Patent Application
20230184784
This application claims priority to Australian Provisional Application No. 2016903160 entitled “Immunostimulatory Compositions and Uses Therefor” filed 11 Aug. 2016, the contents of which are incorporated herein by reference in their entirety.
This invention relates generally to compositions, methods, apparatus and kits for diagnosing and/or monitoring the Th1 immune status of a subject. The invention can be used for diagnosis, monitoring, making treatment decisions, or management of subjects suspected of having Th1-related disease. More particularly, the present invention relates to peripheral blood biomarkers that are useful for determining the Th1 immune status of the subject.
Programmed cell death protein 1 (PD-1) is recognized as an important player in immune regulation, through its actions as a brake on effector T cells and in reducing immune responses in the tissue microenvironment. PD-1 is expressed on activated T cells including immunosuppressive CD4+ T cells (Treg) and exhausted CD8+ T cells, but also on B cells, myeloid dendritic cells (MDCs), monocytes, thymocytes, and natural killer (NK) cells. This broad PD-1 expression suggests a wide implication of the PD-1 signaling pathway needed for effective immunity and maintenance of T cell homeostasis (Gianchecchi et al., Autoimmun. Rev. 12: 1091-100, 2013).
Significantly, the PD-1 signaling pathway contributes to the maintenance of both central and peripheral tolerance in normal individuals. In the thymus, the interaction of PD-1 and its ligands suppresses positive selection thereby inhibiting the transformation of CD4− CD8− double negative cells to CD4+ CD8+ double positive T cells (Keir et al., J. Immunol. 175:7329-7379, 2005). PD-1 signaling is also responsible for inhibition of self-reactive and inflammatory effector T cells that escape negative selection to avoid collateral immune-mediated tissue damage (Keir et al., J. Exp. Med. 203:883-895, 2006).
PD-1 has two known ligands: protein death ligand 1 (PD-L1; Freeman et al., J. Exp. Med. 192:1027-34, 2000), also known as B7-H1 in humans (Dong et al., Nat. Med. 5:1365-9, 1999), and protein death ligand 2 (PD-L2; Latchman et al., Nat. Immunol. 2:261-8, 2001), also known as B7-DC (Tseng et al., J. Exp. Med. 193:839-46, 2001). The patterns of expression of PD-L1 and PD-L2 are quite distinct. PD-L1 is expressed constitutively by a wide variety of immune cells and non-immune cells and appears to be upregulated in most normal tissue cells in the presence of strong inflammatory signals (Matzinger et al., Nat. Rev. Immunol. 11:221-230, 2011; Muhlbauer et al., J. Hepatol. 45:520-528, 2006; Pinchuk et al., Gastroenterol. 135:1228-1237, 2008; Stanciu et al, J. Infect. Dis., 193:404-412, 2006). By contrast, constitutive basal expression of PD-L2 is low compared to PD-L1, and although PD-L2 expression was initially thought to be restricted to antigen-presenting cells (APCs) such as monocytes, macrophages and dendritic cells (DCs) (Latchman et al., Nature Immunol. 2:261-268, 2001; Yamazaki et al., J. Immunol. 169:5538-5545, 2002), several groups have recently shown that PD-L2 expression can be induced on a wide variety of other immune cells and non-immune cells depending on microenvironmental stimuli (Kinter et al., J. Immunol. 181:6738-6746, 2008; Zhong et al., Eur. J. Immunol. 37:2405-2410, 2007; Messal et al., Mol. Immunol. 48:2214-2219, 2011; Lesterhuis et al., Mol. Immunol. 49:1-3, 2011).
PD-1 and its ligands are aberrantly expressed by malignant cells and surrounding microenvironmental cells. Within the tumor microenvironment, PD-1 is highly expressed on a large proportion of tumor-infiltrating lymphocytes (TILs) from many different tumor types and suppresses local effector immune responses. TIL expression of PD-1 is associated with impaired effector function (cytokine production and cytotoxic efficacy against tumor cells) and/or poor outcome in several tumor types (Thompson et al., Clin. Cancer Res. 13:1757-1761, 2007; Zhang et al., Mol. Immunol. 7:389-395, 2010; Ahmadzadeh M et al., Blood 114: 1537-1544, 2009; Shi et al., Int. J. Cancer 128:887-896, 2011), including renal cell carcinoma, metastatic melanoma, as well as stomach, breast, ovarian, pancreatic, and lung cancers. Similarly, PD-L2 has been observed to be upregulated in a subset of human tumors and has occasionally been linked to poor outcome (Rozali et al., Clin. Dev. Immunol. 2012:656340, 2012).
Given its potential role in cancer-associated immune suppression in the tumor microenvironment, targeting the PD-1/PD-ligand pathway has been proposed as an attractive treatment strategy. Several studies in this regard have investigated the therapeutic effect of blocking antibodies against the PD-1/PD-L1 pathway, demonstrating enhanced tumor control rates, (Curran et al., Proc. Natl. Acad Sci. USA 107:4275-4280, 2010; Iwai et al., Proc. Natl. Acad Sci. USA 99:12293-12297, 2002; Pilon-Thomas et al., J. Immunol. 184:3442-3449, 2010; Zhang et al., Blood 114:1545-1552). However, few studies have investigated blocking of PD-L2 as a defined treatment strategy. Although in a few studies PD-L2 blocking strategies were used, this was always in combination with the targeting of PD-L1 (Parekh et al., J. Immunol. 182:2816-1826, 2009; He et al., J. Immunol. 173:4919-4928, 2004), which did not permit deducing the true value of anti-PD-L2 strategies.
The present invention is predicated in part on the determination that PD-L2 expression on cells such as APCs, which interact with immune system effector cells, inversely correlates with the severity of Th1-related diseases and that PD-L2 is required to establish Th1 immunity. Therefore, the present inventors determined that PD-L2 is a reliable indicator of an upregulated and/or enhanced Th1 immune response in a subject. The present inventors have also discovered other biomarkers that are modulated during a Th1 immune response. Inclusion of these additional biomarkers increases the diagnostic power and reliability of the diagnostic and prognostic assays taught herein. Based on these determinations, it is proposed that PD-L2, optionally in combination with other Th1 immune status biomarkers, is indicative of the Th1 immune status of a subject, and has utility for tracking Th1 immune status development in subjects suffering from Th1-related diseases.
Accordingly, in one aspect, the present invention provides methods for determining an indicator used in assessing a subject's Th1 immune status, the method comprising: (1) determining a Th1 immune status biomarker profile of a sample obtained from the subject, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least one Th1 immune status biomarker in the sample, wherein the at least one Th1 immune status biomarker comprises programmed cell death protein 1 ligand 2 (PD-L2) of immune effector cell (IEC)-interacting cells in the sample; and (2) determining the indicator using the biomarker value(s), wherein the indicator is at least partially indicative of the Th1 immune status of the subject.
Suitably, the IEC-interacting cells are selected from APCs and tumor cells. In a related aspect, the present invention provides methods for determining an indicator for use in assessing the Th1 immune status of a subject, the method comprising: (1) determining a Th1 immune status biomarker profile of a sample obtained from the subject, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least one Th1 immune status biomarker in the sample, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of APCs in the sample; and (2) determining the indicator using the biomarker value(s), wherein the indicator is at least partially indicative of the Th1 immune status of the subject. The APC is suitably selected from the group consisting of a dendritic cell or a macrophage. In representative examples of this type, the APC is a CD11c-expressing dendritic cells.
Suitably, in any of the aspects or embodiments disclosed herein, the biomarker value(s) is(are) at least partially indicative of a concentration of the Th1 immune status biomarker in the sample obtained from the subject, and in some embodiments of this type the biomarker value includes the abundance of the Th1 immune status biomarker. In a representative example, an individual biomarker value includes the percentage of IEC-interacting cells (e.g., APCs or tumor cells) that express the Th1 immune status biomarker on the cell surface (e.g., PD-L2+ dendritic cells). In some embodiments of this type, the Th1 immune status biomarker is PD-L2 and the biomarker value is a measurement of PD-L2 clustering on the surface of an IEC-interacting cell (e.g., an APC, such as a dendritic cell).
When determining the Th1 immune status of a subject, in some embodiments the level of PD-L2 is reduced in the sample relative to a control level of PD-L2 that correlates with the presence of normal or unimpaired Th1 immunity, and the indicator is thereby determined to be at least partially indicative of impaired Th1 immunity. In other embodiments, the level of PD-L2 in the sample is about the same as a control level of PD-L2 that correlates with the presence of normal or unimpaired Th1 immunity, and the indicator is therefore determined to be at least partially indicative of normal or unimpaired Th1 immunity. In still other embodiments, the level of PD-L2 in the sample is increased relative to a control level of PD-L2 that correlates with the presence of normal or unimpaired Th1 immunity, and the indicator is therefore determined to be at least partially indicative of elevated Th1 immunity.
The indicator used in assessing Th1 immune status is made more reliable and of greater diagnostic power when the at least one Th1 immune status biomarkers further comprises PD-L1. Accordingly, in some embodiments the biomarker values from a pair of Th1 immune status biomarkers are used to determine the indicator. For example, in some preferred embodiments, the pair of biomarkers are PD-L2 and PD-L1. When more than one Th1 immune status biomarker is used in the methods of the invention, the method suitably further comprises applying a combining function to the biomarker values. In this regard, illustrative examples of suitable combining functions are selected from the group comprising: an additive model; a linear model; a support vector machine; a neural network model; a random forest model; a regression model; a genetic algorithm; an annealing algorithm; a weighted sum; a nearest neighbor model; and a probabilistic model.
Preferably, the methods described above and elsewhere herein comprise: (a) determining a biomarker value for a first Th1 immune status biomarker; (b) determining a corresponding biomarker value for a second Th1 immune status biomarker; (c) determining the indicator using the biomarker values recorded on the first and second Th1 immune status biomarkers, the indicator being indicative of a ratio of the biomarker values recorded on the first and second Th1 immune status biomarkers. In illustrative methods of this type, the first Th1 immune status biomarker is PD-L2, and the second Th1 immune status biomarker is PD-L1. By way of an example, in some embodiments the ratio of the first and second Th1 immune status biomarker values determined from the sample (“the sample Th1 immune status biomarker ratio”) is reduced relative to a control PD-L2:PD-L1 biomarker value ratio that correlates with the presence of normal or unimpaired Th1 immunity, and the indicator is determined to be at least partially indicative of impaired Th1 immunity. For example, the sample biomarker value ratio is suitably no more than about 95%, 94%, 93%, 92%, 91%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, or 10% (and every integer in between) of the control biomarker value ratio of (e.g., determined from a control sample obtained from a subject with a normal or unimpaired Th1 immune response).
Conversely, when the sample PD-L2:PD-L1 biomarker value ratio is increased relative to a control PD-L2:PD-L1 biomarker value ratio that correlates with the presence of normal or unimpaired Th1 immunity, the indicator is determined to be at least partially indicative of elevated Th1 immunity. In these instances, the sample PD-L2:PD-L1 biomarker value ratio is at least about 105%, 106%, 107%, 108%, 109%, 110%, 120%, 130%, 140% 150%, 160%, 170%, 180%, 190%, 200%, 250%, 300%, 400%, 500%, 600%, 700%, 800%, 900%, or 1000% (and every integer in between) of the control biomarker value ratio (e.g., determined from a control sample obtained from a subject with a normal or unimpaired Th1 immune response).
In other embodiments, when the sample PD-L2:PD-L1 biomarker value ratio is about the same as a control PD-L2:PD-L1 biomarker value ratio that correlates with the presence of normal or unimpaired Th1 immunity, the indicator is determined to be at least partially indicative of normal or unimpaired Th1 immunity. In these instances, the sample PD-L2:PD-L1 biomarker value ratio is usually from about 96% to 104% (and all integer percentages in between) of the control biomarker value ratio (e.g., determined from a control sample obtained from a subject with a normal or unimpaired Th1 immune response).
Any known techniques for measuring protein biomarkers or nucleic acid biomarkers are suitable for use with the present invention. For example, the biomarkers can be measured using flow cytometry, immunoassays, mass spectrometry, sequencing platforms, array and hybridization platforms, or a combination thereof.
Suitable immunoassays include enzyme-linked immunosorbent assays (ELISA) or a radioimmunoassay (RIA). In some preferred embodiments, the biomarker value is measured using flow cytometry.
The inventors' findings enable methods of diagnosing diseases and/or conditions with an undesirable Th1 immune status (also referred to interchangeably herein as “Th1-related diseases” or “Th1-related disorders”), as well as for monitoring treatment regimens that are prescribed for treating said diseases. Accordingly, in another aspect, the present invention provides a method as described above and elsewhere herein, wherein the indicator is used to diagnose the presence or absence of a disease. In some embodiments, the disease is associated with a reduced or suppressed Th1 immune status, and is diagnosed when the level of PD-L2 in the sample obtained from the subject is below a predetermined threshold. For example, the disease that is associated with a reduced or suppressed Th1 immune status could be a metastatic cancer or a pathogenic infection.
In other embodiments, the indicator can be used to diagnose a Th1-related disease that is associated with an elevated Th1 immune response, and is therefore diagnosed when the level of PD-L2 in the sample obtained from the subject is above a predetermined threshold. Exemplary diseases of this type include autoimmune diseases. For example, the autoimmune disease can be selected from any one of the group comprising: ankylosing spondylitis, Barrett's esophagus, chronic fatigue syndrome (CFS/CFIDS/ME), chronic Lyme disease (borreliosis), Crohn's disease, diabetes, depression, fibromyalgia (FM), gastroesophageal reflux disease (GERD), Hashimoto's thyroiditis, hypertension, hyperthyroidism, hypothyroidism, irritable bowel syndrome (IBS), interstitial cystitis (IC), kidney stones, Lofgren's syndrome, systemic lupus erythematosus (SLE), multiple chemical sensitivity (MCS), migraine headache, Morgellon's, multiple sclerosis, osteoarthritis, polymyalgia rheumatic, prostatitis, psoriasis, psoriatic arthritis, Raynaud's syndrome/phenomenon, reactive arthritis (Reiter syndrome), restless leg syndrome, reflex sympathetic dystrophy (RSD), rheumatoid arthritis, sarcoidosis, scleroderma, sinusitis, seasonal affective disorder (SAD), Sjdgren's syndrome, ulcerative colitis, uveitis, and vertigo.
In yet another aspect, the present invention includes methods of monitoring disease progression or regression, the methods comprising: (a) obtaining a first sample from a subject at a point in time; (b) obtaining a second sample from a subject at a later point in time; and (c) determining disease progression or regression on the basis of the indicator determined by the methods of the invention described above and elsewhere herein.
Methods are also provided for determining a treatment regimen for a subject diagnosed with a Th1-related disease. Such methods comprise monitoring disease progression or regression using the methods described above and elsewhere herein, and administering a treatment regimen for the subject on identifying a change or no change in the subject's Th1 immune status. In embodiments in which the disease is observed to be progressing (or unchanged), the dosage or frequency of a current treatment regimen is suitably increased or maintained or a different treatment regimen may be administered. In other embodiments, if the disease is observed to be regressing the dosage of the current treatment regimen may be reduced or stopped.
In still another aspect, the present invention provides a method for determining an indicator that is useful for distinguishing between a metastatic cancer and a non-metastatic cancer in a subject, the method comprising: (1) determining a Th1 immune status biomarker profile of a sample obtained from the subject, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least one (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more then 10) Th1 immune status biomarker in the sample, wherein the at least one Th1 immune status biomarker comprises PD-L2 of IEC-interacting cells (e.g., APCs or tumor cells) in a sample; and (2) determining the indicator using the biomarker value(s), wherein the indicator is at least partially capable of distinguishing between metastatic cancer and non-metastatic cancer in a subject. Suitably, the at least one biomarker value is at least partially indicative of a concentration of PD-L2 in the sample obtained from the subject. In some embodiments of this type, the IEC-interacting cells (e.g., APCs such as dendritic cells), and the at least one biomarker value is at least partially indicative of the percentage of dendritic cells that express PD-L2+ on the cell surface. As such, the cancer can be determined likely to be non-metastatic when the PD-L2 biomarker value indicates PD-L2 expression on at least around 60% of the dendritic cells in the sample obtained from the subject. Conversely, the cancer can be determined likely to be metastatic when the PD-L2 biomarker value indicates PD-L2 expression on less than about 50% of the dendritic cells of the sample.
