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During epithelial-to-mesenchymal transition (EMT), cancer cells lose their cell–cell adhesion junctions as they become more metastatic, altering cell motility and focal adhesion disassembly associated with increased detachment from the primary tumor and a migratory response into nearby tissue and vasculature. Current in vitro strategies characterizing a cell's metastatic potential heavily favor quantifying the presence of cell adhesion biomarkers through biochemical analysis; however, mechanical cues such as adhesion and motility directly relate to cell metastatic potential without needing to first identify a cell specific biomarker for a particular type of cancer. This paper presents a comprehensive comparison of two functional metrics of cancer aggression, wound closure migration velocity and cell detachment from a culture surface, for three pairs of epithelial cancer cell lines (breast, endometrium, tongue tissue origins). It was found that one functional metric alone was not sufficient to categorize the cancer cell lines; instead, both metrics were necessary to identify functional trends and accurately place cells on the spectrum of metastasis. On average, cell lines with low metastatic potential (MCF-7, Ishikawa, and Cal-27) were more aggressive through wound closure migration compared to loss of cell adhesion. On the other hand, cell lines with high metastatic potential (MDA-MB-231, KLE, and SCC-25) were on average more aggressive through loss of cell adhesion compared to wound closure migration. This trend was true independent of the tissue type where the cells originated, indicating that there is a relationship between metastatic potential and the predominate type of cancer aggression. Our work presents one of the first combined studies relating cell metastatic potential to functional migration and adhesion metrics across cancer cell lines from selected tissue origins, without needing to identify tissue-specific biomarkers to achieve success. Using functional metrics provides powerful clinical relevancy for future predictive tools of cancer metastasis.