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Activation of TRPC6 channels is essential for lung ischaemia–reperfusion induced oedema in mice
(2012)
Lung ischaemia–reperfusion-induced oedema (LIRE) is a life-threatening condition that causes pulmonary oedema induced by endothelial dysfunction. Here we show that lungs from mice lacking nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (Nox2y/−) or the classical transient receptor potential channel 6 (TRPC6−/−) are protected from LIR-induced oedema (LIRE). Generation of chimeric mice by bone marrow cell transplantation and endothelial-specific Nox2 deletion showed that endothelial Nox2, but not leukocytic Nox2 or TRPC6, are responsible for LIRE. Lung endothelial cells from Nox2- or TRPC6-deficient mice showed attenuated ischaemia-induced Ca2+ influx, cellular shape changes and impaired barrier function. Production of reactive oxygen species was completely abolished in Nox2y/− cells. A novel mechanistic model comprising endothelial Nox2-derived production of superoxide, activation of phospholipase C-γ, inhibition of diacylglycerol (DAG) kinase, DAG-mediated activation of TRPC6 and ensuing LIRE is supported by pharmacological and molecular evidence. This mechanism highlights novel pharmacological targets for the treatment of LIRE.
Background: The inclusion of immune checkpoint inhibitors (ICIs) in therapeutic algorithms has led to significant survival benefits in patients with various metastatic cancers. Concurrently, an increasing number of neurological immune related adverse events (IRAE) has been observed. In this retrospective analysis, we examine the ICI-induced incidence of cerebral pseudoprogression and propose a classification system.
Methods: We screened our hospital information system to identify patients with any in-house ICI treatment for any tumor disease during the years 2007-2019. All patients with cerebral MR imaging (cMRI) of sufficient diagnostic quality were included. cMRIs were retrospectively analyzed according to immunotherapy response assessment for neuro-oncology (iRANO) criteria.
Results: We identified 12 cases of cerebral pseudoprogression in 123 patients treated with ICIs and sufficient MRI. These patients were receiving ICI therapy for lung cancer (n=5), malignant melanoma (n=4), glioblastoma (n=1), hepatocellular carcinoma (n=1) or lymphoma (n=1) when cerebral pseudoprogression was detected. Median time from the start of ICI treatment to pseudoprogression was 5 months. All but one patient developed neurological symptoms. Three different patterns of cerebral pseudoprogression could be distinguished: new or increasing contrast-enhancing lesions, new or increasing T2 predominant lesions and cerebral vasculitis type pattern.
Conclusion: Cerebral pseudoprogression followed three distinct patterns and was detectable in 3.2% of all patients during ICI treatment and in 9.75% of the patients with sufficient brain imaging follow up. The fact that all but one of the affected patients developed neurological symptoms, which would be classified as progressive disease according to iRANO criteria, mandates vigilance in the diagnosis and treatment of ICI-induced cerebral lesions.
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influenced by several "strategy parameters". Choosing reasonable parameter values for the PSO is crucial for its convergence behavior, and depends on the optimization task. We present a method for parameter meta-optimization based on PSO and its application to neural network training. The concept of the Optimized Particle Swarm Optimization (OPSO) is to optimize the free parameters of the PSO by having swarms within a swarm. We assessed the performance of the OPSO method on a set of five artificial fitness functions and compared it to the performance of two popular PSO implementations. Results: Our results indicate that PSO performance can be improved if meta-optimized parameter sets are applied. In addition, we could improve optimization speed and quality on the other PSO methods in the majority of our experiments. We applied the OPSO method to neural network training with the aim to build a quantitative model for predicting blood-brain barrier permeation of small organic molecules. On average, training time decreased by a factor of four and two in comparison to the other PSO methods, respectively. By applying the OPSO method, a prediction model showing good correlation with training-, test- and validation data was obtained. Conclusion: Optimizing the free parameters of the PSO method can result in performance gain. The OPSO approach yields parameter combinations improving overall optimization performance. Its conceptual simplicity makes implementing the method a straightforward task.
Background: Since there is no standardized and effective treatment for advanced uveal melanoma (UM), the prognosis is dismal once metastases develop. Due to the availability of immune checkpoint blockade (ICB) in the real-world setting, the prognosis of metastatic UM has improved. However, it is unclear how the presence of hepatic and extrahepatic metastasis impacts the response and survival after ICB. Methods: A total of 178 patients with metastatic UM treated with ICB were included in this analysis. Patients were recruited from German skin cancer centers and the German national skin cancer registry (ADOReg). To investigate the impact of hepatic metastasis, two cohorts were compared: patients with liver metastasis only (cohort A, n = 55) versus those with both liver and extra-hepatic metastasis (cohort B, n = 123). Data were analyzed in both cohorts for response to treatment, progression-free survival (PFS), and overall survival (OS). The survival and progression probabilities were calculated with the Kaplan–Meier method. Log-rank tests, χ2 tests, and t-tests were performed to detect significant differences between both cohorts. Results: The median OS of the overall population was 16 months (95% CI 13.4–23.7) and the median PFS, 2.8 months (95% CI 2.5–3.0). The median OS was longer in cohort B than in cohort A (18.2 vs. 6.1 months; p = 0.071). The best objective response rate to dual ICB was 13.8% and to anti-PD-1 monotherapy 8.9% in the entire population. Patients with liver metastases only had a lower response to dual ICB, yet without significance (cohort A 8.7% vs. cohort B 16.7%; p = 0.45). Adverse events (AE) occurred in 41.6%. Severe AE were observed in 26.3% and evenly distributed between both cohorts. Conclusion: The survival of this large cohort of patients with advanced UM was more favorable than reported in previous benchmark studies. Patients with both hepatic and extrahepatic metastasis showed more favorable survival and higher response to dual ICB than those with hepatic metastasis only.
