Clinical efficacy comparison of avapritinib with other tyrosine kinase inhibitors in gastrointestinal stromal tumors with PDGFRA D842V mutation: a retrospective analysis of clinical trial and real-world data.

BACKGROUND: Avapritinib, a potent inhibitor of KIT and platelet-derived growth factor receptor A (PDGFRA) tyrosine kinases, has demonstrated unprecedented clinical activity in PDGFRA D842V-mutant gastrointestinal stromal tumors (GIST). METHODS: This retrospective analysis compared efficacy of avapritinib in patients enrolled in the NAVIGATOR phase 1 trial (NCT02508532) with the efficacy of other tyrosine kinase inhibitors (TKIs) in patients with unresectable/metastatic PDGFRA D842V-mutant GIST enrolled in a retrospective natural history study (Study 1002). The primary endpoint was overall survival (OS) from the start of reference treatment (avapritinib for NAVIGATOR patients or first-line TKI for treatment of unresectable/metastatic GIST for Study 1002 patients); the secondary endpoint was progression-free survival (PFS). Adjusted Kaplan-Meier survival curves were compared by Cox regression. RESULTS: Fifty-six (NAVIGATOR) and 19 (Study 1002) patients with PDGFRA D842V-mutant GIST were evaluated; of the 56 patients from NAVIGATOR, a subgroup of patients treated with either 300 mg (recommended phase 2 dose) or 400 mg (maximum tolerated dose) avapritinib starting dose (n = 38) were analyzed separately. Patient characteristics were adjusted for imbalances by propensity score between the study groups. Inverse probability of treatment weighting-adjusted Kaplan-Meier analysis of OS showed median OS was not reached for NAVIGATOR patients treated with any of the avapritinib doses tested and was 12.6 months for Study 1002 patients; OS rate at 6/48 months was 100%/63% in NAVIGATOR and 56%/17% in Study 1002 (P = 0.0001). In the 300/400 mg subgroup, adjusted OS rates at 6/36 months were 100%/73 and 68%/20% in Study 1002 (P = 0.0016). Adjusted median PFS was 29.5 months in NAVIGATOR and 3.4 months in Study 1002. CONCLUSIONS: In this indirect, retrospective analysis, avapritinib demonstrated more durable survival outcomes compared with other TKIs in patients with unresectable/metastatic PDGFRA D842V-mutant GIST. TRIAL REGISTRATION: The NAVIGATOR trial was registered at ClinicalTrials.gov as per July 2015, Identifier: NCT02508532 .

The diagnostic workup for systemic mastocytosis differs from consensus recommendations: Results of a worldwide survey.

Objective: Mastocytosis is a complex disorder affecting various organs. The diagnostic workup can be challenging and requires a multidisciplinary approach including the use of uncommon tests. To assess mastocytosis management around the globe, we conducted the first worldwide online survey for physicians. Methods: A 21-item questionnaire was sent out to the members of the World Allergy Organization (WAO), the Global Allergy and Asthma European Network (GA2LEN), the Urticaria (UCARE) and Angioedema (ACARE) Centers of Reference and Excellence, the German Society of Allergology and Clinical Immunology (DGAKI), and the European Mast Cell and Basophil Research Network (EMBRN) in April-June 2021. Results: Across 628 respondents from 79 countries 87.7% and 9.7% of physicians were allergists/clinical immunologists and/or dermatologists. Participating physicians were from all regions of the world (Europe, EU: 41.6%; North America, NA: 24.8%; Latin America, LA: 14.5%; Asia-Pacific, AP: 12.6%; and Africa/Middle East, AME: 6.5%). Only 2.2% of respondents worked at Specialized Mastocytosis Centers (SMCs) in North America or European Union. Physicians reported caring for 4 patients with mastocytosis per year, with higher numbers in European Union and Asia Pacific (5/year) compared to Latin America (2/year). Dermatologists and physicians who work at SMCs reported higher patient numbers (15/year and 80/year, respectively). Suspicion of mastocytosis in the allergology and dermatology community is commonly driven by anaphylaxis (82.9%), mastocytosis skin lesions (82.1%), or elevated tryptase levels (76.6%). Osteoporosis and gastrointestinal symptoms less often prompted suspicion of mastocytosis (21.4% and 49.9%, respectively). World Health Organisation (WHO)-diagnostic criteria and classification, regardless of the region, are only used by about 50% of physicians, with higher rates for SMCs (83.3%). Serum tryptase, bone marrow biopsy, and KIT D816V mutation analysis are included in the diagnostic workup by 90.9%, 61.5%, and 58.4% of physicians, respectively. The biggest challenges for the management of mastocytosis are the lack of more effective treatment options (51.1%), missing multidisciplinary networks (47.1%), and the lack of experience of specialists from other disciplines (39.0%). Conclusions: The diagnostic workup for mastocytosis differs from consensus recommendations and varies between regions. This may be improved by establishing active multidisciplinary networks, increasing access to diagnostic procedures, consistently applying WHO criteria, and developing new Mastocytosis Centers of Reference and Excellence.

