Biological misinterpretation of transcriptional signatures in tumour samples can unknowingly undermine mechanistic understanding and faithful alignment with preclinical data

Fisher, N. C. et al. (2022) Biological misinterpretation of transcriptional signatures in tumour samples can unknowingly undermine mechanistic understanding and faithful alignment with preclinical data. Clinical Cancer Research, 28(18), pp. 4056-4069. (doi: 10.1158/1078-0432.CCR-22-1102) (PMID:35792866) (PMCID:PMC9475248)

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Purpose: Precise mechanism-based gene expression signatures (GESs) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signaling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumor samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumor stroma percentage can directly influence GESs, undermining the intended mechanistic signaling. Experimental Design: Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single cell RNA-Seq and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely used GESs to be influenced, or confounded, by stromal content in tumor tissue. To complement this work, we generated a freely-available resource, ConfoundR;, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets. Results: Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment. Conclusions: Efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Jamieson, Dr Nigel and Cameron, Mr Andrew and legrini, assya and Wood, Dr Colin and Sansom, Professor Owen and Leslie, Ms Holly
Authors: Fisher, N. C., Byrne, R. M., Leslie, H., Wood, C., Legrini, A., Cameron, A. J., Ahmaderaghi, B., Corry, S. M., Malla, S. B., Amirkhah, R., McCooey, A. J., Rogan, E., Redmond, K. L., Sakhnevych, S., Domingo, E., Jackson, J., Loughrey, M. B., Leedham, S., Maughan, T., Lawler, M., Sansom, O. J., Lamrock, F., Koelzer, V. H., Jamieson, N., and Dunne, P. D.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
Journal Name:Clinical Cancer Research
Publisher:American Association for Cancer Research
ISSN (Online):1557-3265
Published Online:06 July 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Clinical Cancer Research 28(18): 4056-4069
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
301364COMBINATION THERAPIES TARGETING IMMUNE EVASION IN PANCREATIC CANCERNigel JamiesonCancer Research UK (CRUK)C55370/A25813CS -Translational Research Centre