Patent Application
20200386758
The present invention relates to methods for predicting the probability of survival of a human melanoma cancer patient, and to apparatuses and kits which can be used in these methods.
The serum level of lactate dehydrogenase (sLDH) is the most widely used prognostic biomarker in melanoma and has been incorporated in the AJCC staging system for melanoma patients with distant metastases since 2001 (Balch, C M et al., J Clin Oncol/19/3635-48. 2001). sLDH had been identified as an independent prognostic marker for patients with unresectable disease by different research groups (Sirott, M N et al., Cancer/72/3091-8. 1993; Eton, 0 et al., J Clin Oncol/16/1103-11. 1998; Manola, J et al., J Clin Oncol/18/3782-93. 2000). Results from a comprehensive meta-analysis based on a large pool of clinical studies (31,857 patients with various solid tumors) confirmed the consistent effect of elevated LDH on OS (HR=1.48, 95% Cl=1.43 to 1.53) across all disease subgroups and stages, with particular relevance for metastatic tumors. While the exact mechanism underlying tumor promotion by LDH remains unknown and may also be related to hypoxia and metabolic reprogramming via a Warburg effect, LDH also reflects high tumor burden (Zhang, J., Yao, Y.-H., Li, B.-G., Yang, Q., Zhang, P.-Y., and Wang, H.-T. (2015). Prognostic value of pretreatment serum lactate dehydrogenase level in patients with solid tumors: a systematic review and meta-analysis. Scientific Reports 5, 9800). Still, there is a need for improved prognostic biomarkers for melanoma patients.
Serum concentrations of S100B (sS100B) are widely used mainly in Europe to screen patients without evidence of disease to detect recurrences early (Pflugfelder, A et al., J Dtsch Dermatol Ges/11 Suppl 6/1-116, 1-26. 2013). A meta-analysis by Mocellin et al. summarized the evidence on the suitability of sS100B to predict patients' survival. Twenty-two series enrolling 3393 patients comprising all stages were included in this analysis. Serum S100B positivity was associated with significantly poorer survival in melanoma patients of all stages especially in the subgroup of stage I to III patients independent from other prognostic factors (Mocellin, S et al., Int J Cancer/123/2370-6. 2008). In prior studies, it was demonstrated that sS100B and sLDH had independent impact on prognosis of patients with distant metastases and the combined analysis of both markers might be used to select patients for complete metastasectomy (Weide, B et al., PLoS One/8/e81624. 2013; Weide, B et al., Br J Cancer/107/422-8. 2012). However, despite this large evidence, no worldwide consensus exists on its implementation in the routine clinical setting in melanoma patients.
Growth and Differentiation Factor-15 (GDF-15, also known as Macrophage Inhibitor Cytokine-1 (MIC-1), Placental TGF-β (PTGFβ), Placental Bone Morphogenetic Protein (PLAB), Nonsteroidal Anti-inflammatory Drug-Activated Gene (NAG1) or Prostate-Derived Factor (PDF) is over-expressed in tumor cells of several types of solid cancers (Mimeault, M et al., Br J Cancer/108/1079-91. 2013; Bock, A J et al., Int J Gynecol Cancer/20/1448-55. 2010; Zhang, L et al., Oral Oncol/45/627-32. 2009). GDF-15 is induced by a number of tumor suppressor pathways including p53, GSK-33, and EGR-1 (Wang, X et al., Biochem Pharmacol/85/597-606. 2013) and there is also evidence that GDF-15 itself can exert tumor suppressive effects, as shown in nude mouse xenograft models (Martinez, J M et al., J Pharmacol Exp Ther/318/899-906. 2006; Eling, T E et al., J Biochem Mol Biol/39/649-55. 2006) and in transgenic mice (Baek, S J et al., Mol Pharmacol/59/901-8. 2001). With regard to tumor cells both pro- and anti-apoptotic effects have been described for GDF-15 (Mimeault, M et al., Br J Cancer/108/1079-91. 2013; Baek, S J et al., Mol Pharmacol/59/901-8. 2001; Zimmers, T A et al., J Cancer Res Clin Oncol/136/571-6. 2010; Jones, M F et al., Cell Death Differ/2015) and a multitude of possible signaling pathways has been suggested (Mimeault, M and Batra S K, J Cell Physiol/224/626-35. 2010). Further complexity was added recently when the unprocessed pro-protein was shown to go into the nucleus where it altered TGF-beta dependent SMAD signaling and thereby transcription patterns (Min, K W et al., Oncogene/2015). In vivo, constitutive GDF-15 overexpression reduced tumor formation but increased metastasis in an animal model for prostate cancer (Husaini, Y et al., PLoS One/7/e43833. 2012). GDF-15 was further shown to induce cancer cachexia (Johnen, H et al., Nat Med/13/1333-40. 2007). Similarly, patent applications WO 2005/099746 and WO 2009/021293 relate to an anti-human-GDF-15 antibody (Mab26) capable of antagonizing effects of human GDF-15 (hGDF-15) on tumor-induced weight loss in vivo in mice. WO 2014/049087 and PCT/EP2015/056654 relate to monoclonal antibodies to hGDF-15 and medical uses thereof.
Clinically, a high GDF-15 serum level (sGDF-15) was found to correlate with the presence of bone metastases and poor prognosis in prostate cancer (Selander, K S et al., Cancer Epidemiol Biomarkers Prev/16/532-7. 2007). In colorectal cancer, patients with high plasma levels showed shorter time to recurrence and reduced overall survival (Wallin, U et al., Br J Cancer/104/1619-27. 2011). The allelic H6D polymorphism in the GDF-15 gene was further identified as independent predictor of metastasis at the time of diagnosis (Brown, DA, Clin Cancer Res/9/2642-50. 2003). The association between high sGDF-15 and poor outcome was further shown for thyroid, pancreatic, gastric, ovarian and other cancers (Mimeault, M and Batra S K, J Cell Physiol/224/626-35. 2010; Bauskin, A R et al., Cancer Res/66/4983-6. 2006; Brown, D A et al., Clin Cancer Res/15/6658-64. 2009; Blanco-Calvo, M et al., Future Oncol/10/1187-202. 2014; Staff, A C et al., Gynecol Oncol/118/237-43. 2010). Similar findings have also been reported for the level of GDF-15 tissue expression as assessed by immunohistochemistry (Wallin, U et al., Br J Cancer/104/1619-27. 2011). In melanoma, GDF-15 expression was found to increase from benign nevi over primary melanoma to melanoma metastases (Mauerer, A et al., Exp Dermatol/20/502-7. 2011; Boyle, G M et al., J Invest Dermatol/129/383-91. 2009). Serum concentrations of GDF-15 were indicative for metastasis in patients with uveal melanoma (Suesskind, D et al., Graefes Arch Clin Exp Ophthalmol/250/887-95. 2012) and correlated with stage in patients with cutaneous melanoma (Kluger, H M et al., ClinCancer Res/17/2417-25. 2011). Riker et al. compared gene expression in melanoma metastasis and primary tumor, and identified GDF-15 as the only soluble factor among the top 5 genes correlating with metastasis (Riker, A I et al., BMC Med Genomics/1/13. 2008). Boyle et al. (Boyle, G M et al., J Invest Dermatol/129/383-91. 2009) found by immunohistochemistry that 15 of 22 primary melanomas expressed low levels of GDF-15 whereas 16 of 16 melanoma metastasis showed strong expression. Furthermore, knock-down of GDF-15 in three melanoma cell lines results in decreased tumorigenicity in the same study. Before that, Talantov et al. (Talantov, D et al., Clin Cancer Res/11/7234-42. 2005) had already identified GDF-15 in melanoma metastases, but not in nevi and normal lymph nodes. Similar findings were reported in a study of Mauerer et al. who found GDF-15 to be preferentially expressed in metastatic tumors and in some primary melanomas, but not in melanocytic nevi (Mauerer, A et al., Exp Dermatol/20/502-7. 2011). However, a direct role of GDF-15 in metastasis has only been shown in prostate cancer where constitutive overexpression of GDF-15 slowed cancer development but increased metastases (Husaini, Y et al., PLoS One/7/e43833. 2012). Clinical relevance of GDF-15 serum levels in melanoma patients was reported in two studies. GDF-15 serum concentrations were associated with metastasis in a cohort of 188 patients with metastatic (n=170) or non-metastatic (n=18) uveal melanoma (Suesskind, D et al., Graefes Arch Clin Exp Ophthalmol/250/887-95. 2012). Finally, Kluger et al. reported a correlation between plasma levels of GDF-15 and stage in 216 patients with cutaneous melanoma (Kluger, H M et al., ClinCancer Res/17/2417-25. 2011). In contrast to these findings, however, some studies have suggested an anti-tumorigenic role of GDF-15 (see, for instance, Liu T et al: “Macrophage inhibitory cytokine 1 reduces cell adhesion and induces apoptosis in prostate cancer cells.” Cancer Res., vol. 63, no. 16, 1 Aug. 2003, pp. 5034-5040).
Thus, from the above-mentioned studies, and in view of the complex functional role of human GDF-15 (hGDF-15) in various cancers and its different effects on primary tumors and metastases in prostate cancer, it remained, however, unknown whether hGDF-15 could be used as a prognostic clinical marker for patient survival in melanoma.