Targeting signals direct proteins to their extra- or intracellular destination such as the plasma membrane or cellular organelles. Here we investigated the structure and function of exceptionally long signal peptides encompassing at least 40 amino acid residues. We discovered a two-domain organization ("NtraC model") in many long signals from vertebrate precursor proteins. Accordingly, long signal peptides may contain an N-terminal domain (N-domain) and a C-terminal domain (C-domain) with different signal or targeting capabilities, separable by a presumably turn-rich transition area (tra). Individual domain functions were probed by cellular targeting experiments with fusion proteins containing parts of the long signal peptide of human membrane protein shrew-1 and secreted alkaline phosphatase as a reporter protein. As predicted, the N-domain of the fusion protein alone was shown to act as a mitochondrial targeting signal, whereas the C-domain alone functions as an export signal. Selective disruption of the transition area in the signal peptide impairs the export efficiency of the reporter protein. Altogether, the results of cellular targeting studies provide a proof-of-principle for our NtraC model and highlight the particular functional importance of the predicted transition area, which critically affects the rate of protein export. In conclusion, the NtraC approach enables the systematic detection and prediction of cryptic targeting signals present in one coherent sequence, and provides a structurally motivated basis for decoding the functional complexity of long protein targeting signals.
Background: Uveal melanoma (UM) is highly refractory to treatment with dismal prognosis in advanced stages. The value of the combined checkpoint blockade with CTLA-4 and PD-1 inhibition in metastatic UM is currently unclear.
Methods: Patients with metastatic or unresectable UM treated with ipilimumab in combination with a PD-1 inhibitor were collected from 16 German skin cancer centers. Patient records of 64 cases were analyzed for response, progression-free survival (PFS), overall survival (OS), and safety. Clinical parameters and serum biomarkers associated with OS and treatment response were determined with Cox regression modelling and logistic regression.
Results: The best overall response rate to combined checkpoint blockade was 15.6% with 3.1 and 12.5% complete and partial response, respectively. The median duration of response was 25.5 months (range 9.0–65.0). Stable disease was achieved in 21.9%, resulting in a disease control rate of 37.5% with a median duration of the clinical benefit of 28.0 months (range 7.0–65.0). The median PFS was 3.0 months (95% CI 2.4–3.6). The median OS was estimated to 16.1 months (95% CI 12.9–19.3). Regarding safety, 39.1% of treated patients experienced a severe, treatment-related adverse event according to the CTCAE criteria (grade 3: 37.5%; grade 4: 1.6%). The most common toxicities were colitis (20.3%), hepatitis (20.3%), thyreoiditis (15.6%), and hypophysitis (7.8%). A poor ECOG performance status was an independent risk factor for decreased OS (p = 0.007).
Conclusions: The tolerability of the combined checkpoint blockade in UM may possibly be better than in trials on cutaneous melanoma. This study implies that combined checkpoint blockade represents the hitherto most effective treatment option available for metastatic UM available outside of clinical trials.
DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma
(2021)
Background: Therapies based on targeting immune checkpoints have revolutionized the treatment of metastatic melanoma in recent years. Still, biomarkers predicting long-term therapy responses are lacking. Methods: A novel approach of reference-free deconvolution of large-scale DNA methylation data enabled us to develop a machine learning classifier based on CpG sites, specific for latent methylation components (LMC), that allowed for patient allocation to prognostic clusters. DNA methylation data were processed using reference-free analyses (MeDeCom) and reference-based computational tumor deconvolution (MethylCIBERSORT, LUMP). Results: We provide evidence that DNA methylation signatures of tumor tissue from cutaneous metastases are predictive for therapy response to immune checkpoint inhibition in patients with stage IV metastatic melanoma. Conclusions: These results demonstrate that LMC-based segregation of large-scale DNA methylation data is a promising tool for classifier development and treatment response estimation in cancer patients under targeted immunotherapy.
The first measurements of light antinucleus production in Au+Au collisions at the Relativistic Heavy-Ion Collider are reported. The observed production rates for d-bar and 3He-bar are much larger than in lower energy nucleus-nucleus collisions. A coalescence model analysis of the yields indicates that there is little or no increase in the antinucleon freeze-out volume compared to collisions at CERN SPS energy. These analyses also indicate that the 3He-bar freeze-out volume is smaller than the d-bar freeze-out volume.
We present the first measurement of midrapidity vector meson phi production in Au+Au collisions at RHIC (sqrt[sNN]=130 GeV) from the STAR detector. For the 11% highest multiplicity collisions, the slope parameter from an exponential fit to the transverse mass distribution is T=379±50(stat)±45(syst) MeV, the yield dN/dy=5.73±0.37(stat)±0.69(syst) per event, and the ratio N phi /Nh- is found to be 0.021±0.001(stat)±0.004(syst). The measured ratio N phi /Nh- and T for the phi meson at midrapidity do not change for the selected multiplicity bins.
We report the first measurement of inclusive antiproton production at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV by the STAR experiment at RHIC. The antiproton transverse mass distributions in the measured transverse momentum range of 0.25<pperp<0.95 GeV/c are found to fall less steeply for more central collisions. The extrapolated antiproton rapidity density is found to scale approximately with the negative hadron multiplicity density.