Cancer risk in carriers of TP53 germline variants grouped into different functional categories.

Li-Fraumeni syndrome is a cancer predisposition syndrome caused by pathogenic TP53 germline variants and associated with a high lifelong cancer risk. We analysed the German LFS registry that contains data on 304 individuals. Cancer phenotypes were correlated with variants grouped according to their ability to transactivate target genes in a yeast assay using a traditional (non-functional, partially-functional) and a novel (clusters A, B, C) classification of variants into different groups.

Cancer Neuroscience of Brain Tumors: From Multicellular Networks to Neuroscience-Instructed Cancer Therapies.

Deepening our understanding of neuro-cancer interactions can innovate brain tumor treatment. This mini review unfolds the most relevant and recent insights into the neural mechanisms contributing to brain tumor initiation, progression, and resistance, including synaptic connections between neurons and cancer cells, paracrine neuro-cancer signaling, and cancer cells' intrinsic neural properties. We explain the basic and clinical-translational relevance of these findings, identify unresolved questions and particularly interesting future research avenues, such as central nervous system neuro-immunooncology, and discuss the potential transferability to extracranial cancers.

Biglycan-driven risk stratification in ZFTA-RELA fusion supratentorial ependymomas through transcriptome profiling.

Recent genomic studies have allowed the subdivision of intracranial ependymomas into molecularly distinct groups with highly specific clinical features and outcomes. The majority of supratentorial ependymomas (ST-EPN) harbor ZFTA-RELA fusions which were designated, in general, as an intermediate risk tumor variant. However, molecular prognosticators within ST-EPN ZFTA-RELA have not been determined yet.

Spatial optimization of industrial symbiosis for heat supply of agricultural greenhouses.

Despite the many benefits of greenhouses, it is challenging to meet their heating demand, as greenhouses belong to the most energy-intensive production systems in the agriculture sector. Industrial symbiosis can bring an effective solution by utilizing waste heat from other industries to meet the greenhouse heat demand. This study proposes an optimization framework by which optimum symbiotic relationships can be identified.