Biomarkers in fasting serum to estimate glucose tolerance, insulin sensitivity, and insulin secretion.

BACKGROUND: Biomarkers for estimating reduced glucose tolerance, insulin sensitivity, or impaired insulin secretion would be clinically useful, since these physiologic measures are important in the pathogenesis of type 2 diabetes mellitus. METHODS: We conducted a cross-sectional study in which 94 individuals, of whom 84 had 1 or more risk factors and 10 had no known risk factors for diabetes, underwent oral glucose tolerance testing. We measured 34 protein biomarkers associated with diabetes risk in 250-µL fasting serum samples. We applied multiple regression selection techniques to identify the most informative biomarkers and develop multivariate models to estimate glucose tolerance, insulin sensitivity, and insulin secretion. The ability of the glucose tolerance model to discriminate between diabetic individuals and those with impaired or normal glucose tolerance was evaluated by area under the ROC curve (AUC) analysis. RESULTS: Of the at-risk participants, 25 (30%) were found to have impaired glucose tolerance, and 11 (13%) diabetes. Using molecular counting technology, we assessed multiple biomarkers with high accuracy in small volume samples. Multivariate biomarker models derived from fasting samples correlated strongly with 2-h postload glucose tolerance (R(2) = 0.45, P < 0.0001), composite insulin sensitivity index (R(2) = 0.91, P < 0.0001), and insulin secretion (R(2) = 0.45, P < 0.0001). Additionally, the glucose tolerance model provided strong discrimination between diabetes vs impaired or normal glucose tolerance (AUC 0.89) and between diabetes and impaired glucose tolerance vs normal tolerance (AUC 0.78). CONCLUSIONS: Biomarkers in fasting blood samples may be useful in estimating glucose tolerance, insulin sensitivity, and insulin secretion.

Treatment parameters modulating regression of human melanoma xenografts by an antibody-drug conjugate (CR011-vcMMAE) targeting GPNMB.

PURPOSE: To investigate the pharmacological properties of the CR011-vcMMAE fully human antibody-drug conjugate (ADC), such as dose titrations, quantitation of the time (days) to complete regression, pharmacokinetics, and schedule dependency. Our prior study characterized a fully human antibody to GPNMB covalently linked to monomethylauristatin E, CR011-vcMMAE, and further demonstrated cell surface staining of melanoma lines susceptible to the immunoconjugate's cytotoxicity (Clin Cancer Res 2005; 12(4): 1373-1382). METHODS: The human SK-MEL-2 and SK-MEL-5 melanoma xenografts were used in athymic mice to assess anti-tumor efficacy. After s.c. implantation, tumors became established (60-100 mg), and treatment commenced by i.v. injection of the immunoconjugate or vinblastine or paclitaxel. Short-term anti-tumor effects (inhibition of tumor growth) and long-term effects (complete regression) were observed. RESULTS: CR011-vcMMAE induced regression of established human SK-MEL-2 and SK-MEL-5 xenografts at doses from 1.25 to 80 mg/kg treatment when administered intravenously every 4 days (4 treatments); strikingly, regressions were not associated with re-growth during the observation period (200 days). The disappearance rate of implants was dose dependent (minimum time, 18.5 days). Detectable serum CR011-vcMMAE >or=1 microg/mL (approximately 0.01 microM) was observed for >30 days post-dose; CR011-vcMMAE showed an elimination half-life of 10.3 days. A low volume of distribution suggested that CR011-vcMMAE was confined to blood and interstitial fluid. CR011-vcMMAE could be delivered by either a single bolus dose or by intermittent dosing (i.e., every 1, 2, 4, 8, or 16 days) with no discernible differences in the proportion of tumor-free survivors, indicating a lack of schedule dependency. The antibody-drug conjugate produced complete regressions, but the equivalent doses of free monomethylauristatin E or unconjugated antibody did not show anti-tumor effects. In addition, decreases in plasma tumor-derived human interleukin-8 coincided with tumor nodule disappearance. CONCLUSIONS: Short-term anti-tumor effects and long-term effects (complete regression) were observed with CR011-vcMMAE, but not with the reference agents. These results suggest that CR011-vcMMAE may provide therapeutic benefit in malignant melanoma.

Validation of a multi-marker model for the prediction of incident type 2 diabetes mellitus: combined results of the Inter99 and Botnia studies.

