Effect of Predation on Fouling Communities in an Italian Hotspot of Non-Indigenous Species

The role of native predators in controlling or facilitating non-indigenous species (NIS) growing in a fouling assemblage was investigated with a 70-day caging experiment in a marina inside the Gulf of La Spezia (Italy). Submerged PVC panels were divided into three experimental treatment levels: “control panels”, “open-caged panels” and “caged panels”, to assess the predation effect on the fouling assemblages growing on the panels. Predation effect was observed for two investigated variables. The Shannon Index was significantly higher in caged panels in comparison with controls, while an opposite trend was observed for the coverage area of native species. When testing single NIS abundance, both facilitation and limitation of individual NIS settlement has been observed. Mean coverage of the sabellid Branchiomma luctuosum was significantly higher in caged than in uncaged or open-caged panels, while the ascidian Styela plicata was prevalent in open-caged panels. In general, a predation effect was observed when considering the whole fouling assemblage, including different trends in NIS coverage among treatment levels. The results of this first attempt performed in the Mediterranean Sea encourage further experiments to investigate the biotic resistance provided by native predators against NIS

Non-FG mediated transport of the large pre-ribosomal subunit through the nuclear pore complex by the mRNA export factor Gle2

Multiple export receptors passage bound pre-ribosomes through nuclear pore complexes (NPCs) by transiently interacting with the Phe-Gly (FG) meshwork of their transport channels. Here, we reveal how the non-FG interacting yeast mRNA export factor Gly-Leu-FG lethal 2 (Gle2) functions in the export of the large pre-ribosomal subunit (pre-60S). Structure-guided studies uncovered conserved platforms used by Gle2 to export pre-60S: an uncharacterized basic patch required to bind pre-60S, and a second surface that makes non-FG contacts with the nucleoporin Nup116. A basic patch mutant of Gle2 is able to function in mRNA export, but not pre-60S export. Thus, Gle2 provides a distinct interaction platform to transport pre-60S to the cytoplasm. Notably, Gle2's interaction platforms become crucial for pre-60S export when FG-interacting receptors are either not recruited to pre-60S or are impaired. We propose that large complex cargos rely on non-FG as well as FG-interactions for their efficient translocation through the nuclear pore complex channe

Solid lipid nanoparticles of cholesteryl butyrate inhibit the proliferation of cancer cells in vitro and in vivo models.

BACKGROUND AND PURPOSE: Solid lipid nanoparticles containing cholesteryl butyrate (cholbut SLN) can be a delivery system for the anti-cancer drug butyrate. These nanoparticles inhibit adhesion of polymorphonuclear and tumour cells to endothelial cells and migration of tumour cells, suggesting that they may act as anti-inflammatory and anti-tumour agents. Here we have evaluated the effects of cholbut SLN on tumour cell growth using in vitro and in vivo models. EXPERIMENTAL APPROACH: Cholbut SLNs were incubated with cultures of four tumour cell lines, and cell growth was analysed by assessing viability, clonogenic capacity and cell cycle. Effects on intracellular signalling was assessed by Western blot analysis of Akt expression. The in vivo anti-tumour activity was measured in two models of PC-3 cell xenografts in SCID/Beige mice. KEY RESULTS: Cholbut SLN inhibited tumour cell line viability, clonogenic activity, Akt phosphorylation and cell cycle progression. In mice injected i.v. with PC3-Luc cells and treated with cholbut SLN, . in vivo optical imaging and histological analysis showed no metastases in the lungs of the treated mice. In another set of mice injected s.c. with PC-3 cells and treated with cholbut SLN when the tumour diameter reached 2 mm, analysis of the tumour dimensions showed that treatment with cholbut SLN substantially delayed tumour growth. CONCLUSION AND IMPLICATIONS: Cholbut SLN were effective in inhibiting tumour growth in vitro and in vivo. These effects may involve, in part, inhibition of Akt phosphorylation, which adds another mechanism to the activity of this multipotent drug

Targeted proteomics reveals compositional dynamics of 60S pre‐ribosomes after nuclear export

