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4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer

De Marchi, Tommaso LU ; Liu, Ning Qing ; Stingl, Cristoph ; Timmermans, Mieke A ; Smid, Marcel ; Look, Maxime P. ; Tjoa, Mila ; Braakman, Rene B H ; Opdam, Mark and Linn, Sabine C. , et al. (2016) In Molecular Oncology 10(1). p.24-39
Abstract

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were... (More)

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker.

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publishing date
type
Contribution to journal
publication status
published
keywords
Antineoplastic Agents, Hormonal, Breast Neoplasms, Female, Humans, Middle Aged, Neoplasm Proteins, Neoplasm Recurrence, Local, Tamoxifen, Treatment Outcome
in
Molecular Oncology
volume
10
issue
1
pages
16 pages
publisher
Elsevier
external identifiers
  • scopus:84953368340
  • pmid:26285647
ISSN
1574-7891
DOI
10.1016/j.molonc.2015.07.004
language
English
LU publication?
no
id
75269d00-ab60-4974-8b59-8c3c13916a9d
date added to LUP
2017-06-27 14:31:38
date last changed
2024-04-14 13:15:39
@article{75269d00-ab60-4974-8b59-8c3c13916a9d,
  abstract     = {{<p>Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded &gt;3000 and &gt;4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker.</p>}},
  author       = {{De Marchi, Tommaso and Liu, Ning Qing and Stingl, Cristoph and Timmermans, Mieke A and Smid, Marcel and Look, Maxime P. and Tjoa, Mila and Braakman, Rene B H and Opdam, Mark and Linn, Sabine C. and Sweep, Fred C G J and Span, Paul N. and Kliffen, Mike and Luider, Theo M. and Foekens, John A. and Martens, John W. M. and Umar, Arzu}},
  issn         = {{1574-7891}},
  keywords     = {{Antineoplastic Agents, Hormonal; Breast Neoplasms; Female; Humans; Middle Aged; Neoplasm Proteins; Neoplasm Recurrence, Local; Tamoxifen; Treatment Outcome}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{24--39}},
  publisher    = {{Elsevier}},
  series       = {{Molecular Oncology}},
  title        = {{4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer}},
  url          = {{http://dx.doi.org/10.1016/j.molonc.2015.07.004}},
  doi          = {{10.1016/j.molonc.2015.07.004}},
  volume       = {{10}},
  year         = {{2016}},
}