Patent Grant
11193945
The present disclosure relates generally to biomarkers for evaluating subjects at risk of sinusoidal obstruction syndrome (SOS) early after hematopoietic stem cell transplantation (HSCT). In particular, the present disclosure relates to the use of ST2, ANG2, L-Ficolin, HA, and VCAM1 as a biomarker panel for prognosing, diagnosing, and/or treating SOS (also referred to as veno-occlusive disease (VOD)). The present disclosure is further directed to the use of this biomarker panel for preemptive intervention to minimize the incidence and severity of SOS.
Hematopoietic stem cell transplantation (HSCT) is a potentially life-saving treatment for many patients with inherited disorders and hematologic malignancies. However, its practical use is impeded by the risk of serious adverse events, including sinusoidal obstruction syndrome (SOS, the now preferred name for veno-occlusive disease (VOD), occurring after stem cell transplantation or chemotherapy). Although the overall incidence and severity has fallen in the recent years, SOS is still a life-threatening liver injury complication with greater than 80% mortality in severe cases that affects up to 20% of allogeneic HSCT recipients in some centers. SOS can also occur after intense chemotherapy when either the chemotherapy or radiation induces both systemic inflammation and tissue damage particularly to the sinusoidal endothelial cells of the hepatic acinus. In addition, SOS can also occur after use of drugs such as gemtuzumab ozogamicin and the combination of tacrolimus and sirolimus under certain circumstances.
The pathogenesis of SOS is complex, involving cytokine release, endothelial injury, hemostatic activation, and hepatic drug detoxification through the glutathione pathway. Hepatocellular necrosis, fibrosis, and vascular occlusion ultimately lead to liver failure, hepatorenal syndrome, multiorgan failure, and death. Patients with SOS may present with the classical triad of unexplained weight gain and ascites and, in more severe cases, respiratory distress due to fluid overload, elevated bilirubin, and right upper quadrant pain in severe cases. However, the presentation may be variable in less severe cases. Thus, the etiology of abdominal pain and weight gain following HSCT presents a diagnostic challenge. SOS typically occurs between the first and third weeks after HSCT, but may occur later, and is often clinically indistinguishable from other causes of weight gain and respiratory distress particularly in children (e.g., cytokine storm syndrome and idiopathic pneumonia syndrome) or other causes of abdominal pain and jaundice (e.g., graft-versus-host disease of the gastrointestinal tract or liver). Diagnosis of SOS is assessed according to two clinical scales (Baltimore (Jones R J et al., “Venoocclusive disease of the liver following bone marrow transplantation,” Transplantation, 1987: 44(6):778-783) and Seattle (Shulman H M et al., “Hepatic veno-occlusion disease—liver toxicity syndrome after bone marrow transplantation,” Bone Marrow Transplant. 1992: 10(3):197-214)) that measures different degrees of liver dysfunction and weight gain, and abdominal ultrasound, showing a reversal of the sinusoidal flow, is commonly used to confirm the diagnosis. However, these clinical criteria and reversal of the sinusoidal flow are late events in the pathology of the disease, and ultrasound examination for this phenomenon is not standardized and varies according to operator-dependent practices. Histological evaluation is not routinely performed to confirm the diagnosis in these patients due to their increased risk for bleeding complications with liver biopsy.
Although there is general agreement on the use of clinical criteria for diagnosing SOS, no definitive consensus has been reached regarding a suitable classification system for disease severity beyond the Bearman scale (Bearman S I et al., “Venoocclusive disease of the liver: development of a model for predicting fatal outcome after marrow transplantation,” J Clin Oncol. 1993: 11(9):1729-1736). Consequently, a diagnosis of severe SOS is associated with multiorgan failure and a high mortality rate.
Although no agents have been approved for SOS treatment in the United States, the investigational drug defibrotide has shown the most promising results in several clinical trials and is approved in the European Union for treatment of SOS. Defibrotide is a polydisperse oligonucleotide with fibrinolytic properties and protective effects on vascular endothelium. However, treatment with defibrotide therapy carries significant risks when given late in the disease course, particularly severe hemorrhage. Therefore, a noninvasive method for early and accurate diagnosis of SOS is urgently needed.