Construction and intracellular targeting of eukaryotic pre-ribosomal particles involve a multitude of diverse transiently associating trans-acting assembly factors, energy-consuming enzymes, and transport factors. The ability to rapidly and reliably measure co-enrichment of multiple factors with maturing pre-ribosomal particles presents a major biochemical bottleneck towards revealing their function and the precise contribution of >50 energy-consuming steps that drive ribosome assembly. Here, we devised a workflow that combines genetic trapping, affinity-capture, and selected reaction monitoring mass spectrometry (SRM-MS), to overcome this deficiency. We exploited this approach to interrogate the dynamic proteome of pre-60S particles after nuclear export. We uncovered assembly factors that travel with pre-60S particles to the cytoplasm, where they are released before initiating translation. Notably, we identified a novel shuttling factor that facilitates nuclear export of pre-60S particles. Capturing and quantitating protein interaction networks of trapped intermediates of macromolecular complexes by our workflow is a reliable discovery tool to unveil dynamic processes that contribute to their in vivo assembly and transport

B7h triggering inhibits the migration of tumor cell lines

Vascular endothelial cells (ECs) and several cancer cells express B7h, which is the ligand of the ICOS T cell costimulatory molecule. We have previously shown that B7h triggering via a soluble form of ICOS (ICOS-Fc) inhibits the adhesion of polymorphonuclear and tumor cell lines to HUVECs; thus, we suggested that ICOS-Fc may act as an anti-inflammatory and antitumor agent. Because cancer cell migration and angiogenesis are crucial for metastasis dissemination, the aim of this work was to evaluate the effect of ICOS-Fc on the migration of cancer cells and ECs. ICOS-Fc specifically inhibited the migration of HUVECs, human dermal lymphatic ECs, and the HT29, HCT116, PC-3, HepG2, JR8, and M14 tumor cell lines expressing high levels of B7h, whereas it was ineffective in the RPMI7932, PCF-2, LM, and BHT-101 cell lines expressing low levels of B7h. Furthermore, ICOS-Fc downmodulated hepatocyte growth factor facilitated the epithelial-to-mesenchymal transition in HepG2 cells. Moreover, ICOS-Fc downmodulated the phosphorylation of focal adhesion kinase and the expression of \u3b2-Pix in both HUVECs and tumor cell lines. Finally, treatment with ICOS-Fc inhibited the development of lung metastases upon injection of NOD-SCID-IL2R\u3b3null mice with CF-PAC1 cells, as well as C57BL/6 mice with B16-F10 cells. Therefore, the B7h-ICOS interaction may modulate the spread of cancer metastases, which suggests the novel use of ICOS-Fc as an immunomodulatory drug. However, in the B16-F10-metastasized lungs, ICOS-Fc also increased IL-17A/RORc and decreased IL-10/Foxp3 expression, which indicates that it also exerts positive effects on the antitumor immune response

Enhanced cytotoxic effect of camptothecin nanosponges in anaplastic thyroid cancer cellsin vitroandin vivoon orthotopic xenograft tumors

Anaplastic carcinoma of the thyroid (ATC) is a lethal human malignant cancer with median survival of 6 months. To date, no treatment has substantially changed its course, which makes urgent need for the development of novel drugs or novel formulations for drug delivery. Nanomedicine has enormous potential to improve the accuracy of cancer therapy by enhancing availability and stability, decreasing effective doses and reducing side effects of drugs. Camptothecin (CPT) is an inhibitor of DNA topoisomerase-I with several anticancer properties but has poor solubility and a high degradation rate. Previously, we reported that CPT encapsulated in β-cyclodextrin-nanosponges (CN-CPT) increased solubility, was protected from degradation and inhibited the growth of prostate tumor cells both in vitro and in vivo. The aim of this study was to extend that work by assessing the CN-CPT effectiveness on ATC both in vitro and in vivo. Results showed that CN-CPT significantly inhibited viability, clonogenic capacity and cell-cycle progression of ATC cell lines showing a faster and enhanced effect compared to free CPT. Moreover, CN-CPT inhibited tumor cell adhesion to vascular endothelial cells, migration, secretion of pro-angiogenic factors (IL-8 and VEGF-α), expression of β-PIX, belonging to the Rho family activators, and phosphorylation of the Erk1/2 MAPK. Finally, CN-CPT significantly inhibited the growth, the metastatization and the vascularization of orthotopic ATC xenografts in SCID/beige mice without apparent toxic effects in vivo. This work extends the previous insight showing that β-cyclodextrin-nanosponges are a promising tool for the treatment of ATC

Chimeric Rat/Human HER2 Efficiently Circumvents HER2 Tolerance in Cancer Patients.