In some embodiments, the Th1 immune status biomarker profile comprises a biomarker value for PD-L1 of the IEC-interacting cells (e.g., APCs, such as dendritic cells). As described above, in some embodiments the biomarker values of PD-L2 and PD-L1 are at least partially indicative of the percentage of IEC-interacting cells (e.g., APCs, such as dendritic cells) expressing these biomarkers on the cell surface. In some embodiments of this type the indicator is indicative of a ratio of the percentages of the IEC-interacting cells (e.g., APCs, such as dendritic cells) in the sample that express PD-L2 and PD-L1 biomarkers.
In some embodiments of this type the IEC-interacting cells are dendritic cells. For example, a PD-L2:PD-L1 biomarker value ratio of between around 0.9 to 1.3 is indicative that the subject has a normal or unimpaired Th1 immunity and is therefore likely to be suffering from a non-metastatic cancer (e.g., a benign lesion). Alternatively, a PD-L2:PD-L1 biomarker value ratio of between around 0.4 to 0.8 is indicative that the subject has a reduced Th1 immunity and is likely to be suffering from a metastatic cancer.
Still another aspect of the present invention provides a method of treating, preventing or inhibiting the development of a Th1-related disease or disorder in a subject, comprising: exposing the subject to a treatment regimen for treating the Th1-related disease based on an indicator obtained from an indicator-determining method as broadly described above and elsewhere herein.
Yet another aspect of the present invention provides compositions for determining an indicator used in assessing a subject's Th1 immune status, or for diagnosing diseases and/or conditions with an undesirable Th1 immune status, or for monitoring disease progression or regression, or for determining an indicator that is useful for distinguishing between a metastatic cancer and a non-metastatic cancer in a subject, the compositions comprising, consisting or consisting essentially of IEC-interacting cells (e.g., APCs or tumor cells), a PD-L2 detection agent and optionally a PD-L1 detection agent. In some embodiments, the IEC-interacting cells have a PD-L2:PD-L1 ratio of between about 0.9 to 1.3. In other embodiments, the IEC-interacting cells have a PD-L2:PD-L1 ratio of between about 0.4 to 0.8. Suitably, the PD-L2 detection agent and/or PD-L1 detection agent are bound to PD-L2 and/or PD-L1, respectively, on the surface of the IEC-interacting cells. The surface PD-L2 and/or PD-L1 may be in the form of clusters. The PD-L2 and/or PD-L1 detection agents are suitably antibodies. In specific embodiments, the PD-L2 and/or PD-L1 detection agents comprise a covalently attached label.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, preferred methods and materials are described. For the purposes of the present invention, the following terms are defined below.
The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.
As used herein the terms “abundance,” “level” and “amount” are used interchangeably herein to refer to a quantitative amount (e.g., weight or moles), a semi-quantitative amount, a relative amount (e.g., weight % or mole % within class), a concentration, and the like. Thus, these terms encompass absolute or relative amounts or concentrations of Th1 immune status biomarkers in a sample.
As used herein, “and/or” refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative (or).
The term “antibody” and its grammatical equivalents refer to a protein which is capable of specifically binding to a target antigen such as PD-L2 or any other surface molecule on an APC and includes any substance, or group of substances, which has a specific binding affinity for an antigen, suitably to the exclusion of other substances. This term encompasses an immunoglobulin molecule capable of specifically binding to a target antigen by virtue of an antigen binding site contained within at least one variable region. This term includes four chain antibodies (e.g., two light chains and two heavy chains), recombinant or modified antibodies (e.g., chimeric antibodies, humanized antibodies, primatized antibodies, de-immunized antibodies, half antibodies, bispecific antibodies) and single domain antibodies such as domain antibodies and heavy chain only antibodies (e.g., camelid antibodies or cartilaginous fish immunoglobulin new antigen receptors (IgNARs)). An antibody generally comprises constant domains, which can be arranged into a constant region or constant fragment or fragment crystallizable (Fc). In specific embodiments, the antibodies comprise a four-chain structure as their basic unit. Full-length antibodies comprise two heavy chains (50-70 kDa) covalently linked and two light chains (23 kDa each). A light chain generally comprises a variable region and a constant domain and in mammals is either a K light chain or a k light chain. A heavy chain generally comprises a variable region and one or two constant domain(s) linked by a hinge region to additional constant domain(s). Heavy chains of mammals are of one of the following types α, δ, ε, γ, or p. Each light chain is also covalently linked to one of the heavy chains. For example, the two heavy chains and the heavy and light chains are held together by inter-chain disulfide bonds and by non-covalent interactions. The number of inter-chain disulfide bonds can vary among different types of antibodies. Each chain has an N-terminal variable region (VH or VL wherein each are 110 amino acids in length) and one or more constant domains at the C-terminus. The constant domain of the light chain (CL which is 110 amino acids in length) is aligned with and disulfide bonded to the first constant domain of the heavy chain (CH which is 330-440 amino acids in length). The light chain variable region is aligned with the variable region of the heavy chain. The antibody heavy chain can comprise two or more additional CH domains (such as, CH2, CH3 and the like) and can comprise a hinge region can be identified between the CH1 and Cm constant domains. Antibodies can be of any type (e.g., IgG, IgE, IgM, IgD, IgA, and IgY), class (e.g., IgG1, IgG2, IgG3, IgG4, IgA1 and IgA2) or subclass. In one example, the antibody is a murine (mouse or rat) antibody or a primate (suitably human) antibody. The term “antibody” encompasses not only intact polyclonal or monoclonal antibodies, but also variants, fusion proteins comprising an antibody portion with an antigen binding site, humanized antibodies, human antibodies, chimeric antibodies, primatized antibodies, de-immunized antibodies or veneered antibodies. Also within the scope of the term “antibody” are antigen binding fragments that retain specific binding affinity for an antigen, suitably to the exclusion of other substances. This term includes a Fab fragment, a Fab′ fragment, a F(ab′) fragment, a single chain antibody (SCA or SCAB) amongst others. An “Fab fragment” consists of a monovalent antigen-binding fragment of an antibody molecule, and can be produced by digestion of a whole antibody molecule with the enzyme papain, to yield a fragment consisting of an intact light chain and a portion of a heavy chain. An “Fab′ fragment” of an antibody molecule can be obtained by treating a whole antibody molecule with pepsin, followed by reduction, to yield a molecule consisting of an intact light chain and a portion of a heavy chain. Two Fab′ fragments are obtained per antibody molecule treated in this manner. An “F(ab′)2 fragment” of an antibody consists of a dimer of two Fab′ fragments held together by two disulfide bonds, and is obtained by treating a whole antibody molecule with the enzyme pepsin, without subsequent reduction. A (Fab′)2 fragment. An “Fv fragment” is a genetically engineered fragment containing the variable region of a light chain and the variable region of a heavy chain expressed as two chains. A “single chain antibody” (SCA) is a genetically engineered single chain molecule containing the variable region of a light chain and the variable region of a heavy chain, linked by a suitable, flexible polypeptide linker.
The term “antigen-presenting cells” (APCs) refers to a class of cells capable of presenting one or more antigens in the form of peptide-MHC complex recognizable by specific effector cells of the immune system (also referred to herein as “immune effector cells” or “IECs”), and thereby modulating (e.g., stimulating/enhancing or reducing/tolerizing/anergizing) an immune response to the antigen or antigens being presented. In specific embodiments of the present invention, the APCs are capable of activating IECs such as T lymphocytes, including CD8+ and/or CD4+ lymphocytes. Cells that have in vivo the potential to act as APC include, for example, not only professional APCs such as dendritic cells, macrophages, Langerhans cell, monocytes and B cells but also non-professional APCs illustrative examples of which include activated epithelial cells, fibroblasts, glial cells, pancreatic beta cells and vascular endothelial cells. Many types of cells are capable of presenting antigens on their cell surface for IEC, including T cell, recognition.
As used herein, “around”, “about” or “approximately” shall generally mean within 20 percent, preferably within 10 percent, and more preferably within 5 percent of a given value or range. Numerical quantities given herein are approximate, meaning that the term “around”, “about” or “approximately” can be inferred if not expressly stated.
The term “biomarker” typically refers to a measurable characteristic that reflects the presence or nature (e.g., severity or status) of a physiological and/or pathophysiological state, including an indicator of risk of developing a particular physiological or pathophysiological state. For example, a biomarker may be present in a sample obtained from a subject before the onset of a physiological or pathophysiological state, including a symptom, thereof. Thus, the presence of the biomarker in a sample obtained from the subject is likely to be indicative of an increased risk that the subject will develop the physiological or pathophysiological state or symptom thereof. Alternatively, or in addition, the biomarker may be normally expressed in an individual, but its expression may change (i.e., it is increased (upregulated; over-expressed) or decreased (downregulated; under-expressed) before the onset of a physiological or pathophysiological state, including a symptom thereof. Thus, a change in the level of the biomarker is likely to be indicative of an increased risk that the subject will develop the physiological or pathophysiological state or symptom thereof. Alternatively, or in addition, a change in the level of a biomarker may reflect a change in a particular physiological or pathophysiological state, or symptom thereof, in a subject, thereby allowing the nature (e.g., severity) of the physiological or pathophysiological state, or symptom thereof, to be tracked over a period of time. This approach may be useful in, for example, monitoring a treatment regimen for the purpose of assessing its effectiveness (or otherwise) in a subject. As herein described, reference to the level of a biomarker includes the concentration of a biomarker, or the level of expression of a biomarker, or the activity of the biomarker, as will be described in more detail below.
The term “biomarker value” refers to a value measured or derived for at least one corresponding biomarker of a subject and which is typically at least partially indicative of an abundance or concentration of a biomarker in a sample taken from the subject. Thus, the biomarker values could be measured biomarker values, which are values of biomarkers measured for the subject, or alternatively could be derived biomarker values, which are values that have been derived from one or more measured biomarker values, for example by applying a function to the one or more measured biomarker values. Biomarker values can be of any appropriate form depending on the manner in which the values are determined. For example, the biomarker values could be determined using high-throughput technologies such as mass spectrometry, sequencing platforms, array and hybridization platforms, immunoassays, flow cytometry, or any combination of such technologies. In one preferred example, the biomarker values relate to a level of activity or abundance of a protein expression product or other measurable molecule, quantified using a technique such as flow cytometry or the like. In this case, the biomarker values can be in the form of a percentage value of cells expressing the biomarker within a sample, as will be appreciated by persons skilled in the art and as will be described in more detail below.
The term “biomarker profile” refers to one or a plurality of one or more types of biomarkers (e.g., a polypeptide molecule, a cDNA molecule, etc.), or an indication thereof, together with a feature, such as a measurable aspect (e.g., biomarker value) of the biomarker(s). A biomarker profile may comprise a single biomarker whole level, abundance or amount correlates with the Th1 immune status of a subject (e.g., an enhanced Th1 immune status or a reduced Th1 immune status). Alternatively, a biomarker profile may comprise at least two such biomarkers or indications thereof, where the biomarkers can be in the same or different classes, such as, for example, a polypeptide and a nucleic acid. Thus, a biomarker profile may comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 or more biomarkers or indications thereof. In some embodiments, a biomarker profile comprises a couple, several, tens, or hundreds of biomarkers or indications thereof. A biomarker profile can further comprise one or more controls or internal standards. In certain embodiments, the biomarker profile comprises at least one biomarker, or indication thereof, that serves as an internal standard. In other embodiments, a biomarker profile comprises an indication of one or more types of biomarkers. The term “indication” as used herein in this context merely refers to a situation where the biomarker profile contains symbols, data, abbreviations or other similar indicia for a biomarker, rather than the biomarker molecular entity itself. The term “biomarker profile” is also used herein to refer to a biomarker value or combination of at least two biomarker values, wherein individual biomarker values correspond to values of biomarkers that can be measured or derived from one or more subjects, which combination is characteristic of a Th1 immune status, discrete condition, stage of condition, subtype of condition or a prognosis for a discrete condition, stage of condition, subtype of condition. The term “profile biomarkers” is used to refer to a subset of the biomarkers that have been identified for use in a biomarker profile that can be used in performing a clinical assessment, such as to rule in or rule out a specific condition, different stages or severity of conditions, subtypes of different conditions or different prognoses. The number of profile biomarkers will vary, but is typically of the order of 10 or less.
By “clustering,” and grammatical equivalents used herein, is meant any reversible or irreversible association of more than two of the same Th1 immune status biomarkers (e.g., PD-L2). Clusters can be made up of 3, 4, 5, 6, 7, 8, 9, 10, 12, 20, etc. biomarkers. Clusters of three or more biomarkers are generally termed oligomers, with individual numbers of clusters having their own designation, for example, a cluster of three biomarkers is a trimer, a cluster of four biomarkers is a tetramer, a cluster of five biomarkers is a pentamer, a cluster of six biomarkers is a hexamer, a cluster of seven biomarkers is a heptamer, a cluster of eight biomarkers is an octamer, a cluster of nine biomarkers is a nonamer, a cluster of ten biomarkers is a decamer, a cluster of twelve biomarkers is a dodecamer, and a cluster of twenty biomarkers is a eicosamer.
Throughout this specification, unless the context requires otherwise, the words “comprise,” “comprises” and “comprising” will be understood to imply the inclusion of a stated step or element or group of steps or elements but not the exclusion of any other step or element or group of steps or elements. Thus, use of the term “comprising” and the like indicates that the listed elements are required or mandatory, but that other elements are optional and may or may not be present. By “consisting of” is meant including, and limited to, whatever follows the phrase “consisting of.” Thus, the phrase “consisting of” indicates that the listed elements are required or mandatory, and that no other elements may be present. By “consisting essentially of” is meant including any elements listed after the phrase, and limited to other elements that do not interfere with or contribute to the activity or action specified in the disclosure for the listed elements. Thus, the phrase “consisting essentially of” indicates that the listed elements are required or mandatory, but that other elements are optional and may or may not be present depending upon whether or not they affect the activity or action of the listed elements.
The term “correlating” refers to determining a relationship between one type of data with another or with a state (e.g., Th1 immune status).
As used herein, the terms “diagnosis,” “diagnosing” and the like are used interchangeably herein to encompass determining the likelihood that a subject will develop a condition, or the existence or nature of a condition in a subject. These terms also encompass determining the severity of disease or episode of disease, as well as in the context of rational therapy, in which the diagnosis guides therapy, including initial selection of therapy, modification of therapy (e.g., adjustment of dose or dosage regimen), and the like. By “likelihood” is meant a measure of whether a subject with particular measured or derived biomarker values actually has a condition (or not) based on a given mathematical model. An increased likelihood for example may be relative or absolute and may be expressed qualitatively or quantitatively. For instance, an increased likelihood may be determined simply by determining the subject's measured or derived biomarker values for at least two Th1 immune status biomarkers and placing the subject in an “increased likelihood” category, based upon previous population studies. The term “likelihood” is also used interchangeably herein with the term “probability”. The term “risk” relates to the possibility or probability of a particular event occurring at some point in the future. “Risk stratification” refers to an arraying of known clinical risk factors to allow physicians to classify patients into a low, moderate, high or highest risk of developing a particular disease.
As used herein, the term “immune effector cells” (IECs) refers to a population of lymphocytes that display effector moiety receptors, e.g., cytokine receptors, and/or Fc receptors on their surface through which they bind an effector moiety, e.g., a cytokine, and/or an Fc region of an antibody and contribute to the destruction of target cells, e.g., tumor cells. IECs may for example mediate cytotoxic or phagocytic effects. IECs include, but are not limited to, effector T cells such as CD8+ cytotoxic T cells, CD4+ helper T cells, γδ T cells, NK cells, NK-like T cells, lymphokine-activated killer (LAK) cells, B cells and macrophages/monocytes.
The term “immune system”, as used herein, refers to cells, molecular components and mechanisms, including antigen-specific and non-specific categories of the adaptive and innate immune systems, respectively, that provide a defense against damage and insults resulting from a viral infection. The term “innate immune system” refers to a host's non-specific reaction to insult to include antigen-nonspecific defense cells, molecular components and mechanisms that come into action immediately or within several hours after exposure to almost any insult or antigen. Elements of the innate immunity include for example phagocytic cells (monocytes, macrophages, dendritic cells, polymorphonuclear leukocytes such as neutrophils, reticuloendothelial cells such as Kupffer cells, and microglia), cells that release inflammatory mediators (basophils, mast cells and eosinophils), natural killer cells (NK cells) and physical barriers and molecules such as keratin, mucous, secretions, complement proteins, immunoglobulin M (IgM), acute phase proteins, fibrinogen and molecules of the clotting cascade, and cytokines. Effector compounds of the innate immune system include chemicals such as lysozymes, IgM, mucous and chemo-attractants (e.g., cytokines or histamine), complement and clotting proteins. The term “adaptive immune system” refers to antigen-specific cells, molecular components and mechanisms that emerge over several days, and react with and remove a specific antigen. The adaptive immune system develops throughout a host's lifetime. The adaptive immune system is based on leukocytes, and is divided into two major sections: the humoral immune system, which acts mainly via immunoglobulins produced by B cells, and the cell-mediated immune system, which functions mainly via T cells.
