Long non-coding RNAs (lncRNAs) have emerged as integral components of E2F1-regulated gene regulatory networks (GRNs), but their implication in advanced or treatment-refractory malignancy is unknown. Methods We combined high-throughput transcriptomic approaches with bioinformatics and structure modeling to search for lncRNAs that participate in E2F1-activated prometastatic GRNs and their phenotypic targets in the highly-relevant case of E2F1-driven aggressive bladder cancer (BC). RNA immunoprecipitation was performed to verify RNA-protein interactions. Functional analyses including qRT-PCR, immunoblotting, luciferase assays and measurement of extracellular fluxes were conducted to validate expression and target gene regulation. Results We identified E2F1-responsive lncRNA-SLC16A1-AS1 and its associated neighboring protein-coding gene, SLC16A1/MCT1, which both promote cancer invasiveness. Mechanistically, upon E2F1-mediated co-transactivation of the gene pair, SLC16A1-AS1 associates with E2F1 in a structure-dependent manner and forms an RNA-protein complex that enhances SLC16A1/MCT1 expression through binding to a composite SLC16A1-AS1E2F1-responsive promoter element. Moreover, SLC16A1-AS1 increases aerobic glycolysis and mitochondrial respiration and fuels ATP production by fatty acid β-oxidation.  https://www.selleckchem.com/products/mira-1.html  These metabolic changes are accompanied by alterations in the expression of the SLC16A1-AS1E2F1-responsive gene PPARA, a key mediator of fatty acid β-oxidation. Conclusions Our results unveil a new gene regulatory program by which E2F1-induced lncRNA-SLC16A1-AS1 forms a complex with its transcription factor that promotes cancer metabolic reprogramming towards the acquisition of a hybrid oxidative phosphorylation/glycolysis cell phenotype favoring BC invasiveness.[This retracts the article DOI 10.7150/thno.32738.].Rationale Gastric cancer (GC) is a solid tumor that contains subpopulations of cancer stem cells (CSCs), which are considered drivers of tumor initiation and metastasis; responsible for therapeutic resistance; and promoters of tumor relapse. The balance between symmetric and asymmetric division is crucial for stem cell maintenance. The objective of this study is to evaluate the role of MAD2, a key protein for proper mitotic checkpoint activity, in the tumorigenesis of GC. Methods Gastric cancer stem cells (GCSCs) were obtained from MKN45, SNU638 and ST2957 cell lines. Pluripotency and stemness markers were evaluated by RT-qPCR and autofluorescence and membrane markers by flow cytometry. Relevant signal transduction pathways were studied by WB. We analysed cell cycle progression, migration and invasion after modulation of MAD2 activity or protein expression levels in these in vitro models. In vivo assays were performed in a nude mouse subcutaneous xenograft model. Results We found that NANOG, CXCR4 and autofluorescence are common and consistent markers for the GCSCs analysed, with other markers showing more variability. The three main signalling pathways (Wnt/β-catenin; Hedgehog and Notch) were activated in GCSCs. Downregulation of MAD2 in MKN45CSCs decreased the expression of markers CXCR4, CD133, CD90, LGR5 and VIM, without affecting cell cycle profile or therapy resistance. Moreover, migration, invasion and tumor growth were clearly reduced, and accordingly, we found that metalloprotease expression decreased. These results were accompanied by a reduction in the levels of transcription factors related with epithelial-to-mesenchymal transition. Conclusions We can conclude that MAD2 is important for GCSCs stemness and its downregulation in MKN45CSCs plays a central role in GC tumorigenesis, likely through CXCR4-SNAI2-MMP1. Thus, its potential use in the clinical setting should be studied as its functions appear to extend beyond mitosis.Cytokine storms, defined by the dysregulated and excessive production of multiple pro-inflammatory cytokines, are closely associated with the pathology and mortality of several infectious diseases, including coronavirus disease 2019 (COVID-19). Effective therapies are urgently needed to block the development of cytokine storms to improve patient outcomes, but approaches that target individual cytokines may have limited effect due to the number of cytokines involved in this process. Dysfunctional macrophages appear to play an essential role in cytokine storm development, and therapeutic interventions that target these cells may be a more feasible approach than targeting specific cytokines. Nanomedicine-based therapeutics that target macrophages have recently been shown to reduce cytokine production in animal models of diseases that are associated with excessive proinflammatory responses. In this mini-review, we summarize important studies and discuss how macrophage-targeted nanomedicines can be employed to attenuate cytokine storms and their associated pathological effects to improve outcomes in patients with severe infections or other conditions associated with excessive pro-inflammatory responses. We also discuss engineering approaches that can improve nanocarriers targeting efficiency to macrophages, and key issues should be considered before initiating such studies.The metabolic properties of tumor microenvironment (TME) are dynamically dysregulated to achieve immune escape and promote cancer cell survival. However, in vivo properties of glucose metabolism in cancer and immune cells are poorly understood and their clinical application to development of a biomarker reflecting immune functionality is still lacking. Methods We analyzed RNA-seq and fluorodeoxyglucose (FDG) positron emission tomography profiles of 63 lung squamous cell carcinoma (LUSC) specimens to correlate FDG uptake, expression of glucose transporters (GLUT) by RNA-seq and immune cell enrichment score (ImmuneScore). Single cell RNA-seq analysis in five lung cancer specimens was performed. We tested the GLUT3/GLUT1 ratio, the GLUT-ratio, as a surrogate representing immune metabolic functionality by investigating the association with immunotherapy response in two melanoma cohorts. Results ImmuneScore showed a negative correlation with GLUT1 (r = -0.70, p less then 0.01) and a positive correlation with GLUT3 (r = 0.