Thus, there is a need in the art for prognostic biomarkers for melanoma, and in particular for improved prognostic biomarkers in melanoma, and for methods which allow to predict patient survival in melanoma more reliably.
The present invention meets the above needs and solves the above problems in the art by providing the embodiments described below:
In particular, in order to solve the above problems, the present inventors set out to investigate the impact of serum GDF-15 levels on overall survival (OS) of melanoma patients. In the course of these studies, the present inventors have surprisingly found that the probability of survival in melanoma patients significantly decreases with increasing hGDF-15 levels in the patient sera and vice versa. For instance, the inventors have shown that a high serum level of hGDF-15 is a potent biomarker for poor overall survival in tumor-free stage III and unresectable stage IV melanoma patients.
Thus, according to the invention, the probability of survival in melanoma patients inversely correlates with hGDF-15 levels.
Moreover, in the studies of the inventors, Cox regression analysis revealed that the knowledge of hGDF-15 serum levels adds independent prognostic information, e.g. if considered in combination with the M-category, and is superior to the established biomarker LDH in patients with distant metastasis.
Therefore, according to the invention, hGDF-15 levels can be used as a biomarker for the prediction of survival. This biomarker is advantageous, e.g. because it has a prognostic value that is independent of known biomarkers such as LDH. This means that if hGDF-15 levels are used for the prediction of melanoma patient survival according to the invention, they may, in a preferred aspect of the invention, be combined with additional biomarkers.
According to the invention, the combination of hGDF-15 levels as a biomarker with additional biomarkers such as LDH or S100B provides an improved prediction of survival, which is improved even when compared to the use of hGDF-15 levels alone.
Additionally, the use of hGDF-15 level as a biomarker is also advantageous because it allows to provide a prediction of survival that includes sub-groups of melanoma patients such as macroscopically tumor-free stage III patients, for which S100B represents the only available predictive and diagnostic marker.
Thus, the present invention provides improved means to predict survival of melanoma patients by providing the preferred embodiments described below:
Unless otherwise defined below, the terms used in the present invention shall be understood in accordance with their common meaning known to the person skilled in the art.
The term “antibody” as used herein refers to any functional antibody that is capable of specific binding to the antigen of interest, as generally outlined in chapter 7 of Paul, W. E. (Ed.).: Fundamental Immunology 2nd Ed. Raven Press, Ltd., New York 1989, which is incorporated herein by reference. Without particular limitation, the term “antibody” encompasses antibodies from any appropriate source species, including chicken and mammalian such as mouse, goat, non-human primate and human. Preferably, the antibody is a humanized antibody. The antibody is preferably a monoclonal antibody which can be prepared by methods well-known in the art. The term “antibody” encompasses an IgG-1, -2, -3, or -4, IgE, IgA, IgM, or IgD isotype antibody. The term “antibody” encompasses monomeric antibodies (such as IgD, IgE, IgG) or oligomeric antibodies (such as IgA or IgM). The term “antibody” also encompasses—without particular limitations—isolated antibodies and modified antibodies such as genetically engineered antibodies, e.g. chimeric antibodies.
The nomenclature of the domains of antibodies follows the terms as known in the art. Each monomer of an antibody comprises two heavy chains and two light chains, as generally known in the art. Of these, each heavy and light chain comprises a variable domain (termed VH for the heavy chain and VL for the light chain) which is important for antigen binding. These heavy and light chain variable domains comprise (in an N-terminal to C-terminal order) the regions FR1, CDR1, FR2, CDR2, FR3, CDR3, and FR4 (FR, framework region; CDR, complementarity determining region which is also known as hypervariable region). The identification and assignment of the above-mentioned antibody regions within the antibody sequence is generally in accordance with Kabat et al. (Sequences of proteins of immunological interest, U.S. Dept. of Health and Human Services, Public Health Service, National Institutes of Health, Bethesda, Md. 1983), or Chothia et al. (Conformations of immunoglobulin hypervariable regions. Nature. 1989 Dec. 21-28; 342(6252):877-83.), or may be performed by using the IMGTN-QUEST software described in Giudicelli et al. (IMGTN-QUEST, an integrated software program for immunoglobulin and T cell receptor V-J and V-D-J rearrangement analysis. Nucleic Acids Res. 2004 Jul. 1; 32 (Web Server issue):W435-40.), which is incorporated herein by reference. Preferably, the antibody regions indicated above are identified and assigned by using the IMGTN-QUEST software.
A “monoclonal antibody” is an antibody from an essentially homogenous population of antibodies, wherein the antibodies are substantially identical in sequence (i.e. identical except for minor fraction of antibodies containing naturally occurring sequence modifications such as amino acid modifications at their N- and C-termini). Unlike polyclonal antibodies which contain a mixture of different antibodies directed to either a single epitope or to numerous different epitopes, monoclonal antibodies are directed to the same epitope and are therefore highly specific. The term “monoclonal antibody” includes (but is not limited to) antibodies which are obtained from a monoclonal cell population derived from a single cell clone, as for instance the antibodies generated by the hybridoma method described in Köhler and Milstein (Nature, 1975 Aug. 7; 256(5517):495-7) or Harlow and Lane (“Antibodies: A Laboratory Manual” Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. 1988). A monoclonal antibody may also be obtained from other suitable methods, including phage display techniques such as those described in Clackson et al. (Nature. 1991 Aug. 15; 352(6336):624-8) or Marks et al. (J Mol Biol. 1991 Dec. 5; 222(3):581-97). A monoclonal antibody may be an antibody that has been optimized for antigen-binding properties such as decreased Kd values, optimized association and dissociation kinetics by methods known in the art. For instance, Kd values may be optimized by display methods including phage display, resulting in affinity-matured monoclonal antibodies. The term “monoclonal antibody” is not limited to antibody sequences from particular species of origin or from one single species of origin. Thus, the meaning of the term “monoclonal antibody” encompasses chimeric monoclonal antibodies such as humanized monoclonal antibodies.
“Humanized antibodies” are antibodies which contain human sequences and a minor portion of non-human sequences which confer binding specificity to an antigen of interest (e.g. human GDF-15). Typically, humanized antibodies are generated by replacing hypervariable region sequences from a human acceptor antibody by hypervariable region sequences from a non-human donor antibody (e.g. a mouse, rabbit, rat donor antibody) that binds to an antigen of interest (e.g. human GDF-15). In some cases, framework region sequences of the acceptor antibody may also be replaced by the corresponding sequences of the donor antibody. In addition to the sequences derived from the donor and acceptor antibodies, a “humanized antibody” may either contain other (additional or substitute) residues or sequences or not. Such other residues or sequences may serve to further improve antibody properties such as binding properties (e.g. to decrease Kd values) and/or immunogenic properties (e.g. to decrease antigenicity in humans). Non-limiting examples for methods to generate humanized antibodies are known in the art, e.g. from Riechmann et al. (Nature. 1988 Mar. 24; 332(6162):323-7) or Jones et al. (Nature. 1986 May 29-Jun. 4; 321(6069):522-5).
The term “human antibody” relates to an antibody containing human variable and constant domain sequences. This definition encompasses antibodies having human sequences bearing single amino acid substitutions or modifications which may serve to further improve antibody properties such as binding properties (e.g. to decrease Kd values) and/or immunogenic properties (e.g. to decrease antigenicity in humans). The term “human antibody” excludes humanized antibodies where a portion of non-human sequences confers binding specificity to an antigen of interest.
An “antigen-binding portion” of an antibody as used herein refers to a portion of an antibody that retains the capability of the antibody to specifically bind to the antigen (e.g. hGDF-15, PD-1, PD-L1 or CTLA4). This capability can, for instance, be determined by determining the capability of the antigen-binding portion to compete with the antibody for specific binding to the antigen by methods known in the art. The antigen-binding portion may contain one or more fragments of the antibody. Without particular limitation, the antigen-binding portion can be produced by any suitable method known in the art, including recombinant DNA methods and preparation by chemical or enzymatic fragmentation of antibodies. Antigen-binding portions may be Fab fragments, F(ab′) fragments, F(ab′)2 fragments, single chain antibodies (scFv), single-domain antibodies, diabodies or any other portion(s) of the antibody that retain the capability of the antibody to specifically bind to the antigen.
An “antibody” (e.g. a monoclonal antibody) or an “antigen-binding portion” may have been derivatized or be linked to a different molecule. For example, molecules that may be linked to the antibody are other proteins (e.g. other antibodies), a molecular label (e.g. a fluorescent, luminescent, colored or radioactive molecule), a pharmaceutical and/or a toxic agent. The antibody or antigen-binding portion may be linked directly (e.g. in form of a fusion between two proteins), or via a linker molecule (e.g. any suitable type of chemical linker known in the art).
As used herein, the terms “binding” or “bind” refer to specific binding to the antigen of interest (e.g. human GDF-15). Preferably, the Kd value is less than 100 nM, more preferably less than 50 nM, still more preferably less than 10 nM, still more preferably less than 5 nM and most preferably less than 2 nM.
The term “epitope” as used herein refers to a small portion of an antigen that forms the binding site for an antibody.
In the context of the present invention, for the purposes of characterizing the binding properties of antibodies, binding or competitive binding of antibodies or their antigen-binding portions to the antigen of interest (e.g. human GDF-15) is preferably measured by using surface plasmon resonance measurements as a reference standard assay, as described below.
