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High‐throughput proteomic analysis of human infiltrating ductal carcinoma of the breast
Author(s) -
Somiari Richard I.,
Sullivan Anthony,
Russell Stephen,
Somiari Stella,
Hu Hai,
Jordan Rick,
George Alisha,
Katenhusen Richard,
Buchowiecka Alicja,
Arciero Cletus,
Brzeski Henry,
Hooke Jeff,
Shriver Craig
Publication year - 2003
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200300560
Subject(s) - proteomics , proteome , biology , mass spectrometry , breast cancer , tandem mass spectrometry , mass spectrometry imaging , computational biology , pathology , microbiology and biotechnology , cancer , chemistry , bioinformatics , medicine , biochemistry , chromatography , genetics , gene
Large‐scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high‐throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two‐dimensional difference gel electrophoresis (2‐D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non‐neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed ≥ three‐fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, ∼ 80% were unambiguously assigned identities by matrix‐assisted laser desorbtion/ionization‐time of flight mass spectrometry or liquid chromatography‐tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha‐1‐antitrypsin, heat shock protein‐60, cytokeratin‐18, transferrin, enolase‐1 and β‐actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein‐70 (more abundant) and peroxiredoxin‐2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2‐D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.