Proteomic identification of altered apolipoprotein patterns in pulmonary hypertension and vasculopathy of sickle cell disease.

Pulmonary arterial hypertension (PAH) is emerging as a major complication and independent risk factor for death among adults with sickle cell disease (SCD). Using surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS), we searched for biomarkers of PAH in plasma specimens from 27 homozygous sickle cell anemia (HbSS) patients with PAH and 28 without PAH. In PAH patients, analysis consistently showed lower abundance of a 28.1-kDa peak (P < .001), identified by high-resolution mass spectrometry as the oxidant-scavenging protein apolipoprotein A-I (apoA-I), which correlated with clinical assays of apoA-I (r = .58, P < .001) and high-density lipoprotein (HDL) levels (r = .50, P = .001). Consistent with endothelial dysfunction that may mediate this effect in PAH, HbSS patients with lower apoA-I levels also displayed impaired vasodilatory responses to acetylcholine (mean +/- SEM, 189% +/- 34% [n = 13] vs 339% +/- 51% [n = 13], P < .001). As a group, patients with SCD demonstrated significantly lower apoA-I levels than African-American control subjects. The PAH cohort was further characterized by high levels of apolipoproteins A-II and B and serum amyloid A, and low levels of haptoglobin dimers and plasminogen. These results imply a relationship of apolipoproteins to the development of PAH vasculopathy in SCD, potentially involving an unexpected mechanistic parallel to atherosclerosis, another proliferative vasculopathy.

Apolipoprotein A-I and serum amyloid A plasma levels are biomarkers of acute painful episodes in patients with sickle cell disease.

BACKGROUND: Acute painful episodes are the clinical hallmark of sickle cell disease and have been linked to morbidity and mortality in the sickle cell population. DESIGN AND METHODS: We undertook exploratory proteomic studies on paired plasma samples collected from a cohort of 26 adult sickle cell patients during steady state and on the first day of an acute painful episode. We screened for changes in abundance of specific protein peaks via surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS), and confirmed the identify of candidate protein peaks by specific immunoassays. RESULTS: The levels of hemoglobin, hematocrit, total protein, and albumin were lower and the levels of lactate dehydrogenase and absolute reticulocytes higher during acute painful episodes than during the steady state. Surface-enhanced laser desorption/ionization time of flight mass spectrometry spectral analysis consistently showed a mass-to-charge peak at 11.7 kDa with elevated intensities during acute painful episodes, which correlated significantly with the serum amyloid A immunoassay. Serum amyloid A levels were significantly elevated during acute painful episodes, especially in four patients with marked end-organ complications of such episodes. A second, recurring peak, less abundant during acute painful episodes, was present at 28.1 kDa; this peak was correlated significantly with immunoassay measurements of apolipoprotein A1. CONCLUSIONS: On the average, plasma serum amyloid A rises and apolipoprotein AI falls during acute painful episodes. The serum amyloid A/apolipoprotein AI ratio increased in 81% of the patients during acute painful episodes, potentially making it a useful objective marker of such episodes. We propose that these protein alterations, known to contribute to endothelial dysfunction in other settings, might do likewise acutely in acute painful episodes and present a new target for therapeutic intervention in sickle cell disease. (ClincalTrials.gov Identifier: NCT00081523).