The term “indicator” as used herein refers to a result or representation of a result, including any information, number, ratio, signal, sign, mark, or note by which a skilled artisan can estimate and/or determine a likelihood or risk of whether or not a subject is suffering from a given disease. In the case of the present invention, the “indicator” may optionally be used together with other clinical characteristics, to arrive at a determination of the Th1 immune status of the subject. That such an indicator is “determined” is not meant to imply that the indicator is 100% accurate. The skilled clinician may use the indicator together with other clinical indicia to arrive at a diagnosis.
The term “nucleic acid” or “polynucleotide” as used herein includes RNA, mRNA, miRNA, cRNA, cDNA mtDNA, or DNA. The term typically refers to a polymeric form of nucleotides of at least 10 bases in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide. The term includes single and double stranded forms of DNA or RNA.
By “obtained” is meant to come into possession. Samples so obtained include, for example, nucleic acid extracts or polypeptide extracts isolated or derived from a particular source. For instance, the extract may be isolated directly from a biological fluid or tissue of a subject.
The terms “PD-L2 expression” and “PD-L1 expression” refers to the transcription and/or translation and/or activity of PD-L2 and PD-L1 respectively. Several methods can be utilized to determine the level of PD-L2 and PD-L1 expression, as described in detail below.
As used herein, the term “positive response” means that the result of a treatment regimen includes some clinically significant benefit, such as the prevention, or reduction of severity, of symptoms, or a slowing of the progression of the condition. By contrast, the term “negative response” means that a treatment regimen provides no clinically significant benefit, such as the prevention, or reduction of severity, of symptoms, or increases the rate of progression of the condition.
“Protein,” “polypeptide” and “peptide” are used interchangeably herein to refer to a polymer of amino acid residues and to variants and synthetic analogues of the same.
The term “prognosis” as used herein refers to a prediction of the probable course and outcome of a clinical condition or disease. A prognosis is usually made by evaluating factors or symptoms of a disease that are indicative of a favorable or unfavorable course or outcome of the disease (e.g., Th1 immune status). The skilled artisan will understand that the term “prognosis” refers to an increased probability that a certain course or outcome will occur; that is, that a course or outcome is more likely to occur in a subject exhibiting a given condition, when compared to those individuals not exhibiting the condition.
The term “sample” as used herein includes any biological specimen that may be extracted, untreated, treated, diluted or concentrated from a subject. Samples may include, without limitation, biological fluids such as whole blood, serum, red blood cells, white blood cells, plasma, saliva, urine, stool (i.e., faeces), tears, sweat, sebum, nipple aspirate, ductal lavage, tumor exudates, synovial fluid, ascitic fluid, peritoneal fluid, amniotic fluid, cerebrospinal fluid, lymph, fine needle aspirate, amniotic fluid, any other bodily fluid, cell lysates, cellular secretion products, inflammation fluid, semen and vaginal secretions. Samples may include tissue samples and biopsies, tissue homogenates and the like. Advantageous samples may include ones comprising any one or more biomarkers as taught herein in detectable quantities. Suitably, the sample is readily obtainable by minimally invasive methods, allowing the removal or isolation of the sample from the subject. In certain embodiments, the sample contains blood, especially peripheral blood, or a fraction or extract thereof. Typically, the sample comprises blood cells such as mature, immature or developing leukocytes, including lymphocytes, polymorphonuclear leukocytes, neutrophils, monocytes, reticulocytes, basophils, coelomocytes, hemocytes, eosinophils, megakaryocytes, macrophages, dendritic cells natural killer cells, or fraction of such cells (e.g., a nucleic acid or protein fraction). In specific embodiments, the sample comprises leukocytes including peripheral blood mononuclear cells (PBMC).
The terms “subject”, “individual” and “patient” are used interchangeably herein to refer to an animal subject, particularly a vertebrate subject, and even more particularly a mammalian subject. Suitable vertebrate animals that fall within the scope of the invention include, but are not restricted to, any member of the phylum Chordata, subphylum vertebrata including primates, rodents (e.g., mice rats, guinea pigs), lagomorphs (e.g., rabbits, hares), bovines (e.g., cattle), ovines (e.g., sheep), caprines (e.g., goats), porcines (e.g., pigs), equines (e.g., horses), canines (e.g., dogs), felines (e.g., cats), avians (e.g., chickens, turkeys, ducks, geese, companion birds such as canaries, budgerigars etc.), marine mammals (e.g., dolphins, whales), reptiles (snakes, frogs, lizards, etc.), and fish. A preferred subject is a primate (e.g., a human, ape, monkey, chimpanzee). The subject suitably has at least one (e.g., 1, 2, 3, 4, 5 or more) clinical sign of a Th1 immune status-associated disease.
A “Th1-related disease” or “Th1-related disorder” as used interchangeably herein refers to a disease that is associated with the development of a Th1 immune response. A “Th1 immune response” as used herein refers to the proliferation or increased differentiation of Th1 cells. A Th1-related disease or disorder is suitably identified by (1) levels of Th1 cells, Th1 cytokines and/or Th1 antibodies that exceed those normally found in a human, animal, or cell culture; (2) pathological findings associated with the disease or medical condition that can be mimicked experimentally in animals by administration of agents that upregulate proliferation or differentiation of Th1 cells; or (3) a pathology induced in experimental animal models of the disease or medical condition can be inhibited or abolished by treatment with agents that inhibit the proliferation or differentiation of Th1 cells. In most Th1-related diseases, at least two of the three conditions are met.
As used herein, the term “treatment regimen” refers to prophylactic and/or therapeutic (i.e., after onset of a specified condition) treatments, unless the context specifically indicates otherwise. The term “treatment regimen” encompasses natural substances and pharmaceutical agents (i.e., “drugs”) as well as any other treatment regimen including but not limited to dietary treatments, physical therapy or exercise regimens, surgical interventions, and combinations thereof.
It will be appreciated that the terms used herein and associated definitions are used for the purpose of explanation only and are not intended to be limiting.
The present invention concerns methods, compositions, apparatus and kits for identifying the Th1 immune status of a subject, or for providing a prognosis for subjects with a Th1-related disease. In particular, Th1 immune status biomarkers are disclosed for use in these modalities to determine the presence, absence or degree of a Th1 immune response in a subject, or for providing a prognosis for subjects with clinical symptoms of a Th1-related disease.
2.1 Th1 Immune Status Biomarkers
The present inventors have determined that certain surface markers are present on cells that interact with IEC and that are specifically expressed in humans and mice during a Th1 immune response. The results presented herein provide clear evidence that a unique biologically-relevant biomarker profile predicts the Th1 immune status of a subject with a remarkable degree of accuracy. Overall, these findings provide compelling evidence that the IEC-interacting cell surface biomarkers disclosed herein, and particularly PD-L2, can function as biomarkers for determining Th1 immune status and may potentially serve as a useful diagnostic for triaging treatment decisions for subjects suffering with a disease associated with an undesirable Th1 immune status. In this regard, it is proposed that the methods, compositions, apparatus and kits disclosed herein that are based on these biomarkers may serve in the point-of-care diagnostics that allow for rapid and inexpensive determination of a Th1 immune status, which may result in significant cost savings to the medical system as subjects with an undesirable Th1 immune response can be exposed to therapeutic agents that are suitable for enhancing or depleting the Th1 immune response in the subject as necessary.
Using the methods described herein, a number of biomarkers have been identified that are particularly useful for determining the Th1 immune status of a subject. These biomarkers are referred to herein as “Th1 immune status biomarkers”. As used herein, the term “Th1 immune status biomarker” refers to a biomarker of the subject, generally a biomarker of the subject's immune system, which is altered, or whose level of expression is altered, as part of a Th1 immune response. The Th1 immune status biomarkers are suitably expression products of genes (also referred to interchangeably herein as “Th1 immune response biomarker genes”), including polynucleotide and polypeptide expression products. As used herein, polynucleotide expression products of Th1 immune status biomarker genes are referred to herein as “Th1 immune status biomarker polynucleotides.” Polypeptide expression products of the Th1 immune response biomarker genes are referred to herein as “Th1 immune status biomarker polypeptides.”
The at least one Th1 immune status biomarker of the present invention suitably comprises PD-L2. The native human PD-L2 amino acid sequence is set forth in SEQ ID NO: 1, and is encoded by the nucleic acid sequence set forth in SEQ ID NO: 3. Another Th1 immune status biomarker that can optionally be used in the methods of the invention is PD-L1. The native human PD-L1 amino acid sequence is set forth in SEQ ID NO: 2, and is encoded by the nucleic acid sequence set forth in SEQ ID NO: 4.
Of the above Th1 immune status biomarkers, the PD-L2 polypeptide has been found to have strong diagnostic performance on its own for detecting Th1 immune status (as measured, for example, using FACS analysis by measuring percentage of PD-L2+ IEC-interacting cells (e.g., APCs or tumor cells)). Thus, in specific embodiments the PD-L2 biomarker may be used either by itself or in combination with other Th1 immune status biomarkers for the determination of the indicator. Suitably, in these embodiments, a biomarker value is measured or derived for the PD-L2 biomarker and optionally another Th1 immune status biomarker(s) (e.g., PD-L1) to determine the indicator.
The present inventors have also determined that other Th1 immune status biomarkers have strong diagnostic performance when used in combination with the PD-L2 biomarker. In advantageous embodiments, pairs of Th1 immune status biomarkers have been identified that can be used to determine the indicator. Accordingly, in representative examples of this type, and as described in detail below, an indicator is determined that correlates to a ratio of Th1 immune status biomarkers, which can be used in determining the Th1 immune status of a subject.
Thus, specific protein products are disclosed herein as Th1 immune response biomarkers that provide a means for determining the Th1 immune status of a subject. Evaluation of these Th1 immune status biomarkers through analysis of their levels in a subject, or in a sample obtained from a subject, provides a measured or derived biomarker value for determining an indicator that can be used for assessing the Th1 immune status in a subject.
2.2 Sample Preparation
Generally, a sample is processed prior to Th1 immune status biomarker detection or quantification. For example, proteins and/or nucleic acids may be extracted, isolated, and/or purified from a sample prior to analysis. Various protein, DNA, and/or mRNA extraction and purification techniques are well known to those skilled in the art. Processing may include centrifugation, ultracentrifugation, ethanol precipitation, filtration, fractionation, resuspension, dilution, concentration, etc. In some embodiments, the methods taught above and elsewhere herein provide analysis (e.g., quantification of protein biomarkers) from raw sample (e.g., biological fluid such as blood, serum, etc.) without or with limited processing.
Furthermore, a sample can be processed prior to Th1 immune status biomarker detection or quantification in order to purify or enrich the sample for a particular fraction or cell type of interest. For example, the sample can be enriched for IEC-interacting cells (e.g., APCs or tumor cells), or a particular subset of IEC-interacting cells (e.g., dendritic cells, macrophages, monocytes or a combination thereof). In preferred embodiments, the sample is enriched for dendritic cells (e.g., CD11c+ dendritic cells) prior to Th1 immune status biomarker detection or quantification. Methods for enriching biological samples for a particular cell type are well known in the art. For example, dendritic cells may be isolated by differential gradient separation using, for example, Ficoll-hypaque or sucrose gradient solutions for cell separations, followed by ammonium chloride or hypotonic lysis of remaining contaminating erythrocytes (“Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis, J. E., ed. (1994); “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds)).
Sample preparation methods may comprise steps of homogenizing a sample in a suitable buffer, removal of contaminants and/or assay inhibitors, adding a Th1 immune status biomarker capture reagent (e.g., a magnetic bead which is linked to a moiety that can specifically bind to a target Th1 immune status biomarker), incubated under conditions that promote the association of the target biomarker with the capture reagent to produce a target biomarker: capture reagent complex, and incubating the target biomarker: capture complex under target biomarker-release conditions. In some embodiments, multiple Th1 immune status biomarkers are isolated in each round of isolation by adding multiple Th1 immune status biomarkers capture reagents (e.g., specific to the desired biomarkers) to the solution. For example, in an illustrative embodiment in which the biomarker is a nucleic acid, multiple Th1 immune status biomarker capture reagents, each comprising an oligonucleotide specific for a different target Th1 immune status biomarker can be added to the sample for isolation of multiple Th1 immune status biomarkers. It is contemplated that the methods encompass multiple experimental designs that vary both in the number of capture steps and in the number of target Th1 immune status biomarkers captured in each capture step. In some embodiments, capture reagents are molecules, moieties, substances, or compositions that preferentially (e.g., specifically and selectively) interact with a particular biomarker sought to be isolated, purified, detected, and/or quantified. Any capture reagent having desired binding affinity and/or specificity to the particular Th1 immune status biomarker can be used in the present technology. For example, the capture reagent can be a macromolecule such as a peptide, a protein (e.g., an antibody or receptor), an oligonucleotide, a nucleic acid, (e.g., nucleic acids capable of hybridizing with the Th1 immune status biomarkers), vitamins, oligosaccharides, carbohydrates, lipids, or small molecules, or a complex thereof. As illustrative and non-limiting examples, an avidin target capture reagent may be used to isolate and purify targets comprising a biotin moiety, an antibody may be used to isolate and purify targets comprising the appropriate antigen or epitope, and an oligonucleotide may be used to isolate and purify a complementary oligonucleotide.
Any nucleic acids, including single-stranded and double-stranded nucleic acids, that are capable of binding, or specifically binding, to a target Th1 immune status biomarker can be used as the capture reagent. Examples of such nucleic acids include DNA, RNA, aptamers, peptide nucleic acids, and other modifications to the sugar, phosphate, or nucleoside base. Thus, there are many strategies for capturing a target and accordingly many types of capture reagents are known to those in the art.
In addition, Th1 immune status biomarker capture reagents may comprise a functionality to localize, concentrate, aggregate, etc. the capture reagent and thus provide a way to isolate and purify the target Th1 immune status biomarker when captured (e.g., bound, hybridized, etc.) to the capture reagent (e.g., when a target:capture reagent complex is formed). For example, in some embodiments the portion of the capture reagent that interacts with the Th1 immune status biomarker (e.g., a polypeptide) is linked to a solid support (e.g., a bead, surface, resin, column, and the like) that allows manipulation by the user on a macroscopic scale. Often, the solid support allows the use of a mechanical means to isolate and purify the target:capture reagent complex from a heterogeneous solution. For example, when linked to a bead, separation is achieved by removing the bead from the heterogeneous solution, e.g., by physical movement. In embodiments in which the bead is magnetic or paramagnetic, a magnetic field is used to achieve physical separation of the capture reagent (and thus the target Th1 immune status biomarker) from the heterogeneous solution.
2.3 Evaluation of Th1 Immune Status Biomarker Polypeptides
In order to obtain the biomarker value, the Th1 immune status biomarkers may be quantified or detected using any suitable technique that is known in the art. In specific embodiments, the Th1 immune status biomarkers are quantified using reagents that determine the level, abundance or amount of individual Th1 immune status biomarkers. Non-limiting reagents of this type include reagents for use in protein-based and nucleic acid-based assays.
Th1 immune status biomarker expression may be evaluated at the level of protein expression, either by demonstration of the presence of the protein, or by one or more known functional properties of the biomarker. For example, anti-PD-L2 antibodies for use in PD-L2-specific protein detection are described in U.S. Pat. No. 7,709,214; U.S. patent application Ser. No. 2009/296,392; and European Pat. No. 1537878, which are incorporated by reference herein in their entirety. The antibodies bind both native and denatured PD-L2 protein and may be detected by several well-known assays in the art, including enzyme linked immunosorbent assays (ELISA), radioimmunoassays (RIA), light emission immunoassays, Western blot analysis, immunofluorescence assays, immunohistochemistry and fluorescence activated cell sorting (FACS) analysis.