Further, although a few potential biomarkers for SOS have been identified based on hypothesis-driven testing, there is still no validated blood test for SOS. Accordingly, there exists a need to identify non-invasive biomarkers for use in diagnosing and prognosing SOS early after HSCT. It would further be advantageous if these methods can be used to provide preemptive intervention to minimize the incidence and severity of SOS.
In one aspect, the present disclosure is directed to a diagnostic biomarker panel comprising suppressor of tumorigenicity 2 (ST2), angiopoietin 2 (ANG2), L-Ficolin, hyaluronic acid (HA) and vascular cell adhesion molecule 1 (VCAM1).
In another aspect, the present disclosure is directed to a prognosis biomarker panel comprising L-Ficolin, hyaluronic acid (HA) and vascular cell adhesion molecule 1 (VCAM1).
In another aspect, the present disclosure is directed to a method of diagnosing or of aiding diagnosis of sinusoidal obstructive syndrome (SOS) in a subject receiving hematopoietic stem cell transplantation (HSCT). The method comprises measuring in a biological sample from the subject the expression of at least one biomarker selected from the group consisting of ST2, ANG2, L-Ficolin, HA, and VCAM1 by contacting the biological sample obtained from the subject with a specific binding agent that specifically binds to the biomarker, wherein the specific binding agent forms a complex with the biomarker; and detecting the agent-biomarker complex, thereby determining the biomarker expression level; wherein an elevated biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of SOS.
In another aspect, the present disclosure is directed to a method of prognosing or of aiding prognosis of sinusoidal obstructive syndrome (SOS) in a subject receiving hematopoietic stem cell transplantation (HSCT). The method comprises: measuring in a biological sample from the subject the expression of at least one biomarker selected from the group consisting of ST2, ANG2, L-Ficolin, HA, and VCAM1 by contacting the biological sample obtained from the subject with a specific binding agent that specifically binds to the biomarker, wherein the specific binding agent forms a complex with the biomarker; and detecting the agent-biomarker complex, thereby determining the biomarker expression level; wherein an elevated biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of a prognosis for shortened survival compared to median survival in a subject having SOS, and wherein a reduced biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of a prognosis for increased survival compared to median survival in a subject having SOS.
It has been discovered herein that suppressor of tumorigenicity 2 (ST2), angiopoietin 2 (ANG2), L-Ficolin, hyaluronic acid (HA) and vascular cell adhesion molecule 1 (VCAM1) can be employed in biomarker panels to diagnosis SOS. Further, in one embodiment, a biomarker panel can be employed to provide opportunities for preemptive intervention to minimize the incidence and severity of SOS clinical symptoms, and thereby increase survival. The present disclosure further relates to the use of these biomarkers and biomarker panels for prognosing, diagnosing, and/or treating SOS in a subject that has received or is receiving hematopoietic stem cell transplantation (HSCT).
The present disclosure uses examples to disclose the invention to enable any person skilled in the art to practice the invention, including making and using any panels or devices and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal language of the claims.
Unless otherwise defined, all terms of art, notations and other scientific terminology used herein are intended to have the ordinary meanings commonly understood by those of ordinary skill in the art to which this invention pertains. In some cases, terms with commonly understood meanings are defined herein for clarity and/or for ready reference, and the inclusion of such definitions herein should not necessarily be construed to represent a substantial difference over what is generally understood in the art. The techniques and procedures described or referenced herein are generally well understood and commonly employed using conventional methodology by those skilled in the art, such as, for example, the widely utilized molecular cloning methodologies described in Sambrook et al., Molecular Cloning: A Laboratory Manual 2nd. edition (1989) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. As appropriate, procedures involving the use of commercially available kits and reagents are generally carried out in accordance with manufacturer defined protocols and/or parameters unless otherwise noted.
