Insulin-like growth factors and insulin control a multifunctional signalling network of significant importance in cancer

Insulin-like growth factor (IGF) and insulin (INS) proteins regulate key cellular functions through a complex interacting multi-component molecular network, known as the IGF/INS axis. We describe how dynamic and multilayer interactions give rise to the multifunctional role of the IGF/INS axis. Furthermore, we summarise the importance of the regulatory IGF/INS network in cancer, and discuss the possibilities and limitations of therapies targeting the IGF/INS axis with reference to ongoing clinical trials concerning the blockage of IGF1R in several types of cancer

Energy-efficient cooperative adaptive cruise control strategy using V2I

In an increasingly connected world, this paper presents an advanced and cooperative semi-autonomous driving system which targets not only convenient and safe mobility, but also achieves noticeably enhanced energy efficiency. By utilizing V2V and V2I communication, a vehicle\u27s energy consumption can be significantly reduced, while maintaining safety and driving comfort. A holistic control strategy is considered, which integrates features from earlier Cooperative Adaptive Cruise Control (CACC) and Traffic Light Assistant (TLA) research. This strategy incorporate s traffic light signal phase timing (SPAT), speed limits, road gradients and curves, surrounding traffic and detailed powertrain characteristics of the ego vehicle into a single Model Predictive Controller (MPC) formulation. The system\u27s performance was evaluated using a realistic cosimulation toolchain and tested on a real conventional vehicle on a powertrain testbed with real V2I hardware. Results for a D-class diesel passenger car driven over an urban route, show energy savings up to 25%, with an unchanged journey time compared to a typical human driver. The approach is valid for both urban cities driving and highways, whilst being adaptable to commercial vehicles and other powertrains (hybrid, fully electric)

Serum Autoantibodies in Chronic Prostate Inflammation in Prostate Cancer Patients.

BACKGROUND:Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens. METHODS:Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology. RESULTS:Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076). CONCLUSIONS:We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation

Characterization of Transcriptional Changes in ERG Rearrangement-Positive Prostate Cancer Identifies the Regulation of Metabolic Sensors Such as Neuropeptide Y

<div><p>ERG gene rearrangements are found in about one half of all prostate cancers. Functional analyses do not fully explain the selective pressure causing ERG rearrangement during the development of prostate cancer. To identify transcriptional changes in prostate cancer, including tumors with ERG gene rearrangements, we performed a meta-analysis on published gene expression data followed by validations on mRNA and protein levels as well as first functional investigations. Eight expression studies (n = 561) on human prostate tissues were included in the meta-analysis. Transcriptional changes between prostate cancer and non-cancerous prostate, as well as ERG rearrangement-positive (ERG+) and ERG rearrangement-negative (ERG−) prostate cancer, were analyzed. Detailed results can be accessed through an online database. We validated our meta-analysis using data from our own independent microarray study (n = 57). 84% and 49% (fold-change>2 and >1.5, respectively) of all transcriptional changes between ERG+ and ERG− prostate cancer determined by meta-analysis were verified in the validation study. Selected targets were confirmed by immunohistochemistry: NPY and PLA2G7 (up-regulated in ERG+ cancers), and AZGP1 and TFF3 (down-regulated in ERG+ cancers). First functional investigations for one of the most prominent ERG rearrangement-associated genes - neuropeptide Y (NPY) - revealed increased glucose uptake <em>in vitro</em> indicating the potential role of NPY in regulating cellular metabolism. In summary, we found robust population-independent transcriptional changes in prostate cancer and first signs of ERG rearrangements inducing metabolic changes in cancer cells by activating major metabolic signaling molecules like NPY. Our study indicates that metabolic changes possibly contribute to the selective pressure favoring ERG rearrangements in prostate cancer.</p> </div