophore (e.g. FITC-conjugated and/or PE-conjugated). The aforementioned assays may involve the binding of the binding partners (ie. antibodies or aptamers) to a solid support. The solid surface could a microtitration plate coated with the binding partner for the surface marker. Alternatively, the solid surfaces may be beads, such as activated beads, magnetically responsive beads. Beads may be made of different materials, including but not limited to glass, plastic, polystyrene, and acrylic. In addition, the beads are preferably fluorescently labelled. In a preferred embodiment, fluorescent beads are those contained in TruCount(TM) tubes, available from Becton Dickinson Biosciences, (San Jose, California). According to the invention, methods of flow cytometry are preferred methods for detecting (presence or absence of) the surface expression of the surface markers (i.e. CD66b, CD10, CD16, CD64, CD123 and PD-L1). Said methods are well known in the art. For example, fluorescence activated cell sorting (FACS) may be therefore used. Cell sorting protocols using fluorescent labeled antibodies directed against the surface marker (or immunobeads coated with antibody) in combination with antibodies directed against CD66b, CD10, CD16, CD64, CD123 and PD-L1 coupled with distinct fluorochromes (or immunobeads coated with anti-CD66b, anti CD 10 antibodies, anti CD 16 antibodies, anti CD64 antibodies, anti CD 123 antibodies and anti PD-Lls antibodies) can allow direct sorting, using cell sorters with the adequate optic configuration.

Such methods comprise contacting a biological sample obtained from the subject to be tested under conditions allowing detection (presence or absence) of CD66b, CD 10, CD 16, CD64 and CD123 and/or CD66b, CD10, CD16, and PD-L1 surface markers. Once the sample from the subject is prepared, the level of sepsis biomarkers (“Biomarkerl23”: CD66b+CD10- CD 16-CD64+CD 123+ cells and/or“Biomarker274”: CD66b+CD10-CD16-PD-Ll+ cells) may be measured by any known method in the art.

Typically, the high or low level of sepsis-specific neutrophil cell surface biomarkers (“Biomarkerl23”: CD66b+CD10-CD16-CD64+CD123+ cells and/or “Biomarker274”: CD66b+CD10-CD16-PD-Ll+ cells) is intended by comparison to a control reference value.

Said reference control values may be determined in regard to the level of biomarker present in blood samples taken from one or more healthy subject(s) or to the cell surface biomarker in a control population.

In one embodiment, the method according to the present invention comprises the step of comparing said level of sepsis-specific neutrophil biomarkers (“Biomarkerl23”: CD66b+CD 10-CD 16-CD64+CD 123+ cells and/or“Biomarker274”: CD66b+CD10-CD16- PD-L1+ cells) to a control reference value wherein a high level of sepsis-specific neutrophil biomarkers (“Biomarkerl23”: CD66b+CD10-CD16-CD64+CD123+ cells and/or “Biomarker274”: CD66b+CD10-CD16-PD-Ll+cells) compared to said control reference value is predictive of a high risk of having a sepsis and a low level of sepsis-specific neutrophil biomarkers (“Biomarkerl23”: CD66b+CD10-CD16-CD64+CD123+ cells and/or “Biomarker274”: CD66b+CD10-CD16-PD-Ll+ cells) compared to said control reference value is predictive of a low risk of having a sepsis.

In one embodiment, for sepsis-specific neutrophil biomarker “Biomarker274” (CD66b+CD10-CD16-PD-Ll+ cells) the control reference is null (not detected), which means when the Biomarker274 is detected, subject have a high risk of having a sepsis

The control reference value may depend on various parameters such as the method used to measure the level sepsis-specific neutrophil biomarker Biomarker274 (CD66b+CD10- CD16-PD-L1+ cells) or the gender of the subject.

Typically regarding the reference value using“Biomarkerl23” (CD66b+CD10-CD16- CD64+CD123+ cells), as indicated in the Example section (figure 4), for a level of neutrophil CD66b+CD10-CD16-CD64+CD123+ using CyTOF multidimensional approach and unsupervised analysis with Cytobank tools (SPADE, viSNE) and R based packages (SPADEVizR, MEM), a level of neutrophil CD66b+CD10-CD16-CD64+CD123+ superior to 0.4% is predictive of having or a high risk of having a sepsis and a level of neutrophil CD66b+CD10-CD16-CD64+CD123+ lower than 0.4% is predictive of not having or at a low risk of having a sepsis.