As used herein, the term “biomarker” refers to an indicator of, for example, a pathological state of a subject, which can be detected in a biological sample of the subject. Biomarkers include DNA-based, RNA-based and protein-based molecular markers.
As used herein, the term “diagnosis” refers to the identification or classification of a molecular or pathological state, disease or condition. For example, “diagnosis” can refer to identification of a particular type of a condition (such as sinusoidal obstruction syndrome (“SOS”)).
As used herein, the term “aiding diagnosis” refers to methods that assist in making a clinical determination regarding the presence, or nature, of a particular type of symptom of a condition (such as SOS). For example, a method of aiding diagnosis of a condition (such as SOS) can include measuring the expression of certain genes in a biological sample from an individual.
As used herein, the term “prognosis” is used herein to refer to the categorization of patients by degree of risk for a disease (such as SOS) or progression of such disease. A “prognostic marker” refers to an assay that categorizes patients by degree of risk for disease occurrence or progression.
As used herein, the term “sample” refers to a composition that is obtained or derived from a subject of interest that contains a cellular and/or other molecular entity that is to be characterized and/or identified, for example based on physical, biochemical, chemical and/or physiological characteristics. For example, the phrase “disease sample” and variations thereof refers to any sample obtained from a subject of interest that would be expected or is known to contain the cellular and/or molecular entity that is to be characterized. A “tissue” or “cell sample” refers to a collection of similar cells obtained from a tissue of a subject or patient. The source of the tissue or cell sample may be blood or any blood constituents (e.g., whole blood, plasma, serum) from the subject. The tissue sample can also be primary or cultured cells or cell lines. Optionally, the tissue or cell sample is obtained from a disease tissue/organ. The tissue sample can contain compounds which are not naturally intermixed with the tissue in nature such as preservatives, anticoagulants, buffers, fixatives, nutrients, antibiotics, and the like.
As used herein, the terms “control”, “control cohort”, “reference sample”, “reference cell”, “reference tissue”, “control sample”, “control cell”, and “control tissue” refer to a sample, cell or tissue obtained from a source that is known, or believed, to not be afflicted with the disease or condition for which a method or composition of the invention is being used to identify. The control can include one control or multiple controls. In one embodiment, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from a healthy part of the body of the same subject or patient in whom a disease or condition is being identified using a composition or method of the invention. In one embodiment, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from a healthy part of the body of an individual who is not the subject or patient in whom a disease or condition is being identified using a composition or method of the invention.
The term “antibody” is used in its broadest sense and specifically covers, for example, monoclonal antibodies, polyclonal antibodies, antibodies with polyepitopic specificity, single chain antibodies, multi-specific antibodies and fragments of antibodies. Such antibodies can be chimeric, humanized, human and synthetic.
The term “subject” is used interchangeably herein with “patient” to refer to an individual to be treated. The subject is a mammal (e.g., human, non-human primate, rat, mouse, cow, horse, pig, sheep, goat, dog, cat, etc.). The subject can be a clinical patient, a clinical trial volunteer, an experimental animal, etc. The subject can be suspected of having or at risk for having a condition (such as SOS) or be diagnosed with a condition (such as SOS). The subject can also be suspected of having or at risk for having SOS. According to one embodiment, the subject to be treated according to this invention is a human.
As used herein, “treating”, “treatment” and “alleviation” refer to measures, wherein the object is to prevent or slow down (lessen) the targeted pathologic condition or disorder or relieve some of the symptoms of the disorder. Those in need of treatment can include those already with the disorder as well as those prone to have the disorder, those at risk for having the disorder and those in whom the disorder is to be prevented.
“Elevated expression level” and “elevated levels” refer to an increased expression of a mRNA or a protein in a patient (e.g., a patient suspected of having or diagnosed as having SOS) relative to a control, such as subject or subjects who are not suffering from SOS.