The terms “KD” or “KD value” relate to the equilibrium dissociation constant as known in the art. In the context of the present invention, these terms relate to the equilibrium dissociation constant of an antibody with respect to a particular antigen of interest (e.g. human GDF-15) The equilibrium dissociation constant is a measure of the propensity of a complex (e.g. an antigen-antibody complex) to reversibly dissociate into its components (e.g. the antigen and the antibody). For the antibodies according to the invention, KD values (such as those for the antigen human GDF-15) are preferably determined by using surface plasmon resonance measurements as described below.
An “isolated antibody” as used herein is an antibody that has been identified and separated from the majority of components (by weight) of its source environment, e.g. from the components of a hybridoma cell culture or a different cell culture that was used for its production (e.g. producer cells such as CHO cells that recombinantly express the antibody). The separation is performed such that it sufficiently removes components that may otherwise interfere with the suitability of the antibody for the desired applications (e.g. with a therapeutic use of the anti-human GDF-15 antibody according to the invention). Methods for preparing isolated antibodies are known in the art and include Protein A chromatography, anion exchange chromatography, cation exchange chromatography, virus retentive filtration and ultrafiltration. Preferably, the isolated antibody preparation is at least 70% pure (w/w), more preferably at least 80% pure (w/w), still more preferably at least 90% pure (w/w), still more preferably at least 95% pure (w/w), and most preferably at least 99% pure (w/w), as measured by using the Lowry protein assay.
A “diabody” as used herein is a small bivalent antigen-binding antibody portion which comprises a heavy chain variable domain linked to a light chain variable domain on the same polypeptide chain linked by a peptide linker that is too short to allow pairing between the two domains on the same chain. This results in pairing with the complementary domains of another chain and in the assembly of a dimeric molecule with two antigen binding sites. Diabodies may be bivalent and monospecific (such as diabodies with two antigen binding sites for human GDF-15), or may be bivalent and bispecific (e.g. diabodies with two antigen binding sites, one being a binding site for human GDF-15, and the other one being a binding site for a different antigen). A detailed description of diabodies can be found in Holliger P et al. (““Diabodies”: small bivalent and bispecific antibody fragments.” Proc Natl Acad Sci USA. 1993 Jul. 15; 90(14):6444-8.).
A “single-domain antibody” (which is also referred to as “Nanobody™”) as used herein is an antibody fragment consisting of a single monomeric variable antibody domain. Structures of and methods for producing single-domain antibodies are known from the art, e.g. from Holt L J et al. (“Domain antibodies: proteins for therapy.” Trends Biotechnol. 2003 Nov.; 21(11):484-90.), Saerens D et al. (“Single-domain antibodies as building blocks for novel therapeutics.” Curr Opin Pharmacol. 2008 Oct.; 8(5):600-8. Epub 2008 Aug. 22.), and Arbabi Ghahroudi M et al. (“Selection and identification of single domain antibody fragments from camel heavy-chain antibodies.” FEBS Lett. 1997 Sep. 15; 414(3):521-6.).
The terms “significant”, “significantly”, etc. as used herein refer to a statistically significant difference between values as assessed by appropriate methods known in the art, and as assessed by the methods referred to herein.
In accordance with the present invention, each occurrence of the term “comprising” may optionally be substituted with the term “consisting of”.
The terms “cancer” and “cancer cell” is used herein in accordance with their common meaning in the art (see for instance Weinberg R. et al.: The Biology of Cancer. Garland Science: New York 2006. 850p., which is incorporated herein by reference in its entirety).
The cancers, for which a prediction of a clinical outcome, in particular a prediction of patient survival according to the present invention is provided, is melanoma. As used herein, the term “melanoma” is used in accordance with its general meaning known in the art. Melanomas are classified according to the AJCC staging system for melanoma patients with distant metastases since 2001 (Balch, C M et al., J Clin Oncol/19/3635-48. 2001). The melanoma stages referred to herein refer to this staging system. In a preferred aspect of the present invention in accordance with all of the embodiments of the present invention, the melanoma is not a uveal melanoma.
The melanoma patients, for which a prediction of survival according to the invention is provided, may be subject to a treatment of the melanoma. As used herein, terms such as “treatment of cancer” or “treating cancer” or “treatment of melanoma” or “treating melanoma” refer to a therapeutic treatment. As used herein, such treatments do not only include treatments of the melanoma itself but also palliative treatments. Such palliative treatments are known in the art and include, for instance, treatments which only improve the symptoms of the melanoma disease.
As referred to herein, a treatment of cancer can be a first-line therapy, a second-line therapy or a third-line therapy or a therapy that is beyond third-line therapy. The meaning of these terms is known in the art and in accordance with the terminology that is commonly used by the US National Cancer Institute.
A treatment of cancer does not exclude that additional or secondary therapeutic benefits also occur in patients. For example, an additional or secondary benefit may be an influence on cancer-induced weight loss.
As referred to herein, a “tumor-free” melanoma patient is a patient in which no primary tumor and no metastasis can be detected according to clinical standard methods known in the art. This, however, does not exclude that tumors (or micrometastases) exist in the patient, which are below the detection limit, or that tumor cells exist, which may form a new tumor.
As referred to herein, the term “blood sample” includes, without limitation, whole blood, serum and plasma samples. It also includes other sample types such as blood fractions other than serum and plasma. Such samples and fractions are known in the art.
Blood samples which are used for the methods according to the invention can be any types of blood samples which contain hGDF-15. Suitable types of blood samples containing hGDF-15 are known in the art and include serum and plasma samples. Alternatively, further types of blood samples which contain hGDF-15 can also be readily identified by the skilled person, e.g. by measuring whether hGDF-15 is contained in these samples, and which levels of hGDF-15 are contained in these samples, by using the methods disclosed herein.
According to the invention, levels of hGDF-15 in human blood samples can be used to predict the probability of survival of a human melanoma patient.
Survival of patient groups can be analysed by methods known in the art, e.g. by Kaplan-Meier curves.
Appropriate time periods for the assessment of survival are known in the art and will be chosen by the skilled person with due regard to factors such as the respective stage of the melanoma.
For example, survival, preferably short-term survival, may, for instance, be predicted for time points of 6 months, 12 months and/or 18 months after the time point when the prediction was made. Alternatively, survival, preferably long-term survival, may, for instance, be assessed at a time point of 2 years, 3 years, 5 years and/or 10 years after the time point when the prediction was made.
For predicting the probability of a positive clinical outcome (e.g. survival) according to the invention, e.g. based on hGDF-15 levels, the methods for predicting, which are defined above in the preferred embodiments, are preferably used.
In order to practice the methods of the invention, statistical methods known in the art can be employed.
For instance, overall survival can be analyzed by Cox regression analysis.
Preferred statistical methods, which can be used according to the invention to generate statistical models of patient data from clinical studies, are disclosed in Example 1. It is understood that the statistical methods disclosed in Example 1 are not limited to the particular features of Example 1 such as the melanoma stage, the particular threshold levels chosen and the particular statistical values obtained in the Example. Rather, these methods disclosed in Example 1 can generally be used in connection with any embodiment of the present invention.
hGDF-15 Levels
In an advantageous aspect of the invention, there is an inverse relationship between hGDF-15 levels and the probability of a positive clinical outcome, in particular the probability of survival, in human melanoma patients. Thus, according to the invention, a decreased level of hGDF-15 indicates an increased probability of survival in human melanoma patients.
Thus, as used herein, terms such as “wherein a decreased level of hGDF-15 in said human blood sample indicates an increased probability of survival” mean that the level of hGDF-15 in said human blood sample and the probability of survival follow an inverse relationship. Thus, the higher the level of hGDF-15 in said human blood sample is, the lower is the probability of survival.
For instance, in connection with the methods for predicting according to the invention defined herein, hGDF-15 threshold levels can be used.
According to the invention, the inverse relationship between hGDF-15 levels and the probability of survival applies to any threshold value, and hence the invention is not limited to particular threshold values.
Preferable hGDF-15 threshold levels are hGDF-15 serum levels as defined above in the preferred embodiments.
Alternatively, hGDF-15 threshold levels according to the present invention can be obtained, and/or further adjusted, by using the above-mentioned statistical methods, e.g. the methods of Example 1.
An hGDF-15 threshold level may be a single hGDF-15 threshold level. The invention also encompasses the use of more than one hGDF-15 threshold level, e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10 or more hGDF-15 threshold levels.
For each single hGDF-15 threshold level of the one or more hGDF-15 threshold levels, a corresponding probability of survival can be predicted at a given time point.
hGDF-15 levels in blood samples can be measured by any methods known in the art. For instance, a preferred method of measuring hGDF-15 levels in blood samples including serum levels is a measurement of hGDF-15 levels by Enzyme-Linked Immunosorbent Assay (ELISA) by using antibodies to hGDF-15. Such ELISA methods are exemplified in Example 1, but can also include bead-based methods like the Luminex technology and others. Alternatively, hGDF-15 levels in blood samples including serum levels may be determined by known electrochemiluminesence immunoassays using antibodies to hGDF-15. For instance, the Roche Elecsys® technology can be used for such electrochemiluminesence immunoassays. Other possible methods would include antibody-based detection from bodily fluids after separation of proteins in an electrical field.
