Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell–intrinsic Stemness or Mesenchymality Characteristics

Abstract

Abstract Epithelial-to-mesenchymal transition (EMT) in cancer cells confers migratory abilities, a crucial aspect in the metastasis of tumors that frequently leads to death. In multiple studies, authors proposed gene expression signatures for EMT, stemness, or mesenchymality of tumors based on bulk tumor expression profiling. However, recent studies suggested that noncancerous cells from the microenvironment or macroenvironment heavily influence such signature profiles. Here, we strengthen these findings by investigating 11 published and frequently referenced gene expression signatures that were proposed to describe EMT-related (EMT, mesenchymal, or stemness) characteristics in various cancer types. By analyses of bulk, single-cell, and pseudobulk expression data, we show that the cell type composition of a tumor sample frequently dominates scores of these EMT-related signatures. A comprehensive, integrated analysis of bulk RNA sequencing (RNA-seq) and single-cell RNA-seq data shows that stromal cells, most often fibroblasts, are the main drivers of EMT-related signature scores. We call attention to the risk of false conclusions about tumor properties when interpreting EMT-related signatures, especially in a clinical setting: high patient scores of EMT-related signatures or calls of “stemness subtypes” often result from low cancer cell content in tumor biopsies rather than cancer cell–specific stemness or mesenchymal/EMT characteristics. Significance: Cancer self-renewal and migratory abilities are often characterized via gene module expression profiles, also called EMT or stemness gene expression signatures. Using published clinical tumor samples, cancer cell lines, and single cancer cells, we highlight the dominating influence of noncancer cells in low cancer cell content biopsies on their scores. We caution on their application for low cancer cell content clinical cancer samples with the intent to assign such characteristics or subtypes.