In one embodiment, the present disclosure is directed to a method of prognosing or of aiding in the prognosis of sinusoidal obstructive syndrome (SOS) in a subject receiving hematopoietic stem cell transplantation (HSCT). The method comprises: obtaining a biological sample from the subject; measuring in a biological sample from the subject, the expression of at least one biomarker selected from the group consisting of ST2, ANG2, L-Ficolin, HA, and VCAM1 by contacting the biological sample obtained from the subject with a specific binding agent that specifically binds to the biomarker, wherein the specific binding agent forms a complex with the biomarker; and detecting the agent-biomarker complex, thereby determining the biomarker expression level; wherein an elevated biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of a prognosis for shortened survival compared to median survival in a subject having SOS, and wherein a reduced biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of a prognosis for increased survival compared to median survival in a subject having SOS.
The specific binding agent can be selected from a nucleic acid, an antibody, a receptor, and a lectin.
The sample can be selected from liver tissue, whole blood, plasma and serum.
In some embodiments, the step of measuring includes contacting the biological sample with a biomarker panel comprising L-Ficolin, hyaluronic acid (HA) and vascular cell adhesion molecule 1 (VCAM1).
The specific binding agent-biomarker complex can be detected using methods known to those skilled in the art such as, for example, microarray analysis, immunoassay, immunohistochemistry, and mass spectrometry. Representative immunoassays include Western blot analysis and ELISA.
It has been advantageously found that the biomarker panels used in the methods of the present disclosure can be used for prognosing SOS early after HSCT. Particularly, in some embodiments, the methods can be used to prognosis SOS the same day as HSCT. In other embodiments, prognosis can be made one week, two weeks, or three weeks from HSCT. Accordingly, the methods of prognosing SOS can include obtaining the biological sample at day 0 from HSCT, including obtaining the sample from day 0 to day 7 from HSCT, including obtaining the sample from day 0 to day 14 from HSCT, and including obtaining the sample from day 0 to day 21 from HSCT.
In another embodiment, the present disclosure is directed to a method for diagnosing SOS in a subject, particularly a subject receiving hematopoietic stem cell transplantation (HSCT). The method comprises: measuring in a biological sample from the subject the expression of at least one biomarker selected from the group consisting of ST2, ANG2, L-Ficolin, HA, and VCAM1 by contacting the biological sample obtained from the subject with a specific binding agent that specifically binds to the biomarker, wherein the specific binding agent forms a complex with the biomarker; and detecting the agent-biomarker complex, thereby determining the biomarker expression level; wherein an elevated biomarker expression level compared to biomarker expression obtained from a biological sample obtained from a control is indicative of SOS.
The specific binding agent can be selected from a nucleic acid, an antibody, a receptor, and a lectin.
The sample can be selected from whole blood and plasma.
In some embodiments, the step of measuring includes contacting the biological sample with a biomarker panel comprising tumorigenicity 2 (ST2), angiopoietin 2 (ANG2), L-Ficolin, hyaluronic acid (HA) and vascular cell adhesion molecule 1 (VCAM1).
The specific binding agent-biomarker complex can be detected using methods known to those skilled in the art such as, for example, microarray analysis, immunoassay, immunohistochemistry, and mass spectrometry. Representative immunoassays include Western blot analysis and ELISA.
It has been advantageously found that the biomarker panels used in the methods of the present disclosure can be used for diagnosing SOS early after HSCT. Particularly, in some embodiments, the methods can be used to diagnose SOS the same day as HSCT. In other embodiments, diagnosis can be made one week, two weeks, or three weeks from HSCT. Accordingly, the methods of diagnosing SOS can include obtaining the biological sample at day 0 from HSCT, including obtaining the sample from day 0 to day 7 from HSCT, including obtaining the sample from day 0 to day 14 from HSCT, and including obtaining the sample from day 0 to day 21 from HSCT.
The biological sample used in the methods of the present disclosure can be obtained using certain methods known to those skilled in the art. Biological samples may be obtained from vertebrate animals, and in particular, mammals. In certain instances, a biological sample is whole blood, plasma, or serum. By screening such body samples, a prognosis or diagnosis can be achieved for SOS.
