To better understand and diagnose cancer, precise mechanism-based gene expression signatures (GES) have been created in relevant in vitro and in vivo model systems. Some GESs, however, are now being applied to heterogeneous tumor samples, where the expression of the genes in the signature may no longer be epithelium-specific, while they were originally intended to represent specific disease processes, largely with an epithelial cell emphasis. As a result, unintentional shifts in tumor stroma percentage can have a substantial impact on GESs, which can disrupt the mechanistic signaling that was intended. Using colorectal cancer as a model, researchers used a battery of orthogonal profiling techniques to determine how stromal content in tumor tissue might affect the most popular GESs. These techniques included laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single-cell RNA sequencing, and spatial transcriptomics. This work is supplemented by ConfoundR, a freely available resource that allows users to assess the level of stromal influence on an unlimited number of genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian, and prostate cancer datasets. The results presented here highlight the obvious risk of misinterpreting GESs due to pervasive stromal influences, which in turn can undermine faithful alignment between clinical samples and preclinical data/models, especially cell lines and organoids, or tumor models not fully recapitulating the stromal and immune microenvironment.
