High-throughput mass spectrometry and bioinformatics analysis of breast cancer proteomic data

• Published in: Data in brief Vol. 25; p. 104125
• Main Authors: Gomig, Talita Helen Bombardelli, Cavalli, Iglenir João, Souza, Ricardo Lehtonen Rodrigues de, Lucena, Aline Castro Rodrigues, Batista, Michel, Machado, Kelly Cavalcanti, Marchini, Fabricio Klerynton, Marchi, Fabio Albuquerque, Lima, Rubens Silveira, Urban, Cícero de Andrade, Cavalli, Luciane Regina, Ribeiro, Enilze Maria de Souza Fonseca
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.08.2019; Elsevier
• Subjects: Bioinformatics; Breast cancer; Contralateral non-tumor breast tissue; LC-ESI-MS/MS; Proteomics; Breast cancer; Bioinformatics; Contralateral non-tumor breast tissue; LC-ESI-MS/MS
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2019.104125

Data present here describe a comparative proteomic analysis among the malignant [primary breast tumor (PT) and axillary metastatic lymph nodes (LN)], and the non-tumor [contralateral (NCT) and adjacent (ANT)] breast tissues. Protein identification and quantification were performed through label-free mass spectrometry using a nano-liquid chromatography coupled to an electrospray ionization–mass spectrometry (nLC-ESI-MS/MS). The mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via PRIDE partner repository with the dataset identifier PXD012431. A total of 462 differentially expressed proteins was identified among these tissues and was analyzed in six groups' comparisons (named NCTxANT, PTxNCT, PTxANT, LNxNCT, LNxANT and PTxLN). Proteins at 1.5 log2 fold change were submitted to the Ingenuity® Pathway Analysis (IPA) software version 2.3 (QIAGEN Inc.) to identify biological pathways, disease and function annotation, and interaction networks related to cancer biology. The detailed data present here provides information about the proteome alterations and their role on breast tumorigenesis. This information can lead to novel biological insights on cancer research. For further interpretation of these data, please see our research article ‘Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer’ [2].