Cancer is a complex disease and an evolutionary phenomenon in which malignant cells and the tumor microenvironment (TME) co-evolve over time. A tumor is comprised of multiple cell types that engage in dynamic paracrine communication to orchestrate tumor growth, progression and metastasis. This project combines single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) with state-of-the-art computational algorithms, to functionally define the cellular components of the TME at unprecedented resolution, uncover their spatial organization, and elucidate cell-subtype specific paracrine signaling and micro-niche organization. More specifically, we have established a faithful mouse model of glioblastoma (GBM) in wild-type (Pdgfbret/+) and pericyte-poor mice (Pdgfbret/ret) to investigate how pericyte absence affects the intra- and inter- tumoral expression heterogeneity and cellular composition. We used single cell sequencing Chromium 10X technology to analyze the expression profile of more than 60,000 cells from 7 wild type and 4 pericyte-poor tumors. We also performed a spatial transcriptomics using the Visium platform form 10X on 4 pericyte-poor and 4 control tumors. The integration of this molecular and spatial information is crucial for properly characterizing microniche organization in GBM and uncover the the complex interactions of pericytes, immune cells and tumour cells in GBM. Our study is currently developing, and we are still analysing similarities and difference between spatial transcriptomics samples and conditions. We are also validating the presence of identified microniches and their specific active pathways at the protein and cellular level in the laboratory. We are asking for renovation of this project, both the computational and storage resources, as we anticipate that further studies will result from the analyses of diverse aspect of this data. For example, we are analyzing the impact of hypoxic regions on diverse cell population, and we will next focus on characterizing the heterogeneity and role of different macrophage and microglia populations on GBM. The resources and support provided by National Academic Infrastructure for Supercomputing in Sweden (NAISS) and Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) have been vital for the realization of this project and we would be grateful to be granted a continuation.