The median hGDF-15 serum level of healthy human control individuals is <0.8 ng/ml. The expected range is between 0.2 ng/ml and 1.2 ng/ml in healthy human controls (Reference: Tanno T et al.: “Growth differentiation factor 15 in erythroid health and disease.” Curr Opin Hematol. 2010 May; 17(3): 184-190.).
According to the invention, preferable hGDF-15 threshold levels are hGDF-15 serum levels as defined above in the preferred embodiments.
It is understood that for these hGDF-15 serum levels, and based on the disclosure of the invention provided herein, corresponding hGDF-15 levels in other blood samples can be routinely obtained by the skilled person (e.g. by comparing the relative level of hGDF-15 in serum with the respective level in other blood samples). Thus, the present invention also encompasses preferred hGDF-15 levels in plasma, whole blood and other blood samples, which correspond to each of the preferred hGDF-15 serum levels and ranges indicated above.
Lactate dehydrogenase levels in blood samples can be measured by any methods known in the art Lactate dehydrogenase (LDH) levels are typically measured in enzymatic units (U). One unit will reduce 1.0 μmole of pyruvate to L-lactate per minute at pH 7.5 at 37° C.
Lactate and NAD+ are converted to pyruvate and NADH by the action of LDH. NADH strongly absorbs light at 340 nm, whereas NAD+ does not. The rate of increase in absorbance at 340 nm is directly proportional to the LDH activity in the sample. Thus, LDH units are preferably determined by measuring absorbance at 340 nm.
Various clinically accepted diagnostic tests are available for the measurement of LDH levels. In accordance with the present invention, tests which can be applied to melanoma will be selected based on known clinical standards. Isoform-specific tests for LDH can be performed according to methods known in the art.
In a further advantageous aspect of the invention, there is also an inverse relationship between lactate dehydrogenase (LDH) levels and the probability of a positive clinical outcome, in particular the probability of survival, in human melanoma patients. Thus, in an embodiment according to the invention, a decreased level of lactate dehydrogenase indicates an increased probability of survival in melanoma patients.
Thus, as used herein, terms such as “wherein a decreased level of lactate dehydrogenase in said human blood sample indicates an increased probability of survival” mean that the level of lactate dehydrogenase in said human blood sample and the probability of survival follow an inverse relationship. Thus, the higher the level of lactate dehydrogenase in said human blood sample is, the lower is the probability of survival.
For instance, in connection with the methods for predicting according to the invention defined herein, lactate dehydrogenase threshold levels can be used.
According to the invention, the inverse relationship between lactate dehydrogenase levels and the probability of survival applies to any threshold value, and hence the invention is not limited to particular threshold values.
Alternatively, lactate dehydrogenase threshold levels according to the present invention can be obtained, and/or further adjusted, by using the above-mentioned statistical methods, e.g. the methods of Example 1.
A lactate dehydrogenase threshold level may be a single lactate dehydrogenase threshold level. The invention also encompasses the use of more than one lactate dehydrogenase threshold level, e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10 or more lactate dehydrogenase threshold levels.
For each single lactate dehydrogenase threshold level of the one or more lactate dehydrogenase threshold levels, a corresponding probability of survival can be predicted.
According to the invention, preferable lactate dehydrogenase threshold levels are lactate dehydrogenase serum levels as defined above in the preferred embodiments.
In a very preferred embodiment, the lactate dehydrogenase threshold level is a clinically accepted threshold level which distinguishes between normal and elevated LDH levels in patients. Such very preferred clinically accepted threshold levels are known in the art, and will be chosen by the skilled person with regard to the particular specifications of the LDH test.
It is understood that for these lactate dehydrogenase serum levels, and based on the disclosure of the invention provided herein, corresponding lactate dehydrogenase levels in other blood samples can be routinely obtained by the skilled person (e.g. by comparing the relative level of lactate dehydrogenase in serum with the respective level in other blood samples). Thus, the present invention also encompasses preferred lactate dehydrogenase levels in plasma, whole blood and other blood samples, which correspond to each of the preferred lactate dehydrogenase serum levels and ranges indicated above.
In a further advantageous aspect of the invention, there is also an inverse relationship between S100B levels and the probability of a positive clinical outcome, in particular the probability of survival, in human melanoma patients. Thus, in an embodiment according to the invention, a decreased level of S100B indicates an increased probability of survival in melanoma patients.
Thus, as used herein, terms such as “wherein a decreased level of S100B in said human blood sample indicates an increased probability of survival” mean that the level of S100B in said human blood sample and the probability of survival follow an inverse relationship. Thus, the higher the level of S100B in said human blood sample is, the lower is the probability of survival.
For instance, in connection with the methods for predicting according to the invention defined herein, S100B threshold levels can be used.
According to the invention, the inverse relationship between S100B levels and the probability of survival applies to any threshold value, and hence the invention is not limited to particular threshold values.
S100B threshold levels according to the present invention can, for instance, be obtained, and/or further adjusted, by using the above-mentioned statistical methods, e.g. the methods of Example 1.
An S100B threshold level may be a single S100B threshold level. The invention also encompasses the use of more than one S100B threshold level, e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10 or more S100B threshold levels.
In a very preferred embodiment, the S100B threshold level is a clinically accepted threshold level which distinguishes between normal and elevated S100B levels in patients. Such very preferred clinically accepted threshold levels are known in the art, and will be chosen by the skilled person with regard to the particular specifications of the S100B test.
For each single S100B threshold level of the one or more S100B threshold levels, a corresponding probability of survival can be predicted.
S100B levels in blood samples can be measured by any methods known in the art. Such methods include antibody-based assays. A preferred method of measuring S100B levels in blood samples a measurement of S100B serum levels by electrochemoluminescence assays, e.g. by using an Elecsys S100 electrochemiluminescence immunoassay. Further non-limiting examples of methods to measure S100B levels are given in Gonçalves et al.: “Biological and methodological features of the measurement of S100B, a putative marker of brain injury.” Clinical Biochemistry 41 (2008) 755-763).
Antibodies Capable of Binding to hGDF-15 which can be Used in Accordance with the Invention
The methods, apparatuses and kits of the invention may use one or more antibodies capable of binding to hGDF-15 or an antigen-binding portion thereof, as defined above.
It was previously shown that human GDF-15 protein can be advantageously targeted by a monoclonal antibody (WO2014/049087, which is incorporated herein by reference in its entirety), and that such antibody has advantageous properties including a high binding affinity to human GDF-15, as demonstrated by an equilibrium dissociation constant of about 790 pM for recombinant human GDF-15 (see Reference Example 1). Thus, in a preferred embodiment, the invention uses an antibody capable of binding to hGDF-15, or an antigen-binding portion thereof. Preferably, the antibody is a monoclonal antibody capable of binding to hGDF-15, or an antigen-binding portion thereof.
Thus, in a more preferred embodiment, the antibody capable of binding to hGDF-15 or antigen-binding portion thereof in accordance with the invention is a monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, wherein the heavy chain variable domain comprises a CDR3 region comprising the amino acid sequence of SEQ ID NO: 5 or an amino acid sequence at least 90% identical thereto, and wherein the light chain variable domain comprises a CDR3 region comprising the amino acid sequence of SEQ ID NO: 7 or an amino acid sequence at least 85% identical thereto. In this embodiment, preferably, the antibody or antigen-binding portion thereof comprises a heavy chain variable domain which comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 3 and a CDR2 region comprising the amino acid sequence of SEQ ID NO: 4, and the antibody or antigen-binding portion thereof comprises a light chain variable domain which comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 6, and a CDR2 region comprising the amino acid sequence ser-ala-ser.
Thus, in a still more preferred embodiment, the antibody capable of binding to hGDF-15 or antigen-binding portion thereof in accordance with the invention is a monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, wherein the antibody or antigen-binding portion thereof comprises a heavy chain variable domain which comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 3, a CDR2 region comprising the amino acid sequence of SEQ ID NO: 4 and a CDR3 region comprising the amino acid sequence of SEQ ID NO: 5, and wherein the antibody or antigen-binding portion thereof comprises a light chain variable domain which comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 6, a CDR2 region comprising the amino acid sequence ser-ala-ser and a CDR3 region comprising the amino acid sequence of SEQ ID NO: 7.
In another embodiment in accordance with the above embodiments of the monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, the heavy chain variable domain comprises a region comprising an FR1, a CDR1, an FR2, a CDR2 and an FR3 region and comprising the amino acid sequence of SEQ ID NO: 1 or a sequence 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% identical thereto, and the light chain variable domain comprises a region comprising an FR1, a CDR1, an FR2, a CDR2 and an FR3 region and comprising the amino acid sequence of SEQ ID NO: 2 or a sequence 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% identical thereto.
In another embodiment in accordance with the above embodiments of the monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, the heavy chain variable domain comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 3 and a CDR2 region comprising the amino acid sequence of SEQ ID NO: 4, and the light chain variable domain comprises a CDR1 region comprising the amino acid sequence of SEQ ID NO: 6 and a CDR2 region comprising the amino acid sequence of SEQ ID NO: 7. In a preferred aspect of this embodiment, the antibody may have CDR3 sequences as defined in any of the embodiments of the invention described above.
