Epithelial-mesenchymal transition (EMT) is a key cellular process involved in development and disease progression. Single-cell transcriptomes can characterize intermediate EMT states observed in tumors and fibrotic tissues, but previous in vitro models focused on time-dependent responses after stimulation with single dose of EMT signals. It was therefore unclear whether single-cell transcriptomes support stable intermediate EMT phenotypes crucial for disease progression. We performed single-cell RNA-sequencing with human mammary epithelial cells treated with various concentrations of TGF-β. We found that the dose-dependent EMT harbors multiple intermediate states at the single-cell level after two weeks of treatment, suggesting a stable continuum. After correcting batch effects from experiments, we performed comparative analyses of the dose- and time-dependent EMT. We found that the dose-dependent EMT shows a stronger anti-correlation between epithelial and mesenchymal transcriptional programs and a better resolution of transition stages compared to the time-dependent process. These properties enable higher sensitivity to detect genes whose expressions are associated with core EMT regulatory networks. Nonetheless, we found cell clusters unique to the time-dependent EMT, which correspond to en route cell populations that do not appear at steady states. Furthermore, combining dose- and time-dependent cell clusters gave rise to more accurate prognosis for cancer patients compared to individual EMT spectrum. Our new data and analyses reveal a stable EMT continuum at the single-cell resolution and the transcriptomic level. The dose-dependent experimental model can complement the widely used time-course experiments to reflect physiologically or pathologically relevant EMT phenotypes in a comprehensive manner.