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Label‐Free Quantitative Proteomic Screening of Candidate Plasma Biomarkers for the Prognosis of Breast Cancer with Different Lymph Node Statuses
Author(s) -
Chen Ling,
Zhao Weibo,
He Jing,
Li Liqi,
Meng Dong,
Cai Dongyan,
Yu Jinjin,
Chen Daozhen,
Wu Yibo,
Zhou Tao
Publication year - 2018
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.201700117
Subject(s) - breast cancer , lymph node , medicine , lymph , metastasis , oncology , cancer , biomarker , proteome , lymph node metastasis , bioinformatics , pathology , biology , biochemistry
Purpose Lymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2‐positive patients. Since patients with lymph node involvement has less favorable prognosis and higher risk of recurrence, it is important to develop plasma protein biomarkers for distinguishing lymph node metastasis. Experimental design A label‐free quantitative proteomic strategy to construct plasma proteomes of ten patients with small size HER2‐positive breast cancer (five patients with lymph node metastasis versus five patients without lymph node metastasis) is applied. Results A total of 388 proteins are identified, of which 33 proteins are differentially expressed. Statistical analyses suggested the present strategy is low cost and highly efficient in initial screening of plasma biomarkers. In silico analyses using various bioinformatics databases show that these altered proteins are highly associated with breast disease, cancer pathway, lymph node morphology, metastasis, complement pathway, and immune regulation. Conclusions and clinical relevance The present dataset provides a list of candidate biomarkers that could be used for early differentiation diagnosis and prognosis of breast cancer with lymph node metastasis.