Typically regarding the reference value using“Biomarker274” (CD66b+CD10-CD16- PD-L1+ cells), as indicated in the Example section (figure 4), for a level of neutrophil CD66b+CD10-CD64+PDLl+ using CyTOF multidimensional approach and unsupervised analysis with Cytobank tools (SPADE, viSNE) and R based packages (SPADEVizR, MEM), a level of neutrophil CD66b+CD10-CD64+PDLl+superior to 0.2%, is predictive of having or a high risk of having a sepsis and a level of neutrophil CD66b+CD10-CD16-CD64+CD123+ lower than 0.2% is predictive of not having or at a low risk of having a sepsis.

Control reference values are easily determinable by the one skilled in the art, by using the same techniques as for determining the level of cell surface biomarker or cell death in blood samples previously collected from the patient under testing.

A“reference value” can be a“threshold value” or a“cut-off value”. Typically, a "threshold value" or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by a person of ordinary skilled in the art. The threshold value has to be determined in order to obtain the optimal sensitivity and specificity according to the function of the test and the benefit/risk balance (clinical consequences of false positive and false negative). Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. Preferably, the person skilled in the art may compare the level of neutrophil biomarkers (“Biomarkerl23”: CD66b+CD10-CD16- CD64+CD123+ cells and/or“Biomarker274”: CD66b+CD10-CD16-PD-Ll+cells) with a defined threshold value. In one embodiment of the present invention, the threshold value is derived from the neutrophil level (or ratio, or score) determined in a blood sample derived from one or more subjects who are responders (to the method according to the invention). In one embodiment of the present invention, the threshold value may also be derived from neutrophil level (or ratio, or score) determined in a blood sample derived from one or more subjects or who are non-responders. Furthermore, retrospective measurement of the activated neutrophil level (or ratio, or scores) in properly banked historical subject samples may be used in establishing these threshold values.

In particular embodiment, when using CD123 neutrophil subset proportion or combining both CD123 and PD-L1 neutrophil subsets proportions, inventors shows that the reference value is 0.35 or 0.40 respectively (see example 2, figure 11).

Reference values are easily determinable by the one skilled in the art, by using the same techniques as for determining the level of activated neutrophils in fluids samples previously collected from the patient under testing.

"Risk" in the context of the present invention, relates to the probability that an event will occur over a specific time period, as in the conversion to sepsis, and can mean a subject's "absolute" risk or "relative" risk. Absolute risk can be measured with reference to either actual observation post-measurement for the relevant time cohort, or with reference to index values developed from statistically valid historical cohorts that have been followed for the relevant time period. Relative risk refers to the ratio of absolute risks of a subject compared either to the absolute risks of low risk cohorts or an average population risk, which can vary by how clinical risk factors are assessed. Odds ratios, the proportion of positive events to negative events for a given test result, are also commonly used (odds are according to the formula p/(l- p) where p is the probability of event and (1- p) is the probability of no event) to no conversion. Alternative continuous measures, which may be assessed in the context of the present invention, include time to sepsis conversion risk reduction ratios.

"Risk evaluation," or "evaluation of risk" in the context of the present invention encompasses making a prediction of the probability, odds, or likelihood that an event or disease state may occur, the rate of occurrence of the event or conversion from one disease state to another, i.e., from a normal condition to a sepsis condition or to one at risk of developing a sepsis. Risk evaluation can also comprise prediction of future clinical parameters, traditional laboratory risk factor values, or other indices of sepsis, such as cellular population determination in peripheral tissues, in serum or other fluid, either in absolute or relative terms in reference to a previously measured population. The methods of the present invention may be used to make continuous or categorical measurements of the risk of conversion to sepsis, thus diagnosing and defining the risk spectrum of a category of subjects defined as being at risk for a sepsis. In the categorical scenario, the invention can be used to discriminate between normal and other subject cohorts at higher risk for sepsis. In other embodiments, the present invention may be used so as to help to discriminate those having SEPSIS from normal.

Accordingly, the method of detection of the invention is consequently useful for the in vitro diagnosis of sepsis from a biological sample. In particular, the method of detection of the invention is consequently useful for the in vitro diagnosis of early stage sepsis from a biological sample.

Prognostic methods and Management

After the identification of neutrophil subsets that harbour an immature phenotype (“Biomarkerl23”: CD66b+CD10-CD16-CD64+CD123+ cells, “Biomarker274”:

CD66b+CD10-CD16-PD-Ll+cells), confirmed by doing a staining of bone marrow cells, inventors determined the functional characterisation of “immature neutrophils”, and they highlighted the impaired ability of this immature neutrophils from sepsis patients to be activated by microbial particles and exhibit a deficient phagocytosis.

As used herein, the term“Immature neutrophils” refers to cells phenotypically and functionally immature. Immature neutrophils were described as cells expressing CD66b and CD64 and lacking the expression of CD10 and CD16 (Taylor OY Br. J. Haematol. 2005).

