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

被引:4
|
作者
Bombardelli Gomig, Talita Helen [1 ]
Cavalli, Iglenir Joao [1 ]
Rodrigues de Souza, Ricardo Lehtonen [1 ]
Rodrigues Lucena, Aline Castro [2 ]
Batista, Michel [2 ,3 ]
Machado, Kelly Cavalcanti [3 ]
Marchini, Fabricio Klerynton [2 ,3 ,4 ]
Marchi, Fabio Albuquerque
Lima, Rubens Silveira [5 ]
Urban, Cicero de Andrade [5 ]
Cavalli, Luciane Regina [6 ,7 ]
de Souza Fonseca Ribeiro, Enilze Maria [1 ]
机构
[1] Univ Fed Parana, Genet Dept, Curitiba, Parana, Brazil
[2] Carlos Chagas Inst, Funct Genom Lab, Curitiba, Parana, Brazil
[3] Carlos Chagas Inst, Mass Spectrometry Facil RPT02H, Curitiba, Parana, Brazil
[4] AC Camargo Canc Ctr, Int Res Ctr CIPE, Sao Paulo, SP, Brazil
[5] Hosp Nossa Senhora Gracas, Breast Dis Ctr, Curitiba, Parana, Brazil
[6] Res Inst Pele Pequeno Principe, Curitiba, Parana, Brazil
[7] Georgetown Univ, Lombardi Comprehens Canc Ctr, Washington, DC USA
来源
DATA IN BRIEF | 2019年 / 25卷
关键词
Breast cancer; Contralateral non-tumor breast tissue; LC-ESI-MS/MS; Bioinformatics;
D O I
10.1016/j.dib.2019.104125
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 ionizationemass 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 (R) 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 in-sights 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]. (c) 2019 The Author(s). Published by Elsevier Inc.
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页数:5
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