Anticancer therapy is >70 years old, and nucleotides are the oldest target in cancer treatment. Despite its long history, this treatment suffers high rates of resistance and toxicity. What are the reasons? A cell can gain nucleotides via de novo synthesis (DNS) or from salvage pathways. DNS inhibition can be bypassed by nucleotides produced by surrounding cells or distant organs, causing resistance. Cancer cells were traditionally studied in isolation, with (bulk) techniques precluding identification of cell type-specific targets, causing toxicity. To date, the cellular sources of nucleotides in healthy and tumor tissues are poorly characterized. Can the complexity of metabolic crosstalk in tissues be captured by the traditional means? I hypothesize that cancer and stromal cells differ in how they utilize nucleic acid building blocks from external and internal sources. A single cell resolution is needed to disentangle their interactions, and inhibition of both DNS and cancer-specific salvage is required for a successful blockade. I aim to define the nucleotide sources in heathy tissues and tumors, characterize their adaptations to DNS blockade to uncover the network of metabolic interactions in tissues and find effective and specific combinations of targets. To reach this goal, I will use a unique combination of single cell multi-omics and tailored mouse models, an expertise and tools that I took the lead to set up. I will selectively disable DNS in the stroma (host mouse) and in cancer cells (syngeneic lung tumors) to generate tumors dependent on internally or externally produced nucleotides. In an integrative approach using spatial and single cell transcriptomics & metabolomics in situ, and functional genetic screen, I will search for targetable metabolic vulnerabilities of DNS-disabled cancer cells. This innovative research opens the path to understanding the organization of tissue metabolic homeostasis for new personalized metabolism-based anticancer medicine.