Accordingly, an additional object of the invention relates to an in vitro method for monitoring a sepsis disease comprising the steps of i) determining the level of a population of neutrophils having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers in a sample obtained from the subject at a first specific time of the disease, ii) determining the level of a population of neutrophils having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10- CD64+PDL1+ markers in a sample obtained from the subject at a second specific time of the disease, iii) comparing the level determined at step i) with the level determined at step ii) and iv) concluding that the disease has evolved in worse manner when the level determined at step ii) is higher than the level determined at step i).

An additional object of the invention relates to an in vitro method for monitoring the treatment of a sepsis disease comprising the steps of i) determining the level of a population of neutrophils having cell surface expression of CD66+CD10-CD16-CD64+CD123+ and/or CD66+CD10-CD64+PDL1+ in a sample obtained from the subject before the treatment, ii) determining the level of a population of neutrophils having cell surface expression of CD66b+CD 10-CD 16-CD64+CD 123+ markers and/or CD66b+CD10-CD64+PDLl+ markers in a sample obtained from the subject after the treatment”, iii) comparing the level determined at step i) with the level determined at step ii) and iv) concluding that the treatment is efficient when the level determined at step ii) is lower than the level determined at step i).

The decrease can be e.g. at least 5%, or at least 10%, or at least 20%, more preferably at least 50% even more preferably at least 100%. As illustrated in Fig-4, inventors observe a decrease of the two neutrophils biomarkers level (“Biomarkerl23” and“Biomarker274”) in sepsis patients 7 days after treatment.

Another object of the invention relates to an in vitro method for monitoring the immunological status of patient a sepsis disease comprising the steps of i) determining the level of neutrophil cells having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers in a sample obtained from the subject, ii) comparing the level determined at step i) with the with a reference value and iv) concluding that:

- when the level of neutrophil having cell surface expression of CD66b+CD10-CD16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers determined at step i) is higher than the reference value, then said patient is at risk of having an unresponsive profile; or

- when the level of neutrophil having cell surface expression of CD 10-CD 16- CD64+CD123+ markers and/or CD66b+CD10-CD64+PDLl+ markers determined at step i) is lower or equal than the reference value, then said patient is at risk of having a responsive profile.

The expression“monitoring the immunological profile” means evaluating changes in cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers on neutrophil cells. The monitoring of the immunological profile of a given subject allows monitoring the neutrophils cell activity of said subject.

According to the monitoring method of the invention, for a given subject, if the level of neutrophil having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers is higher than the reference value, then one can conclude that said patient is at risk of having an unresponsive profile.

An“unresponsive profile” means that the neutrophil cells of said subject have an immature neutrophil behaviour, this will result in an impaired ability of this immature neutrophils from sepsis patients to inadequately clear the infection such us poor activation by microbial particles and exhibit an impaired phagocytosis. In such a case, then one can conclude that said patient is at risk of having immature neutrophils cells which failed to induce an efficient immune response.

According to the monitoring method of the invention, for a given subject, if the level of neutrophil having cell surface expression of CD66b+CD10-CD16-CD64+CD123+ markers and/or CD66b+CD10-CD64+PD-Ll+ markers is lower or equal than the reference value, then one can conclude that said patient is at risk of having a responsive profile.

A“responsive profile” means that the neutrophil cells of said subject having less an immature neutrophils behaviour: this will result in a higher ability of the neutrophils population from sepsis patients to adequately clear the infection such us good activation by microbial particles and exhibit-an efficient phagocytosis activity. In such a case, then one can conclude that said patient has a greater proportion of neutrophils cells which induce an efficient immune response.

"Risk" in the context of the present invention, relates to the probability that an event will occur over a specific time period, as in the conversion to sepsis, and can mean a subject's "absolute" risk or "relative" risk. Absolute risk can be measured with reference to either actual observation post-measurement for the relevant time cohort, or with reference to index values developed from statistically valid historical cohorts that have been followed for the relevant time period. Relative risk refers to the ratio of absolute risks of a subject compared either to the absolute risks of low risk cohorts or an average population risk, which can vary by how clinical risk factors are assessed. Odds ratios, the proportion of positive events to negative events for a given test result, are also commonly used (odds are according to the formula p/(l- p) where p is the probability of event and (1- p) is the probability of no event) to no conversion. Alternative continuous measures, which may be assessed in the context of the present invention, include time to sepsis conversion risk reduction ratios. "Risk evaluation," or "evaluation of risk" in the context of the present invention encompasses making a prediction of the probability, odds, or likelihood that an event or disease state may occur, the rate of occurrence of the event or conversion from one disease state to another, i.e., from a normal condition to a sepsis condition or to one at risk of developing a sepsis. Risk evaluation can also comprise prediction of future clinical parameters, traditional laboratory risk factor values, or other indices of sepsis, such as cellular population determination in peripheral tissues, in serum or other fluid, either in absolute or relative terms in reference to a previously measured population.