Purpose: Despite the great success of HER2 vaccine strategies in animal models, effective clinical results have not yet been obtained. We studied the feasibility of using DNA coding for chimeric rat/human HER2 as a tool to break the unresponsiveness of T cells from patients with HER2-overexpressing tumors (HER2-CP). Experimental Design: Dendritic cells (DCs) generated from patients with HER2-overexpressing breast (n = 28) and pancreatic (n = 16) cancer were transfected with DNA plasmids that express human HER2 or heterologous rat sequences in separate plasmids or as chimeric constructs encoding rat/human HER2 fusion proteins and used to activate autologous T cells. Activation was evaluated by IFN-γ ELISPOT assay, perforin expression, and ability to halt HER2+ tumor growth in vivo. Results: Specific sustained proliferation and IFN-γ production by CD4 and CD8 T cells from HER2-CP was observed after stimulation with autologous DCs transfected with chimeric rat/human HER2 plasmids. Instead, T cells from healthy donors ( n = 22) could be easily stimulated with autologous DCs transfected with any human, rat, or chimeric rat/human HER2 plasmid. Chimeric HER2-transfected DCs from HER2-CP were also able to induce a sustained T-cell response that significantly hindered the in vivo growth of HER2+ tumors. The efficacy of chimeric plasmids in overcoming tumor-induced T-cell dysfunction relies on their ability to circumvent suppressor effects exerted by regulatory T cells (Treg) and/or interleukin (IL)-10 and TGF-β1. Conclusions: These results provide the proof of concept that chimeric rat/human HER2 plasmids can be used as effective vaccines for any HER2-CP with the advantage of being not limited to specific MHC

Real-world data to build explainable trustworthy artificial intelligence models for prediction of immunotherapy efficacy in NSCLC patients

IntroductionArtificial Intelligence (AI) methods are being increasingly investigated as a means to generate predictive models applicable in the clinical practice. In this study, we developed a model to predict the efficacy of immunotherapy (IO) in patients with advanced non-small cell lung cancer (NSCLC) using eXplainable AI (XAI) Machine Learning (ML) methods. MethodsWe prospectively collected real-world data from patients with an advanced NSCLC condition receiving immune-checkpoint inhibitors (ICIs) either as a single agent or in combination with chemotherapy. With regards to six different outcomes - Disease Control Rate (DCR), Objective Response Rate (ORR), 6 and 24-month Overall Survival (OS6 and OS24), 3-months Progression-Free Survival (PFS3) and Time to Treatment Failure (TTF3) - we evaluated five different classification ML models: CatBoost (CB), Logistic Regression (LR), Neural Network (NN), Random Forest (RF) and Support Vector Machine (SVM). We used the Shapley Additive Explanation (SHAP) values to explain model predictions. ResultsOf 480 patients included in the study 407 received immunotherapy and 73 chemo- and immunotherapy. From all the ML models, CB performed the best for OS6 and TTF3, (accuracy 0.83 and 0.81, respectively). CB and LR reached accuracy of 0.75 and 0.73 for the outcome DCR. SHAP for CB demonstrated that the feature that strongly influences models' prediction for all three outcomes was Neutrophil to Lymphocyte Ratio (NLR). Performance Status (ECOG-PS) was an important feature for the outcomes OS6 and TTF3, while PD-L1, Line of IO and chemo-immunotherapy appeared to be more important in predicting DCR. ConclusionsIn this study we developed a ML algorithm based on real-world data, explained by SHAP techniques, and able to accurately predict the efficacy of immunotherapy in sets of NSCLC patients

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project