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Poster lunch

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

Date

18 Nov 2017

Session

Poster lunch

Presenters

HanSuk Ryu

Citation

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

Authors

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
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Resources

Abstract 1598

Background

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.

Methods

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.

Results

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.

Conclusions

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

N/A

Funding

None

Disclosure

All authors have declared no conflicts of interest.

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