This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
For further information about this project, please contact:
This project investigates how mitochondrial dysfunction shapes the spatial organisation, transcriptional programs, and ecological interactions of primary and metastatic colorectal cancer (CRC). Using high‑resolution spatial transcriptomics, the study aims to map metabolic stress, mitochondrial gene dysregulation, and microenvironmental remodelling directly within intact tumour architecture. The goal is to uncover spatially resolved metabolic vulnerabilities that may drive tumour progression, immune evasion, and metastatic competence.
By linking mitochondrial biology to spatial tumour evolution, this project has the potential to redefine how metabolic dysfunction contributes to CRC progression. The findings could inform new therapeutic strategies targeting metabolic vulnerabilities, improve risk stratification based on spatial metabolic signatures, and enhance understanding of metastatic evolution.
Modules and Packages:
- Python
- MuSpAn (Multiscale Spatial Analysis)
- Matplotlib
- NumPy
- Pandas
Computational Requirements:
The workflow requires importing and processing large spatial datasets. Domain creation is computationally intensive, typically demanding approximately 16 CPU cores and around 1 TB of RAM (or more, depending on dataset size and model complexity). Workflow. Once domain initialization is complete, Jupyter Notebooks will be used to run analyses and generate outputs.