ELISA and RIA follow similar principles for detection of specific antigens. By way of an illustrative example, PD-L2 can be measured using RIA by way of a PD-L2-specific antibody that is radioactively labeled, typically with 125I. In ELISA assays a PD-L2-specific antibody is chemically linked to an enzyme. PD-L2-specific capturing antibody is immobilized onto a solid support. Unlabeled specimens, e.g., protein extracts from biological samples are then incubated with the immobilized antibody under conditions where non-specific binding is blocked, and unbound antibody and/or protein removed by washing. Bound PD-L2 is detected by a second PD-L2 specific labeled antibody. Antibody binding is measured directly in RIA by measuring radioactivity, while in ELISA binding is detected by a reaction converting a colourless substrate into a coloured reaction product, as a function of linked-enzyme activity. Changes can thus readily be detected by spectrophotometry (Janeway C. A. et al. (1997). “Immunobiology” 3.sup.rd Edition, Current Biology Ltd., Garland Publishing Inc.; “Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis, J. E., ed. (1994); “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds)). Both assays therefore provide a means of quantification of PD-L2 protein content in a biological sample.
Protein biomarker expression may also be detected via light emission immunoassays. Much like ELISA and RIA, in light emission immunoassays the biological sample/protein extract to be tested is immobilized on a solid support, and probed with a specific label, labeled anti-PD-L2 antibody. The label, in turn, is luminescent, and emits light upon binding, as an indication of specific recognition. Luminescent labels include substances that emit light upon activation by electromagnetic radiation, electro chemical excitation, or chemical activation and may include fluorescent and phosphorescent substances, scintillators, and chemiluminescent substances. The label can be a part of a catalytic reaction system such as enzymes, enzyme fragments, enzyme substrates, enzyme inhibitors, coenzymes, or catalysts; part of a chromogen system such as fluorophores, dyes, chemiluminescers, luminescers, or sensitizers; a dispersible particle that can be non-magnetic or magnetic, a solid support, a liposome, a ligand, a receptor, a hapten radioactive isotope, and so forth (U.S. Pat. Nos. 6,410,696, 4,652,533 and European Patent Application No. 0,345,776), and provide an additional, highly sensitive method for detection of PD-L2 protein expression.
Western blot analysis is another means of assessing Th1 immune status biomarker polypeptide content in a biological sample. Protein extracts from biological samples of IEC-interacting cells (e.g., APCs, such as dendritic cells, or tumor cells), are solubilized in a denaturing ionizing environment, and aliquots are applied to polyacrylamide gel matrixes. Proteins separate based on molecular size properties as they migrate toward the anode. Antigens are then transferred to nitrocellulose, PVDF or nylon membranes, followed by membrane blocking to minimize non-specific binding. Membranes are probed with antibodies directly coupled to a detectable moiety, or are subsequently probed with a secondary antibody containing the detectable moiety. Typically, the enzymes horseradish peroxidase or alkaline phosphatase are coupled to the antibodies, and chromogenic or luminescent substrates are used to visualize activity (Harlow E. et al., (1998) Immunoblotting. In Antibodies: A Laboratory Manual, pp. 471-510 CSH Laboratory, cold Spring Harbor, N.Y. and Bronstein I. et al. (1992) Biotechniques 12: 748-753).
Unlike RIA, ELISA, light emission immunoassays and immunoblotting, which quantify protein biomarker content in whole samples, immunofluorescence/immunocytochemistry may be used to detect proteins in a cell-specific manner, though quantification is compromised.
As described above, IEC-interacting cells (e.g., APCs, including dendritic cells, or tumor cells) may be isolated or enriched by methods known in the art. Isolation or enrichment of IEC-interacting cells (e.g., APCs or tumor cells) refers to a process wherein the percentage of IEC-interacting cells (e.g., APCs or tumor cells) is increased (relative to the percentage in the sample before the enrichment procedure). Purification is one example of enrichment. In certain embodiments, the increase in the number of IEC-interacting cells (e.g., APCs or tumor cells) of the invention as a percentage of cells in the enriched sample, relative to the sample prior to the enrichment procedure, is at least 25-, 50-, 75-, 100-, 150-, 200-, 250-, 300-, 350-fold, and suitably is 100-200-fold. In specific embodiments, antibodies to surface markers on IEC-interacting cells (e.g., APCs or tumor cells) may be attached to a solid support to allow for separation. Procedures for separation may include magnetic separation, using antibody magnetic beads (e.g., Miltenyi™ beads), affinity chromatography, “panning” with antibody attached to a solid matrix or any other convenient technique such as Laser Capture Microdissection. In specific embodiments, the APCs are enriched using an antibody that is specific for CD11c, which antibody is conjugated to a magnetic bead, and a magnetic cell separation device to separate out the CD11c+ cells. Other techniques providing particularly accurate separation include FACS. Once cells are deposited on slides, they may be fixed, and probed with labeled antibody for detection of Th1 immune status biomarker in a cell specific fashion.
Antibodies specific for a Th1 immune status biomarker, for example, anti-PD-L2 antibodies, may be directly conjugated to fluorescent markers, including fluorescein, FITC, rhodamine, Texas Red, Cy3, Cy5, Cy7, and other fluorescent markers, and viewed in a fluorescent microscope, equipped with the appropriate filters. Antibodies may also be conjugated to enzymes, which upon addition of an appropriate substrate commence a reaction providing a coloured precipitate over cells with detected PD-L2 protein. Slides may then be viewed by standard light microscopy. Alternatively, primary antibodies specific for PD-L2 may be further bound to secondary antibodies conjugated to the detectable moieties. Cell surface expression can be thus assessed, and the addition of cell permeabilization solutions, such as Triton-X and saponin may be applied to facilitate reagent penetration within cell cytoplasms (“Cell Biology: A Laboratory Handbook”, Volumes 1-111 Cellis, J. E., ed. (1994); “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds), “Basic and Clinical Immunology” (8th Edition), Appleton & Lange, Norwalk, Conn. (1994); Mishell and Shiigi (eds), “Selected Methods in Cellular Immunology”, W. H. Freeman and Co., New York (1980)).
Immunohistochemistry is quite similar to immunofluorescence or immunocytochemistry, in principle, however tissue specimens are probed with PD-L2 antibody, for example, as opposed to cell suspensions. Biopsy specimens are fixed and processed and optionally embedded in paraffin, sectioned if needed, providing cell or tissue slides subsequently probed with heparanase specific antibodies. Alternatively, frozen tissue may be sectioned on a cryostat, with subsequent antibody probing, obviating fixation-induced antigen masking. Antibodies, as in immunofluorescence or immunocytochemistry, are coupled to a detectable moiety, either fluorescent, or enzyme-linked, and are used to probe tissue sections by methods described for immunofluorescence, and are subsequently visualized by fluorescent or confocal microscopy, depending upon the detection method employed. Visualization of a reaction product precipitate may be viewed by standard light microscopy, if an enzymatic detectable moiety was utilized, following development of the reaction product (“Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis, J. E., ed. (1994); “Current Protocols in Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al. (eds), “Basic and Clinical Immunology” (8th Edition), Appleton & Lange, Norwalk, Conn. (1994); Mishell and Shiigi (eds), “Selected Methods in Cellular Immunology”, W. H. Freeman and Co., New York (1980)).
In specific embodiments, FACS analysis is used to assess Th1 immune status biomarker expression (e.g., PD-L2, and optionally PD-L1, expression). A general description of FACS apparatus and methods in provided in U.S. Pat. Nos. 4,172,227; 4,347,935; 4,661,913; 4,667,830; 5,093,234; 5,094,940; and 5,144,224. Cells are introduced into the FACS machine and are delivered via tubing into the FACS cell, which they pass through as single cells. A laser beam is directed at the FACS cell, and forward laser scatter is collected by a photodiode, side laser scatter is directed to a PMT tube via a lens, directed to PMT1. Specific filters direct fluorescence from the side scatter to other PMT tubes for multivariate analysis. Side laser scatter is a reflection of cell size and granularity, and may be used to identify cell populations in mixed samples. Cells labeled with fluorescent anti-PD-L2 antibody may be detected by laser excitation and collection via PMT tubes, which can be identified for cell type via size and granularity, or via incorporation of additional cell surface markers for identification, as for example disclosed above. Typically, FACS analysis is used for determination of cell surface expression of a particular protein (e.g., PD-L2, and optionally PD-L1, expression), and hence specific antibodies may be utilized for probing detection of cell surface biomarker expression in APC populations (e.g., PD-L2, and optionally PD-L1, expression on the surface of dendritic cells). Specific APC subtypes (e.g., CD11c+ dendritic cells) expressing surface PD-L2 protein and optionally PD-L1 may be ascertained by size and granularity characteristics, or alternatively by co-staining with additional cell surface marker proteins.
In specific embodiments, protein-capture arrays that permit simultaneous detection and/or quantification of a large number of proteins are employed. For example, low-density protein arrays on filter membranes, such as the universal protein array system (Ge, 2000 Nucleic Acids Res. 28(2):e3) allow imaging of arrayed antigens using standard ELISA techniques and a scanning charge-coupled device (CCD) detector. Immuno-sensor arrays have also been developed that enable the simultaneous detection of clinical analytes. It is now possible using protein arrays, to profile protein expression in bodily fluids, such as in sera of healthy or diseased subjects, as well as in subjects pre- and post-drug treatment.
Exemplary protein capture arrays include arrays comprising spatially addressed antigen-binding molecules, commonly referred to as antibody arrays, which can facilitate extensive parallel analysis of numerous proteins defining a proteome or subproteome. Antibody arrays have been shown to have the required properties of specificity and acceptable background, and some are available commercially (e.g., BD Biosciences, Clontech, Bio-Rad and Sigma). Various methods for the preparation of antibody arrays have been reported (see, e.g., Lopez et al., 2003 J. Chromatogram. B 787:19-27; Cahill, 2000 Trends in Biotechnology 7:47-51; U.S. Pat. App. Pub. 2002/0055186; U.S. Pat. App. Pub. 2003/0003599; PCT publication WO 03/062444; PCT publication WO 03/077851; PCT publication WO 02/59601; PCT publication WO 02/39120; PCT publication WO 01/79849; PCT publication WO 99/39210). The antigen-binding molecules of such arrays may recognize at least a subset of proteins expressed by a cell or population of cells, illustrative examples of which include growth factor receptors, hormone receptors, neurotransmitter receptors, catecholamine receptors, amino acid derivative receptors, cytokine receptors, extracellular matrix receptors, antibodies, lectins, cytokines, serpins, proteases, kinases, phosphatases, ras-like GTPases, hydrolases, steroid hormone receptors, transcription factors, heat-shock transcription factors, DNA-binding proteins, zinc-finger proteins, leucine-zipper proteins, homeodomain proteins, intracellular signal transduction modulators and effectors, apoptosis-related factors, DNA synthesis factors, DNA repair factors, DNA recombination factors and cell-surface antigens.
Individual spatially distinct protein-capture agents are typically attached to a support surface, which is generally planar or contoured. Common physical supports include glass slides, silicon, microwells, nitrocellulose or PVDF membranes, and magnetic and other microbeads.
Particles in suspension can also be used as the basis of arrays, providing they are coded for identification; systems include color coding for microbeads (e.g., available from Luminex, Bio-Rad and Nanomics Biosystems) and semiconductor nanocrystals (e.g., QDots™, available from Quantum Dots), and barcoding for beads (UltraPlex™, available from Smartbeads) and multimetal microrods (Nanobarcodes™ particles, available from Surromed). Beads can also be assembled into planar arrays on semiconductor chips (e.g., available from LEAPS technology and BioArray Solutions). Where particles are used, individual protein-capture agents are typically attached to an individual particle to provide the spatial definition or separation of the array. The particles may then be assayed separately, but in parallel, in a compartmentalized way, for example in the wells of a microtiter plate or in separate test tubes.
In operation, a protein sample, which is optionally fragmented to form peptide fragments (see, e.g., U.S. Pat. App. Pub. 2002/0055186), is delivered to a protein-capture array under conditions suitable for protein or peptide binding, and the array is washed to remove unbound or non-specifically bound components of the sample from the array. Next, the presence or amount of protein or peptide bound to each feature of the array is detected using a suitable detection system. The amount of protein bound to a feature of the array may be determined relative to the amount of a second protein bound to a second feature of the array. In certain embodiments, the amount of the second protein in the sample is already known or known to be invariant.
In specific embodiments, the Th1 immune status biomarker is a target polypeptide whose level is measured using at least one antigen-binding molecule that is immuno-interactive with the target polypeptide. In these embodiments, the measured level of the target polypeptide is normalized to the level of a reference polypeptide. Suitably, the antigen-binding molecule is immobilized on a solid or semi-solid support. In illustrative examples of this type, the antigen-binding molecule forms part of a spatial array of antigen-binding molecule. In some embodiments, the level of antigen-binding molecule that is bound to the target polypeptide is measured by immunoassay (e.g., using an ELISA).
Demonstration of the absence or presence of biomarker activity within a sample is an additional means of distinguishing IEC-interacting cells (e.g., APCs or tumor cells) expressing a specific Th1 immune status biomarker versus non-expressing cell populations.
2.4 Evaluation of PD-L2 Biomarker Clustering
The present inventors have also discovered that clustering of PD-L2 on the cell surface of IEC-interacting cells (e.g., APCs or tumor cells) is indicative of a normal or elevated Th1 immune response. Thus, in some embodiments the biomarker value of the Th1 immune status biomarker is indicative of the level or abundance of PD-L2, as determined by analyzing the PD-L2 clustering on the cell surface of an APC (e.g., a dendritic cell).
There are a number of widely available assays to detect clustering of PD-L2 on the cell surface of an APC (e.g., a dendritic cell). For example, PD-L2 ligands and/or PD-L2-specific antibodies can be labeled, and these labels detected to visualize clustering of PD-L2. In one example of this type of assay, a dendritic cell comprising the PD-L2 is contacted with a PD-L2-specific antibody, and a fluorescently labeled secondary antibody that binds to the PD-L2-specific antibody. Using confocal scanning laser microscopy, fluorescence emitted from the secondary antibody can be detected to identify the location of the PD-L2. (Van Steensel, et al., 1995. J. Cell Sci. 108: 3003-3011). In another example, a cell comprising PD-L2 on the cell surface is contacted with a labeled ligand of the cell surface PD-L2 and cell surface PD-L2 clustering analyzed by super resolution microscopy, as described for example by Kaufmann et al. (2011. J. Microsc. 242(1):46-54), Huber et al. (2011. PLoS One. 7(9):e44776), Wang et al. (2014. Biochim. Biophys. Acta. 1838(4):1191-1198), and Sams et al. (2014. J Biomed. Opt. 19(1):011021).
Alternatively, cell surface PD-L2 clustering is analyzed by in situ proximity assay as described for example by Bellucci et al. (2014. Methods Mol. Biol. 1174:397-405), Barros et al. (2014. Breast Cancer Res. Treat. 144(2):273-85) and Pacchiana et al. (2014. Histochem. Cell. Biol. 142(5):593-60).
In other embodiments, FRET and FRAP microscopy can be employed to analyze PD-L2 clustering, as described for example by Wallrabe et al. (2003. Biophys. J. 85(1):559-571), Wallrabe et al. (2003. J. Biomed. Opt. 8(3):339-346) and de Heus et al. (2013. Methods Cell. Biol. 117:305-321).
Other methods of analyzing PD-L2 clustering include: image correlation spectroscopy as described for example by Petersen et al. (1998. Faraday Discuss. (111):289-305), Kozer et al. (2013. Mol. Biosyst. 9(7):1849-1863), and Ciccotosto et al. (2013. Biophys. J. 104(5):1056-1064); electric field analysis, as described for example by Giugni et al. (1987. J. Cell. Biol. 104(5):1291-1297), and Zhang et al. (2011. PLoS One. 6(10):e26805), electron microscopy, as described for example by Plowman et al. (2005. Proc. Natl. Acad. Sci. USA. 102(43):15500-15505), and D'Amico et al. (2008. Micron. 39(1):1-6); electron cryotomography, as described for example by Gold et al. (2014. Nat. Commun. 5:4129); nanoparticle (NP) immunolabelling in combination with plasmon coupling microscopy (PCM), as described for example by Wang et al. (2012. Nano. Lett. 12(6):3231-3237) and Rong et al. (2012. PLoS One. 7(3):e34175); enzyme-mediated activation of radical source (EMARS) analysis, as described for example by Miyagawa-Yamaguchi et al. (2014. PLoS One. 9(3):e93054) and Kotani et al. (2008. Proc. Natl. Acad. Sci. USA. 105(21):7405-7409); and quantum dots analysis, as described for example by Li et al. (2010. Biophys. J. 98(11):2554-2563).