PURPOSE: To assess performance of a biomarker-based score that predicts the five-year risk of diabetes (Diabetes Risk Score, DRS) in an independent cohort that included 15-year follow-up. METHOD: DRS was developed on the Inter99 cohort, and validated on the Botnia cohort. Performance was benchmarked against other risk-assessment tools comparing calibration, time to event analysis, and net reclassification. RESULTS: The area under the receiver-operating characteristic curve (AUC) was 0.84 for the Inter99 cohort and 0.78 for the Botnia cohort. In the Botnia cohort, DRS provided better discrimination than fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance, oral glucose tolerance test or risk scores derived from Framingham or San Antonio Study cohorts. Overall reclassification with DRS was significantly better than using FPG and glucose tolerance status (p < 0.0001). In time to event analysis, rates of conversion to diabetes in low, moderate, and high DRS groups were significantly different (p < 0.001). CONCLUSION: This study validates DRS performance in an independent population, and provides a more accurate assessment of T2DM risk than other methods.

Biomarkers in Type 2 diabetes: improving risk stratification with the PreDx ® Diabetes Risk Score.

Type 2 diabetes is a chronic, debilitating and often deadly disease that has reached epidemic proportions. The onset of diabetes can be delayed or prevented in high-risk individuals by diet and lifestyle changes and medications, and hence a key element for addressing the diabetes epidemic is to identify those most at risk of developing diabetes so that preventative measures can be effectively focused. The PreDx(®) Diabetes Risk Score is a multimarker tool for assessing a patient's risk of developing diabetes within the next 5 years. Requiring a simple blood draw using standard sample collection and handling procedures, the PreDx Diabetes Risk Score is easily implemented in clinical practice and provides an assessment of diabetes risk that is superior to other measures, including fasting plasma glucose, glycated hemoglobin, measures of insulin resistance and other clinical measures. In this article, we provide an overview of the PreDx Diabetes Risk Score.

Development of a type 2 diabetes risk model from a panel of serum biomarkers from the Inter99 cohort.

OBJECTIVE: The purpose of this study was to develop a model for assessing the 5-year risk of developing type 2 diabetes from a panel of 64 circulating candidate biomarkers. RESEARCH DESIGN AND METHODS: Subjects were selected from the Inter99 cohort, a longitudinal population-based study of approximately 6,600 Danes in a nested case-control design with the primary outcome of 5-year conversion to type 2 diabetes. Nondiabetic subjects, aged >or=39 years, with BMI >or=25 kg/m(2) at baseline were selected. Baseline fasting serum samples from 160 individuals who developed type 2 diabetes and from 472 who did not were tested. An ultrasensitive immunoassay was used to measure of 58 candidate biomarkers in multiple diabetes-associated pathways, along with six routine clinical variables. Statistical learning methods and permutation testing were used to select the most informative biomarkers. Risk model performance was estimated using a validated bootstrap bias-correction procedure. RESULTS: A model using six biomarkers (adiponectin, C-reactive protein, ferritin, interleukin-2 receptor A, glucose, and insulin) was developed for assessing an individual's 5-year risk of developing type 2 diabetes. This model has a bootstrap-estimated area under the curve of 0.76, which is greater than that for A1C, fasting plasma glucose, fasting serum insulin, BMI, sex-adjusted waist circumference, a model using fasting glucose and insulin, and a noninvasive clinical model. CONCLUSIONS: A model incorporating six circulating biomarkers provides an objective and quantitative estimate of the 5-year risk of developing type 2 diabetes, performs better than single risk indicators and a noninvasive clinical model, and provides better stratification than fasting plasma glucose alone.

Safety and tolerability of velafermin (CG53135-05) in patients receiving high-dose chemotherapy and autologous peripheral blood stem cell transplant.

