Author:
Voorde Johan Vande,Najumudeen Arafath K.,Steven Rory T.,Nikula Chelsea J.,Dexter Alex,Zeiger Lucas B.,Elia Efstathios A.,Nasif Ammar,Gonzalez-Fernandez Ariadna,Murta Teresa,Gillespie Michael,Ford Catriona A.,Lannagan Tamsin R.M.,Vlahov Nikola,Ridgway Rachel A.,Nixon Colin,Gilroy Kathryn,Gay David M.,Burton Amy,Yan Bin,Sellers Katherine,Wu Vincen,Xiang Yuchen,Shokry Engy,Clark William,Li Vivian S.W.,Barry Simon T.,Goodwin Richard J.A.,Takats Zoltan,Maddocks Oliver D.K.,Sumpton David,Yuneva Mariia O.,Campbell Andrew D.,Bunch Josephine,Sansom Owen J.
Abstract
With colorectal cancer (CRC) being the second most common cause of cancer-related deaths worldwide1, there is an urgent need for better diagnostic tools and new, more targeted therapies. Here we used genetically engineered mouse models (GEMMs), 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 unsupervised metabolic profiling can stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging (MSI) to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-mutant CRC, and propose one of its enzymes, i.e. adenosylhomocysteinase (AHCY), as a new therapeutic target. Collectively, we show that the profound genotype-dependent alterations in both lipid and small molecule metabolism in CRC may be exploited for tissue classification with no need for ion identification, and we applied further data analysis to expose a novel metabolic vulnerability of CRC.
Publisher
Cold Spring Harbor Laboratory