As used in the various methods of the present disclosure, the terms “control”, “control value”, “reference” and “reference value” refer to an expression level value obtained from “control sample”, “control cell”, and “control tissue” “reference sample”, “reference cell”, and “reference tissue” obtained from a source that is known, or believed, to not be afflicted with the condition for which a method or composition is being used to identify. It is to be understood that the control need not be obtained at the same time as the biological sample of the subject is obtained. Thus, a control value for an expression level can be determined and used for comparison of the expression level for the biological sample of the subject or the biological samples of multiple subjects.
Expression levels of proteins may be detected in samples of whole blood, plasma, or serum. Various methods are known in the art for detecting protein expression levels in such biological samples, including various immunoassay methods.
Materials and Methods
A. Patients and Samples
Three sets of HSCT patients were included in these Examples. Patients were treated at the University of Michigan, at Indiana University, and at University of Barcelona. All patients or their legal guardians provided written informed consent, and the study for post-HSCT complications samples collection was approved by the institutional review boards of the University of Michigan, Indiana University, and Hospital Clinic, University of Barcelona.
Heparinized blood samples were collected before or on the day of HCT, then weekly for 2 or 4 weeks after allogeneic HSCT, then monthly for 2 months, as well as at the time of key clinical events, including the onset of symptoms consistent with SOS. Plasma samples were collected prospectively per institutional guidelines.
For analysis, plasma samples were thawed and centrifuged at 12,000 rpm for 10 minutes to separate the clots at the bottom and lipids on top from the plasma. Then, 150-μl aliquots of each undiluted plasma sample were plated in 96-well V-bottom plates by manual pipetting. The plates were wrapped in parafilm and kept in a humid chamber at 4° C. during the entire process, which did not exceed 96 hours.
B. Proteomics Analysis
The methods used for sample preparation, protein fractionation, MS analysis, protein identification, and quantitative analysis of protein concentrations during the intact protein analysis system have been previously reported in Faca V. et al., “Quantitative analysis of acrylamide labeled serum proteins by LC-MS/MS,” J. Proteome Res. 2006: 5(8):2009-2018; Faca V. et al., “Contribution of protein fractionation to depth of analysis of the serum and plasma proteomes,” J Proteome Res. 2007: 6(9):3558-3565; and Paczesny S. et al., “Elafin is a biomarker of graft-versus-host disease of the skin,” Science Translational Medicine, 2010: 2(13):13ra12. The MS-based proteomics approach used in these Examples is illustrated in
C. Immunoassays
Suppressor of tumorigenicity 2 (ST2), angiopoietin2 (ANG2), L-Ficolin, hyaluronic acid (HA), vascular cell adhesion molecule 1 (VCAM1), tissue inhibitor of metalloproteinase 1 (TIMP1), thrombomodulin (sCD141), intercellular adhesion molecule 1 (ICAM1), plasminogen activator inhibitor-1 (PAI-1), von Willebrand factor (vWF), and CD97 concentrations were measured by enzyme-linked immunosorbent assays (ELISAs). The antibody pairs used for these ELISAs were as follows: anti-ST2 (R&D Systems, Minneapolis, Minn.), anti-ANG2 (R&D Systems), anti-L-Ficolin (Hycult Biotech, Plymouth Meeting, Pa.), anti-HA (Corgenix, Broomfield, Colo.), anti-VCAM1 (R&D Systems), anti-TIMP1 (R&D Systems), anti-thrombomodulin (Diaclone, Besancon, France), anti-ICAM1 (R&D Systems), anti-PAI-1 (eBioscience, San Diego, Calif.), anti-vWF (American Diagnostica, Stamford, Conn.), and anti-CD97 (R&D Systems).