Therapeutic method

As mentioned antibiotics is the current main treatment for sepsis.

The invention also relates to a method for treating sepsis with antibiotics in a subject wherein the level of a population of neutrophils CD66b+CD10-CD16-CD64+CD123+ and/or CD66b+CD10-CD64+PDLl+ obtained from said patient have been detected by one of method of the invention.

Another object of the present invention is a method of treating sepsis in a subject comprising the steps of:

a) providing a sample containing neutrophil from a subject,

b) detecting the level of a population of neutrophils CD66b+CD10-CD16- CD64+CD123+ and/or CD66b+CD10-CD64+PDLl+ iii) comparing the level determined in step ii) with a reference value and if level determined at step ii) is higher than the reference value, treating the subject with antibiotics.

In the context of the invention, the term "treating" or "treatment", as used herein, means reversing, alleviating, inhibiting the progress of, or preventing the disorder or condition to which such term applies, or reversing, alleviating, inhibiting the progress of, or preventing one or more symptoms of the disorder or condition to which such term applies.

Example of antibiotic agents include, without limitation, penicillin, quinoline, vancomycin, sulfonamides, ampicillin, ciprofloxacin, teicoplanin, telavancin, bleomycin, ramoplanin, decaplanin, chloramphenicol and sulfisoxazole.

The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention. FIGURES:

Figure 1: An overview of the analysis approach. (A) Blood samples from sepsis patients (S) (n=17) or non -infected post-cardiothoracic surgery patients (NIC) (n=12) enrolled in the study were processed within 3h after blood draws at day 1 and day 7 post-admission in ICU (S group) or post-surgery (NIC group). In addition, blood samples were obtained from healthy donors (HD) (n=12) and bone marrows biopsies from orthopedic surgery patients (BM) (n=5). (B) Immunostainings targeting 42 parameters were performed. Stained cells were stored at -80°C. When the collection was complete, samples were thawed and analyzed by mass cytometry. (C) After data normalization and cleaning, expert gating on the sample- specific t-SNE plots was used to separate neutrophils from other circulating immune cells that were analyzed apart, strategy-1 viSNE and SPADE tools were then used to identify sepsis- specific neutrophil subsets.

Figure 2: Neutrophils heterogeneity assessed by dimensional reduction. t-SNE analysis was performed on all samples non-neutrophils and cells were organized along a second couple of t-SNE axes (t-SNE- 1-2 and t-SNE-2-2). Cell density for the concatenated file of all individuals of each group is shown (healthy donors (HD), bone marrow (BM), sepsis (S), non-infected controls (NIC) at day-1 (D-l) and day-7 (D-7)), on a black to with heat scale.

Figure 3: Identification of sepsis day 1-specific neutrophil nodes. SPADE clustering was done to separate neutrophils subsets nodes. SPADE nodes specific of each group (black area) were overlaid on t-SNE map of the merged files of HD group, S and NIC groups at Dl.

Figure 4: Characterization of two sepsis-specific neutrophil subsets. (A) shows the proportion of sepsis-specific neutrophil subsets for each patient group assessed by unsupervised analysis. (B) shows the gating strategy to identify CD10-CD64+CD16-CD123+ sepsis-specific neutrophil subset. (C) shows the proportion of CD10-CD64+CD16-CD123+ neutrophil subset for each patient group assessed by expert gating. (D) shows the gating strategy to identify CD10-CD64+PD-L1+ sepsis-specific neutrophil subset. (E) shows the proportion of CD10-CD64+PD-L1+ neutrophil subset for each patient group assessed by expert gating. (F) Shows the correlation between the proportion of CD10-CD64+CD16- CD123+ neutrophils subset and ISG II score.

Figure 5: Activation and phagocytosis are impaired in sepsis immature neutrophils. To address sepsis immature (CD64+CD10-) neutrophils phagocytic capacities, 100pL of blood were incubated with 20pL or 40pL of beads coated with Staphylococcus aureus or Zymosan, respectively, coated-particles and coupled with pH acidification-sensitive fluorochrome. After lh incubation at 37°C (PC: positive control) or 4°C (NC: negative control) cells were stained and analyses by flow cytometry. The proportion of total phagocytic neutrophils for Staphylococcus aureus coated beads (A) or Zymosan coated beads (A) were presented for the three groups. The ratio between PC and NC CD66b CD l ib and particles MFI, of each individual after Staphylococcus aureus (C) or Zymosan (D) stimulations, in each group were plotted in histograms.