Real-world healthcare resource utilization in patients with indolent non-Hodgkin lymphoma: differences between patients treated with first-line ibrutinib or bendamustine + rituximab.

Objective: This study evaluated the real-world healthcare resource utilization (HCRU) and costs in patients diagnosed with an indolent non-Hodgkin lymphoma (iNHL) and treated with either first-line ibrutinib monotherapy (IbM) therapy or bendamustine plus rituximab combination therapy (BR).Methods: Treatment-naïve iNHL patients in the IBM MarketScan Research Databases were identified based on the first prescription of either IbM or BR therapy between 02/01/2014 and 08/30/2017.Results: A greater proportion of IbM patients (n = 207) had at least one inpatient admission (IP) or emergency room visit (ER), both all-cause and iNHL-related, than BR (n = 1337) patients. In addition, the mean number of IP admissions and ER visits was significantly higher in the IbM cohort. No differences in total costs were found. Outpatients costs were higher in IbM patients and medical costs were higher in BR patients.Conclusions: These real-world findings highlight the importance of considering the healthcare resource utilization and the associated costs of iNHL patients which may be associated with their first-line therapy.

Identification of biomarkers for risk stratification of cardiovascular events using genetic algorithm with recursive local floating search.

Conventional biomarker discovery focuses mostly on the identification of single markers and thus often has limited success in disease diagnosis and prognosis. This study proposes a method to identify an optimized protein biomarker panel based on MS studies for predicting the risk of major adverse cardiac events (MACE) in patients. Since the simplicity and concision requirement for the development of immunoassays can only tolerate the complexity of the prediction model with a very few selected discriminative biomarkers, established optimization methods, such as conventional genetic algorithm (GA), thus fails in the high-dimensional space. In this paper, we present a novel variant of GA that embeds the recursive local floating enhancement technique to discover a panel of protein biomarkers with far better prognostic value for prediction of MACE than existing methods, including the one approved recently by FDA (Food and Drug Administration). The new pragmatic method applies the constraints of MACE relevance and biomarker redundancy to shrink the local searching space in order to avoid heavy computation penalty resulted from the local floating optimization. The proposed method is compared with standard GA and other variable selection approaches based on the MACE prediction experiments. Two powerful classification techniques, partial least squares logistic regression (PLS-LR) and support vector machine classifier (SVMC), are deployed as the MACE predictors owing to their ability in dealing with small scale and binary response data. New preprocessing algorithms, such as low-level signal processing, duplicated spectra elimination, and outliner patient's samples removal, are also included in the proposed method. The experimental results show that an optimized panel of seven selected biomarkers can provide more than 77.1% MACE prediction accuracy using SVMC. The experimental results empirically demonstrate that the new GA algorithm with local floating enhancement (GA-LFE) can achieve the better MACE prediction performance comparing with the existing techniques. The method has been applied to SELDI/MALDI MS datasets to discover an optimized panel of protein biomarkers to distinguish disease from control.

A novel peak detection approach with chemical noise removal using short-time FFT for prOTOF MS data.

Peak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short-time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut-off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin-bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease-free patients to detect peaks with S/N> or =2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.

Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke.