Capture antibodies were reconstituted and diluted per manufacturers' specifications or pre-coated plates were used as recommended by the manufacturer. Then, 50-μl of diluted antibodies were added to wells of 96-well high-binding half-well plates, which were then sealed and incubated overnight. The next day, the test plates containing the capture antibodies were washed and blocked with specific manufacturer's recommended blocking buffer. After additional wash steps, 50-μl or 100-μl aliquots of plasma samples (dilutions listed in Table 1) were added in duplicate to the ELISA test plates. In addition, 50-μl or 100-μl aliquots of reconstituted standard at different concentrations (see Table 1) were added in duplicate for the preparation of 8-point standard curves per the manufacturers' protocols. After addition of samples and standard solutions, the plates were sealed and incubated for 2 hours at room temperature on a plate rotator at 300 rpm. The ELISAs were completed by adding biotinylated detection antibodies specific for each target followed by the enzyme horseradish peroxidase (HRP) and HRP substrate. The optical density of each well was read using a plate reader set to 450-570 nm. The ELISAs were performed in duplicate and sequentially.
D. Statistical Analysis
The statistical methods used for the IPAS were previously described in Faca V. et al., J Proteome Res. 2006: 5(8):2009-2018; Faca V. et al., J Proteome Res. 2007: 6(9):3558-3565; and Paczesny S. et al., Science Translational Medicine. 2010: 2(13):13ra12. Differences in characteristics between patient groups were assessed with Kruska-Wallis tests for continuous values and chi-squared tests of association for categorical values. Protein concentrations from individual samples in the discovery and validation sets were compared using two sample t-tests. Receiver operating characteristic (ROC) areas under the curves (AUCs) were estimated nonparametrically. A ROC curve is a plot of the false positive rate on the x axis and true positive rate on the y axis for every possible level of a marker. A perfect test would have a ROC curve that is a right angle demonstrating 100% of true positives and no false positives. In this case, the corresponding Area Under the Curve (AUC) will equal to 1. A random test will have an AUC of 0.5 meaning there is one false positive for every true positive. Differences in median pre-HCT, day 0, +7, and +14 biomarker levels between SOS− and SOS+ patients were assessed using a Wilcoxon rank-sum test. Additionally, the differences in biomarkers trajectories were examined over time using a modeling approach.
E. Prognostic Bayesian Modeling
The plasma concentrations of 3 proteomic biomarkers (L-Ficolin, HA, and VCAM1) on the day of HCT were used to evaluate their prognostic performance for future occurrence of SOS onset. The clinical characteristics also included in the analysis were age, gender, donor type (related or unrelated), donor match (matched or mismatched), transplantation period (before or in 2005 or after 2005), transplantation number (1 or >1), conditioning regimen (chemotherapy only or combined with irradiation), busulfan (16 mg/kg) use in the conditioning (yes or no), and cyclophosphamide use in the conditioning (yes or no). Plasma protein concentrations and clinical characteristics were used as attributes for the prognosis of SOS onset. The Naïve Bayes classifier was selected for SOS onset prognosis because of its simplicity and high classification performance. Ten-fold cross-validation was used to avoid over training, bias, and/or artifacts. This Naïve Bayes classifier was developed with Waikato Environment for Knowledge Analysis software v3.6.10.
In this Example, proteomic analysis was conducted to compare plasma pooled from 20 patients with SOS to plasma pooled from 20 patients without SOS. The clinical characteristics of patients are provided in Table 2.
§Other GVHD prophylaxis included Tacro/corticosteroids (n = 3), MTX/corticosteroids (n = 2), Tacro/MTX/corticosteroids (n = 1).
Of 494 proteins identified and quantified, 151 proteins showed at least a 2-fold increase in the heavy/light isotope ratio, and 77 proteins showed a heavy-light isotope ratio of 0.5 or less (see Table 3 for complete summary) From the identified proteins, six proteins were selected for further analysis: L-Ficolin, VCAM1, TIMP1, vWF, and CD97. These proteins were selected based on the observation of at least a 2-fold increase or decrease in the heavy/light isotope ratio and their involvement in networks possibly involved in the pathogenesis of SOS. In addition, five endothelial markers (ST2, ANG2, HA, thrombomodulin, and PAI-1) were analyzed based on their involvement in SOS.
homo sapiens clone 23623.
In this Example, the biomarkers identified in Example 1 were further analyzed in plasma using sequential ELISAs from a validation set of 45 patients: 32 SOS patients at disease onset (days +14 to +21 post-HSCT) and from 13 time-matched controls.