In another embodiment in accordance with the monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, the antigen-binding portion is a single-domain antibody (also referred to as “Nanobody™”). In one aspect of this embodiment, the single-domain antibody comprises the CDR1, CDR2, and CDR3 amino acid sequences of SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5, respectively. In another aspect of this embodiment, the single-domain antibody comprises the CDR1, CDR2, and CDR3 amino acid sequences of SEQ ID NO: 6, ser-ala-ser, and SEQ ID NO: 7, respectively. In a preferred aspect of this embodiment, the single-domain antibody is a humanized antibody.
Preferably, the antibodies capable of binding to human GDF-15 or the antigen-binding portions thereof have an equilibrium dissociation constant for human GDF-15 that is equal to or less than 100 nM, less than 20 nM, preferably less than 10 nM, more preferably less than 5 nM and most preferably between 0.1 nM and 2 nM.
In another embodiment in accordance with the above embodiments of the monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, the antibody capable of binding to human GDF-15 or the antigen-binding portion thereof binds to the same human GDF-15 epitope as the antibody to human GDF-15 obtainable from the cell line B1-23 deposited with the Deutsche Sammlung für Mikroorganismen and Zellkulturen GmbH (DMSZ) under the accession No. DSM ACC3142. As described herein, antibody binding to human GDF-15 in accordance with the present invention is preferably assessed by surface plasmon resonance measurements as a reference standard method, in accordance with the procedures described in Reference Example 1. Binding to the same epitope on human GDF-15 can be assessed similarly by surface plasmon resonance competitive binding experiments of the antibody to human GDF-15 obtainable from the cell line B1-23 and the antibody that is expected to bind to the same human GDF-15 epitope as the antibody to human GDF-15 obtainable from the cell line B1-23.
In a very preferred embodiment, the antibody capable of binding to human GDF-15 or the antigen-binding portion thereof is a monoclonal antibody capable of binding to human GDF-15, or an antigen-binding portion thereof, wherein the binding is binding to a conformational or discontinuous epitope on human GDF-15 comprised by the amino acid sequences of SEQ ID No: 25 and SEQ ID No: 26. In a preferred aspect of this embodiment, the antibody or antigen-binding portion thereof is an antibody or antigen-binding portion thereof as defined by the sequences of any one of the above embodiments.
In a further embodiment in accordance with the above embodiments, antibodies including the antibody capable of binding to human GDF-15 or the antigen-binding portion thereof can be modified, e.g. by a tag or a label.
A tag can, for instance, be a biotin tag or an amino acid tag. Non-limiting examples of such acid tag tags include Polyhistidin (His-) tags, FLAG-tag, Hemagglutinin (HA) tag, glycoprotein D (gD) tag, and c-myc tag. Tags may be used for various purposes. For instance, tags may be used to assist purification of the antibody capable of binding to human GDF-15 or the antigen-binding portion thereof. Preferably, such tags are present at the C-terminus or N-terminus of the antibody capable of binding to human GDF-15 or the antigen-binding portion thereof.
As used herein, the term “label” relates to any molecule or group of molecules which can facilitate detection of the antibody. For instance, labels may be enzymatic such as horseradish peroxidase (HRP), alkaline phosphatase (AP) or glucose oxidase. Enzymatically labelled antibodies may, for instance, be employed in enzyme-linked immunosorbent assays. Labels may also be radioactive isotopes, DNA sequences (which may, for instance, be used to detect the antibodies by polymerase chain reaction (PCR)), fluorogenic reporters and electrochemiluminescent groups (e.g. ruthenium complexes). As an alternative to labelling, antibodies used according to the invention, in particular an antibody capable of binding to human GDF-15 or the antigen-binding portion thereof, can be detected directly, e.g. by surface plasmon resonance measurements.
Generally, unless otherwise defined herein, the methods used in the present invention (e.g. cloning methods or methods relating to antibodies) are performed in accordance with procedures known in the art, e.g. the procedures described in Sambrook et al. (“Molecular Cloning: A Laboratory Manual.”, 2nd Ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. 1989), Ausubel et al. (“Current Protocols in Molecular Biology.” Greene Publishing Associates and Wiley Interscience; New York 1992), and Harlow and Lane (“Antibodies: A Laboratory Manual” Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. 1988), all of which are incorporated herein by reference.
Binding of antibodies to their respective target proteins can be assessed by methods known in the art. The binding of monoclonal antibodies to their respective targets is preferably assessed by surface plasmon resonance measurements. These measurements are preferably carried out by using a Biorad ProteOn XPR36 system and Biorad GLC sensor chips, as exemplified for anti-human GDF-15 mAb-B1-23 in Reference Example 1.
Sequence Alignments of sequences according to the invention are performed by using the BLAST algorithm (see Altschul et al. (1990) “Basic local alignment search tool.” Journal of Molecular Biology 215. p. 403-410.; Altschul et al.: (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402., all of which are incorporated herein by reference). Preferably, the following parameters are used: Max target sequences 10; Word size 3; BLOSUM 62 matrix; gap costs: existence 11, extension 1; conditional compositional score matrix adjustment. Thus, when used in connection with sequences, terms such as “identity” or “identical” refer to the identity value obtained by using the BLAST algorithm.
Monoclonal antibodies according to the invention can be produced by any method known in the art, including but not limited to the methods referred to in Siegel D L (“Recombinant monoclonal antibody technology.” Transfus Clin Biol. 2002 Jan.; 9(1):15-22., which is incorporated herein by reference). In one embodiment, an antibody according to the invention is produced by the hybridoma cell line B1-23 deposited with the Deutsche Sammlung für Mikroorganismen and Zellkulturen GmbH (DSMZ) at Inhoffenstraße 7B, 38124 Braunschweig, Germany, under the accession No. DSM ACC3142 under the Budapest treaty. The deposit was filed on Sep. 29, 2011.
Levels of human GDF-15 (hGDF-15) can be measured by any method known in the art, including measurements of hGDF-15 protein levels by methods including (but not limited to) mass spectrometry for proteins or peptides derived from human GDF-15, Western Blotting using antibodies specific to human GDF-15, strip tests using antibodies specific to human GDF-15, or immunocytochemistry using antibodies specific to human GDF-15. A preferred method of measuring hGDF-15 serum levels is a measurement of hGDF-15 serum levels by Enzyme-Linked Immunosorbent Assay (ELISA) by using antibodies to GDF-15. Such ELISA methods are exemplified in Example 1. Alternatively, hGDF-15 serum levels may be determined by known electrochemiluminesence immunoassays using antibodies to hGDF-15. For instance, the Roche Elecsys® technology can be used for such electrochemiluminesence immunoassays.
The invention also relates to the apparatuses defined above.
An apparatus of the invention can be any apparatus which is configured to perform the methods of the invention.
As used herein, the term “configured to perform” means that the apparatus us specifically configured for the recited method steps. For instance, an apparatus configured to perform a method which uses a particular threshold level will be specifically configured to use that particular threshold.
In a preferred embodiment, the apparatus is an electrochemiluminescence analyzer such as Cobas® analyzer. In this embodiment, if LDH is measured, this may, for instance, be measured on an additional apparatus, which is not an electrochemiluminescence analyzer, and which is configured to perform LDH measurements such as enzymatic tests. Thus, in a preferred aspect of this embodiment, the electrochemiluminescence analyzer of the invention is configured to perform the methods of the invention except for the measurements of LDH levels.
The invention also relates to the kits defined above.
The recombinant hGDF-15 contained in the kits may be present in a form which can conveniently be used for calibration purposes. For instance, it may be present in the form of stock solutions which cover several concentrations in the range of 0 to 15 ng/ml, e.g. at least one concentration in the range of 0-1 ng/ml, at least one concentration in the range of 1-3 ng/ml, at least one concentration in the range of 3-6 ng/ml, and preferably at least one further concentration in the range of 6-10 ng/ml, and more preferably further comprising at least one further concentration in the range of 10-15 ng/ml.
The amino acid sequences referred to in the present application are as follows (in an N-terminal to C-terminal order; represented in the one-letter amino acid code):
The nucleic acid sequences referred to in the present application are as follows (in a 5′ to 3′ order; represented in accordance with the standard nucleic acid code):
Reference Examples 1 to 3 exemplify an antibody to hGDF-15, which can be used in the methods, kits, and in the apparatuses according to the invention. This hGDF-15 antibody is a monoclonal antibody which is known from WO 2014/049087, which is incorporated herein by reference in its entirety.
The antibody B1-23 was generated in a GDF-15 knock out mouse. Recombinant human GDF-15 (SEQ ID No: 8) was used as the immunogen.
The hybridoma cell line B1-23 producing mAb-B1-23 was deposited by the Julius-Maximilians-Universität Würzburg, Sanderring 2, 97070 Würzburg, Germany, with the Deutsche Sammlung für Mikroorganismen and Zellkulturen GmbH (DMSZ) at Inhoffenstraße 7B, 38124 Braunschweig, Germany, under the accession No. DSM ACC3142, in accordance with the Budapest Treaty. The deposit was filed on Sep. 29, 2011.