Figure 6: Study design. (A) Blood samples from sepsis patients (S) (n=17) or non- infected post-cardiothoracic surgery patients (NIC) (n=12) enrolled in the study, in addition, blood samples were obtained from healthy donors (HD) (n=l l) and bone marrows biopsies from orthopedic surgery patients (BM) (n=5). Immunostainings targeting 42 parameters were performed and analyzed by mass cytometry. (B) A computational“discovery strategy” was used to identify sepsis-specific neutrophils subsets, followed by a“validation strategy” and with an additional“expert driven strategy”. (C) A second independent cohort was used for the biological validation of these sepsis-specific neutrophil subsets by flow cytometry.

Figure 7: Identification of sepsis day 1-specific neutrophils with a discovery analysis strategy. Cells abundance of each meta-cluster subset (CD10-CD64+PD-L1+ cell subset, CD10-CD64+CD16-CD123+ cell subset and CD10-CD64+ cell subset), assessed by the“discovery strategy”, was presented as cell proportion among total neutrophils of each group samples.

Figure 8: Validation of sepsis day-l-specific neutrophil subsets by a second computational strategy. Cells abundance of each meta-cluster subset (CD10-CD64+PDL1+ cell subset and CD10-CD64+CD16-CD123+ cell subset), assessed by the “validation strategy”, was presented as cell proportion among total neutrophils of each group samples.

Figure 9: Sepsis day 1-specific neutrophil subsets validated by expert gating. Cells abundance of each meta-cluster subset (CD10-CD64+PDL1+ cell subset and CD 10- CD64+CD16-CD123+ cell subset), assessed by the“expert driven strategy”, was presented as cell proportion among total neutrophils of each group samples.

Figure 10: Sepsis day 1-specific neutrophil subsets proportions correlate with severity scores. Correlation between the Log 10 transformed frequency of CD 10- CD64+CD16-CD123+ neutrophils subset and SAPS II score (black dots and full line) or SOFA score (white squares and hatched line) are shown. Figure 11: Sepsis-specific neutrophils are detectable by conventional cytometry and discriminate infected from non-infected patients. The ROC curves obtained using CD123+ neutrophil subset proportion or CD123+ and PD-L1+ neutrophil subsets proportions were presented.

EXAMPLE:

Methods:

Previous studies in sepsis evaluated only few markers simultaneously and only on enriched cell populations from peripheral blood mononuclear cells. We designed a longitudinal pilot study to explore the co-evolution of circulating immune cell phenotypes of sepsis patients (n=17), and non-infected post-cardiothoracic surgery patients (NIC) (n=12) between day-1 and day-7 after patient entry to the intensive care unit. The comparison included also eleven blood samples, from age and gender matched healthy donors (HD) and five bone marrow biopsies from orthopaedic surgery patients. All specimens were obtained in accordance with the Declaration of Helsinki following protocols approved by Paris-hospitals Ethical Comity (AP-HP DRCI).

Blood samples from sepsis patients (S) or non-infected post-cardiothoracic surgery patients (NIC) enrolled in the study were processed within 3h after blood draws at day 1 and day 7 post-admission in intensive care units (ICU) (S group) or post-surgery (NIC group). In addition, blood samples were obtained from healthy donors (HD) and bone marrows biopsies from orthopedic surgery patients (BM) (Figure-l-A). Immunostainings targeting 40 markers were performed. Stained cells were stored at minus 80°C. When the collection was complete, samples were thawed and analysed by mass cytometry (CyTOF) (Figure-l-B). Sepsis specific cell subsets were characterized using an unsupervised computational workflow (Figure- 1-C). The viSNE tool (Amir ED et al, Nat. Biotech. 2013) was used first to separate neutrophils from other circulating immune cell populations by expert gating on tSNE plot (Van der Maaten L et al, J. Mach. Learn. Res. 2008). A second step of dimensionality reduction was performed to separate neutrophils subsets and a SPADE analysis (Qiu P, et al. Nat. Biotech. 2011) was done with the new tSNE axes to identify distinct clusters on the tSNE map.

To address neutrophils activation and phagocytic capacities, blood was incubated with beads coated with Zymosan or Staphylococcus aureus particles and pH acidification-sensitive fluorochrome (pHrodo Bioparticules) that allowed the identification of phagocytic cells (Neaga A J. Immunol. Methods 2013).

Result Mapping of neutrophils heterogeneity across patients’ groups and healthy donors viSNE analysis was performed on all samples neutrophils and cells was organized along a second couple of t-SNE axes (t-SNE-1-2 and t-SNE-2-2) according to per-cell expression of CDl lb, CD66b, CD16, CD10, CD64 and CD123. After the dimensional reduction, the cells of the merged files of each group were represented on the tSNE map to have an overview of neutrophil subsets landmarks and a black to white heat scale/contour plot represents the cell density on this map (Figure-2). viSNE arranged, in a non-supervised manner, the healthy donors (HD) neutrophils on the lower left area of the map. While non- infected post-cardiothoracic surgery patients (NIC) cells are in the central/upper area, bone marrow (BM) cells and sepsis patients (S) blood cells on the upper right area of the map. Most of day 7 samples cells were arranged near HD area of the map.

