Updated project metadata. We performed quantitative TMT-based proteomic analysis of eight human-derived breast cell lines growing in 2D. The dataset includes the total and phospho-proteomes of seven tumour cell lines: T47D (Epithelial, Luminal, ER+/PR+/HER2-), BT474 (Epithelial, Luminal, ER+/PR+/HER2+), SKBR3 (Epithelial, Luminal, ER-/PR-/HER2+), MDA-MB-468 (Epithelial, Basal A, ER-/PR-/HER2-), MDA-MB-231 (Mesenchymal, Basal B, ER-/PR-/HER2-), MDA-MB-231-LM2 (Mesenchymal, Basal B, ER-/PR-/HER2-, a highly metastatic subpopulation 4175 from MDA-MB-231), and SUM159 (Mesenchymal, Basal B, ER-/PR-/HER2-) and one non-tumour cell line: MCF10A (Epithelial, Basal B, ER-/PR-/HER2-). We achieved a depth of over 8,000 proteins and a total of over 20,000 phosphopeptides with MS2 acquisition covering a wide range of biological processes. These eight lines encompass a wide range of genetic subtypes and have diverse morphologies in either 2D (epithelial vs mesenchymal), and/or in 3D environments (Mass, Grape-like, Stellate, Round) (Neve RM, 2006) (Kenny PA, 2007). The study also explored the effects of TGF-β1 during 10 days on the non-tumorigenic MCF10A cells, and their posterior washout and recovery for 40 days. TGF-β1 is a cytokine known to induce epithelial-to-mesenchymal transition (EMT), a process associated with cancer progression (Xu J, 2009) (Nieto, 2016). The data can be analysed in isolation or in combination with other orthogonal datasets such as transcriptomes or image-based data (OMICS), for the purpose of predicting tumour outcome, identifying markers, drug response or mechanisms of resistance to therapeutics. These data can provide insights for therapeutic strategies and better understanding of the diverse molecular landscapes of breast cancer cells.