By means of a commercially available test strip system, B1-23 was identified as an IgG2a (kappa chain) isotype. Using surface plasmon resonance measurements, the dissociation constant (Kd) was determined as follows:
Binding of the monoclonal anti-human-GDF-15 antibody anti-human GDF-15 mAb-B1-23 according to the invention was measured by employing surface plasmon resonance measurements using a Biorad ProteOn XPR36 system and Biorad GLC sensor chips:
For preparing the biosensors recombinant mature human GDF-15 protein was immobilized on flow cells 1 and 2. On one flow cell recombinant GDF-15 derived from Baculvirus-transfected insect cells (HighFive insect cells) and on the other recombinant protein derived from expression in E. coli was used. The GLC sensor chip was activated using Sulfo-NHS (N-Hydroxysulfosuccinimide) and EDC (1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride) (Biorad ProteOn Amine Coupling Kit) according to the manufacturer's recommendation, the sensor surface was subsequently loaded with the proteins up to a density of about 600RU (1Ru=1 pg mm−2). The non-reacted coupling groups were then quenched by perfusion with 1M ethanolamine pH 8.5 and the biosensor was equilibrated by perfusing the chip with running buffer (10M HEPES, 150 mM NaCl, 3.4 mM EDTA, 0.005% Tween-20, pH 7.4, referred to as HBS150). As controls two flow cells were used, one empty with no protein coupled and one coupled with an non-physiological protein partner (human Interleukin-5), which was immobilized using the same coupling chemistry and the same coupling density. For interaction measurements anti-human GDF-15 mAb-B1-23 was dissolved in HBS150 and used in six different concentrations as analyte (concentration: 0.4, 0.8, 3, 12, 49 and 98 nM). The analyte was perfused over the biosensor using the one-shot kinetics setup to avoid intermittent regeneration, all measurements were performed at 25° C. and using a flow rate of 100 μl min−1. For processing the bulk face effect and unspecific binding to the sensor matrix was removed by subtracting the SPR data of the empty flow cell (flow cell 3) from all other SPR data. The resulting sensogram was analyzed using the software ProteOn Manager version 3.0. For analysis of the binding kinetics a 1:1 Langmuir-type interaction was assumed. For the association rate constant a value of 5.4±0.06×105 M−1s−1 (kon) and for the dissociation rate constant a value of 4.3±0.03×10−4 s−1 (koff) could be determined (values are for the interaction of anti-human GDF-15 mAb-B1-23 with GDF-15 derived from insect cell expression). The equilibrium dissociation constant was calculated using the equation KD=koff/kon to yield a value of about 790 pM. Affinity values for the interaction of GDF-15 derived from E. coli expression and the anti-human GDF-15 mAb-B1-23 differ by less than a factor of 2, rate constants for GDF-15 derived from insect cells and E. coli deviate by about 45% and are thus within the accuracy of SPR measurements and likely do not reflect a real difference in affinity. Under the conditions used the anti-human GDF-15 mAb-B1-23 shows no binding to human interleukin-5 and thus confirms the specificity of the interaction data and the anti-human GDF-15 mAb-B1-23.
The amino acid sequence of recombinant human GDF-15 (as expressed in Baculovirus-transfected insect cells) is:
Thus, using surface plasmon resonance measurements, the dissociation constant (Kd) of 790 pM was determined. As a comparison: the therapeutically used antibody Rituximab has a significantly lower affinity (Kd=8 nM).
It was previously shown that mAb B1-23 inhibits cancer cell proliferation in vitro, and that mAb B1-23 inhibits growth of tumors in vivo (WO2014/049087).
Epitope Mapping: Monoclonal mouse antibody GDF-15 against 13mer linear peptides derived from GDF-15
GSGSGSGMPGQELRTVNGSQMLLVLLVLSWLPHGGALSLAEASRASFPGP
The protein sequence was translated into 13mer peptides with a shift of one amino acid. The C- and N-termini were elongated by a neutral GSGS linker to avoid truncated peptides (bold letters).
000264_01 (10/90, Ala2Asp linker)
Standard buffer: PBS, pH 7.4+0.05% Tween 20
Blocking buffer: Rockland blocking buffer MB-070
Incubation buffer: Standard buffer with 10% Rockland blocking buffer MB-070
Primary sample: Monoclonal mouse antibody GDF-15 (1 μg/μl): Staining in incubation buffer for 16 h at 4° C. at a dilution of 1:100 and slight shaking at 500 rpm
Secondary antibody: Goat anti-mouse IgG (H+L) IRDye680, staining in incubation buffer with a dilution of 1:5000 for 30 min at room temperature (RT)
Control antibodies: Monoclonal anti-HA (12CA5)-LL-Atto 680 (1:1000), monoclonal anti-FLAG(M2)-FluoProbes752 (1:1000); staining in incubation buffer for 1 h at RT
Settings: offset: 1 mm; resolution: 21 μm; intensity green/red: 7/7
After 30 min pre-swelling in standard buffer and 30 min in blocking buffer, the peptide array with 10, 12 and 15mer B7H3-derived linear peptides was incubated with secondary goat anti-mouse IgG (H+L) IRDye680 antibody only at a dilution of 1:5000 for 1 h at room temperature to analyze background interactions of the secondary antibody. The PEPperCHIP® was washed 2×1 min with standard buffer, rinsed with dist. water and dried in a stream of air. Read-out was done with Odyssey Imaging System at a resolution of 21 μm and green/red intensities of 7/7: We observed a weak interaction of arginine-rich peptides (ELHLRPQAARGRR (SEQ ID No:15), LHLRPQAARGRRR (SEQ ID No:16), HLRPQAARGRRRA (SEQ ID No:17), LRPQAARGRRRAR (SEQ ID No:18), RPQAARGRRRARA (SEQ ID No:19), PQAARGRRRARAR (SEQ ID No:20) and QAARGRRRARARN (SEQ ID No:21)) that are known as frequent binders, and with the basic peptide MHAQIKTSLHRLK (SEQ ID No:22) due to ionic interactions with the charged antibody dye.
After pre-swelling for 10 min in standard buffer, the peptide microarray was incubated overnight at 4° C. with monoclonal mouse antibody GDF-15 at a dilution of 1:100. Repeated washing in standard buffer (2×1 min) was followed by incubation for 30 min with the secondary antibody at a dilution of 1:5000 at room temperature. After 2×10 sec. washing in standard buffer and short rinsing with dist. water, the PEPperCHIP® was dried in a stream of air. Read-out was done with Odyssey Imaging System at a resolution of 21 μm and green/red intensities of 7/7 before and after staining of control peptides by anti-HA and anti-FLAG(M2) antibodies.
It was shown that none of the linear 13mer peptides derived from GDF-15 interacted with monoclonal mouse antibody GDF-15 even at overregulated intensities. Staining of Flag and HA control peptides that frame the array, however, gave rise to good and homogeneous spot intensities.
The Epitope Mapping of monoclonal mouse GDF-15 antibody against GDF-15 did not reveal any linear epitope with the 13mer peptides derived from the antigen. According to this finding it is very likely that monoclonal mouse antibody GDF-15 recognizes a conformational or a discontinuous epitope with low affinity of partial epitopes. Due to the obvious absence of any GDF-15 signal above the background staining of the secondary antibody only, quantification of spot intensities with PepSlide® Analyzer and subsequent peptide annotation were omitted.
The epitope of recombinant human GDF-15 which binds to the antibody B1-23 was identified by means of the epitope excision method and epitope extraction method (Suckau et al. Proc Natl Acad Sci USA. 1990 December; 87(24): 9848-9852.; R. Stefanescu et al., Eur.J.Mass Spectrom. 13, 69-75 (2007)).
For preparation of the antibody column, the antibody B1-23 was added to NHS-activated 6-aminohexanoic acid coupled sepharose. The sepharose-coupled antibody B1-23 was then loaded into a 0.8 ml microcolumn and washed with blocking and washing buffers.
Recombinant human GDF-15 was digested with trypsin for 2 h at 37° C. (in solution), resulting in different peptides, according to the trypsin cleavage sites in the protein. After complete digestion, the peptides were loaded on the affinity column containing the immobilized antibody B1-23. Unbound as well as potentially bound peptides of GDF-15 were used for mass spectrometry analysis. An identification of peptides by means of mass spectrometry was not possible. This was a further indicator that the binding region of GDF-15 in the immune complex B1-23 comprises a discontinuous or conformational epitope. In case of a continuous linear epitope, the digested peptides should bind its interaction partner, unless there was a trypsin cleavage site in the epitope peptide. A discontinuous or conformational epitope could be confirmed by the epitope excision method described in the following part.
The immobilized antibody B1-23 on the affinity column was then incubated with recombinant GDF-15 for 2 h. The formed immune complex on the affinity column was then incubated with trypsin for 2 h at 37° C. The cleavage resulted in different peptides derived from the recombinant GDF-15. The immobilized antibody itself is proteolytically stable. The resulting peptides of the digested GDF-15 protein, which were shielded by the antibody and thus protected from proteolytic cleavage, were eluted under acidic conditions (TFA, pH2), collected and identified by mass spectrometry.
The epitope excision method using MS/MS identification resulted in the following peptides:
The part of human GDF-15, which binds the antibody B1-23, comprises a discontinuous or conformational epitope. Mass spectrometry identified 2 peptides in the GDF-15 protein, which are responsible for the formation of the immune complex. These peptides are restricted to the positions 40-55 (EVQVTMCIGACPSQFR) and 94-114 (TDTGVSLQTYDDLLAKDCHCI) in the GDF-15 amino acid sequence. Thus, these two peptides comprise an epitope of the GDF-15 protein that binds to the antibody B1-23.
