The genomic landscape of colorectal cancer (CRC) is shaped by inactivating mutations in tumour suppressors such as APC, and oncogenic mutations such as mutant KRAS. Here we used genetically engineered mouse models, and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that untargeted metabolic profiling can be applied to stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging to identify tumour, stromal and normal adjacent tissues.
View Article and Find Full Text PDFRAC1 activity is critical for intestinal homeostasis, and is required for hyperproliferation driven by loss of the tumour suppressor gene Apc in the murine intestine. To avoid the impact of direct targeting upon homeostasis, we reasoned that indirect targeting of RAC1 via RAC-GEFs might be effective. Transcriptional profiling of Apc deficient intestinal tissue identified Vav3 and Tiam1 as key targets.
View Article and Find Full Text PDFMass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses.
View Article and Find Full Text PDFMany epithelial stem cell populations follow a pattern of stochastic stem cell divisions called 'neutral drift'. It is hypothesised that neutral competition between stem cells protects against the acquisition of deleterious mutations. Here we use a Porcupine inhibitor to reduce Wnt secretion at a dose where intestinal homoeostasis is maintained despite a reduction of Lgr5+ stem cells.
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