MmCMS: mouse models' consensus molecular subtypes of colorectal cancer

Amirkhah, R. et al. (2023) MmCMS: mouse models' consensus molecular subtypes of colorectal cancer. British Journal of Cancer, 128(7), pp. 1333-1343. (doi: 10.1038/s41416-023-02157-6) (PMID:36717674) (PMCID:PMC10050155)

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Background: Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1–4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. Methods: Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. Results: We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. Conclusions: When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.

Item Type:Articles
Additional Information:This research was supported by a CRUK early detection project grant (A29834), an International Accelerator Award, ACRCelerate, jointly funded by Cancer Research UK (A26825 and A28223), FC AECC (GEACC18004TAB) and AIRC (22795), the CRUK Glasgow Centre (A25142), a CRUK core funding (A21139, A17196 and A31287) and the Cancer Cluster programme within the MRC National Mouse Genetics Network (MC_PC_21042).
Glasgow Author(s) Enlighten ID:Dunne, Dr Philip and Gilroy, Dr Kathryn and Mills, Ms Megan and Ridgway, Dr Rachel and Sansom, Professor Owen and Campbell, Dr Andrew
Authors: Amirkhah, R., Gilroy, K., Malla, S. B., Lannagan, T. R.M., Byrne, R. M., Fisher, N. C., Corry, S. M., Mohamed, N.-E., Naderi-Meshkin, H., Mills, M. L., Campbell, A. D., Ridgway, R. A., Ahmaderaghi, B., Murray, R., Llergo, A. B., Sanz-Pamplona, R., Villanueva, A., Batlle, E., Salazar, R., Lawler, M., Sansom, O. J., and Dunne, P. D.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
Journal Name:British Journal of Cancer
Publisher:Springer Nature
ISSN (Online):1532-1827
Published Online:30 January 2023
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in British Journal of Cancer 128(7): 1333-1343
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
301989ACRClerate: Colorectal Cancer Stratified Medicine NetworkOwen SansomCancer Research UK (CRUK)C7932/A26825CS - Beatson Institute for Cancer Research
174115CRUK Centre RenewalOwen SansomCancer Research UK (CRUK)C7932/A25142CS - Beatson Institute for Cancer Research
315691Using complex state of the art mouse models of cancer to improve the understanding and treatment of human cancerKaren BlythMedical Research Council (MRC)MC_PC_21042CS - Beatson Institute for Cancer Research