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Sequential dosing in chemosensitization : targeting the PI3K/Akt/mTOR pathway in neuroblastoma
(2013)
Breaking resistance to chemotherapy is a major goal of combination therapy in many tumors, including advanced neuroblastoma. We recently demonstrated that increased activity of the PI3K/Akt network is associated with poor prognosis, thus providing an ideal target for chemosensitization. Here we show that targeted therapy using the PI3K/mTOR inhibitor NVP-BEZ235 significantly enhances doxorubicin-induced apoptosis in neuroblastoma cells. Importantly, this increase in apoptosis was dependent on scheduling: while pretreatment with the inhibitor reduced doxorubicin-induced apoptosis, the sensitizing effect in co-treatment could further be increased by delayed addition of the inhibitor post chemotherapy. Desensitization for doxorubicin-induced apoptosis seemed to be mediated by a combination of cell cycle-arrest and autophagy induction, whereas sensitization was found to occur at the level of mitochondria within one hour of NVP-BEZ235 posttreatment, leading to a rapid loss of mitochondrial membrane potential with subsequent cytochrome c release and caspase-3 activation. Within the relevant time span we observed marked alterations in a ~30 kDa protein associated with mitochondrial proteins and identified it as VDAC1/Porin protein, an integral part of the mitochondrial permeability transition pore complex. VDAC1 is negatively regulated by the PI3K/Akt pathway via GSK3β and inhibition of GSK3β, which is activated when Akt is blocked, ablated the sensitizing effect of NVP-BEZ235 posttreatment. Our findings show that cancer cells can be sensitized for chemotherapy induced cell death – at least in part – by NVP-BEZ235-mediated modulation of VDAC1. More generally, we show data that suggest that sequential dosing, in particular when multiple inhibitors of a single pathway are used in the optimal sequence, has important implications for the general design of combination therapies involving molecular targeted approaches towards the PI3K/Akt/mTOR signaling network.
Objectives: The authors sought to evaluate the performance of the Ranger paclitaxel-coated balloon versus uncoated balloon angioplasty for femoropopliteal lesions at 12 months.
Background: Drug-coated balloons (DCBs) are a promising endovascular treatment option for peripheral artery disease of the femoropopliteal segment, and each unique device requires dedicated clinical study.
Methods: The prospective, randomized RANGER SFA (Comparison of the Ranger™ Paclitaxel-Coated PTA Balloon Catheter and Uncoated PTA Balloons in Femoropopliteal Arteries) study (NCT02013193) enrolled 105 patients with symptomatic lower limb ischemia (Rutherford category 2 to 4) and stenotic lesions in the nonstented femoropopliteal segment at 10 European centers. Seventy-one patients (mean age 68 ± 8 years, n = 53 men) were enrolled in the Ranger DCB arm, and 34 patients (mean age 67 ± 9 years, n = 23 men) were assigned to the control group. Twelve-month analysis included patency, safety, and clinical outcomes and quality-of-life assessments.
Results: The DCB group had a greater primary patency rate at 12 months (Kaplan-Meier estimate 86.4% vs. 56.5%), with a significantly longer time to patency failure (log-rank p < 0.001). The estimated freedom from target lesion revascularization rate was 91.2% in the DCB group and 69.9% in the control group at 12 months, with a significantly longer time to reintervention (p = 0.010). No target limb amputations or device-related deaths occurred in either group.
Conclusions: Twelve-month results show that patency was maintained longer after Ranger DCB treatment than after conventional balloon angioplasty, and this result was associated with a low revascularization rate and good clinical outcomes.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.