BACKGROUND: Strokes are a leading cause of morbidity and the first cause of adult disability in the United States. Currently, no biomarkers are being used clinically to diagnose acute ischemic stroke. A diagnostic test using a blood sample from a patient would potentially be beneficial in treating the disease. RESULTS: A classification approach is described for differentiating between proteomic samples of stroke patients and controls, and a second novel predictive model is developed for predicting the severity of stroke as measured by the National Institutes of Health Stroke Scale (NIHSS). The models were constructed by applying the Logical Analysis of Data (LAD) methodology to the mass peak profiles of 48 stroke patients and 32 controls. The classification model was shown to have an accuracy of 75% when tested on an independent validation set of 35 stroke patients and 25 controls, while the predictive model exhibited superior performance when compared to alternative algorithms. In spite of their high accuracy, both models are extremely simple and were developed using a common set consisting of only 3 peaks. CONCLUSION: We have successfully identified 3 biomarkers that can detect ischemic stroke with an accuracy of 75%. The performance of the classification model on the validation set and on cross-validation does not deteriorate significantly when compared to that on the training set, indicating the robustness of the model. As in the case of the LAD classification model, the results of the predictive model validate the function constructed on our support-set for approximating the severity scores of stroke patients. The correlation and root mean absolute error of the LAD predictive model are consistently superior to those of the other algorithms used (Support vector machines, C4.5 decision trees, Logistic regression and Multilayer perceptron).

Changes in salivary proteome following allogeneic hematopoietic stem cell transplantation.

OBJECTIVE: Allogeneic hematopoietic stem cell transplantation (allo-HCT) is frequently complicated by severe infections and graft-vs-host disease (GVHD). Saliva contains many components of adaptive and innate immune response crucial for local host defenses. Changes in salivary constituents could reflect systemic processes such as immune reconstitution and development of GVHD that occur posttransplant. This study was an initial evaluation of salivary protein changes that occur after allo-HCT. PATIENTS AND METHODS: Serially collected saliva samples from 41 patients undergoing allo-HCT were evaluated. Changes in salivary proteome were initially examined by SELDI-TOF mass spectrometry. Individual protein changes were identified by 2-dimensional differential in-gel electrophoresis (2D-DIGE) with subsequent MS/MS sequencing and ELISA. RESULTS: Significant increases and decreases in multiple salivary proteins that lasted at least 2 months posttransplant were detected by SELDI-TOF mass spectrometry. Lactoferrin and secretory leukocyte protease inhibitor demonstrated elevations 1 month post-HCT that persisted at least 6 months. Secretory IgA (sIgA) levels were decreased 1 month posttransplant, with recovery at approximately 6 months. Levels of salivary beta(2)-microglobulin were elevated at 6 months and correlated with sIgA levels. CONCLUSION: Allo-HCT is associated with long-term changes in several salivary proteins important for innate immune responses. These results support further studies on the association of salivary proteins with posttransplant complications including infections and GVHD.

Autoimmunity to GABAA-receptor-associated protein in stiff-person syndrome.

Stiff-person syndrome (SPS) is an autoimmune neurological disorder characterized by autoantibodies to glutamic acid decarboxylase (GAD), the enzyme responsible for the synthesis of inhibitory neurotransmitter GABA. To search for biomarkers that distinguish SPS from other neurological disorders (OND), we used surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry to obtain proteomic profile of sera from 25 GAD-positive SPS patients and 25 controls. A significant decrease was found in the level of a protein corresponding to GABA(A)-receptor-associated protein (GABARAP), which is responsible for the stability and surface expression of the GABA(A)-receptor. Up to 70% of the SPS sera examined, compared with 10% of the controls, immunoprecipitated GABARAP protein. Antibodies raised against GABARAP immunostained neuronal cell bodies as well as axonal and dendritic processes, as visualized by confocal microscopy. In vitro experiments demonstrated that the IgG from GABARAP antibody-positive patients, but not control IgG, significantly inhibited the surface expression of GABA(A)-receptor. We conclude that GABARAP is a new autoantigen in SPS. Because the patients' IgG inhibits the expression of GABA(A)-receptors, the circulating antibodies could impair GABAergic pathways and play a role in the clinical symptomatology of SPS patients.

Biomarker discovery in serum from patients with carotid atherosclerosis.

