Carboxypeptidase G2 rescue in patients with methotrexate intoxication and renal failure

The methotrexate (MTX) rescue agent carboxypeptidase G2 (CPDG2) rapidly hydrolyses MTX to the inactive metabolite DAMPA (4-[[2,4-diamino-6-(pteridinyl)methyl]-methylamino]-benzoic acid) and glutamate in patients with MTX-induced renal failure and delayed MTX excretion. DAMPA is thought to be an inactive metabolite of MTX because it is not an effective inhibitor of the MTX target enzyme dihydrofolate reductase. DAMPA is eliminated more rapidly than MTX in these patients, which suggests a nonrenal route of elimination. In a phase II study (May 1997–March 2002), CPDG2 was administered intravenously to 82 patients at a median dose of 50 U kg−1 (range 33–60 U kg−1). Eligible patients for this study had serum MTX concentrations of >10 μM at 36 h or >5 μM at 42 h after start of MTX infusion and documented renal failure (serum creatinine ⩾1.5 times the upper limit of normal). Immediately before CPDG2 administration, a median MTX serum level of 11.93 μM (range 0.52–901 μM) was documented. Carboxypeptidase G2 was given at a median of 52 h (range 25–178 h) following the start of an MTX infusion of 1–12 g m−2 4–36 h−1 and resulted in a rapid 97% (range 73–99%) reduction of the MTX serum level. Toxicity related to CPDG2 was not observed. Toxicity related to MTX was documented in about half the patients; four patients died despite CPDG2 administration due to severe myelosuppression and septic complications. In conclusion, administration of CPDG2 is a well-tolerated, safe and a very effective way of MTX elimination in delayed excretion due to renal failure

Current status and recommendations for biomarkers and biobanking in neurofibromatosis

Objective: Clinically validated biomarkers for neurofibromatosis 1 (NF1), neurofibromatosis 2 (NF2), and schwannomatosis (SWN) have not been identified to date. The biomarker working group's goals are to (1) define biomarker needs in NF1, NF2, and SWN; (2) summarize existing data on biomarkers in NF1, NF2, and SWN; (3) outline recommendations for sample collection and biomarker development; and (4) standardize sample collection and methodology protocols where possible to promote comparison between studies by publishing standard operating procedures (SOPs). Methods: The biomarker group reviewed published data on biomarkers in NF1, NF2, and SWN and on biobanking efforts outside these diseases via literature search, defined the need for biomarkers in NF, and developed recommendations in a series of consensus meetings. Results: We describe existing biomarkers in NF and report consensus recommendations for SOP and a minimal clinical dataset to accompany samples derived from patients with NF1, NF2, and SWN in decentralized biobanks. Conclusions: These recommendations are intended to provide clinicians and researchers with a common set of guidelines to collect and store biospecimens and for establishment of biobanks for NF1, NF2, and SWN.N

Management of toxic ingestions with the use of renal replacement therapy

Although rare, renal replacement therapy (RRT) for the treatment of the metabolic, respiratory and hemodynamic complications of intoxications may be required. Understanding the natural clearance of the medications along with their volume of distribution, protein binding and molecular weight will help in understanding the benefit of commencing RRT. This information will aid in choosing the optimal forms of RRT in an urgent setting. Overdose of common pediatric medications are discussed with suggestions on the type of RRT within this educational review

Circulating endothelial cell count: a reliable marker of endothelial damage in patients undergoing hematopoietic stem cell transplantation

The physio-pathologic interrelationships between endothelium and GvHD have been better elucidated and have led to definition of the entity 'endothelial GvHD' as an essential early phase prior to the clinical presentation of acute GvHD. Using the CellSearch system, we analyzed circulating endothelial cells (CEC) in 90 allogeneic hematopoietic stem cell transplantation (allo-HSCT) patients at the following time-points: T1 (pre-conditioning), T2 (pre-transplant), T3 (engraftment), T4 (onset of GvHD) and T5 (1 week after steroid treatment). Although CEC changes in allo-HSCT represent a dynamic phenomenon influenced by many variables (that is, conditioning, immunosuppressive treatments, engraftment syndrome and infections), we showed that CEC peaks were constantly seen at onset of acute GvHD and invariably returned to pre-transplant values after treatment response. Since we showed that CEC changes during allo-HSCT has rapid kinetics that may be easily missed if blood samples are drawn at pre-fixed time-points, we rather suggest an 'on demand' evaluation of CEC counts right at onset of GvHD clinical symptoms to possibly help differentiate GvHD from other non-endothelial complications. We confirm that CEC changes are a suitable biomarker to monitor endothelial damage in patients undergoing allo-transplantation and hold the potential to become a useful tool to support GvHD diagnosis (ClinicalTrials.gov NCT02064972).Bone Marrow Transplantation advance online publication, 11 September 2017; doi:10.1038/bmt.2017.194

Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

<p>Abstract</p> <p>Background</p> <p>Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.</p> <p>Methods</p> <p>Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.</p> <p>Results</p> <p>The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.</p> <p>Conclusion</p> <p>The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.</p

Identifying Resistance Mechanisms against Five Tyrosine Kinase Inhibitors Targeting the ERBB/RAS Pathway in 45 Cancer Cell Lines

Because of the low overall response rates of 10-47% to targeted cancer therapeutics, there is an increasing need for predictive biomarkers. We aimed to identify genes predicting response to five already approved tyrosine kinase inhibitors. We tested 45 cancer cell lines for sensitivity to sunitinib, erlotinib, lapatinib, sorafenib and gefitinib at the clinically administered doses. A resistance matrix was determined, and gene expression profiles of the subsets of resistant vs. sensitive cell lines were compared. Triplicate gene expression signatures were obtained from the caArray project. Significance analysis of microarrays and rank products were applied for feature selection. Ninety-five genes were also measured by RT-PCR. In case of four sunitinib resistance associated genes, the results were validated in clinical samples by immunohistochemistry. A list of 63 top genes associated with resistance against the five tyrosine kinase inhibitors was identified. Quantitative RT-PCR analysis confirmed 45 of 63 genes identified by microarray analysis. Only two genes (ANXA3 and RAB25) were related to sensitivity against more than three inhibitors. The immunohistochemical analysis of sunitinib-treated metastatic renal cell carcinomas confirmed the correlation between RAB17, LGALS8, and EPCAM and overall survival. In summary, we determined predictive biomarkers for five tyrosine kinase inhibitors, and validated sunitinib resistance biomarkers by immunohistochemistry in an independent patient cohort. © 2013 Pénzváltó et al

Phase II study of mTORC1 inhibition by everolimus in neurofibromatosis type 2 patients with growing vestibular schwannomas

Neurofibromatosis type 2 (NF2) is a genetic disorder with bilateral vestibular schwannomas (VS) as the most frequent manifestation. Merlin, the NF2 tumor suppressor, was identified as a negative regulator of mammalian target of rapamycin complex 1. Pre-clinical data in mice showed that mTORC1 inhibition delayed growth of NF2-schwannomas. We conducted a prospective single-institution open-label phase II study to evaluate the effects of everolimus in ten NF2 patients with progressive VS. Drug activity was monitored every 3 months. Everolimus was administered orally for 12 months and, if the decrease in tumor volume was &gt;20 % from baseline, treatment was continued for 12 additional months. Other patients stopped when completed 12 months of everolimus but were allowed to resume treatment when VS volume was &gt;20 % during 1 year follow-up. Nine patients were evaluable. Safety was evaluated using CTCAE 3.0 criteria. After 12 months of everolimus, no reduction in volume ≥20 % was observed. Four patients had progressive disease, and five patients had stable disease with a median annual growth rate decreasing from 67 %/year before treatment to 0.5 %/year during treatment. In these patients, tumor growth resumed within 3-6 months after treatment discontinuation. Everolimus was then reintroduced and VS decreased by a median 6.8 % at 24 months. Time to tumor progression increased threefold from 4.2 months before treatment to &gt; 12 months. Hearing was stable under treatment. The safety of everolimus was manageable. Although the primary endpoint was not reached, further studies are required to confirm the potential for stabilization of everolimus

Receptor Tyrosine Kinases in Osteosarcoma: 2019 Update

The primary conclusions of our 2014 contribution to this series were as follows: Multiple receptor tyrosine kinases (RTKs) likely contribute to aggressive phenotypes in osteosarcoma and, therefore, inhibition of multiple RTKs is likely necessary for successful clinical outcomes. Inhibition of multiple RTKs may also be useful to overcome resistance to inhibitors of individual RTKs as well as resistance to conventional chemotherapies. Different combinations of RTKs are likely important in individual patients. AXL, EPHB2, FGFR2, IGF1R, and RET were identified as promising therapeutic targets by our in vitro phosphoproteomic/siRNA screen of 42 RTKs in the highly metastatic LM7 and 143B human osteosarcoma cell lines. This chapter is intended to provide an update on these topics as well as the large number of osteosarcoma clinical studies of inhibitors of multiple tyrosine kinases (multi-TKIs) that were recently published