Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk patients to demonstrate reversal of risk signatures and malignant phenotypes. Using neuroblastoma xenograft models, we establish CNR2 and MAPK8 as promising candidates for the treatment of high-risk neuroblastoma. We expect that our method, available as a public tool (targettranslator.org), will enhance and expedite the discovery of risk-associated targets for paediatric and adult cancers.

Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single‐cell analysis have enabled the delineation of distinct cellular states of brain tumor cells, but the time‐dependent changes in such states remain poorly understood. Here, we construct quantitative models of the time‐dependent transcriptional variation of patient‐derived glioblastoma (GBM) cells. We build the models by sampling and profiling barcoded GBM cells and their progeny over the course of 3 weeks and by fitting a mathematical model to estimate changes in GBM cell states and their growth rates. Our model suggests a hierarchical yet plastic organization of GBM, where the rates and patterns of cell state switching are partly patient‐specific. Therapeutic interventions produce complex dynamic effects, including inhibition of specific states and altered differentiation. Our method provides a general strategy to uncover time‐dependent changes in cancer cells and offers a way to evaluate and predict how therapy affects cell state composition.

Glioblastoma (GBM) is the most common primary brain cancer. It causes death mainly by local invasion via several routes, including infiltration of white matter tracts and penetration of perivascular spaces. However, the pathways that mediate these invasion routes are only partly known. Here, we conduct an integrative study to identify cell states and central drivers of route-specific invasion in GBM. Combining single-cell profiling and spatial protein detection in patient-derived xenograft models and clinical tumor samples, we demonstrate a close association between the differentiation state of GBM cells and their choice of invasion route. Computational modeling identifies ANXA1 as a driver of perivascular involvement in GBM cells with mesenchymal differentiation and the transcription factors RFX4 and HOPX as orchestrators of growth and differentiation in diffusely invading GBM cells. Ablation of these targets in tumor cells alters their invasion route, redistributes the cell states, and extends survival in xenografted mice. Our results define a close association between GBM cell differentiation states and invasion routes, identify functional biomarkers of route-specific invasion, and point toward targeted modulation of specific invasive cell states as a therapeutic strategy in GBM.

Grape pomace (GPO), the main by-product of the wine making process, is a rich source of polyphenols with potent antioxidant properties. Recently, GPO has emerged as a potential feed additive in livestock nutrition, with several reports describing its beneficial effects on animals’ overall health status or production traits. However, little is known about it from a molecular biology standpoint. In the present study, we report the first RNA sequencing-based whole-transcriptome profiling of Friesian calves fed with a GPO-supplemented diet. We identified 367 differentially expressed genes (p < 0.05) in the GPO-supplemented calves (n = 5), when compared with unsupplemented control group (n = 5). The pathway analysis showed that ‘cholesterol lipid biosynthesis’ was the most negatively-enriched (p < 0.001) pathway in the GPO-supplemented animals. In specific terms, five important genes coding for cholesterol biosynthesis enzymes, namely the Farnesyl-diphosphate Farnesyltransferase 1 (FDFT-1), Squalene Epoxidase (SQLE), NAD(P)-dependent Steroid Dehydrogenase-like (NSDHL), Methylsterol Monooxygenase (MSMO)-1, and Sterol-C5-desaturase (SC5D), two major transcription factors (the Sterol Regulatory Element-binding Transcription Factor 1 and 2), as well as the Low-Density Lipoprotein Receptor (LDLR), were all downregulated following GPO supplementation. Such an effect was mirrored by a reduction of blood cholesterol levels (p = 0.07) and a lowered (p < 0.001) Malondialdehyde (lipid oxidation marker) level in carcasses. We provide evidence on the effects of GPO-supplemented diets on the whole-transcriptome signature in veal calves, which mainly reflects an antioxidant activity.

The increasing demand for more animal products put pressure on improving livestock production efficiency and sustainability. In this context, advanced animal nutrition studies appear indispensable. Here, the effect of grape pomace (GP), the polyphenol-rich agricultural by-product, was evaluated on Holstein-Friesian cows’ whole-blood transcriptome, milk production and composition. Two experimental groups were set up. The first one received a basal diet and served as a control, while the second one received a 7.5% GP-supplemented diet for a total of 60 days. Milk production and composition were not different between the group; however, the transcriptome analysis revealed a total of 40 genes significantly affected by GP supplementation. Among the most interesting down-regulated genes, we found the DnaJ heat-shock protein family member A1 (DNAJA1), the mitochondrial fission factor (MFF), and the impact RWD domain protein (IMPACT) genes. The gene set enrichment analysis evidenced the positive enrichment of ‘interferon alpha (IFN-α) and IFN-γ response’, ‘IL6-JAK-STAT3 signaling’ and ‘complement’ genes. Moreover, the functional analysis denoted positive enrichment of the ‘response to protozoan’ and ‘negative regulation of viral genome replication’ biological processes. Our data provide an overall view of the blood transcriptomic signature after a 60-day GP supplementation in dairy cows which mainly reflects a GP-induced immunomodulatory effect.

G-quadruplexes (G4) are secondary nucleic acid structures that have been associated with genomic instability and cancer progression. When present in the promoter of some oncogenes, G4 structures can affect gene regulation and, hence, represent a possible therapeutic target. In this study, RNA-Seq was used to explore the effect of a G4-binding anthraquinone derivative, named AQ1, on the whole-transcriptome profiles of two common cell models for the study of KIT pathways; the human mast cell leukemia (HMC1.2) and the canine mast cell tumor (C2). The highest non-cytotoxic dose of AQ1 (2 µM) resulted in 5441 and 1201 differentially expressed genes in the HMC1.2 and C2 cells, respectively. In both cell lines, major pathways such as cell cycle progression, KIT- and MYC-related pathways were negatively enriched in the AQ1-treated group, while other pathways such as p53, apoptosis and hypoxia-related were positively enriched. These findings suggest that AQ1 treatment induces a similar functional response in the human and canine cell models, and provide news insights into using dogs as a reliable translational model for studying G4-binding compounds.