Dataset Information

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

ABSTRACT:

Purpose

Precise mechanism-based gene expression signatures (GES) 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 sequencing 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; https://confoundr.qub.ac.uk/, 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.

SUBMITTER: Fisher NC

PROVIDER: S-EPMC9475248 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

Fisher Natalie C NC Byrne Ryan M RM Leslie Holly H Wood Colin C Legrini Assya A Cameron Andrew J AJ Ahmaderaghi Baharak B Corry Shania M SM Malla Sudhir B SB Amirkhah Raheleh R McCooey Aoife J AJ Rogan Emily E Redmond Keara L KL Sakhnevych Svetlana S Domingo Enric E Jackson James J Loughrey Maurice B MB Leedham Simon S Maughan Tim T Lawler Mark M Sansom Owen J OJ Lamrock Felicity F Koelzer Viktor H VH Jamieson Nigel B NB Dunne Philip D PD

Clinical cancer research : an official journal of the American Association for Cancer Research 20220901 18

<h4>Purpose</h4>Precise mechanism-based gene expression signatures (GES) 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 cha ...[more]

PMID: 35792866

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Dataset Information

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

Purpose

Experimental design

Results

Conclusions

Publications

Biological Misinterpretation of Transcriptional Signatures in Tumor Samples Can Unknowingly Undermine Mechanistic Understanding and Faithful Alignment with Preclinical Data.

Similar Datasets

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