p53 deficient breast cancer cells reprogram preadipocytes toward tumor-protective immunomodulatory cells.

The TP53 gene is mutated in approximately 30% of all breast cancer cases. Adipocytes and preadipocytes, which constitute a substantial fraction of the stroma of normal mammary tissue and breast tumors, undergo transcriptional, metabolic, and phenotypic reprogramming during breast cancer development and play an important role in tumor progression. We report here that p53 loss in breast cancer cells facilitates the reprogramming of preadipocytes, inducing them to acquire a unique transcriptional and metabolic program that combines impaired adipocytic differentiation with augmented cytokine expression. This, in turn, promotes the establishment of an inflammatory tumor microenvironment, including increased abundance of Ly6C+ and Ly6G+ myeloid cells and elevated expression of the immune checkpoint ligand PD-L1. We also describe a potential gain-of-function effect of common p53 missense mutations on the inflammatory reprogramming of preadipocytes. Altogether, our study implicates p53 deregulation in breast cancer cells as a driver of tumor-supportive adipose tissue reprogramming, expanding the network of non-cell autonomous mechanisms whereby p53 dysfunction may promote cancer. Further elucidation of the interplay between p53 and adipocytes within the tumor microenvironment may suggest effective therapeutic targets for the treatment of breast cancer patients.

Proteomic, Metabolomic, and Fatty Acid Profiling of Small Extracellular Vesicles from Glioblastoma Stem-Like Cells and Their Role in Tumor Heterogeneity.

Glioblastoma is a deadly brain tumor for which there is no cure. The presence of glioblastoma stem-like cells (GSCs) contributes to the heterogeneous nature of the disease and makes developing effective therapies challenging. Glioblastoma cells have been shown to influence their environment by releasing biological nanostructures known as extracellular vesicles (EVs). Here, we investigated the role of GSC-derived nanosized EVs (<200 nm) in glioblastoma heterogeneity, plasticity, and aggressiveness, with a particular focus on their protein, metabolite, and fatty acid content. We showed that conditioned medium and small extracellular vesicles (sEVs) derived from cells of one glioblastoma subtype induced transcriptomic and proteomic changes in cells of another subtype. We found that GSC-derived sEVs are enriched in proteins playing a role in the transmembrane transport of amino acids, carboxylic acids, and organic acids, growth factor binding, and metabolites associated with amino acid, carboxylic acid, and sugar metabolism. This suggests a dual role of GSC-derived sEVs in supplying neighboring GSCs with valuable metabolites and proteins responsible for their transport. Moreover, GSC-derived sEVs were enriched in saturated fatty acids, while their respective cells were high in unsaturated fatty acids, supporting that the loading of biological cargos into sEVs is a highly regulated process and that GSC-derived sEVs could be sources of saturated fatty acids for the maintenance of glioblastoma cell metabolism. Interestingly, sEVs isolated from GSCs of the proneural and mesenchymal subtypes are enriched in specific sets of proteins, metabolites, and fatty acids, suggesting a molecular collaboration between transcriptionally different glioblastoma cells. In summary, this study revealed the complexity of GSC-derived sEVs and unveiled their potential contribution to tumor heterogeneity and critical cellular processes commonly deregulated in glioblastoma.

13C-SpaceM: Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer.

Metabolism has emerged as a key factor in homeostasis and disease including cancer. Yet, little is known about the heterogeneity of metabolic activity of cancer cells due to the lack of tools to directly probe it. Here, we present a novel method, 13C-SpaceM for spatial single-cell isotope tracing of glucose-dependent de novo lipogenesis. The method combines imaging mass spectrometry for spatially-resolved detection of 13C6-glucose-derived 13C label incorporated into esterified fatty acids with microscopy and computational methods for data integration and analysis. We validated 13C-SpaceM on a spatially-heterogeneous normoxia-hypoxia model of liver cancer cells. Investigating cultured cells, we revealed single-cell heterogeneity of lipogenic acetyl-CoA pool labelling degree upon ACLY knockdown that is hidden in the bulk analysis and its effect on synthesis of individual fatty acids. Next, we adapted 13C-SpaceM to analyze tissue sections of mice harboring isocitrate dehydrogenase (IDH)-mutant gliomas. We found a strong induction of de novo fatty acid synthesis in the tumor tissue compared to the surrounding brain. Comparison of fatty acid isotopologue patterns revealed elevated uptake of mono-unsaturated and essential fatty acids in the tumor. Furthermore, our analysis uncovered substantial spatial heterogeneity in the labelling of the lipogenic acetyl-CoA pool indicative of metabolic reprogramming during microenvironmental adaptation. Overall, 13C-SpaceM enables novel ways for spatial probing of metabolic activity at the single cell level. Additionally, this methodology provides unprecedented insight into fatty acid uptake, synthesis and modification in normal and cancerous tissues.

A multidimensional atlas of human glioblastoma-like organoids reveals highly coordinated molecular networks and effective drugs.

Recent advances in the genomics of glioblastoma (GBM) led to the introduction of molecular neuropathology but failed to translate into treatment improvement. This is largely attributed to the genetic and phenotypic heterogeneity of GBM, which are considered the major obstacle to GBM therapy. Here, we use advanced human GBM-like organoid (LEGO: Laboratory Engineered Glioblastoma-like Organoid) models and provide an unprecedented comprehensive characterization of LEGO models using single-cell transcriptome, DNA methylome, metabolome, lipidome, proteome, and phospho-proteome analysis. We discovered that genetic heterogeneity dictates functional heterogeneity across molecular layers and demonstrates that NF1 mutation drives mesenchymal signature. Most importantly, we found that glycerol lipid reprogramming is a hallmark of GBM, and several targets and drugs were discovered along this line. We also provide a genotype-based drug reference map using LEGO-based drug screen. This study provides new human GBM models and a research path toward effective GBM therapy.