期刊
BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS
卷 1865, 期 5, 页码 488-498出版社
ELSEVIER
DOI: 10.1016/j.bbapap.2017.02.012
关键词
Breast cancer; Selected reaction monitoring; mTRAQ; Estrogen receptor; Tumor grade; Lymph node
资金
- Czech Science Foundation [1419250S]
- MH CZ-DRO (MMCI) [00209805]
- Ministry of Education, Youth and Sports of the Czech Republic
- Proteomics Core Facility of CEITEC [LM2015043]
- [MEYS-NPS I-L01413]
Breast cancer is the most common and molecularly relatively well characterized malignant disease in women, however, its progression to metastatic cancer remains lethal for 78% of patients 5 years after diagnosis. Novel markers could identify the high risk patients and their verification using quantitative methods is essential to overcome genetic, inter-tumor and intra-tumor variability and translate novel findings into cancer diagnosis and treatment. We recently identified 13 proteins associated with estrogen receptor, tumor grade and lymph node status, the key factors of breast cancer aggressiveness, using untargeted proteomics. Here we verified these findings in the same set of 96 tumors using targeted proteomics based on selected reaction monitoring with mTRAQ labeling (mTRAQ-SRM), transcriptomics and immunohistochemistry and validated in 5 independent sets of 715 patients using transcriptomics. We confirmed: (i) positive association of anterior gradient protein 2 homolog (AGR2) and periostin (POSTN) and negative association of annexin Al (ANXA1) with estrogen receptor status; (ii) positive association of stathmin (STMN1), cofilin-1 (COF1), plasminogen activator inhibitor 1 RNA-binding protein (PAIRBPI) and negative associations of thrombospondin-2 (TSP2) and POSTN levels with tumor grade; and (iii) positive association of POSTN, alpha-actinin-4 (ACTN4) and STMN1 with lymph node status. This study highlights a panel of gene products that can contribute to breast cancer aggressiveness and metastasis, the understanding of which is important for development of more precise breast cancer treatment (C) 2017 Elsevier B.V. All rights reserved.
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