GOALS OF WORK: The objective of this study was to evaluate the safety and tolerability of velafermin in patients at risk of developing severe oral mucositis (OM) from chemotherapy. MATERIALS AND METHODS: This study was a single-center, open-label, single-dose escalation, phase I trial in patients undergoing high-dose chemotherapy (HDCT) and autologous peripheral blood stem cell transplant (PBSCT). Velafermin was administered 24 h after stem cell infusion as a single intravenous dose infused over 15 min. Clinical safety variables were assessed and OM status scored daily for 30 days using the World Health Organization (WHO) grading scale. MAIN RESULTS: Thirty patients were treated with velafermin at doses of 0.03 (n = 10), 0.1 (n = 10), 0.2 (n = 8), or 0.33 mg/kg (n = 2). Patients were diagnosed with multiple myeloma (n = 16), non-Hodgkin's lymphoma (n = 12), acute myelogenous leukemia (n = 1), or desmoplasmic round cell tumor (n = 1). Velafermin was well tolerated at doses up to 0.2 mg/kg. There were no drug-related serious adverse events. No patient discontinued because of adverse events; however, two patients administered 0.33 mg/kg developed adverse reactions immediately after infusion of the study drug. No other patients were treated at this dose level. The most frequent (>35% of patients) treatment-emergent adverse events were diarrhea, fatigue, pyrexia, vomiting, and nausea. Most adverse events were mild or moderate and resolved the same day without sequelae. Eight (27%) patients developed WHO grade 3 or 4 OM during the study; seven of these patients received high-dose melphalan as a conditioning regimen. CONCLUSION: Velafermin was well tolerated by autologous PBSCT patients at doses up to 0.2 mg/kg.

Single-Dose Prevention or Short-Term Treatment with Fibroblast Growth Factor-20 (CG53135-05)Reduces the Severity and Duration of Oral Mucositis.

Oral mucositis (OM) is a treatment-limiting condition associated with myelosupressive chemotherapy and radiation therapy. The objective of this study was to evaluate the activity of recombinant human fibroblast growth factor-20 (FGF-20 or CG53135-05) in the prevention and treatment of OM in experimental animals. Oral mucositis was induced in hamsters with 5-fluorouracil (5-FU; 60 mg/kg) on days -4 and -2, followed by targeted irradiation with 30 Gy on day 0. Oral mucositis was scored every other day using severity scores of 0-5. To test for prevention of OM, animals received varying doses of FGF-20 on day 1 or days 1 and 2 after irradiation before the development of symptoms. To test the effects of FGF-20 on established mucositis, animals were allowed to develop early OM (score of 2) before treatment initiation. Animals then received FGF-20 by intraperitoneal (i.p.) administration (12 mg/kg) for 1, 2, 3, or 4 consecutive days. When prevention of OM was tested, administration of FGF-20 (12 mg/kg i.p.) on day 1 or days 1 and 2 resulted in significant reduction in duration of severe OM to 26% (P < 0.003) or 29.4% (P <0.018) of cumulative days, respectively, compared with untreated control animals, which spent 40.2% of cumulative days with OM scores >/= 3. When the effects of FGF-20 on established mucositis were tested, treatment of animals with FGF-20 for 2, 3, or 4 consecutive days resulted in significant reduction of severe OM to 27.4%, 29.2%, or 18.5% of days, respectively, compared with vehicle-treated control animals, which spent 41.1% of cumulative days with OM scores >/=3 (P < 0.05). These findings support the utility of FGF-20 as a single-dose agent in the prevention of OM. In addition, the positive effects of FGF-20 on established mucositis may permit treatment of patients with OM who may not benefit from prophylactic agents.

Prediction of clinical drug efficacy by classification of drug-induced genomic expression profiles in vitro.

Assays of drug action typically evaluate biochemical activity. However, accurately matching therapeutic efficacy with biochemical activity is a challenge. High-content cellular assays seek to bridge this gap by capturing broad information about the cellular physiology of drug action. Here, we present a method of predicting the general therapeutic classes into which various psychoactive drugs fall, based on high-content statistical categorization of gene expression profiles induced by these drugs. When we used the classification tree and random forest supervised classification algorithms to analyze microarray data, we derived general "efficacy profiles" of biomarker gene expression that correlate with anti-depressant, antipsychotic and opioid drug action on primary human neurons in vitro. These profiles were used as predictive models to classify naïve in vitro drug treatments with 83.3% (random forest) and 88.9% (classification tree) accuracy. Thus, the detailed information contained in genomic expression data is sufficient to match the physiological effect of a novel drug at the cellular level with its clinical relevance. This capacity to identify therapeutic efficacy on the basis of gene expression signatures in vitro has potential utility in drug discovery and drug target validation.