In other embodiments, a flow cytometer equipped with a doublet discriminator is used to determine the distribution of a labeled PD-L2 ligand on a single cell. The distribution of the label on the cell is then correlated with the formation of PD-L2 clusters to thereby determine the receptor element clustering status of the cell. An exemplary method of this type is disclosed in U.S. Pat. Appl. Pub. No. 2016/0003840.
Numerous ligands with specificity for PD-L2 are known, which can be used for clustering analysis. Many of these are also useful as therapeutic agents in accordance with the present invention. For example, any suitable antibody that binds a PD-L2 polypeptide is contemplated for use in the practice of the present invention. Non-limiting examples of such antibodies are listed above.
In specific embodiments, the antibody comprises an Fc region of an immunoglobulin. Alternatively, or in addition, the antibody is a multivalent (e.g., bivalent) antibody.
Any PD-L2 ligand is suitable for use in these embodiments of the invention, including the following classes of ligand: protein, small organic molecule, carbohydrates (including polysaccharides), polynucleotide, lipids, etc. Representative examples of such ligands include PD-1 polypeptides, galectin-9 polypeptides, and repulsive guidance molecule b (RGMb).
2.5 Evaluation of Th1 Immune Status Biomarker Nucleic Acids
In some embodiments, biomarker expression is monitored by determining biomarker nucleic acid transcript levels. RNA may be extracted from biological samples via a number of standard techniques (see Current Protocols in Molecular Biology” Volumes I-III Ausubel, R. M., ed. (1994); Ausubel et al., “Current Protocols in Molecular Biology”, John Wiley and Sons, Baltimore, Md. (1989)). Guanidium-based methods for cell lysis enabling RNA isolation, with subsequent cesium chloride step gradients for separation of the RNA from other cellular macromolecules, followed by RNA precipitation and resuspension, is an older, less commonly employed method of RNA isolation (Glisin, Ve. et al., (1973) Biochemistry 13: 2633). Alternatively, RNA may be isolated in a single step procedure (U.S. Pat. No. 4,843,155, and Puissant, C. And Houdebine L. M. (1990) Biotechniques 8: 148-149). Single step procedures include the use of Guanidium isothiocyanate for RNA extraction, and subsequent phenol/chloroform/isoamyl alcohol extractions facilitating the separation of total RNA from other cellular proteins and DNA. Commercially available single-step formulations based on the above-cited principles may be employed, including, for example, the use of the TRIZOL reagent (Life Technologies, Gaithersburg, Md.).
Th1 immune status biomarker RNA/gene expression can be monitored via a number of other standard techniques, illustrative examples of which include Northern blot and dot blot analysis, primer extension, RNase protection, RT-PCR, in-situ hybridization and chip hybridization.
Specific Th1 immune status biomarker RNA sequences can be readily detected by hybridization of labeled probes to blotted RNA preparations extracted as above. In Northern blot analysis, fractionated RNA is subjected to denaturing agarose gel electrophoresis, which prevents RNA from assuming secondary structures that might inhibit size based separation. RNA is then transferred by capillary transfer to a nylon or nitrocellulose membrane support and may be probed with a labeled oligonucleotide probe complementary to the biomarker sequence (Alwine, et al. (1977). Proc. Natl. Acad. Sci. USA 74: 5350-5354 and Current Protocols in Molecular Biology” Volumes I-III Ausubel, R. M., ed. (1994); Ausubel et al., “Current Protocols in Molecular Biology”, John Wiley and Sons, Baltimore, Md. (1989)).
Alternatively, unfractionated RNA may be immobilized on a nylon or nitrocellulose membrane, and similarly probed for biomarker-specific expression, by Slot/Dot blot analysis. RNA slot/dot blots can be prepared by hand, or alternatively constructed using a manifold apparatus, which facilitates comparing hybridization signals by densitometry scanning (Chomczynski P. (1992) Anal. Biochem. 201: 134-139).
Primer extension is another means whereby quantification of the RNA may be accomplished. Primer extension provides an additional benefit in mapping the 5′ terminus of a particular RNA, by extending a primer using the enzyme reverse transcriptase. In this case, the primer is an oligonucleotide (or restriction fragment) complementary to a portion of the biomarker mRNA. The primer is end-labeled, and is allowed to hybridize to template biomarker mRNA. Once hybridized, the primer is extended by addition of reverse transcriptase, and incorporation of unlabeled deoxynucleotides to for a single-stranded DNA complementary to template biomarker mRNA. DNA is then analyzed on a sequencing gel, with the length of extended primer serving to map the 5′ position of the mRNA, and the yield of extended product reflecting the abundance of RNA in the sample (Jones et al., (1985) Cell. 42: 559-572 and Mierendorf R. C. And Pfeffer, D. (1987). Methods Enzymol. 152: 563-566).
RNase protection assays provide a highly sensitive means of quantifying biomarker RNA, even in low abundance. In protection assays, sequence-specific hybridization of ribonucleotide probes complementary to biomarker RNA, with high specific activity are generated, and hybridized to sample RNA. Hybridization reactions are then treated with ribonuclease to remove free probe, leaving intact fragments of annealed probe hybridized to homologous biomarker sequences in sample RNA. Fragments are then analyzed by electrophoresis on a sequencing gel, when appropriately-sized probe fragments are visualized (Zinn K. et al., (1983) Cell. 34: 865-879 and Melton S. A., et al., (1984). Nucl. Acids Res. 12: 7035-7056).
RT-PCR is another means by which biomarker expression may be analyzed. RT-PCR employs the use of reverse transcriptase to prepare cDNA from RNA samples, using deoxynucleotide primers complementary to the biomarker mRNA. Once the cDNA is generated, it is amplified through the polymerase chain reaction, by the addition of deoxynucleotides and a DNA polymerase that functions at high temperatures. Through repetitive cycles of primer annealing, incorporation of deoxynucleotides facilitating cDNA extension, followed by strand denaturation, amplification of the desired sequence occurs, yielding an appropriately sized fragment that may be detected by agarose gel electrophoresis. Optimal reverse transcription, hybridization, and amplification conditions will vary depending upon the sequence composition and length(s) of the primers and target(s) employed, and the experimental method selected by the practitioner. Various guidelines may be used to select appropriate primer sequences and hybridization conditions (see, e.g., Sambrook et al., 1989, Molecular Cloning, A Laboratory Manual, (Volumes 1-3) Cold Spring Harbor Press, N.Y.; and Ausubel et al., 1989, Current Protocols in Molecular Biology, Green Publishing Associates and Wiley Interscience, N.Y.).
In-situ hybridization provides may be used for detecting and localizing cell/tissue specific biomarker RNA expression. Labeled anti-sense RNA probes are hybridized to mRNAs in cells singly, or in processed tissue slices, which are immobilized on microscope glass slides (In Situ Hybridization: Medical Applications (eds. G. R. Coulton and J. de Belleroche), Kluwer Academic Publishers, Boston (1992); In Situ Hybridization: In Neurobiology; Advances in Methodology (eds. J. H. Eberwine, K. L. Valentino, and J. D. Barchas), Oxford University Press Inc., England (1994); and In Situ Hybridization: A Practical Approach (ed. D. G. Wilkinson), Oxford University Press Inc., England (1992)). Numerous non-isotopic systems have been developed to visualize labeled DNA probes including; a) fluorescence-based direct detection methods, b) the use of digoxigenin- and biotin-labeled DNA probes coupled with fluorescence detection methods, and c) the use of digoxigenin- and biotin-labeled DNA probes coupled with antibody-enzyme detection methods. When fluorescence-labeled anti-sense RNA probes are hybridized to cellular RNA, the hybridized probes can be viewed directly using a fluorescence microscope. Direct fluorochrome-labelling of the nucleic acid probes eliminate the need for multi-layer detection procedures (e.g., antibody-based-systems), which allows fast processing and also reduces non-specific background signals, hence providing a versatile and highly sensitive means of identifying biomarker gene expression.
Chip hybridization utilizes biomarker specific oligonucleotides attached to a solid substrate, which may consist of a particulate solid phase such as nylon filters, glass slides or silicon chips (Schena et al. (1995) Science. 270:467-470) designed as a microarray. Microarrays are known in the art and consist of a surface to which probes that correspond in sequence to gene products (such as cDNAs) can be specifically hybridized or bound at a known position for the detection of biomarker gene expression.
Quantification of the hybridization complexes is well known in the art and may be achieved by any one of several approaches. These approaches are generally based on the detection of a label or marker, such as any radioactive, fluorescent, biological or enzymatic tags or labels of standard use in the art. A label can be applied to either the oligonucleotide probes or the RNA derived from the biological sample.
In general, mRNA quantification is suitably effected alongside a calibration curve so as to enable accurate mRNA determination. Furthermore, quantifying transcript(s) originating from a biological sample is preferably effected by comparison to a normal sample, which sample is characterized by normal expression pattern of the examined transcript(s).
2.6 Deriving Biomarker Values
Biomarker values can be measured biomarker values, which are values of biomarkers directly measured for the subject, or alternatively could be “derived” biomarker values, which are values that have been derived from one or more measured biomarker values, for example by applying a function to the one or more measured biomarker values. As used herein, biomarkers to which a function has been applied are referred to as “derived biomarkers.”
The biomarker values may be determined in any one of a number of ways that are well known in the art. For example, a comprehensive description of biomarker value determination can be found in Intl. Pat. Pub. No. WO 2015/117204, which is incorporated herein by reference in its entirety. In one example, the process of determining biomarker values can include measuring the biomarker values, for example by performing tests on the subject or on sample(s) obtained from the subject.
More typically, however, the step of determining the biomarker values includes having an electronic processing device receive or otherwise obtain biomarker values that have been previously measured or derived. This could include for example, retrieving the biomarker values from a data store such as a remote database, obtaining biomarker values that have been manually input, using an input device, or the like. Suitably, the indicator may be determined using a combination of a plurality of biomarker values, the indicator being at least partially indicative of Th1 immune status. Assuming the method is performed using an electronic processing device, an indication of the indicator is optionally displayed or otherwise provided to the user.
In some embodiments, biomarker values are combined, for example by adding, multiplying, subtracting, or dividing biomarker values to determine an indicator value. This step is performed so that multiple biomarker values can be combined into a single indicator value, providing a more useful and straightforward mechanism for allowing the indicator to be interpreted and hence used in determining the Th1 immune status of the subject.
It will be understood that in this context, the biomarkers used within the above-described method can define a biomarker profile for Th1 immune status, which includes a minimal number of biomarkers (e.g., at least one biomarker), whilst maintaining sufficient performance to allow the biomarker profile to be used in making a clinically relevant determination. Minimizing the number of biomarkers used minimizes the costs associated with performing diagnostic or prognostic tests and in the case of polypeptide biomarkers, allows the test to be performed utilizing relatively straightforward techniques such as fluorescence-activated cell sorting (FACS) and immunohistochemistry, and allowing the test to be performed rapidly in a clinical environment. In this regard, the indication provided by the methods described herein could be a graphical or alphanumeric representation of an indicator value. Alternatively, however, the indication could be the result of a comparison of the indicator value to predefined thresholds or ranges, or alternatively could be an indication of the Th1 immune status.
Furthermore, producing a single indicator value allows the results of the test to be easily interpreted by a clinician or other medical practitioner, so that test can be used for reliable diagnosis in a clinical environment.
Solely by way of an illustration, the indicator-determining methods suitably include determining at least one biomarker value, wherein the biomarker value is a value measured or derived for at least one Th1 immune status biomarker of the subject and is at least partially indicative of a concentration or abundance of the Th1 immune status biomarker in a sample taken from the subject, and wherein the at least one Th1 immune status biomarker comprises PD-L2 of IEC-interacting cells (e.g., APCs or tumor cells). Suitably, the Th1 immune status biomarker profile further comprises PD-L1 of IEC-interacting cells (e.g., APCs or tumor cells) as a Th1 immune status biomarker. The biomarker values are typically used to determine an indicator for use in determining the Th1 immune status of a subject. In some embodiments, the indicator is indicative of a ratio of concentrations of a pair of Th1 immune status biomarkers (e.g., PD-L2 and PD-L1). Thus, if the biomarker values denote the concentrations of the Th1 immune status biomarker, then the derived biomarker value will typically (although not exclusively) be based on a ratio of the biomarker values.
The derived biomarker value is then used to determine the indicator, either by using the derived biomarker value as an indicator value, or by performing additional processing, such as comparing the derived biomarker value to a reference or the like, as generally known in the art and as described in more detail below.
The derived biomarker values could be combined using a combining function such as an additive model; a linear model; a support vector machine; a neural network model; a random forest model; a regression model; a genetic algorithm; an annealing algorithm; a weighted sum; a nearest neighbor model; and a probabilistic model. In some embodiments, biomarker values are measured or derived for PD-L2 and for PD-L1, and the indicator is determined by combining the biomarker values. In some embodiments, the indicator is compared to an indicator reference, with a Th1 immune status being determined in accordance with results of the comparison. The indicator reference may be derived from indicators determined for a number of individuals in a reference population. The reference population typically includes individuals having different characteristics, such as a plurality of individuals of different sexes; and/or ethnicities, with different groups being defined based on different characteristics, with the subject's indicator being compared to indicator references derived from individuals with similar characteristics. The reference population can also include a plurality of healthy individuals, a plurality of individuals known to have an enhanced Th1 immune status, a plurality of individuals known to have a reduced or deficient Th1 immune status, a plurality of individuals showing clinical signs of a metastatic cancer, a plurality of individuals showing clinical signs of a pathogenic infection (e.g., malaria), a plurality of individuals showing clinical signs of an autoimmune disease (e.g., irritable bowel syndrome).
In specific embodiments, the indicator-determining methods of the present invention are performed using at least one electronic processing device, such as a suitably programmed computer system or the like. In this case, the electronic processing device typically obtains at least one measured biomarker value, either by receiving this from a measuring or other quantifying device, or by retrieving these from a database or the like. The processing device then determines the indicator by any suitable means, for example, by calculating a value that is indicative of a ratio of concentrations of a first Th1 immune status biomarker and a second Th1 immune status biomarker. In one aspect, the present invention encompasses an apparatus comprising such electronic processing device(s).
The processing device can then generate a representation of the indicator, for example by generating a sign or alphanumeric indication of the indicator, a graphical indication of a comparison of the indicator to one or more indicator references or an alphanumeric indication of the Th1 immune status of the subject.
The indicator-determining methods of the present invention typically include obtaining a sample from a subject, who typically has at least one clinical sign of a Th1-related disease (for example, irritable bowel syndrome), wherein the sample includes one or more Th1 immune status biomarkers (e.g., PD-L2 and optionally PD-L1) and quantifying or otherwise assessing at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more) of the Th1 immune status biomarkers within the sample to determine biomarker values. This can be achieved using any suitable technique, and will depend on the nature of the Th1 immune status biomarkers. Suitably, an individual measured or derived Th1 immune status biomarker value corresponds to the level, abundance or amount of a respective Th1 immune status biomarker or to a function that is applied to that level or amount. For example, if the indicator in some embodiments of the indicator-determining method of the present invention, which uses a plurality of Th1 immune status biomarkers, is based on a ratio of concentrations of a polypeptide, this process would typically include quantifying the polypeptide by any means known in the art, including immunofluorescence, or by a functional assay.
In some embodiments, the Th1 immune status of a subject is established by determining one or more Th1 immune status biomarker values, wherein an individual Th1 immune status biomarker value is indicative of a value measured or derived for a Th1 immune status biomarker in a subject or in a sample obtained from the subject. These biomarkers are referred to herein as “sample Th1 immune status biomarkers.” In accordance with the present invention, a sample Th1 immune status biomarker corresponds to a reference Th1 immune status biomarker (also referred to herein as a “corresponding Th1 immune status biomarker”). By “corresponding Th1 immune status biomarker” is meant a Th1 immune status biomarker that is structurally and/or functionally similar to a reference Th1 immune status biomarker as set forth for example in SEQ ID NO:1 (PD-L2) and SEQ ID NO: 2 (PD-L1). Representative corresponding Th1 immune status biomarkers include expression products of allelic variants (same locus), homologues (different locus), and orthologues (different organism) of reference Th1 immune response biomarker genes. Nucleic acid variants of reference Th1 immune status biomarker genes and encoded Th1 immune status biomarker polypeptides can contain nucleotide substitutions, deletions, inversions and/or insertions. Variation can occur in either or both the coding and non-coding regions. The variations can produce both conservative and non-conservative amino acid substitutions (as compared in the encoded product). For nucleotide sequences, conservative variants include those sequences that, because of the degeneracy of the genetic code, encode the amino acid sequence of a reference Th1 immune status polypeptide.