BACKGROUND: Blood-based biomarkers of atherosclerosis have been used to identify patients at high risk for developing stroke. We hypothesized that patients with carotid artery disease would have a distinctive proteomic signature in blood as compared to a healthy control population without carotid artery disease. In order to discover protein biomarkers associated with increased atherosclerotic risk, we used two different strategies to identify biomarkers from patients with clinically defined atherosclerosis who were undergoing endarterectomy for atherosclerotic carotid artery disease. These patients were compared with healthy matched controls. METHODS: Serum was obtained from patients undergoing endarterectomy (EA; n = 38) and compared to a group of age-matched healthy controls (n = 40). Serum was fractionated using anion exchange chromatography and three different surface-enhanced laser desorption/ionization (SELDI) chip surfaces and then evaluated with mass spectrometry (MS) and two-dimensional difference gel electrophoresis (2D-DIGE). RESULTS: A random forest (RF) analysis of the SELDI-MS protein peak data distinguished these two groups with 69.2% sensitivity and 73.2% specificity. Four unique SELDI peaks (4.2, 4.4, 16.7 and 28 kDa, all p< 0.01) showed the greatest influence in the RF model. The EA patients with a history of prior clinical atherosclerotic plaque rupture manifested as either stroke or transient ischemic attack (symptomatic; n = 16) were compared to patients with carotid atherosclerosis but no clinical evidence of plaque rupture (asymptomatic; n = 22). Analysis of the SELDI spectra did not separate these two patient subgroups. A subgroup analysis using 2D-DIGE images obtained from albumin-depleted serum comparing symptomatic (n = 10) to asymptomatic EA patients (n = 10) found 4 proteins that were differentially expressed (p < 0.01) in the symptomatic patients. These proteins were identified as α(1)-antitrypsin, haptoglobin and vitamin D binding protein that were downregulated and α(2)-glycoprotein precursor that was upregulated in the symptomatic EA group. CONCLUSIONS: SELDI-MS data analysis of fractionated serum suggests that a distinct protein signature exists in patients with carotid atherosclerosis compared to age-matched healthy controls. Identification of 4 proteins in a subset of patients with symptomatic and asymptomatic carotid atherosclerosis suggests that these and other protein biomarkers may assist in identifying high-risk patients with carotid atherosclerosis.

Computational prediction models for early detection of risk of cardiovascular events using mass spectrometry data.

Early prediction of the risk of cardiovascular events in patients with chest pain is critical in order to provide appropriate medical care for those with positive diagnosis. This paper introduces a computational methodology for predicting such events in the context of robust computerized classification using mass spectrometry data of blood samples collected from patients in emergency departments. We applied the computational theories of statistical and geostatistical linear prediction models to extract effective features of the mass spectra and a simple decision logic to classify disease and control samples for the purpose of early detection. While the statistical and geostatistical techniques provide better results than those obtained from some other methods, the geostatistical approach yields superior results in terms of sensitivity and specificity in various designs of the data set for validation, training, and testing. The proposed computational strategies are very promising for predicting major adverse cardiac events within six months.

Quality control of serum albumin depletion for proteomic analysis.

BACKGROUND: Prefractionation techniques such as serum albumin depletion are useful precursors to proteomic analysis, but they may introduce preanalytical bias if the depletion is not reproducible. We examined the reproducibility of albumin immunodepletion and describe a method of QC for this process. METHODS: Depletion of albumin from pooled serum, performed using IgY immunoaffinity spin columns, was assessed for 21 runs on each of 4 columns. We measured albumin concentrations, after albumin depletion, by use of an immunoturbidimetric assay on the Beckman LX 20 analyzer and assessed mass spectra of albumin-depleted samples by use of SELDI-TOF mass spectrometry. RESULTS: There was substantial run-to-run variation in efficiency of albumin depletion, with systematic decline in efficiency after multiple uses of the columns. Mean depletion efficiency was >95% for 15 of the 1st 17 runs and <90% for runs 18 to 21. We evaluated the 10 highest-intensity peaks present in all spectra from runs 1, 8, 17, and 21 and assessed the effect of albumin depletion on SELDI-TOF mass spectrometry reproducibility. Comparing the %CV of relative intensities for low and high m/z measurements revealed a significant difference of run 21 compared with runs 1, 8, and 17 (P <0.0001). Six-fold more peaks were found in albumin-depleted than unfractionated serum at both high and low m/z. CONCLUSIONS: Sporadic and systematic variation in efficiency of albumin depletion by spin columns may contribute significant preanalytical bias to proteomic approaches of biomarker discovery. This variation requires ongoing QC of the albumin depletion process by quantification of albumin concentration to assess depletion efficiency.

