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Systematic antibody generation and validation via tissue microarray technology leading to identification of a novel protein prognostic panel in breast cancer

O'Leary, Patrick C.; Penny, Sarah A.; Dolan, Roisin T.; Kelly, Catherine M.; Madden, Stephen F.; Rexhepaj, Elton; Brennan, Donal J.; McCann, Amanda H.; Ponten, Fredrik and Uhlen, Mathias, et al. (2013) In BMC Cancer 13.
Abstract
Background: Although omic-based discovery approaches can provide powerful tools for biomarker identification, several reservations have been raised regarding the clinical applicability of gene expression studies, such as their prohibitive cost. However, the limited availability of antibodies is a key barrier to the development of a lower cost alternative, namely a discrete collection of immunohistochemistry (IHC)-based biomarkers. The aim of this study was to use a systematic approach to generate and screen affinity-purified, mono-specific antibodies targeting progression-related biomarkers, with a view towards developing a clinically applicable IHC-based prognostic biomarker panel for breast cancer. Methods: We examined both in-house and... (More)
Background: Although omic-based discovery approaches can provide powerful tools for biomarker identification, several reservations have been raised regarding the clinical applicability of gene expression studies, such as their prohibitive cost. However, the limited availability of antibodies is a key barrier to the development of a lower cost alternative, namely a discrete collection of immunohistochemistry (IHC)-based biomarkers. The aim of this study was to use a systematic approach to generate and screen affinity-purified, mono-specific antibodies targeting progression-related biomarkers, with a view towards developing a clinically applicable IHC-based prognostic biomarker panel for breast cancer. Methods: We examined both in-house and publicly available breast cancer DNA microarray datasets relating to invasion and metastasis, thus identifying a cohort of candidate progression-associated biomarkers. Of these, 18 antibodies were released for extended analysis. Validated antibodies were screened against a tissue microarray (TMA) constructed from a cohort of consecutive breast cancer cases (n = 512) to test the immunohistochemical surrogate signature. Results: Antibody screening revealed 3 candidate prognostic markers: the cell cycle regulator, Anillin (ANLN); the mitogen-activated protein kinase, PDZ-Binding Kinase (PBK); and the estrogen response gene, PDZ-Domain Containing 1 (PDZK1). Increased expression of ANLN and PBK was associated with poor prognosis, whilst increased expression of PDZK1 was associated with good prognosis. A 3-marker signature comprised of high PBK, high ANLN and low PDZK1 expression was associated with decreased recurrence-free survival (p < 0.001) and breast cancer-specific survival (BCSS) (p < 0.001). This novel signature was associated with high tumour grade (p < 0.001), positive nodal status (p = 0.029), ER-negativity (p = 0.006), Her2-positivity (p = 0.036) and high Ki67 status (p < 0.001). However, multivariate Cox regression demonstrated that the signature was not a significant predictor of BCSS (HR = 6.38; 95% CI = 0.79-51.26, p = 0.082). Conclusions: We have developed a comprehensive biomarker pathway that extends from discovery through to validation on a TMA platform. This proof-of-concept study has resulted in the identification of a novel 3-protein prognostic panel. Additional biochemical markers, interrogated using this high-throughput platform, may further augment the prognostic accuracy of this panel to a point that may allow implementation into routine clinical practice. (Less)
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keywords
Prognostic biomarkers, Tissue microarray, Breast cancer, Antibody, screening, Antibody validation
in
BMC Cancer
volume
13
publisher
BioMed Central
external identifiers
  • wos:000319663400001
  • scopus:84875491295
ISSN
1471-2407
DOI
10.1186/1471-2407-13-175
language
English
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yes
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11142abc-0ae1-4ba9-8f44-2b88da2a4081 (old id 3931237)
date added to LUP
2013-08-01 07:38:42
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2019-01-13 04:54:51
@article{11142abc-0ae1-4ba9-8f44-2b88da2a4081,
  abstract     = {Background: Although omic-based discovery approaches can provide powerful tools for biomarker identification, several reservations have been raised regarding the clinical applicability of gene expression studies, such as their prohibitive cost. However, the limited availability of antibodies is a key barrier to the development of a lower cost alternative, namely a discrete collection of immunohistochemistry (IHC)-based biomarkers. The aim of this study was to use a systematic approach to generate and screen affinity-purified, mono-specific antibodies targeting progression-related biomarkers, with a view towards developing a clinically applicable IHC-based prognostic biomarker panel for breast cancer. Methods: We examined both in-house and publicly available breast cancer DNA microarray datasets relating to invasion and metastasis, thus identifying a cohort of candidate progression-associated biomarkers. Of these, 18 antibodies were released for extended analysis. Validated antibodies were screened against a tissue microarray (TMA) constructed from a cohort of consecutive breast cancer cases (n = 512) to test the immunohistochemical surrogate signature. Results: Antibody screening revealed 3 candidate prognostic markers: the cell cycle regulator, Anillin (ANLN); the mitogen-activated protein kinase, PDZ-Binding Kinase (PBK); and the estrogen response gene, PDZ-Domain Containing 1 (PDZK1). Increased expression of ANLN and PBK was associated with poor prognosis, whilst increased expression of PDZK1 was associated with good prognosis. A 3-marker signature comprised of high PBK, high ANLN and low PDZK1 expression was associated with decreased recurrence-free survival (p &lt; 0.001) and breast cancer-specific survival (BCSS) (p &lt; 0.001). This novel signature was associated with high tumour grade (p &lt; 0.001), positive nodal status (p = 0.029), ER-negativity (p = 0.006), Her2-positivity (p = 0.036) and high Ki67 status (p &lt; 0.001). However, multivariate Cox regression demonstrated that the signature was not a significant predictor of BCSS (HR = 6.38; 95% CI = 0.79-51.26, p = 0.082). Conclusions: We have developed a comprehensive biomarker pathway that extends from discovery through to validation on a TMA platform. This proof-of-concept study has resulted in the identification of a novel 3-protein prognostic panel. Additional biochemical markers, interrogated using this high-throughput platform, may further augment the prognostic accuracy of this panel to a point that may allow implementation into routine clinical practice.},
  author       = {O'Leary, Patrick C. and Penny, Sarah A. and Dolan, Roisin T. and Kelly, Catherine M. and Madden, Stephen F. and Rexhepaj, Elton and Brennan, Donal J. and McCann, Amanda H. and Ponten, Fredrik and Uhlen, Mathias and Zagozdzon, Radoslaw and Duffy, Michael J. and Kell, Malcolm R. and Jirström, Karin and Gallagher, William M.},
  issn         = {1471-2407},
  keyword      = {Prognostic biomarkers,Tissue microarray,Breast cancer,Antibody,screening,Antibody validation},
  language     = {eng},
  publisher    = {BioMed Central},
  series       = {BMC Cancer},
  title        = {Systematic antibody generation and validation via tissue microarray technology leading to identification of a novel protein prognostic panel in breast cancer},
  url          = {http://dx.doi.org/10.1186/1471-2407-13-175},
  volume       = {13},
  year         = {2013},
}