The clinical characteristics of patients in this validation set are described in Table 1. Further, diagnosis samples from SOS+ patients that were taken at the time of SOS onset were used and samples from SOS− patients were selected so that both groups of samples were balanced according to time of acquisition. The clinical characteristics of patients in this training cohort are described in Table 1. The SOS− and SOS+ groups were balanced for age, primary disease, donor type (related versus unrelated), donor match, and intensity of the conditioning regimen (all full intensity with most receiving 16 mg/kg busulfan for 4 days or total body irradiation). More than 90% of patients received GVHD prophylaxis of methotrexate and tacrolimus (or cyclosporine) of standard duration. The value of these proteins as diagnostic biomarkers of SOS were analyzed using two-sample t-tests and by calculating the AUCs of the ROCs, which represent the false positive and true positive rates for every possible level of a marker.
ST2, ANG2, L-Ficolin, HA, VCAM1, TIMP1, sCD141, ICAM1, and PAI-1 were identified as diagnostic biomarkers of SOS with p-values ranging from <0.001 to 0.04 and with AUCs between 0.91 and 0.70 (
In this Example, the prognostic significance of the biomarkers identified in Example 2 was analyzed using Wicoxon Rank-Sum analysis of protein levels measured before presentation of the clinical signs (days 0 and +7 post-HSCT). Three diagnostic biomarkers were also determined to be prognostic before clinical signs were apparent (L-Ficolin, HA, and VCAM1; AUC: 0.83-0.69), and the corresponding AUC values for biomarker values on the day of HCT were between 0.84 and 0.70 (
In this Example, three biomarkers (L-Ficolin, HA, and VCAM1) identified as prognostic biomarkers in Example 3 were validated as prognostic biomarkers in an independent set of 35 patients from the Indiana University HSCT biobank (13 patients with SOS; 22 patients without SOS). The prognostic significance of these biomarkers was analyzed using Wilcoxon Rank-Sum analysis of their plasma levels measured before the clinical signs (days 0, +7 post-HSCT, and +14 post-HSCT). Further, plasma levels of these markers measured pre-transplant showed no difference suggesting that the conditioning regimen (i.e., intense chemotherapy +/− total body irradiation to prepare the subject for its graft) explain the levels seen at day 0. Particularly, the conditioning regimen is conducted between day −7 (pre-sample (i.e., samples taken before the conditioning regimen)) and day −1. At day 0, the donor cells were injected before the graft was injected. Thus, the only difference between the day −7 and day 0 samples is the conditioning regimen.
In this smaller set, L-Ficolin remained a strong prognosis marker as early as the day of transplant with an AUC of 0.88. Of note, the three markers were highly significant at day 14 (median day of onset) (see
L-Ficolin, HA, and VCAM1 were then tested as prognostic markers of SOS with samples taken before the appearance of clinical signs of SOS. L-Ficolin and HA also stratified patients at risk for SOS as early as the day of HCT in this independent cohort (
In this Example, a Naïve Bayes classifier implemented in Waikato Environment for Knowledge Analysis (WEKA) was developed for SOS prognosis based on a balanced subset of 24 patients (11 SOS−; 13 SOS+). The classifier performance was evaluated by doing a 10-fold cross-validation.
Naïve Bayes is an algorithm that is based on Bayes rule of probability. It combines all attributes to maximize the probability of a correct prediction for an outcome. It works by calculating the probabilities for each attribute and then multiplying them.
Infogain is an attribute selection algorithm that evaluates each attribute separately by calculating their information gain with respect to the outcome.
10-fold Cross-Validation: a technique that partitions the dataset into 10-folds. Each fold is held out for testing or validating the model and the remainder is used for learning or building the model.
The modeling strategy used both models (see
The attributes tested were:
Three different groups of patients were evaluated:
The balanced subset 2 with no missing attribute information was selected to build the prognostic model. This selection was based on results comparing the correct prognosis between the 3 subsets tested and their corresponding ROC AUCs (Table 4).