Bound homocysteine, cysteine, and cysteinylglycine distribution between albumin and globulins.

BACKGROUND: Major portions of homocysteine (Hcy), cysteine (Cys), cysteinylglycine (CysGly), and glutathione in serum are covalently bound to proteins via disulfides. Albumin has been considered the dominant binding protein. METHODS: Pooled serum and plasma from healthy adults were fractionated into albumin and globulins by affinity columns. Content of Hcy, Cys, CysGly, and glutathione was determined for serum and plasma fractions and purified proteins by an HPLC method before and after incubation with excess CysGly, Hcy, or glutathione RESULTS: Of protein-bound amino acids in pooled serum, 12% of Hcy, 21% of Cys, and 33% of CysGly were bound to globulins, with the remainder bound to albumin. Slightly higher proportions were bound to globulins in pooled plasma. Globulins had approximately 16% of total exchangeable disulfide and thiol groups in serum based on results of loading with CysGly. These results agree with expected abundance of unpaired Cys residues in globulins relative to albumin. Significant amounts of disulfide-linked amino acids were detected for HDL and alpha1-acid glycoprotein but not for transferrin. Exchange of disulfide-linked amino acids on exposure to excess Hcy or glutathione was much faster for albumin than for alpha1-acid glycoprotein. CONCLUSIONS: Approximately 10%-30%, of protein-bound Hcy, Cys, and CysGly are disulfide-linked to globulins. Amino acids disulfide-linked to albumin are rapidly exchangeable, while exchange of disulfide-linked amino acids from globulins, such as alpha1-acid glycoprotein, is much slower. Consequently, the pools of Hcy, Cys, and CysGly bound to albumin and globulin may represent kinetically and functionally distinct pools. Plasma concentrations of total Hcy and Cys, which are dominated by albumin-bound pools, may not reflect the abundance of functionally significant modifications of globulins.

Coelution of other proteins with albumin during size-exclusion HPLC: Implications for analysis of urinary albumin.

BACKGROUND: Size-exclusion HPLC has been used as an alternative to immunoassays for quantifying urinary albumin (microalbumin). Systematically higher values for the HPLC method have been proposed to result from nonimmunoreactive albumin. METHODS: We evaluated separation of purified proteins and urinary components by size-exclusion HPLC using a Zorbax Bio Series GF-250 column eluted with phosphate-buffered saline. Urinary components eluting in the "albumin" peak were analyzed by mass spectrometry and reversed-phase HPLC. RESULTS: Several proteins, such as transferrin, alpha1-proteinase inhibitor, alpha1-acid glycoprotein, and alpha2-HS glycoprotein, analyzed as purified components, were not resolved from albumin by size-exclusion HPLC. Peaks for other proteins, such as IgG and urinary components identified as dimers of alpha1-microglobulin and immunoglobulin light chains, overlapped with the albumin peak. Profiles of urine specimens showed variable amounts of components overlapping with albumin. Furthermore, the albumin peak obtained by size-exclusion HPLC was found by mass spectrometry and reversed-phase HPLC to contain multiple components in addition to albumin. CONCLUSIONS: Size-exclusion HPLC does not resolve albumin from several other proteins in urine. The albumin peak resolved by this technique, although predominantly composed of albumin, contains several coeluting globulins that would contribute to overestimation of albumin concentration by size-exclusion HPLC.