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Poster lunch

1598 - Next generation Proteomic profiling to predict the response to neoadjuvant chemotherapy in breast cancer (28P)


18 Nov 2017


Poster lunch


Cytotoxic Therapy;  Translational Research;  Breast Cancer


HanSuk Ryu


Annals of Oncology (2017) 28 (suppl_10): x7-x15. 10.1093/annonc/mdx653


H. Ryu1, D. Han2

Author affiliations

  • 1 Pathology, Seoul National University Hospital (SNUH)-Yongon Campus, 110-744 - Seoul/KR
  • 2 Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul/KR


Abstract 1598


Since GEPARDUO trial reported the therapeutic benefit of combined doxorubicin and cyclophosphamide regimen in sequential administration with docetaxel, the combination regimen has become a standard therapeutic strategy in neoadjuvant systemic therapy for patients with operable breast cancers. However, pathologic complete response (pCR) rate is still low, ranging from 28% to 47%. Therefore, the need for a marker predictive of response to a particular cytotoxic regimen, especially before neoadjuvant chemotherapy, is becoming all the more necessary to optimize therapeutic efficacy and to avoid unnecessary complications caused by systemic therapy. Various predictive models and parameters for chemotherapeutic response have been reported thus far, especially based on transcriptional gene signatures; however, there remain difficulties employing them in routine practice due to lack of consistency and reproducibility caused by tumor heterogeneity, in breast cancer. The rapid advances of proteomic technologies with computational algorithms and biochemical technologies have recently enabled quantitative analyses to evaluate novel diagnostic markers’ discovery in practical quantities of tumor tissues.


We performed high-throughput proteomics in twenty paired core needle biopsy samples with operable breast cancer who received preoperative NAC followed by surgical resection. All samples were analyzed by in-depth quantitative protomics mass spectrometry (MS) to indicate differentially expressed proteins (DEP) between two groups.


MS data were analyzed using a combination of MaxQuant and Perseus computational platform, and a total of 6,900 proteins were identified identified and 254 DEP were confirmed to be significantly altered proteins related to chemotherapeutic response.


To our knowledge, the present study provides the first evidence to identify a predictive biomarker for chemotherapeutic response based on in-depth proteomics.

Clinical trial identification

Legal entity responsible for the study





All authors have declared no conflicts of interest.

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