Network analysis of colocalised metabolite signals from colorectal cancer using DESI mass spectrometry imaging data
datasetposted on 04.12.2017 by Paolo Inglese, Z. (Zoltan) Takats, R.C. (Robert) Glen
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
A deeper understanding of inter-tumour and intra-tumour heterogeneity is a critical factor for the advancement of next generation strategies against cancer. The heterogeneous morphology exhibited by solid tumours is mirrored by their metabolic heterogeneity. Defining the basic biological mechanisms that underlie tumour cell variability will be fundamental to the development of personalised cancer treatments. Variability in the molecular signatures found in local regions of cancer tissues can be captured through an untargeted analysis of their metabolic constituents. Here we demonstrate that DESI mass spectrometry imaging (MSI) combined with network analysis can provide detailed insight into the metabolic heterogeneity of colorectal cancer (CRC). We show that network modules capture signatures which differentiate tumour metabolism in the core and in the surrounding region. Moreover, module preservation analysis of network modules between patients with and without metastatic recurrence explains the inter-subject metabolic differences associated with diverse clinical outcomes such as metastatic recurrence.