Corresponding Th1 immune status biomarkers include amino acid sequences that display substantial sequence similarity or identity to the amino acid sequence of a reference Th1 immune status biomarker polypeptide. In general, an amino acid sequence that corresponds to a reference amino acid sequence will display at least about 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 97, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99% or even up to 100% sequence similarity or identity to a reference amino acid sequence selected from SEQ ID NO: 1 or SEQ ID NO: 2, as summarized in Table 4.
In some embodiments, calculations of sequence similarity or sequence identity between sequences are performed as follows:
To determine the percentage identity of two amino acid sequences, or of two nucleic acid sequences, the sequences are aligned for optimal comparison purposes (e.g., gaps can be introduced in one or both of a first and a second amino acid or nucleic acid sequence for optimal alignment and non-homologous sequences can be disregarded for comparison purposes). In some embodiments, the length of a reference sequence aligned for comparison purposes is at least 30%, usually at least 40%, more usually at least 50%, 60%, and even more usually at least 70%, 80%, 90%, 100% of the length of the reference sequence. The amino acid residues or nucleotides at corresponding amino acid positions or nucleotide positions are then compared. When a position in the first sequence is occupied by the same amino acid residue or nucleotide at the corresponding position in the second sequence, then the molecules are identical at that position. For amino acid sequence comparison, when a position in the first sequence is occupied by the same or similar amino acid residue (i.e., conservative substitution) at the corresponding position in the second sequence, then the molecules are similar at that position.
The percentage identity between the two sequences is a function of the number of identical amino acid residues shared by the sequences at individual positions, taking into account the number of gaps, and the length of each gap, which need to be introduced for optimal alignment of the two sequences. By contrast, the percentage similarity between the two sequences is a function of the number of identical and similar amino acid residues shared by the sequences at individual positions, taking into account the number of gaps, and the length of each gap, which need to be introduced for optimal alignment of the two sequences.
The comparison of sequences and determination of percentage identity or percentage similarity between sequences can be accomplished using a mathematical algorithm. In certain embodiments, the percentage identity or similarity between amino acid sequences is determined using the Needleman and Wunsch, (1970, J. Mol. Biol. 48: 444-453) algorithm which has been incorporated into the GAP program in the GCG software package (available at http://www.gcg.com), using either a Blossum 62 matrix or a PAM250 matrix, and a gap weight of 16, 14, 12, 10, 8, 6, or 4 and a length weight of 1, 2, 3, 4, 5, or 6. In specific embodiments, the percent identity between nucleotide sequences is determined using the GAP program in the GCG software package (available at http://www.gcg.com), using a NWSgapdna.CMP matrix and a gap weight of 40, 50, 60, 70, or 80 and a length weight of 1, 2, 3, 4, 5, or 6. An non-limiting set of parameters (and the one that should be used unless otherwise specified) includes a Blossum 62 scoring matrix with a gap penalty of 12, a gap extend penalty of 4, and a frameshift gap penalty of 5.
In some embodiments, the percentage identity or similarity between amino acid or nucleotide sequences can be determined using the algorithm of E. Meyers and W. Miller (1989, Cabios, 4: 11-17) which has been incorporated into the ALIGN program (version 2.0), using a PAM120 weight residue table, a gap length penalty of 12 and a gap penalty of 4.
The nucleic acid and protein sequences described herein can be used as a “query sequence” to perform a search against public databases to, for example, identify other family members or related sequences. Such searches can be performed using the NBLAST and XBLAST programs (version 2.0) of Altschul, et al., (1990, J. Mol. Biol., 215: 403-10). BLAST nucleotide searches can be performed with the NBLAST program, score=100, wordlength=12 to obtain nucleotide sequences homologous to 53010 nucleic acid molecules of the invention. BLAST protein searches can be performed with the XBLAST program, score=50, wordlength=3 to obtain amino acid sequences homologous to protein molecules of the invention. To obtain gapped alignments for comparison purposes, Gapped BLAST can be utilized as described in Altschul et al., (1997, Nucleic Acids Res. 25: 3389-3402). When utilizing BLAST and Gapped BLAST programs, the default parameters of the respective programs (e.g., XBLAST and NBLAST) can be used.
Corresponding Th1 immune status biomarker polynucleotides also include nucleic acid sequences that hybridize to reference Th1 immune status biomarker polynucleotides, or to their complements, under stringency conditions described below. As used herein, the term “hybridizes under low stringency, medium stringency, high stringency, or very high stringency conditions” describes conditions for hybridization and washing. “Hybridization” is used herein to denote the pairing of complementary nucleotide sequences to produce a DNA-DNA hybrid or a DNA-RNA hybrid. Complementary base sequences are those sequences that are related by the base-pairing rules. In DNA, A pairs with T and C pairs with G. In RNA, U pairs with A and C pairs with G. In this regard, the terms “match” and “mismatch” as used herein refer to the hybridization potential of paired nucleotides in complementary nucleic acid strands. Matched nucleotides hybridize efficiently, such as the classical A-T and G-C base pair mentioned above. Mismatches are other combinations of nucleotides that do not hybridize efficiently.
Guidance for performing hybridization reactions can be found in Ausubel et al., (1998, supra), Sections 6.3.1-6.3.6. Aqueous and non-aqueous methods are described in that reference and either can be used. Reference herein to low stringency conditions include and encompass from at least about 1% v/v to at least about 15% v/v formamide and from at least about 1 M to at least about 2 M salt for hybridization at 42° C., and at least about 1 M to at least about 2 M salt for washing at 42° C. Low stringency conditions also may include 1% Bovine Serum Albumin (BSA), 1 mM EDTA, 0.5 M NaHPO4 (pH 7.2), 7% SDS for hybridization at 65° C., and (i) 2×SSC, 0.1% SDS; or (ii) 0.5% BSA, 1 mM EDTA, 40 mM NaHPO4 (pH 7.2), 5% SDS for washing at room temperature. One embodiment of low stringency conditions includes hybridization in 6× sodium chloride/sodium citrate (SSC) at about 45° C., followed by two washes in 0.2×SSC, 0.1% SDS at least at 50° C. (the temperature of the washes can be increased to 55° C. for low stringency conditions). Medium stringency conditions include and encompass from at least about 16% v/v to at least about 30% v/v formamide and from at least about 0.5 M to at least about 0.9 M salt for hybridization at 42° C., and at least about 0.1 M to at least about 0.2 M salt for washing at 55° C. Medium stringency conditions also may include 1% Bovine Serum Albumin (BSA), 1 mM EDTA, 0.5 M NaHPO4 (pH 7.2), 7% SDS for hybridization at 65° C., and (i) 2×SSC, 0.1% SDS; or (ii) 0.5% BSA, 1 mM EDTA, 40 mM NaHPO4 (pH 7.2), 5% SDS for washing at 60-65° C. One embodiment of medium stringency conditions includes hybridizing in 6×SSC at about 45° C., followed by one or more washes in 0.2×SSC, 0.1% SDS at 60° C. High stringency conditions include and encompass from at least about 31% v/v to at least about 50% v/v formamide and from about 0.01 M to about 0.15 M salt for hybridization at 42° C., and about 0.01 M to about 0.02 M salt for washing at 55° C. High stringency conditions also may include 1% BSA, 1 mM EDTA, 0.5 M NaHPO4 (pH 7.2), 7% SDS for hybridization at 65° C., and (i) 0.2×SSC, 0.1% SDS; or (ii) 0.5% BSA, 1 mM EDTA, 40 mM NaHPO4 (pH 7.2), 1% SDS for washing at a temperature in excess of 65° C. One embodiment of high stringency conditions includes hybridizing in 6×SSC at about 45° C., followed by one or more washes in 0.2×SSC, 0.1% SDS at 65° C.
In certain embodiments, a corresponding Th1 immune status biomarker polynucleotide is one that hybridizes to a disclosed nucleotide sequence (e.g., SEQ ID NO: 3 or SEQ ID NO: 4) under very high stringency conditions. One embodiment of very high stringency conditions includes hybridizing 0.5 M sodium phosphate, 7% SDS at 65° C., followed by one or more washes at 0.2×SSC, 1% SDS at 65° C.
Other stringency conditions are well known in the art and a skilled addressee will recognize that various factors can be manipulated to optimize the specificity of the hybridization. Optimization of the stringency of the final washes can serve to ensure a high degree of hybridization. For detailed examples, see Ausubel et al., supra at pages 2.10.1 to 2.10.16 and Sambrook et al. (1989, supra) at sections 1.101 to 1.104.
2.6.1 Biomarker Detection Kits
All the essential reagents required for detecting and quantifying the Th1 immune status biomarkers of the invention may be assembled together in a kit. In some embodiments, the kit comprises a reagent that permits quantification of at least one Th1 immune status biomarker. In some embodiments, the kit comprises: (i) a reagent that allows quantification (e.g., determining the abundance or level) of a first Th1 immune status biomarker; and (ii) a reagent that allows quantification (e.g., determining the abundance or level) of a second Th1 immune status biomarker. In some embodiments, the kit further comprises (iii) an optional reagent that allows quantification (e.g., determining the abundance or level) of a third Th1 immune status biomarker; and (iv) an optional reagent that allows quantification (e.g., determining the abundance or level) of a fourth Th1 immune status biomarker. Suitably, the Th1 immune status biomarker is one or both of PD-L2 and PD-L1.
In the context of the present invention, “kit” is understood to mean a product containing the different reagents necessary for carrying out the methods of the invention packed so as to allow their transport and storage. Materials suitable for packing the components of the kit include crystal, plastic (polyethylene, polypropylene, polycarbonate and the like), bottles, vials, paper, envelopes and the like. Additionally, the kits of the invention can contain instructions for the simultaneous, sequential or separate use of the different components contained in the kit. The instructions can be in the form of printed material or in the form of an electronic support capable of storing instructions such that they can be read by a subject, such as electronic storage media (magnetic disks, tapes and the like), optical media (CD-ROM, DVD) and the like. Alternatively, or in addition, the media can contain internet addresses that provide the instructions.
Reagents that allow quantification of a Th1 immune status biomarker include compounds or materials, or sets of compounds or materials, which allow quantification of the Th1 immune status biomarker. In specific embodiments, the compounds, materials or sets of compounds or materials permit determining the level or abundance of a polypeptide (i.e., a PD-L2 polypeptide).
The kits may also optionally include appropriate reagents for detection of labels, positive and negative controls, washing solutions, blotting membranes, microtiter plates, dilution buffers and the like. For example, a protein-based detection kit may include (i) a Th1 immune status biomarker polypeptide (for example, PD-L2 polypeptide and optionally a PD-L1 polypeptide, which may be used as a positive control), (ii) an antibody that binds specifically to a Th1 immune status biomarker polypeptide. Alternatively, a nucleic acid-based detection kit may include (i) a Th1 immune status biomarker polynucleotide (for example, a PD-L2 polynucleotide and optionally a PD-L1 polynucleotide, which may be used as a positive control), (ii) a primer or probe that specifically hybridizes to a Th1 immune status biomarker polynucleotide. Also included may be enzymes suitable for amplifying nucleic acids including various polymerases (reverse transcriptase, Taq, Sequenase™, DNA ligase etc. depending on the nucleic acid amplification technique employed), deoxynucleotides and buffers to provide the necessary reaction mixture for amplification. Such kits also generally will comprise, in suitable means, distinct containers for each individual reagent and enzyme as well as for each primer or probe.
The kit can also feature various devices (e.g., one or more) and reagents (e.g., one or more) for performing one of the assays described herein; and/or printed instructions for using the kit to quantify the expression of a Th1 immune status biomarker gene.
The reagents described herein, which may be optionally associated with detectable labels, can be presented in the format of a microfluidics card, a chip or chamber, a microarray or a kit adapted for use with the assays described in the examples or below, e.g., RT-PCR or Q PCR techniques described herein.
The indicator can also be used for determining a likelihood of the subject having a disease that is associated with an undesirable Th1 immune response status. In this case, this would typically be achieved by comparing the indicator to at least one indicator reference, the indicator reference being indicative of the disease, and determining the likelihood in accordance with the results of the comparison. Non-limiting examples of Th1-related diseases include infectious diseases (particularly viral infections), autoimmune diseases, host versus graft disease (HVGD), tissue transplantation and proliferative disorders (e.g., a metastatic cancer).
In embodiments of this type, the at least one indicator reference is a distribution of indicators determined for a reference population. For example, if a subject presents with clinical symptoms of a pathogenic infection (e.g., hepatitis viruses, fungal infections such as aspergillus, human immunodeficiency virus (HIV), malaria, typhoid, cholera, herpes viruses, chlamydia, and HPV), then a reference group consisting of individuals with the same or a similar disease will be used to compare the indicator of the subject.
In some embodiments, a determination of the likelihood of a subject having the disease is made using more than one reference group of individuals. For example, a first reference group consisting of individuals previously diagnosed and known to have the disease of interest, and second reference group consisting of individuals diagnosed as having a healthy condition.
As described above, the methods of the present invention can be used to diagnose a disease that is associated with an elevated Th1 immune response and is therefore diagnosed when the level of PD-L2 and optionally PD-L1 in the sample obtained from the subject is above or below a predetermined threshold. Exemplary Th1-related diseases of this type are autoimmune diseases. For example, the autoimmune disease can be selected from any one of the group comprising: Alzheimer's disease, ankylosing spondylitis, atherosclerosis, autoimmune-associated infertility, autoimmune encephalomyelitis, autoimmune hemolytic anemia, autoimmune hemophilia, autoimmune hepatitis, autoimmune lymphoproliferative syndrome (ALPS), autoimmune thrombocytopenic purpura, autoimmune uveoretinitis, Barrett's esophagus, chronic fatigue syndrome (CFS/CFIDS/ME), bullous pemphigoid, chronic lyme disease (borreliosis), Crohn's disease, diabetes, depression, fibromyalgia (FM), gastritis, gastroesophageal reflux disease (GERD), glomerulonephritis (e.g., crescentic glomerulonephritis, proliferative glomerulonephritis), Goodpasture's syndrome, Grave's disease, Guillain-Barre syndrome, Hashimoto's thyroiditis, hemolytic anemia, hypertension, hyperthyroidism, hypothyroidism, idiopathic Addison's disease, insulin resistance, irritable bowel syndrome (IBS), interstitial cystitis (IC), kidney stones, Lofgren's syndrome, lupus erythematosus, mixed connective tissue disease, multiple chemical sensitivity (MCS), migraine headache, Morgellon's, multiple sclerosis, myasthenia gravis (MG), osteoarthritis, pemphigus (e.g, pemphigus vulgaris), pernicious anemia, polymyalgia rheumatic, polymyositis prostatitis, psoriasis, psoriatic arthritis, Raynaud's syndrome/phenomenon, reactive arthritis (Reiter syndrome), restless leg syndrome, reflex sympathetic dystrophy (RSD), rheumatoid arthritis, sarcoidosis, scleroderma, sinusitis, seasonal affective disorder (SAD), Sjdgren's syndrome, ulcerative colitis, uveitis, and vertigo.
Suitably, the Th1-related disease may be an infection with a virus, bacteria, fungi, or parasite. Viruses include, but are not limited to, Retroviridae human immunodeficiency viruses, such as HIV-1 (also referred to as HTLV-III, LAV or HTLV-III/LAV, or HIV-III); and other isolates, such as HIV-LP); Picornaviridae (e.g., polio viruses, hepatitis A virus; enteroviruses, human Coxsackie viruses, rhinoviruses, echoviruses); Calciviridae (e.g., strains that cause gastroenteritis, including Norwalk and related viruses); Togaviridae (e.g., equine encephalitis viruses, rubella viruses); Flaviridae (e.g., dengue viruses, encephalitis viruses, yellow fever viruses); Coronoviridae (e.g., coronaviruses); Rhabdoviradae (e.g., vesicular stomatitis viruses, rabies viruses); Filoviridae (e.g., ebola viruses); Pararnyxoviridae (e.g., parainfluenza viruses, mumps virus, measles virus, respiratory syncytial virus, metaneumovirus); Orthomyxoviridae (e.g., influenza viruses); Bungaviridae (e.g., Hantaan viruses, bunga viruses, phleboviruses and Nairo viruses); Arenaviridae (hemorrhagic fever viruses); Reoviridae (e.g., reoviruses, orbiviurses and rotaviruses); Birmaviridae; Hepadnaviridae (Hepatitis B virus); Parvovirida (parvoviruses); Papovaviridae (papilloma viruses, polyoma viruses); Adenoviridae (most adenoviruses); Herpesviridae (herpes simplex virus (HSV) 1 and 2, varicella zoster virus, cytornegalovirus (CMV), herpes virus); Poxyiridae (variola viruses, VACV, pox viruses); and Iridoviridae (e.g., African swine fever virus); and unclassified viruses (e.g., the etiological agents of Spongiforrn encephalopathies, the agent of delta hepatitis (thought to be a defective satellite of hepatitis B virus), the agents of non-A, non-B hepatitis (class 1=internally transmitted; class 2=parenterally transmitted (i.e., Hepatitis C); and astroviruses.
