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Phenotypic plasticity represents the most relevant hallmark of the carcinoma cell as it bestows it with the capacity of transiently altering its morphological and functional features while en route to the metastatic site. However, the study of phenotypic plasticity is hindered by the rarity of these events within primary lesions and by the lack of experimental models. Here, we identified a subpopulation of phenotypic plastic colon cancer cells: EpCAM lo cells are motile, invasive, chemo-resistant, and highly metastatic. EpCAM lo bulk and single-cell RNAseq analysis indicated (1) enhanced Wnt/β-catenin signaling, (2) a broad spectrum of degrees of epithelial to mesenchymal transition (EMT) activation including hybrid E/M states (partial EMT) with highly plastic features, and (3) high correlation with the CMS4 subtype, accounting for colon cancer cases with poor prognosis and a pronounced stromal component. Of note, a signature of genes specifically expressed in EpCAM lo cancer cells is highly predictive of overall survival in tumors other than CMS4, thus highlighting the relevance of quasi-mesenchymal tumor cells across the spectrum of colon cancers. Enhanced Wnt and the downstream EMT activation represent key events in eliciting phenotypic plasticity along the invasive front of primary colon carcinomas. Distinct sets of epithelial and mesenchymal genes define transcriptional trajectories through which state transitions arise. pEMT cells, often earmarked by the extracellular matrix glycoprotein SPARC together with nuclear ZEB1 and β-catenin along the invasive front of primary colon carcinomas, are predicted to represent the origin of these (de)differentiation routes through biologically distinct cellular states and to underlie the phenotypic plasticity of colon cancer cells.

Phenotypic plasticity represents the most relevant hallmark of the carcinoma cell as it bestows it with the capacity of transiently altering its morphologic and functional features while en route to the metastatic site. However, the study of phenotypic plasticity is hindered by the rarity of these events within primary lesions and by the lack of experimental models. Here, we identified a subpopulation of phenotypic plastic colon cancer cells: EpCAMlo cells are motile, invasive, chemo-resistant, and highly metastatic. EpCAMlo bulk and single-cell RNAseq analysis indicated 1. enhanced Wnt/β-catenin signaling, 2. a broad spectrum of degrees of EMT activation including hybrid E/M states (partial EMT) with highly plastic features, and 3. high correlation with the CMS4 subtype, accounting for colon cancer cases with poor prognosis and a pronounced stromal component. Of note, a signature of genes specifically expressed in EpCAMlo cancer cells is highly predictive of overall survival in tumors other than CMS4, thus highlighting the relevance of quasi-mesenchymal tumor cells across the spectrum of colon cancers. Enhanced Wnt and the downstream EMT activation represent key events in eliciting phenotypic plasticity along the invasive front of primary colon carcinomas. Distinct sets of epithelial and mesenchymal genes define transcriptional trajectories through which state transitions arise. pEMT cells, often earmarked by the extracellular matrix glycoprotein SPARC together with nuclear ZEB1 and β-catenin along the invasive front of primary colon carcinomas, are predicted to represent the origin of these (de)differentiation routes through biologically distinct cellular states, and to underlie the phenotypic plasticity of colon cancer cells. Competing Interest Statement The authors have declared no competing interest. Footnotes * We have substantially revised the manuscript both in its overall structure, data presentation, and focus on the more novel aspects. By responding to the reviewers' criticisms and suggestions, we have implemented additional and state-of-the-art computational analysis pointing to the key role of pEMT in underlying phenotypic plasticity in colon cancer. Mining of bulk and scRNAseq data sets from colon cancer patients, we validated the relevance of our study by developing classifiers that outperform existing ones in predicting overall relapse-free survival.