Identification of sepsis day 1 -specific subsets

After the dimensional reduction, a spanning tree was generated with SPADE using t-SNE-1-2 and t-SNE-2-2 axes to separate neutrophils subsets in 50 nodes. Then, a clustering of the samples was done on a heat map according to these 50 nodes cell proportion Log2- transformed and centered on the mean proportion of all samples’ nodes. Samples and mean- centered Log2-transformed nodes cell proportion were arranged according to complete linkage hierarchical clustering. Bone marrow (BM) samples were clustered with most of sepsis (S) day 1 samples. Non-infected post-cardiothoracic surgery patients (NIC) day 1 samples cluster apart from HD, BM and most of S day 1 samples. Healthy donors (HD) samples were all cluster with most of S day 7 and NIC day 7 samples.

A second heatmap was generated to characterise cell nodes according to mean expression of 7 markers (CDl lb, CD66b, CD10, CD16, CD64, CD123 and PDL1). Markers were arranged according to complete linkage hierarchical clustering and nodes were pre ordered according to the previously described heat map nodes clustering. Each group dayl- specific nodes are highlighted in black on the tSNE plot of the group merged file to delimitate neutrophils subsets landmarks (Figure-3).

Cells from sepsis-specific nodes are significantly more abundant in sepsis day 1

Sepsis specific nodes identified above according to their specific phenotype and relative proportion among groups are represented in histograms that show the percentage of each cell subtype among neutrophils of Healthy donors (HD) blood, bone marrow (BM), non- infected post-cardiothoracic surgery patients (NIC) blood collected at day 1 (Dl) and day 7 (D7) post-surgery and sepsis patients (S) blood collected at Dl and D7 post-admission to ICU (Figure-4-A). We succeeded, with our approach, to recapitulate previously described results regarding the sepsis specificity of CD64+ neutrophils (nodes 11, 45 and 32). Moreover, we succeeded to identify two new sepsis-specific subsets, one characterized as CD66b+CD10- CD64+CD123+ immature cells (nodes 3 and 24) and a second subset composed of CD66b+CD 10-CD 16+CD64+PDL 1 + cells (node 28) (Figure-4-A).

Hand gating strategy using 4 markers set based on node 3 cells phenotype allowed the selection of cells that are significantly more abundant in sepsis patients (S) blood collected at D1 post-admission to ICU (4.06±2.27%) when compared to day 1 non-infected post- cardiothoracic surgery patients (NIC) (0.04±0.02%, =0.0003) or Healthy donors (HD) (0.04±0.01%, p=0.002) (Figure-4-B, C).

Expert gating on node 28 cells characterized by 3 markers set allowed the selection of sepsis-specific neutrophils (8.84±4.64%) that are almost absent from day 1 non-infected post- cardiothoracic surgery patients (NIC) (0.03±0.01%, <0.0001 ) or Healthy donors (HD) (0.002±0.002, /?<0.0001 (Figure-4-D, E).

The proposition of CD66+CD10-CD64+CD123+ sepsis-specific neutrophils correlate positively with IGS2 score (clinical gravity score used in ICU) (r=0.8, p= 0.0017, R2=0.684) (Figure-4-F).

Staphylococcus aureus and Zymosan specific activation and phagocytosis are impaired

To address sepsis immature (CD64+CD10-) neutrophils activation and phagocytic capacities, whole blood of each individual was incubated with Staphylococcus aureus or Zymosan pHrodo Bioparticules that allowed the identification of phagocytic competent cells. After lh incubation at +37°C (PC: positive control) or +4°C (NC: negative control) cells were stained and analyses by flow cytometry identify immature neutrophils beads uptake as CD66b+CD14-CD3-CD19- CD10- cells. All circulating neutrophils were able to phagocyte Staphylococcus aureus beads independently from their group (healthy donors (HD), sepsis day 1 (S-Dl), sepsis day-7 (S-D7)) (Figure-5-B) but we observed a defect in sepsis-day-1 neutrophils phagocytosis of Zymozan Beads (28.12±3.75%) when compared to healthy donors (HD) (50.43±6.52, p= 0.02) (Figure-5-A).

The ratio between PC and NC of CD66b and CD l ib MFI, of each group individual, after Staphylococcus aureus (Figure-5-C) or Zymosan (Figure-5-D) stimulations, were plotted in histograms. The impaired phagocytic capacity of immature neutrophils from sepsis patients was confirmed by the measurement of phagocytosed beads MFI. These cells also exhibit a lower level of expression of CD l ib and CD66b after activation, when compared to healthy donors (Figure-5-C, D).