In some embodiments, the pathogenic infection is a bacterial pathogen. Bacteria from which are known to be pathogenic in a subject include, but are not limited to, pathogenic Pasteurella species (e.g., Pasteurella multocida), Staphylococci species (e.g., Staphylococcus aureus), Streptococcus species (e.g., Streptococcus pyogenes (Group A Streptococcus), Streptococcus agalactiae (Group B Streptococcus), Streptococcus (viridans group), Streptococcus faecalis, Streptococcus bovis, Streptococcus (anaerobic sps.), Streptococcus pneumoniae), Neisseria species (e.g., Neisseria gonorrhoeae, Neisseria meningitidis), Escherichia species (e.g., enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), enterohemorrhagic E. coli (EHEC), and enteroinvasive E. coli (EIEC)), Bordetella species, Campylobacter species, Legionella species (e.g., Legionella pneumophila), Pseudomonas species, Shigella species, Vibrio species, Yersinia species, Salmonella species, Haemophilus species (e.g., Haemophilus influenzae), Brucella species, Francisella species, Bacterioides species, Clostridia species (e.g., Clostridium difficile, Clostridium perfringens, Clostridium tetani), Mycobacteria species (e.g., M. tuberculosis, M. avium, M. intracellulare, M. kansaii, M. gordonae), Helicobacter pyloris, Borelia burgdorferi, Listeria monocytogenes, Chlamydia trachomatis, Enterococcus species, Bacillus anthracis, Corynebacterium diphtheriae, Erysipelothrix rhusiopathiae, Enterobacter aerogenes, Klebsiella pneumoniae, Fusobacterium nucleatum, Streptobacillus moniliformis, Treponema pallidium, Treponema pertenue, Leptospira, Rickettsia, and Actinomyces israeli.
In other embodiments of the invention, the pathogenic infection is a eukaryotic pathogen, such as pathogenic fungi and parasites. Fungi that are known to be pathogenic at least to some extent include, but are not limited to, Cryptococcus neoformans, Histoplasma capsulatum, Coccidioides immitis, Blastomyces dermatitidis, Candida albicans, Candida glabrata, Aspergillus fumigata, Aspergillus flavus, and Sporothrix schenckii.
Other eukaryotic pathogens from which the heterologous antigen can be derived include, but are not limited to, pathogenic protozoa, helminths, Plasmodium, such as Plasmodium falciparum, Plasmodium malariae, Plasmodium ovale, and Plasmodium vivax; Toxoplasma gondii; Trypanosoma brucei, Trypanosoma cruzi; Schistosoma haematobium, Schistosoma mansoni, Schistosoma japonicum; Leishmania donovani; Giardia intestinalis; Cryptosporidium parvum; and the like.
Th1-related diseases also include any malignant or pre-malignant condition, proliferative or hyper-proliferative condition or any disease arising or deriving from or associated with a functional or other disturbance or abnormality in the proliferative capacity or behaviour of any cells or tissues of the body. Thus, the methods described herein could be used to diagnose a cancer, including assessing the likelihood whether a cancer is a metastatic cancer. For example, cancers which could be suitably diagnosed in accordance with the practices of this invention include breast cancer, colon cancer, lung cancer and prostate cancer, cancers of the blood and lymphatic systems (including Hodgkin's disease, leukemias, lymphomas, multiple myeloma, and Waldenstrom's disease), skin cancers (including malignant melanoma), cancers of the digestive tract (including head and neck cancers, esophageal cancer, stomach cancer, cancer of the pancreas, liver cancer, colon and rectal cancer, anal cancer), cancers of the genital and urinary systems (including kidney cancer, bladder cancer, testis cancer, prostate cancer), cancers in women (including breast cancer, ovarian cancer, gynecological cancers and choriocarcinoma) as well as in brain, bone carcinoid, nasopharyngeal, retroperitoneal, thyroid and soft tissue tumors.
The present invention also extends to the management of a Th1-related disease, or prevention of further progression of a Th1-related disease, or an assessment of the efficacy of therapies in subjects following positive diagnosis for the presence of a Th1-related disease, in a subject. Once a subject is positively identified as having a Th1-related disease, the subject may be administered a therapeutic agent for treating the Th1-related disease, for example an anti-pathogenic agent, chemotherapy, radiotherapy, or any agent suitable for inhibiting or reducing a Th1 immune response, or enhancing or elevating a Th1 immune response in the subject.
Typically, the therapeutic agents will be administered in pharmaceutical (or veterinary) compositions together with a pharmaceutically acceptable carrier and in an effective amount to achieve their intended purpose. The dose of active compounds administered to a subject should be sufficient to achieve a beneficial response in the subject over time such as a reduction in, or relief from, the symptoms of the Th1-related disease. The quantity of the pharmaceutically active compounds(s) to be administered may depend on the subject to be treated inclusive of the age, sex, weight and general health condition thereof. In this regard, precise amounts of the active compound(s) for administration will depend on the judgment of the practitioner. In determining the effective amount of the active compound(s) to be administered in the treatment or prevention of the Th1-related disease, the medical practitioner or veterinarian may evaluate severity of any symptom or clinical sign associated with the presence of the Th1-related disease or degree of the Th1-related disease including, inflammation, blood pressure anomaly, tachycardia, tachypnea fever, chills, vomiting, diarrhea, skin rash, headaches, confusion, muscle aches, seizures. In any event, those of skill in the art may readily determine suitable dosages of the therapeutic agents and suitable treatment regimens without undue experimentation.
The therapeutic agents may be administered in concert with adjunctive (palliative) therapies to increase oxygen supply to major organs, increase blood flow to major organs and/or to reduce an inflammatory response associated with the disease. Illustrative examples of such adjunctive therapies include non-steroidal-anti-inflammatory drugs (NSAIDs), intravenous saline and oxygen.
The present invention also contemplates the use of the indicator-determining methods, compositions and kits disclosed herein in methods of treating, preventing or inhibiting the development of a Th1-related disease in a subject. These methods (also referred to herein as “treatment methods”) generally comprise: exposing the subject to a treatment regimen for treating the Th1-related disease based on an indicator obtained from an indicator-determining method as disclosed above and elsewhere herein. In specific embodiments, these treatment methods comprise: (1) determining a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarkers of the subject; (2) determining the indicator using the biomarker profile; and (3) administering to the subject, on the basis of the indicator, an effective amount of an agent that treats or ameliorates the symptoms or reverses or inhibits the development of the Th1-related disease. In other embodiments, the treatment methods comprise: (a) determining a Th1 immune status biomarker profile of a sample obtained from the subject, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) Th1 immune status biomarker in the sample, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; (b) determining an indicator using a combination of the biomarker values of the at least one biomarker, the indicator being at least partially indicative of the Th1 immune status; and (c) administering to the subject, on the basis the Th1 immune response status of the subject, an effective amount of an agent that treats or ameliorates the symptoms or reverses or inhibits the development of a Th1-related disease.
In some embodiments, the treatment methods comprise: (1) determining a Th1 immune status biomarker profile of a sample obtained from the subject, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) Th1 immune status biomarker in the sample, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and (2) applying a function to at least two of the measured biomarker values to determine an indicator, the indicator being indicative of a Th1 immune status. The function suitably includes at least one of: (a) multiplying two biomarker values; (b) dividing two biomarker values; (c) adding two biomarker values; (d) subtracting two biomarker values; (e) a weighted sum of at least two biomarker values; (f) a log sum of at least two biomarker values; and (g) a sigmoidal function of at least two biomarker values.
The present invention can be practiced in the field of predictive medicine for the purpose of diagnosis or monitoring the presence or development of a Th1-related disease in a subject, and/or monitoring response to therapy efficacy. The biomarker profiles and corresponding indicators of the present invention further enable determination of endpoints in pharmacotranslational studies. For example, clinical trials can take many months or even years to establish the pharmacological parameters for a medicament to be used in treating or preventing Th1-related disease. However, these parameters may be associated with a biomarker profile and corresponding indicator of a health state (e.g., a healthy condition). Hence, the clinical trial can be expedited by selecting a treatment regimen (e.g., medicament and pharmaceutical parameters), which results in a biomarker profile associated with a desired health state (e.g., healthy condition). This may be determined for example by: (1) determining a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of a subject after treatment with a treatment regimen, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of an APC; (2) determining the indicator using the biomarker value; and (3) determining that the treatment regimen is effective for changing the health status of the subject to the desired health state (e.g., healthy condition) on the basis that the indicator indicates the presence of a healthy condition (i.e., desirable Th1 immune status disease) or the presence of a condition of a lower degree relative to the degree of the condition in the subject before treatment with the treatment regimen. As used herein, the term “degree” refers to the extent or stage of a disease. Alternatively, selection of the treatment regimen may be determined by: (a) determining a Th1 immune status biomarker profile comprising at least one Th1 immune status biomarker value from at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) Th1 immune status biomarker, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, and each biomarker value being indicative of a value measured or derived for the at least one Th1 immune status biomarker of a subject after treatment with a treatment regimen; (b) determining an indicator using a combination of the at least two Th1 immune status biomarker values, the indicator being at least partially indicative of the presence, absence or degree of a healthy condition or a Th1-related disease, and (c) determining that the treatment regimen is effective for changing the health status of the subject to the desired health state (e.g., healthy condition) on the basis that the indicator indicates the presence of a healthy condition or the presence of a condition of a lower degree relative to the degree of the Th1-related disease in the subject before treatment with the treatment regimen. Accordingly, this aspect of the present invention advantageously provides methods of monitoring the efficacy of a particular treatment regimen in a subject (for example, in the context of a clinical trial) already diagnosed with a Th1-related disease. These methods take advantage of measured or derived biomarker values that correlate with treatment efficacy to determine, for example, whether measured or derived biomarker values of a subject undergoing treatment partially or completely normalize during the course of or following therapy or otherwise shows changes associated with responsiveness to the therapy.
Accordingly, the invention provides methods of correlating a biomarker profile with an effective treatment regimen for a Th1-related disease. In some embodiments, these methods comprise: (1) determining a biomarker profile including a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of a subject with a Th1-related disease and for whom an effective treatment has been identified, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and (2) correlating the biomarker profile so determined with an effective treatment regimen for the disease. In other embodiments, the biomarker profile-correlating methods comprise: (a) determining a biomarker profile defining a combination of at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) biomarker values corresponding to values of at least two Th1 immune status biomarkers that can be measured for or derived from a subject with a Th1-related disease and for whom an effective treatment has been identified, wherein the at least two Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and (b) correlating the biomarker profile so determined with an effective treatment regimen for the disease. In preferred embodiments, the at least two Th1 immune status biomarkers comprise both PD-L2 and PD-1.
In some embodiments, an indicator or biomarker profile is correlated to a global probability or a particular outcome, using receiver operating characteristic (ROC) curves.
The invention can also be practiced to evaluate whether a subject is responding (i.e., a positive response) or not responding (i.e., a negative response) to a treatment regimen. This aspect of the invention provides methods of correlating a biomarker profile with a positive or negative response to a treatment regimen. In some embodiments, these methods comprise: (1) determining a biomarker profile defining a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of a subject following commencement of the treatment regimen, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and (2) correlating the biomarker profile so determined with a positive or negative response to the treatment regimen. In other embodiments, these methods comprise: (a) determining a biomarker profile defining a combination of at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) biomarker values corresponding to values of at least two Th1 immune status biomarkers that can be measured for or derived from a subject following commencement of the treatment regimen, wherein the at least two Th1 immune status biomarkers comprises PD-L2, and optionally PD-L1, of an APC; and (b) correlating the biomarker profile so determined with a positive or negative response to the treatment regimen. In preferred embodiments, the at least two Th1 immune status biomarkers comprise both PD-L2 and PD-L1.
The invention also encompasses methods of determining a positive or negative response to a treatment regimen by a subject with Th1-related disease. In some embodiments, these methods comprise: (1) correlating a reference biomarker profile with a positive or negative response to the treatment regimen, wherein the biomarker profile defines a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of a control subject or control group, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; (2) determining a sample biomarker profile defining a biomarker value that is measured or derived for the at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of the subject following commencement of the treatment regimen, wherein the sample biomarker profile indicates whether the subject is responding positively or negatively to the treatment regimen, based on the correlation of the reference biomarker signature with the positive or negative response to the treatment regimen. In other embodiments, the methods comprise: (a) correlating a reference biomarker profile with a positive or negative response to the treatment regimen, wherein the biomarker profile defines a combination of at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) biomarker values corresponding to values of at least two Th1 immune status biomarkers that are measured for or derived from a control subject or control group, wherein the at least two Th1 immune status biomarkers comprise PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and (b) determining a sample biomarker profile defining a combination of at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) biomarker values corresponding to values of the at least two Th1 immune status biomarkers that are measured or derived from the subject following commencement of the treatment regimen, wherein the at least two Th1 immune status biomarkers comprise PD-L2 of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; and wherein the sample biomarker profile indicates whether the subject is responding positively or negatively to the treatment regimen, based on the correlation of the reference biomarker profile with the positive or negative response to the treatment regimen. In preferred embodiments, the at least two Th1 immune status biomarkers comprise both PD-L2 and PD-1.
In related embodiments, the present invention further contemplates methods of determining a positive or negative response to a treatment regimen by a subject. In some embodiments, these methods comprise: (1) determining a sample biomarker profile defining a biomarker value that is measured or derived for at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) corresponding Th1 immune status biomarker of a subject following commencement of the treatment regimen, wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells), and wherein the sample biomarker profile is correlated with a positive or negative response to the treatment regimen; and (2) determining whether the subject is responding positively or negatively to the treatment regimen based on the sample biomarker profile. In other embodiments, these methods comprise: (a) determining a sample biomarker profile defining a combination of at least two (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) biomarker values corresponding to values of at least two Th1 immune status biomarkers that are measured for or derived from a subject following commencement of the treatment regimen, wherein the at least two Th1 immune status biomarkers comprise PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; wherein the sample biomarker profile is correlated with a positive or negative response to the treatment regimen; and (b) determining whether the subject is responding positively or negatively to the treatment regimen based on the sample biomarker profile. In preferred embodiments, the at least two Th1 immune status biomarkers comprise both PD-L2 and PD-L1.
The above methods can be practiced not only to diagnose a Th-related disease, but also to identify whether a subject is responding or not responding to a treatment regimen. Using such methods, an assessment may be made relatively early in the treatment process, i.e., before clinical manifestations of efficacy. In this way, the treatment regimen can optionally be discontinued, a different treatment protocol can be implemented and/or supplemental therapy can be administered. Thus, in some embodiments, a sample Th1 immune status biomarker profile is obtained within about 2 hours, 4 hours, 6 hours, 12 hours, 1 day, 2 days, 3 days, 4 days, 5 days, 1 week, 2 weeks, 3 weeks, 4 weeks, 6 weeks, 8 weeks, 10 weeks, 12 weeks, 4 months, six months or longer of commencing therapy.
The present invention also contemplates methods in which the indicator-determining method of the invention is implemented using one or more processing devices. In some embodiments, these methods comprise: (1) determining a pair of biomarker values, the pair of biomarker values being selected from the group consisting of a pair of biomarker values indicative of a concentration of PD-L2 polypeptide and PD-L1 polypeptide; (2) determining an indicator indicative of a ratio of the concentrations of the polypeptides using the pair of biomarker values; (3) retrieving previously determined indicator references from a database, the indicator reference(s) being determined based on indicators determined from at least one group of a reference population, the at least one group comprises individuals diagnosed with a Th1-related disease; (4) comparing the indicator to the indicator reference(s); (5) using the results of the comparison to determine a probability indicative of the subject having or not having the Th1-related disease; and (6) generating a representation of the probability, the representation being displayed to a user to allow the user to assess the likelihood of a subject having the Th1-related disease.