The present invention is illustrated by the following non-limiting Examples:
Patients from the Department of Dermatology, University of Tubingen, Germany, with histologically confirmed melanoma were identified in the Central Malignant Melanoma Registry (CMMR) database which prospectively records patients from more than 60 dermatological centers in Germany. 761 patients, with (a) archived serum samples taken between January 2008 and February 2012, (b) available follow-up data, and (c) history or presence of loco regional or distant metastasis at the time point of blood draw were selected. The aims and methods of data collection by the CMMR have previously been published in detail (Lasithiotakis, K G et al., Cancer/107/1331-9. 2006). Data obtained for each patient included age, gender, the date of the last follow-up, and the date and cause of death, if applicable. All patients had given written informed consent to have clinical data recorded by the CMMR registry. The institutional ethics committee Tubingen has approved the study (ethic vote 125/2015B02). Age, the pattern of distant metastasis (stage IV patients only), sub-stage (IIIA vs. IIIB vs. IIIC; stage III patients only) according to the AJCC classification (Balch, C M et al., J Clin Oncol/27/6199-206. 2009), serum LDH and serum S100B (Elecsys S100 electrochemiluminescence immunoassay; Roche Diagnostics AG, Rotkreuz, Switzerland) were evaluated at the time of serum sampling. hGDF-15 serum concentrations were quantified in duplicates using a commercial ELISA kit according to the manufacturer's instructions (R&D systems, Wiesbaden, Germany):
Analysis of hGDF-15 Serum Levels by Enzyme-Linked Immunosorbent Assay (ELISA):
Human GDF-15 serum levels were measured by Enzyme-Linked Immunosorbent Assay (ELISA).
Follow-up time for survival analysis was defined from the date of blood sampling to the last follow-up or death. Cumulative survival probabilities according to Kaplan-Meier were calculated together with 95% confidence intervals (CIs) and compared using two-sided log-rank test statistics. For the analysis of OS, patients who were alive at the last follow-up were censored while patients who had died were considered an “event”. To analyze the impact of sGDF-15 on OS, patients were randomly assigned to two cohorts using a 1:2 ratio (identification and validation cohort, respectively). In the identification cohort different cut-off points were applied to categorize patients according to sGDF-15 into two balanced groups comprising 25% of patients each. Differences in OS between patients with high vs. low sGDF-15 were analyzed for each cut-off point and the one resulting in the lowest log rank p-value was selected, similarly to optimization algorithms published earlier (Camp, R L et al., Clin Cancer Res/10/7252-9. 2004). The optimal cut-off point as defined in the identification cohort was thereafter analyzed in 507 patients of validation cohort.
Cox proportional hazard regression analysis was used to calculate the relative effect considering additional prognostic factors in the entire patient cohort. Age was dichotomized according to the median age of patients. Serum S100B levels and sLDH were categorized as elevated vs. normal according to cut-off values as used in clinical routine (upper limit of normal 0.10 μg/I and 250 U/l, respectively). Patients with missing values were excluded from regression analysis. Results of the models were described by means of hazard ratios; p-values were based on the Wald test. All statistical analyses were carried out using the SPSS Version 22 (IBM SPSS, Chicago, Ill., USA).
Patients' characteristics are shown in Table 1. A total of 761 melanoma patients (52.0% male) was analyzed. The median age was 63 years. The median follow-up for patients who died was 10.3 months and 45.3 months for patients who were censored.
Stage IV patients (n=293) were assigned to the M-categories M1c (n=206; 70.3%), M1b (n=51; 17.4%), or M1a (n=36; 12.3%) based on the site of distant metastases and on serum LDH (sLDH) (Balch, C M et al., J Clin Oncol/27/6199-206. 2009). The median survival estimate according to Kaplan Meier was 10.7 months. Survival probabilities were 46.4% at 1-year, 33.3% at 2-years, and 29.3% at 3-years.
A total of 468 stage III patients was included. Sub-stage was IIIA in 15.6%, IIIB in 37.2%, and IIIC in 47.2% of 422 patients with complete data for classification. Survival probabilities were 94.9% at 1-year, 85.0% at 2-years, and 72.8% at 5-years, respectively.
The median hGDF-15 serum concentration was 1.0 ng/mL considering all 761 patients (0.9 ng/mL for stage III vs. 1.5 ng/mL for stage IV patients). Mean sGDF-15 was 2.6 (1.1 ng/mL for stage III vs. 4.8 ng/mL for stage IV patients; p<0.001).
Overall Survival According to hGDF-15 Levels
Thirteen different cut-off points ranging from 0.7 ng/mL to 1.9 ng/mL at increments of 0.1 ng/mL were found to categorize patients of the identification cohort (n=254) according to sGDF-15 into two balanced groups (the smaller group had to comprise at least 25% of patients). The difference in prognosis was largest comparing 86 patients (33.9%) with hGDF-15 levels 1.5 ng/mL and poor OS to 168 (66.1%) patients with lower levels and favorable OS (p<0.001;
This inverse correlation between sGDF-15 and OS was observed in tumor-free stage III patients and in unresectable stage IV patients (
Considering stage III patients of both cohorts, the 1-, 2- and 5 year survival probability was 96.1%, 87.8% and 75.7% for those with sGDF-15 below 1.5 ng/mL (n=369, 78.8% of all stage III patients) but only 90.4%, 74.2% and 61.5% for patients with higher sGDF-15 (n=99, 21.2%) (Table 2).
For patients of both cohorts with unresectable distant metastases and high hGDF-15 levels the probability to survive one year after analysis was only 14.3%, but 45.0% for patients with low sGDF-15. Similarly, the 2-year and 5-year survival was 6.3% and 2.6% compared to 19.9% and 5.2%, respectively. Median survival was 5.7 months versus 11.0 months for unresectable stage IV patients with high and low sGDF-15, respectively (Table 3).
The Relative Prognostic Impact of sGDF-15 in Stage III Patients
Cox regression analyses of the entire cohort of stage III patients were performed to determine the relative impact of sGDF-15 compared to other prognostic factors (Table 3). In the first model the three biomarkers sGDF-15, sS100B, and sLDH were included to allow for direct comparison. Results were adjusted for sub-stage, as univariate analysis had revealed a trend towards better OS for sub-stages IIIA/B versus IIIC (p=0.088). In addition to elevated sGDF-15 (HR 2.3; p<0.001), elevated sS100B was strongly associated with poor OS (
The Relative Impact of hGDF-15 Levels in Stage IV Patients
In stage IV patients without evidence of disease at the time point of blood sampling (n=87), no prognostic relevance was observed for sGDF-15. Neither the pattern of distant metastasis, nor sLDH were associated with OS (Table 4). Instead, sS100B was the only prognostic factor in this patient population (
As an alternative Example in accordance with the invention, the same patient samples, which were already described in Example 1, were evaluated in an alternative manner, as described in the following:
Patients from the Department of Dermatology, Tubingen, Germany, with histologically confirmed melanoma were identified in the Central Malignant Melanoma Registry (CMMR) database (Lasithiotakis et al., 2006). 761 patients, with (a) archived serum samples taken between January 2008 and February 2012, (b) available follow-up data, and either (c) history of loco-regional or (d) history or presence of distant metastasis at the time point of blood draw were selected. Serum used for analysis of sGDF-15 was sampled during routine blood draws for analysis of sS100B stage was defined according to the AJCC classification (Balch et al., 2009), serum LDH and serum S100B (Elecsys S100 electrochemiluminescence immunoassay; Roche Diagnostics, Rotkreuz, Switzerland) were categorized as elevated vs. normal according to cut-off values used in clinical routine (upper limits of normal 0.10 μg/I and 250 U/l, respectively). Distant soft tissue/lymph nodes, lung, brain, liver, bone, and other visceral organs were considered for the calculation of the number of involved distant sites. Thus the number could be between 1 and 6 for each stage IV patient. GDF-15 serum concentrations were quantified in duplicates using a commercial ELISA kit according to the manufacturer's instructions (R&D systems, Wiesbaden, Germany).
All patients had given written informed consent to have clinical data recorded by the CMMR registry. The institutional ethics committee Tubingen has approved the study (ethic vote 125/2015B02).
Follow-up time was defined from the date of blood sampling to the last follow-up or death. Survival probabilities according to Kaplan-Meier were calculated together with 95% confidence intervals and compared using two-sided log-rank tests. Patients who were either alive at the last follow-up or died from reasons other than melanoma were censored. Patients were randomly assigned to two cohorts using a 1:2 ratio. In the identification cohort, differences in OS between patients with high vs. low sGDF-15 were analyzed for cut-off points which yield two balanced groups comprising 25% of patients each. Then, the cut-off point resulting in the lowest log rank p-value was selected, similar to optimization algorithms published earlier (Camp et al., 2004) and thereafter analyzed in the validation cohort.
Cox regression analysis was used excluding patients with missing values. Results of the multivariable models were described by means of HRs; p-values were based on the Wald test. Combination models were developed using the nomogram function in the survival package for R. Differences in sGDF-15 according to prior systemic treatments were analyzed by Mann-Whitney U Testing. All statistical analyses were carried out using SPSS Version 22 (IBM SPSS, Chicago, Ill., USA) and R 3.2.1 (R Foundation for Statistical Computing, Vienna Austria).