Conclusion:

Deep phenotypes analysis allowed the identification of a neutrophil subset highly enriched in sepsis patients compared to NIC patients and almost absent in HD. This subset harbours an immature phenotype (CD66b+CD10-CD16-CD64+CD123+) and its proportion is positively correlated with IGS2 score. A second neutrophil subset was also identified exclusively in sepsis patients and characterised as CD66b+CD10-CD64+PDLl+ cells.

Functional characterisation of immature neutrophils highlighted the impaired ability of neutrophils from sepsis patients to be activated by microbial particles and exhibit a deficient phagocytosis.

EXAMPLE 2:

Methods:

This observational study was approved by the Comite de Protection des Personne Paris VII ethic committee (CPP IDF VII A000142-53) which waived the need for written informed consent since it was with low risk for the patients and with no need for specific procedure besides routine blood sampling. The study was conducted in 4 ICUs: 2 surgical ICUs (Hopital Lariboisiere, Hopital Saint Louis), 1 medical ICU (Hopital Lariboisiere), and 1 post-cardiac surgery ICU (Hopital Europeen Georges Pompidou). All individuals included in the study were adults (>18 years of age) with no pre-existent immunosuppression history. Seventeen sepsis (S) patients (10 male and 7 female), with a median of age of 75 years old were included in the study (Supplemental Table2). Sepsis was defined in accord to The Third International Consensus Definitions for Sepsis (1), i.e. an increase of 2 or more points on SOFA score in related to a suspected or confirmed infection. All patients received prompt treatment with antibiotics, adequate fluid resuscitation, and support for damaged organ function, including mechanical ventilation and continuous renal replacement therapy. Twelve patients (8 male and 4 female), with a median of age of 75, undergoing non-infection related cardiac intervention requiring cardiopulmonary bypass were also included in the study. They were considered in this study as non-infected inflammatory controls (NIC). Patients’ clinical data were collected at day 1 and day 7 and included vital status, component of SAPS II and SOFA score, clinical and biological parameters and blood count. Blood samples drawn in heparin- coated tubes, were collected one- and seven-days post admission of sepsis patients or post surgery for NIC patients (Figure 1A), or were drawn from eleven age and gender matched healthy donors (HD) obtained from the French blood donation center. Five bone marrow (BM) biopsies from orthopedic surgery patients were also included in this study. All specimens were obtained in accordance with the Declaration of Helsinki. Immunostainings targeting 40 markers were performed. Stained cells were stored at minus 80°C. When the collection was complete, samples were thawed and analysed by mass cytometry (CyTOF) (Figure-6-A).

Instead of using a classical hierarchical gating strategy to analyse the CyTOF acquired data, we used a computational analysis approach composed of a“discovery strategy” that aims to identify sepsis-specific subsets, using a dimensional reduction algorithm, viSNE tool (Van der Maaten L et al, J. Mach. Learn. Res. 2008; Amir ED et al, Nat. Biotech. 2013) and a clustering one, SPADE analysis (Qiu P, et al. Nat. Biotech. 2011), followed by a computational“validation strategy”, using different tools, UMAP and FlowSOM algorithms (Becht E et al, Nature biotechnology 2018; Van Gassen S et al, Cytometry Part A 2015) to check whether the identified sepsis-specific subsets are strategy-dependant. Using this approach, we identified two novel, early, and sepsis-specific neutrophil subsets expressing IL- 3 receptor (CD123) and/or PD-L1, and with an additional“expert driven strategy” we defined a small set of markers that identify these two sepsis-specific neutrophil subsets (Figure-6-B).

Using an independent cohort of infected and non-infected patients and conventional flow cytometry, these two cell subsets were biologically validated as sepsis-specific (Figure- 6-C).

Result

Mass cytometry and computational analysis revealed sepsis-specific neutrophil subsets The neutrophils were analysed using the“discovery strategy” based on a dimensionality reduction with t-SNE as a first step. This strategy allowed to define an imprint for each sample group. In an unsupervised manner, the healthy donors (HD) neutrophils, the non- infected post-cardiothoracic surgery patients (NIC) neutrophils and bone marrow (BM) neutrophils were arranged in distinct areas of the map while the sepsis patients (S) blood neutrophils shared part of BM cells area. Most of day 7 samples cells were arranged near HD area of the map.

In the“discovery strategy”, the dimensional reduction was followed by a clustering of the cells in nodes with SPADE. Samples and mean-centred Log2-transformed nodes cell proportion were arranged according to complete linkage hierarchical clustering. Most of sepsis (S) day 1 samples were clustered together with specifically abundant nodes when compared to Non-infected post-cardiothoracic surgery patients (NIC) day 1 nodes and Healthy donors (HD) nodes.

