Statins affect cancer cell plasticity with distinct consequences for tumor progression and metastasis.

Statins are among the most commonly prescribed drugs, and around every fourth person above the age of 40 is on statin medication. Therefore, it is of utmost clinical importance to understand the effect of statins on cancer cell plasticity and its consequences to not only patients with cancer but also patients who are on statins. Here, we find that statins induce a partial epithelial-to-mesenchymal transition (EMT) phenotype in cancer cells of solid tumors. Using a comprehensive STRING network analysis of transcriptome, proteome, and phosphoproteome data combined with multiple mechanistic in vitro and functional in vivo analyses, we demonstrate that statins reduce cellular plasticity by enforcing a mesenchymal-like cell state that increases metastatic seeding ability on one side but reduces the formation of (secondary) tumors on the other due to heterogeneous treatment responses. Taken together, we provide a thorough mechanistic overview of the consequences of statin use for each step of cancer development, progression, and metastasis.

Unraveling Tumor Heterogeneity by Using DNA Barcoding Technologies to Develop Personalized Treatment Strategies in Advanced-Stage PDAC.

Tumor heterogeneity is a hallmark of many solid tumors, including pancreatic ductal adenocarcinoma (PDAC), and an inherent consequence of the clonal evolution of cancers. As such, it is considered the underlying concept of many characteristics of the disease, including the ability to metastasize, adapt to different microenvironments, and to develop therapy resistance. Undoubtedly, the high mortality of PDAC can be attributed to a high extent to these properties. Despite its apparent importance, studying tumor heterogeneity has been a challenging task, mainly due to its complexity and lack of appropriate methods. However, in recent years molecular DNA barcoding has emerged as a sophisticated tool that allows mapping of individual cells or subpopulations in a cell pool to study heterogeneity and thus devise new personalized treatment strategies. In this review, we provide an overview of genetic and non-genetic inter- and intra-tumor heterogeneity and its impact on (personalized) treatment strategies in PDAC and address how DNA barcoding technologies work and can be applied to study this clinically highly relevant question.

In Situ Mapping of H2, O2, and H2O2 in Microreactors: A Parallel, Selective Multianalyte Detection Method.

Determining local concentrations of the analytes in state-of-the-art microreactors is essential for the development of optimized and safe processes. However, the selective, parallel monitoring of all relevant reactants and products in a multianalyte environment is challenging. Electrochemical microsensors can provide unique information on the reaction kinetics and overall performance of the hydrogen peroxide synthesis process in microreactors, thanks to their high spatial and temporal resolution and their ability to measure in situ, in contrast to other techniques. We present a chronoamperometric approach which allows the selective detection of the dissolved gases hydrogen and oxygen and their reaction product hydrogen peroxide on the same platinum microelectrode in an aqueous electrolyte. The method enables us to obtain the concentration of each analyte using three specific potentials and to subtract interfering currents from the mixed signal. While hydrogen can be detected independently, no potentials can be found for a direct, selective measurement of oxygen and hydrogen peroxide. Instead, it was found that for combined signals, the individual contribution of all analytes superimposes linearly additive. We showed that the concentrations determined from the subtracted signals correlate very well with results obtained without interfering analytes present. For the first time, this approach allowed the mapping of the distribution of the analytes hydrogen, oxygen, and hydrogen peroxide inside a multiphase membrane microreactor, paving the way for online process control.

Microsensor Electrodes for 3D Inline Process Monitoring in Multiphase Microreactors.

We present an electrochemical microsensor for the monitoring of hydrogen peroxide direct synthesis in a membrane microreactor environment by measuring the hydrogen peroxide and oxygen concentrations. In prior work, for the first time, we performed in situ measurements with electrochemical microsensors in a microreactor setup. However, the sensors used were only able to measure at the bottom of the microchannel. Therefore, only a limited assessment of the gas distribution and concentration change over the reaction channel dimensions was possible because the dissolved gases entered the reactor through a membrane at the top of the channel. In this work, we developed a new fabrication process to allow the sensor wires, with electrodes at the tip, to protrude from the sensor housing into the reactor channel. This enables measurements not only at the channel bottom, but also along the vertical axis within the channel, between the channel wall and membrane. The new sensor design was integrated into a multiphase microreactor and calibrated for oxygen and hydrogen peroxide measurements. The importance of measurements in three dimensions was demonstrated by the detection of strongly increased gas concentrations towards the membrane, in contrast to measurements at the channel bottom. These findings allow a better understanding of the analyte distribution and diffusion processes in the microreactor channel as the basis for process control of the synthesis reaction.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.