Additionally, the present invention encompasses methods for differentiating between metastatic cancer and non-metastatic cancer (e.g., benign lesions) in a subject. These methods suitably comprise: (a) obtaining a sample taken from a subject showing a clinical sign of metastatic cancer or non-metastatic cancer, the sample comprising cells that interact with IEC (e.g., APCs such as dendritic cells, or tumor cells); (b) determining a Th1 immune status biomarker profile of the sample, wherein the Th1 immune status biomarker profile comprises a biomarker value for at least one (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or more) Th1 immune status biomarker, wherein the biomarker value is at least partially indicative of a concentration of the Th1 immune status biomarker, and wherein the at least one Th1 immune status biomarker comprises PD-L2, and optionally PD-L1, of IEC-interacting cells (e.g., APCs or tumor cells) in the sample; (c) determining an indicator by: determining an indicator that is indicative of the concentration of the at least one Th1 immune status biomarker; (d) retrieving previously determined indicator references from a database, wherein the indicator references are distributions of indicators determined for groups of a reference population, the first group consisting of individuals diagnosed with metastatic cancer, and the second group consisting of individuals diagnosed with non-metastatic cancer (e.g., benign lesions); (e) comparing the indicator to the indicator references; (g) using the results of the comparison to determine a probability of the subject being classified within the first or second group; (f) generating a representation at least partially indicative of the indicator and the probability; and (g) providing the representation to a user to allow the user to assess the likelihood of a subject having metastatic cancer or non-metastatic cancer.
In order that the invention may be readily understood and put into practical effect, particular preferred embodiments will now be described by way of the following non-limiting examples.
To determine if PD-L1 and PD-L2 influenced malarial immunity, seven malaria-naive, healthy human volunteers were infected with 1800 P. falciparum infected red blood cells (pRBC) and their blood examined before and seven days after challenge. We examined DCs, defined by CD11c expression, in view of their important role in pathogenesis (Wykes and Good, 2008) and since PD-L1 and PD-L2 on DCs can down-regulate immune responses by T cells (Brown et al., J. Immunol. 170: 1257-1266, 2003; Freeman et al., J. Exp. Med. 192: 1027-1034, 2000). In all seven volunteers, 90% of DCs expressed PD-L1 before infection, and there was no significant change in the percentage of DCs expressing this ligand by day seven of infection (
Human Studies
The method for conduct of the clinical trial (McCarthy et al., PLoS One. 6: e21914, 2011) (ClinicalTrials.gov identifier: NCT02389348) and the PCR method used to quantify parasitemia (Rockett et al., Malar. J. 10: 48, 2011) are described in detail elsewhere. Each participant gave informed consent. Seven of eight healthy volunteers (n=4 males; and n=3 females) aged 19-55 years (median age, 24 years {interquartile range, 21-37}) who participated in a study to evaluate the effectiveness of the experimental anti-malarial therapeutics OZ439 and DSM265 separately consented to participate in this sub-study, nested within the clinical trial. This study was approved by the Human Research Ethics Committee of the QIMR Berghofer Institute for Medical Research (QIMR). Volunteers received approximately 1800 P. falciparum pRBCs via intravenous injection in 2.0 mL of saline. On day seven, the day designated for commencement of treatment, participants were admitted to the study unit and administered the investigational anti-malarial drug treatment after blood was collected for the study.
To understand the biological relevance of these data, the present inventors next investigated four mouse models of malaria. They chose four different species/strains of Plasmodium that infect mice, with each showing distinct biology and pathogenicity. When WT mice were infected with non-lethal P. yoelii 17XNL or P. chabaudi, and the blood was examined every 1-3 days for parasites, the infection progressed at different rates, but both groups cleared the infection within 30 days (
The present inventors examined surface expression of PD-L1 and PD-L2 on DCs from the spleen, which has been shown to be a major site of parasite killing and regulation of parasite-specific immune responses in mice (Yadava et al., Proc. Natl. Acad. Sci. USA, 93: 4595-4599, 1996). Approximately 70% of CD11c+ DCs in the spleens of native mice expressed PDL1 and this percentage increased in P. berghei and P. chabaudi-infected mice but not during lethal or non-lethal P. yoelii infections (
Finally, CD11c+ DCs from lethal and non-lethal P. yoelii malaria showed similar increases in PD-L1 and PD-L2 mRNA levels (
Overall, the results from all infections are consistent with a hypothesis that a higher percentage of PD-L2+ DCs correlates with a favourable disease outcome.
Mice Studies
Specific pathogen-free C57BL/6J (wt) female mice 8-12 weeks of age were obtained from the Animal Resources Centre (Perth, Australia). Mice were housed in the QIMR animal research facility, and all procedures approved and monitored by the QIMR Animal Ethics Committee. Work was conducted under QIMR animal ethics approval number A0209-622M in accordance with the “Australian code of practice for the care and use of animals for scientific purposes” (Australian National Health & Medical Research Council). PD-1 knockout (ko) (Pdcd1−/−) mice on a C57BL/6 background were kindly provided by Dr. T. Honjo through the Riken BRC (Nishimura et al., Science. 291: 319-322, 2001). The PD-L2 ko (Liang et al., Eur. J. Immunol. 36: 58-64, 2006), PD-L1 ko (Liang et al., Eur. J. Immunol. 36: 58-64, 2006) and PD-1 ko mice on a C57BL/6J background, used in these studies, were confirmed to have the gene deleted by PCR testing and/or flow cytometry. The sample size was estimated based on previous studies with similar assays, using the same parasites.
For experiments with multiple groups, all mice were first infected and then randomly assigned into treatment groups. No blinding was undertaken.
Parasitic Infection and Monitoring
Cohorts of 3-6 WT mice were infected intravenously with 105 P. yoelii 17XNL, 105 P. chabaudi AS, 104 P. yoelii YM, or 104 P. berghei ANKA parasitized red blood cells (pRBCs) freshly obtained from C57BL/6J mice previously infected mice. These parasite doses were previously shown to give obvious parasitemia around the same time. Tail-tip blood films were made every 1-2 days, stained using the Quick Dip modified Wright-Giemsa stain (Thermo Fisher Scientific) and examined for parasitemia, for up to 60 days. The percentage of pRBCs was assessed by counting at least 300 RBCs during parasitemia >1% and 20 fields with around 10,000 cells at other times.
The mean percentage parasitemia shown in several figures is the mean percentage pRBC of total RBC, from individual mice in a group. Mice were monitored daily for anemia, and physical symptoms of disease, including posture (hunching), lack of activity and fur texture. Mice were euthanized if they showed signs of significant distress as described in Tables 1 and 2, below.
P. yoelii YM symptoms include anemia respiratory distress, and haematuria with complications such as coma and convulsions but never cerebral malaria. The mice are monitored daily by the above criteria for distress during the period of the experiment, to determine whether treatments described in the study are causing distress to mice to a degree to where they should be euthanized. If the cumulative score reaches above 3 by these assessment criteria, or if the weight loss is more than 25%, the distressed mouse is euthanized.
Wobbly gait
1
6
Limb paralysis
1
6
Convulsions
1
6-7
Coma
1
6-7
P. berghei causes lethal cerebral disease and symptoms are usually evident by day 7 post infection. Scores are cumulative and mice with a cumulative score=4 are euthanized. Notably, ruffled fur and hunching are general clinical sigs, while other symptoms (in italics) are symptoms of cerebral malaria.
Flow Cytometry
Single-cell suspensions of processed blood or spleen cells were labeled with combinations of fluorophore-conjugated antibodies shown below. Fixable Viability Dye eFluor780 (eBioscience) was used to exclude dead cells from analysis. Serial dilutions of each antibody were pre-tested by flow cytometry to determine the optimal concentration for the main assay. Anti-CD16/32 (clone 2.4G2, BD) was used for blocking nonspecific Fc binding. Intracellular markers denoted with an asterisk were labeled following fixation and permeabilization of cells using BD Pharmingen Transcription Factor Buffer Set. Acquisition of data was performed using a BD LSR Fortessa flow cytometer and BD FACSDiva software. Analysis of data was performed using FCS express (De Novo Software) or FlowJo (Tree Star).
To determine the contribution of PD-L2 to the control of malarial parasites, the present inventors next examined the outcome of P. yoelii 17XNL infection in PD-L2 ko mice (Liang et al., Eur. J. Immunol. 36: 58-64, 2006) (on a C57BL/6J background) compared with wt mice. All wt mice cleared the infection within 27 days (
However, the PD-L2 ko mice had significantly higher parasitemia than wt mice after day 13, and all of these mice died or had to be euthanized by day 19 (
To confirm our observation that PD-L2 was required to survive P. yoelii 17XNL infections, we next blocked PD-L2 with a monoclonal antibody when parasites became detectable in the blood. For this experiment, wt mice were infected with P. yoelii 17XNL and given either anti-PD-L2 or control rat IgG, four days post infection and every 3-4 days until day 14-18 post infection. All wt mice that received rat IgG survived and cleared the infection within 32 days (
To further explore the role of PD-L2 in protection against another non-lethal infection, wt mice were infected with non-lethal P. chabaudi malaria and treated with either anti-PD-L2 or rat IgG (
We next focused on understanding why mice did not survive infection with non-lethal P. yoelii 17XNL when PD-L2 was blocked. We therefore repeated the above blocking experiments and collected spleens at days 7 and 14 for evaluation by multiple immunoassays. First, CD4+ T cells were examined for the expression of Tbet, a transcription factor required for effector functions of Th1 CD4+ T cells, which are known to mediate protection against malaria (Kumar and Miller, Immunol Lett, 25: 109-114, 1990; Stephens and Langhorne, PLoS Pathog, 6: e1001208, 2010; and Su and Stevenson, J Immunol, 168: 1348-1355, 2002). T cells were also evaluated for expression of CD62L, a marker found on native T cells and which also distinguishes central memory (CD62Lhi) from effector memory (CD62Llo) T cells (
Studies with P. yoelii 17XNL-infected PD-L2 ko mice also found significantly lower numbers of Tbet expressing and IFN-γ-secreting, parasite-specific CD4+ T cells per spleen at day 14 compared to infected WT mice (
Overall, the data presented herein show that PD-L2 expression is necessary for effective Th1 CD4+ T cell responses against P. yoelii 17XNL malaria. Given that a higher ratio of PD-L2 to PD-L1 expression on DCs was associated with lower parasitemia and blockade of PD-L2 resulted in reduced Th1 responses, we hypothesized PD-L2 may inhibit PD-L1 functions which were reported to inhibit Th1 responses (Liang et al., Eur. J. Immunol. 36: 58-64, 2006). Furthermore, PD-L2 blockade caused mortality in mice infected with P. yoelii 17XNL but not P. chabaudi malaria. In alignment, PD-L1/PD-1-mediated immune suppression was previously shown to be greater during the acute phase of P. yoelii 17XNL (Butler et al., Nat. Immunol. 13: 188-195, 2012) than P. chabaudi malaria (Horne-Debets et al., Cell. Reports. 5: 1204-1213, 2013). As such, we concluded that PD-L2-mediated inhibition of PD-L1/PD-1-mediated immune suppression, could explain the different outcomes of PD-L2 blockade between the two infections.
The present inventors next undertook DC-transfer studies to establish if PD-L1 expression on DCs was responsible for lethality of malaria. To do so, wt and PD-L1 ko mice were infected with lethal P, yoelii YM malaria, DCs isolated at day 7 post infection (
WT and PD-1 ko mice were then infected with lethal P. yoelii YM to confirm that the PD-1 pathway was responsible for the lethality of P. yoelii YM malaria. While 100% of WT had to be euthanized by day 10 due to clinical scores ≥4, all PD-1 ko mice survived (
Given that PD-L2 expression was associated with survival from malaria, the present inventors next examined how PD-L2 co-expression with PD-L1 on DCs could modulate immunity. A previous study showed that the interaction between PD-L1 on DCs and PD-1 on CD8′ OTI T cells contributed to ligand-induced T cell receptor (TCR) down-modulation (Karwacz et al., EMBO. Mol. Med. 3: 581-592, 2011). It was therefore decided to investigate if PD-L2 co-expression with PD-L1 on DCs could inhibit PD-L1-mediated down-regulation of TCRs and inducible T-cell co-stimulator (ICOS) expression. To do so, purified DCs and T cells were cultured from infected mice (1:5 cells), with antibodies to block PD-1, PD-L1 or PD-L2 functions and examined the T cells after 36 hours for high expression of CD3, a component of the TCR, and high ICOS expression which can indicate T cell activation (
DC Transfer Study
CD11c+ DC obtained from spleens of wt and PD-L1 ko mice infected with 104 P. yoelii YM (lethal) pRBC. Four days post infection, mice were treated with 250 μg Pyrimethamine daily for four days to clear the infection. At day 7, the spleens were digested and DC enriched using Dynal DC enrichment kit. Samples were run on the AutoMACs to remove residual Dynal labeled cells and hemozoin. Highly purified DCs were obtained by labelling DCs with anti-CD11c MACS beads and isolated on AutoMACS. Approximately 1.5×107 DC were then transfused intravenously to naive mice. After resting the mice for greater than 15 hours, they were infected with a lethal dose of P. yoelii YM (104 pRBC). Mice were followed for 48 days when monitoring was stopped.
DC-T Cell Culture
Mice were infected with 105 P. yoelii 17XNL pRBC and on day 14 post infection, the spleens were digested and total T cells were isolated using CD90.2 MACS beads, to minimize any effect on the TCR. DCs were then isolated from remaining spleen cells using Dynal DC enrichment kit.
Approximately 106 T cells were cultured with 2×105 DCs in at least triplicate wells. Control or blocking anti-PD-1 (RMP1-14), anti-PD-L1 (10F.9G2) or anti-PD-L2 (TY25) antibodies were added to cultures at a concentration of 20 μg/ml. After 36 hours culture, cells were washed and labeled for flow cytometry. CD3 and ICOS expression was assessed on viable CD4+ CD62Llo PD-1+ T cells.
To provide additional proof of concept data, blood DCs from patients with either benign lesions or metastatic melanoma were compared. A significant loss of PD-L2+ DCs was observed in patients suffering from metastatic disease (see,
Based on the findings with systemic malaria and cancer, it appears that PD-L2, but not PD-L1 predicts the severity of Th1 immune response-associated systemic disease. Overall, it is predicted that PD-L2 levels increase during autoimmune disease, which drives expansion of damaging effector cells. This is reflected by patients with local lesions having a higher ratio.
The present inventors hypothesized that multimeric soluble PD-L2 (sPD-L2) would outcompete PD-L1 for binding to PD-1 on Th1 cells and thus reduce the suppressive effects of PD-L1 on T cell functions. To test this, wild-type mice were infected with lethal P. yoelii YM or P. berghei and administered PD-L2 on day 3, after parasitemia(s) were measurable and then on days 5 and 7 post-infection. All wild-type mice infected with P. yoelii YM and treated with control human IgG (Control Ig) died or had to be euthanized within ten days (
Similarly, dimeric PD-L2 did not offer any protection from increasing parasitemia (
Similarly, 100% of control mice infected with P. berghei developed experimental cerebral malaria symptoms (ECM) within 8 days (
Approximately 15 mL of blood collected was in lithium heparin from healthy human volunteers and patients diagnosed with Crohns Disease (CD; 12 samples) and 4 Ulcerative colitis patients (UC; 4 samples) and 7 IBD patients after treatment with TNF blockade 7 samples). PBMCs were isolated from blood following layering on Ficoll Paque Plus (GE Health, USA) and centrifugation as recommended by the manufacturer. The buoyant cells, free of red cells and granulocytes, were labelled with a DC lineage negative kit (Becton Dickinson, US; labels all cells except DC), CD11c, HLA-DR, PD-L1 and PD-L2. This will separate all lineage positive cells (CD3+, CD4+, CD8+, CD19+, CD56+, CD16+ and CD14+) from CD11c+ DC. The DCs from these individuals were examined for changes to PD-L1 and PD-L2 expression by flow cytometry. The GMI of PD-L1 and PD-L2 expression on Lineage-/MHC Class II+/CD11c+ DC were calculated.
To determine whether PD-L2 had clinical relevance to IBD patients, PD-L1 and PD-L2 expression on blood DCs from patients with CD and UC, CD/UC patients following TNF blockade (aTNF) and Red Cross blood donors (RC;
| Number | Date | Country | Kind |
|---|---|---|---|
| 2016903160 | Aug 2016 | AU | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/AU2017/050855 | 8/11/2017 | WO |