Sepsis specific nodes identified above according to their specific phenotype and relative proportion among groups are represented in histograms that show the percentage of each cell subtype among neutrophils of Healthy donors (HD) blood, bone marrow (BM), non-infected post-cardiothoracic surgery patients (NIC) blood collected at day 1 (Dl) and day 7 (D7) post surgery and sepsis patients (S) blood collected at Dl and D7 post-admission to ICU (Figure- 7). We succeeded, with the“discovery strategy”, to recapitulate previously described results regarding the sepsis specificity of CD10-CD64+ neutrophils. Moreover, we succeeded to identify two new sepsis-specific subsets, one characterized as CD66b+CD10-CD64CD16- CD123+ immature cells and a second subset composed of CD66b+CD10-CD64+PDLl+ cells. These two novel neutrophil subsets specific to S at day-1 were observed to be relatively lacking in NIC and HD neutrophils. S median proportion of CD66b+CD10-CD64+PDLl+ neutrophils was 18.08±23.33 %, whereas NIC exhibited a median proportion of 0.81±2.92 % ( p=0.0002 ). CD66b+CD10-CD64CD16-CD123+ immature neutrophils were also more abundant in S group with a median proportion of 10.06±23.76 % when compared to NIC group that had a median proportion of 0.04±0.90 % (p<0.0001 ) (Figure-7).

A computational validation strategy confirmed early sepsis specific neutrophil subsets The“validation strategy” based on a dimensionality reduction with UMAP, followed by a clustering of the neutrophils with FlowSOM algorithm allowed the identification of neutrophil clusters and the complete linkage hierarchical clustering of their relative cells abundance arranged again the samples of each patients’ group together. Among these clusters, three groups of clusters were identified, the group of CD10-CD64+ immature cells and two clusters groups phenotypically identical to the“discovery strategy” sepsis-specific neutrophils nodes. One group of clusters contained CD66b+CD10-CD64+PDLl+ neutrophils and the second group gathered CD66b+CD10-CD64+CD16-CD123+ immature neutrophils. As expected, these two neutrophil subsets were also specific to S at day-1 and barely absent in NIC and HD samples (Figure-8).

Expert gating strategy with a small set of markers validated sepsis dav-1 neutrophil signature that correlate with SAPSII and SOFA scores

After cell subsets were identified by automatic and high-dimensional analysis strategies, we determined whether the identified neutrophil signature could be found using conventional analysis applicable by experts. The use of such gating strategy would make it easier to transpose it to clinical use. A bi-parametric gating strategy on a limited set of markers allowed the identification of neutrophils expressing CD123 and PD-L1. This expert gating strategy applied on the current dataset, allowed the selection of PD-L1+ neutrophils that were significantly more abundant in S patients’ blood collected at D1 post-admission to ICU (9.25±27.02 %) when compared to day 1 non-infected post-cardiothoracic surgery patients (NIC) (0.12±0.37 %, p<0.0001) or HD (0.01±0.03 %, p<0.001) (Figure-9). Similarly, expert gating allowed the selection of S- specific neutrophils (2.47±17.55 %) that were consistent with CD123+ red subsets cells phenotype and that were almost absent from day 1 NIC (0.04±0.47 %, p<0.0001) or HD (0.04±0.04 %, p<0.0001(Figure-9). Unlike PD-L1+ sepsis-specific neutrophils, the proportion of CD123+ sepsis-specific, assessed by the simple gating strategy on mass cytometry data, correlate positively with SAPS II score (r=0.62, p=0.0077, R2=0.46) and with SOFA score (r=0.55, p=0.0037, R2=0.31) (Figure-10).

CD123+ and PD-L1+ sepsis-specific neutrophils are detectable by conventional

To evaluate the efficiency and specificity of CD123+ and PD-L1+ neutrophil subsets to discriminate sepsis patients from non-infected ones, we set up a fluorescent flow cytometry panel composed of 7 surface markers that we used to monitor a new validation cohort composed of non-infected patients (n=8) and sepsis patients (n=23) independent from the previously described ones.

Based on flow cytometry results, a CD123+ neutrophil subset proportion cut-off point of 0.35 %, was able to rule out sepsis patients with a specificity of 87.50% and sensitivity of 78.26% (AUC of 0.89 with p=0.0013) (Figure-11). When combining both CD123 and PD-L1 neutrophil subsets proportions and a cut-off point of 0.40%, the increase in the sensitivity was modest (sensitivity of 0.83 (p=0.0007) without any effect on the specificity Figure-11).

These data indicated that these subsets could be reliably quantified by traditional clinical flow cytometric profiling and may help in patient’s diagnosis.

REFERENCES:

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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