Patients' characteristics are shown in Table 5. A total of 761 melanoma patients was analyzed. The median follow-up for patients who died was 10.3 months and 45.3 months for patients who were alive at the time point of last follow-up.
Stage IV patients (n=293) were assigned to the M-categories M1c (n=206; 70.3%), M1b (n=51; 17.4%), or M1a (n=36; 12.3%). The median survival estimate according to Kaplan Meier was 10.7 months. Survival probabilities were 46.4% at 1 year, 33.3% at 2 years, and 29.3% at 3 years. Assessment for stage IV patients was within 12 weeks in 84 (28.7%), or within 12 months after first occurrence of distant metastasis in 96 (32.7%), or at later time points in 113 patients (38.6%). At the respective time-point 87 patients (29.7%) had no evidence of disease while 206 (70.3%) had unresectable tumor.
A total of 468 stage III patients was included. Sub-stage was IIIA in 15.6%, Ill B in 37.2%, and IIIC in 47.2% of 422 patients with complete data for classification. Survival probabilities were 94.9% at 1-year, 85.0% at 2-years, and 72.8% at 5-years, respectively. The time point of assessment was within 12 weeks for 55 patients (11.8%), within 12 months after first occurrence of loco regional metastasis for 100 (21.4%), or later for 313 patients (66.9%). None of the stage III patients had evidence of disease at the respective time point.
Median sGDF-15 was 1.0 ng/mL considering all 761 patients (0.9 ng/mL for stage III vs. 1.5 ng/mL for stage IV patients). Stage IV patients with clinical or radiologic evidence of tumor had higher median sGDF-15 (2.1 ng/mL) than tumor-free stage IV or tumor-free stage III patients (both 0.9 ng/mL;
Thirteen different cut-off points of sGDF-15 ranging from 0.7 ng/mL to 1.9 ng/mL were tested in the identification cohort (n=254). The most significant difference in prognosis was observed when 86 patients (33.9%) with sGDF-15 ng/mL and poor OS were compared to 168 (66.1%) patients with lower levels and favorable OS (p<0.001;
This inverse correlation between sGDF-15 and OS was observed in tumor-free stage III patients and in unresectable stage IV patients (
Among stage III patients, the 1-, 2- and 5-years OS probability was 96.1%, 87.8% and 75.7% for those with sGDF-15<1.5 ng/mL but only 90.4%, 74.2% and 61.5% for patients with higher sGDF-15 (Table 6 and Table 10). The association with OS was significant for patients who had been tumor-free for up to 6 months before serum sampling, or for 6 to 24 months. No difference in OS was observed for patients, who had been tumor-free for more than 24 months (
For patients with unresectable distant metastases and sGDF-15 ng/mL the 1-year OS probability was only 14.3%, but 45.0% for those with low sGDF-15. Similarly, the 2-year and 5-year survival was 6.3% and 2.6% compared to 19.9% and 5.2%, respectively (Table 7 and Table 11). The association with OS was significant for patients whose assessment was within 6 months and between 6 and 24 months after first diagnosis of distant metastasis but not for those, who had been in stage IV for more than 24 months (
The Relative Prognostic Impact of sGDF-15 in Stage III Patients
Cox regression analysis of all tumor-free stage III patients was performed to determine the relative impact of sGDF-15 compared to other prognostic factors. The hazard ratio (HR) was 2.2 (p<0.001) for patients with sGDF15 ≤1.5 ng/mL when adjusted for the sub-stage according to American Joint Committee on Cancer (Table 6; model 1). In model 2, which considered a broad spectrum of factors, elevated sS100B was strongly associated with poor OS (
sGDF-15 had independent impact on OS among the entire cohort of stage IV patients (n=293). As expected, a prominent impact of the disease status at the time-point of serum sampling was observed (unresectable disease HR=8.6; p<0.001 vs. tumor-free; Table 13). Thus, unresectable stage IV patients and those which were tumor-free after metastasectomy or complete responses upon prior systemic treatments were analyzed separately.
In tumor-free stage IV patients (n=87), no impact on OS was observed for sGDF-15 (Table 14). Instead, increased sS100B (
Looking at 206 unresectable stage IV patients (Table 7), elevated sGDF-15 had a strong independent negative impact on OS (HR 1.9; p<0.001) in addition to the M category (HR 1.6; p<0.001 for M1c). The association of sGDF-15 with OS was evident both in M1a/b (
In the current study, the inventors surprisingly found that the serum concentration of hGDF-15 is a powerful prognostic biomarker for patients with metastatic melanoma.
For instance, the inventors found that hGDF-15 serum concentrations above 1.5 ng/mL most strongly predicted poor overall survival in a cohort of 761 patients with metastatic melanoma.
In tumor-free stage III patients, no world-wide accepted prognostic biomarkers are used in daily clinical routine. Estimation of the individual prognosis is mainly based on clinical and histopathological characteristics considered for the definition of the sub-stages IIIA, IIIB, or IIIC, respectively (Balch, C M et al., J Clin Oncol/27/6199-206. 2009). Serum LDH does not harbor prognostic information in tumor-free patients after surgery of loco-regional metastases (Wevers, K P et al., Ann Surg Oncol/20/2772-9. 2013). Serum levels of S100B are only analyzed for early detection of recurrences mainly in Europe (Pflugfelder, A et al., J Dtsch Dermatol Ges/11/563-602. 2013), despite a large body of evidence of its prognostic impact in melanoma patients (Mocellin, S et al., Int J Cancer/123/2370-6. 2008). In the current study, the inventors surprisingly found that sGDF15 and sS100B are both independent prognostic markers for these patients and are greatly superior to the clinical sub-stage for the identification of patients who will likely die from the disease.
The analysis of sGDF-15 alone allowed to identify 21% of all tumor-free stage III patients with high serum concentrations, who had a 2-fold increased risk to die within three years after blood draw compared to patients with low levels (33% vs 16%, respectively). The combined consideration of sGDF-15 and sS100B increased the proportion of patients at risk from 21% (sGDF-15 elevated irrespective of sS100B) to 31% (either one or both biomarkers elevated) and further enlarged the difference in OS between biomarker categories. In detail, the risk to die within 3 years with normal sS100B and low sGDF-15 was only 14% compared to 33% for patients with at least one biomarker elevated. The blood draw was taken at times without clinical or radiological evidence of disease in these patients thereby especially the combined analysis of both biomarkers may allow to identify patients which might profit from more intense surveillance or adjuvant therapies.
Thus, according to the invention, the use of hGDF-15 as a biomarker for the prediction of survival, e.g. in combination with S100B as a further biomarker, is highly advantageous even for sub-groups of melanoma patients, for which no reliable prognosis of survival has yet been available.
In unresectable stage IV melanoma patients, the pattern of visceral metastasis and sLDH are regularly used to classify patients into prognostically different M-categories M1a, M1b, or M1c (Balch, C M et al., J Clin Oncol/27/6199-206. 2009). In the present study, the consideration of sGDF-15 in combination with these two established prognostic factors significantly improved the estimation of prognosis for the individual patient (HR 1.7; p<0.001; pattern of visceral metastasis: HR 1.8; p<0.001; sLDH: HR 1.6; p=0.002) and allowed the identification of a relevant subgroup (comprising 30% of all patients with unresectable distant metastasis) with an extremely poor probability to survive 1 year (3.3%). In contrast, the worst biomarker category without consideration of sGDF-15 (visceral metastases other than lung and elevated sLDH; 35% of all unresectable stage IV patients) indicated a 1-year survival estimate of 8.3%. The additional consideration of sGDF-15 added prognostic information for M1a/b as well as for M1c patients. The gain in prognostic information based on the consideration of sGDF-15 is valuable for patient counselling and stratification within clinical trials, and might impact the individual risk/benefit assessment for therapeutic decisions. Considering the availability (and emergence) of various therapeutic options for advanced melanoma and the inevitable trade-off between efficacy and side effects, enhanced prognosis prediction most likely becomes instrumental for the further guidance of individualized therapy.
In conclusion, according to the invention, sGDF-15 is a powerful prognostic biomarker in patients with melanoma such as metastatic melanoma.
In tumor-free stage III patients the consideration of sGDF-15 alone or in combination with sS100B allows to identify individuals with increased risk to die from disease who might profit from more intense patient surveillance or adjuvant treatments. In patients with unresectable stage IV melanoma sGDF-15, sLDH and the pattern of visceral metastasis are independent prognostic factors. The combined consideration of these three factors improves the individual estimate of prognosis compared to the M-category alone and may influence individualized treatment decisions.
The apparatuses and the kits according to the present invention may be industrially manufactured and sold as products for the itemed prediction methods, in accordance with known standards for the manufacture of diagnostic products. Accordingly, the present invention is industrially applicable.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1517528.4 | Oct 2015 | GB | national |
This application is a continuation of U.S. patent application Ser. No. 15/765,187, filed Mar. 30, 2018, which is a 35 U.S.C. § 371 filing of International Patent Application No. PCT/EP2016/073521, filed Sep. 30, 2016, which claims priority to Great Britain Patent Application No. 1517528.4, filed Oct. 2, 2015. The entire disclosures of each of the aforementioned applications are incorporated herein by reference in their entirety.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15765187 | Mar 2018 | US |
| Child | 16876482 | US |