The clinical characteristics of patients in this set are presented in Table 5.
The model was evaluated using plasma concentrations of biomarkers on day 0 with and without the addition of the clinical characteristics. Table 6 shows the results (correct prognosis and false negatives and positives) of the model building using the selected data subset. The correct prognosis was achieved in 83.3% of patients using the day 0 plasma biomarker concentrations in addition to clinical attributes (ROC AUC=0.90).
The results of the infogain (Table 7) showed that in all groups the biomarkers at day 0 or the biomarker slopes provided the best infogain.
In this Example, the diagnostic and prognostic values of the biomarkers were analyzed in an independent prospective set of 16 patients from the Indiana University HSCT biobank (6 patients with SOS; 10 patients without SOS). The basic and clinical characteristics of patients in this independent set are presented in Table 8. Despite the small sample size, the results further validated L-Ficolin and HA as diagnostic (AUC: 0.83 and 0.75, respectively) and prognostic markers of SOS.
‡Full-Intensity conditioning regimens include: BuCy (n = 1), BAC (n = 15), CyTBI (n = 2), FluBu (n = 1), Fludarabine/Melphalan (n = 1), Carboplatin/Etoposide/Melphalan (n = 4), Carboplatin/Thiotepa (n = 2), CyFlu (n = 4), and CyThiotepa (n = 2)
Based on the foregoing Examples, for the first time, biomarkers of SOS in plasma samples from patients undergoing allogeneic HSCT were identified. In addition to identifying a panel of biomarkers that can be used for SOS diagnosis (i.e., together ST2, ANG2, L-Ficolin, HA, and VCAM1 represent a biomarker panel for reliable, non-invasive diagnosis of SOS (AUC=0.98)), a panel of three biomarkers (L-Ficolin, HA, and VCAM1) were identified that can be used to evaluate the risk of developing SOS before clinical signs appear, even as early as the day of HSCT. L-Ficolin, HA, and VCAM1 can stratify patients at risk of SOS as early as the day of HSCT, which has therapeutic consequences including potential preemptive interventions. L-Ficolin's mechanism of action implicates pathways in SOS other than those related to hemostasis and endothelial injury.
These results demonstrate that SOS can be diagnosed based on a panel of biomarkers in plasma as well as predicted as early as the day of HSC infusion in patients. The identified markers represent several pathways, including pathways suspected to be involved in hemostasis and endothelial injury, as well as novel pathways related to innate immunity and homeostatic clearance of mitochondria. Analyses using the biomarker panels provide preemptive intervention to minimize the incidence and severity of SOS clinical symptoms, and thereby increase survival.
Bayesian Modeling Discussion
Bayesian modeling infers causal relationships between molecular interactions by randomly generating many possible network models and using statistical techniques to select a consensus model that best fits the data. Thus, these methods balance the trade-off between prior knowledge and the data. A Bayesian model was developed to confirm the value of the prognostic biomarker panels to risk-stratify the patients for SOS with a more unbiased approach. The high sensitivity and specificity of the biomarkers identified in the present disclosure make them useful for real-time clinical testing and early clinical intervention.
A proposed SOS preemptive clinical study is presented in
This application is a continuation of U.S. application Ser. No. 15/521,783, filed on Apr. 25, 2017, which is a U.S. national counterpart application of international application serial No. PCT/US2015/057393 filed Oct. 26, 2015, which claims priority to U.S. Provisional Application Ser. No. 62/069,394, filed Oct. 28, 2014, which is hereby incorporated by reference in its entirety.
This invention was made with government support under HD071598, HL101102, and CA168814 awarded by the National Institutes of Health. The government has certain rights in the invention.
| Number | Name | Date | Kind |
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| 20110287964 | Bonventre et al. | Nov 2011 | A1 |
| Number | Date | Country |
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| 102858985 | Jan 2013 | CN |
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| Number | Date | Country | |
|---|---|---|---|
| 20200182886 A1 | Jun 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62069394 | Oct 2014 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15521783 | US | |
| Child | 16781407 | US |
