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. 2013 Apr 2;13:175.
doi: 10.1186/1471-2407-13-175.

Systematic Antibody Generation and Validation via Tissue Microarray Technology Leading to Identification of a Novel Protein Prognostic Panel in Breast Cancer

Free PMC article

Systematic Antibody Generation and Validation via Tissue Microarray Technology Leading to Identification of a Novel Protein Prognostic Panel in Breast Cancer

Patrick C O Leary et al. BMC Cancer. .
Free PMC article


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.


Figure 1
Figure 1
Expression of PBK, PDZK1 and ANLN protein in breast cancer. A: Western blot analysis of PBK, PDZK1 and ANLN protein expression across a panel of 7 breast cancer cell lines of varying invasive capabilities. ANLN antibody specificity also validated by shRNA-mediated knockdown (data not shown). B: Validation of the PBK and PDZK1 antibodies by immunohistochemistry in a panel of FFPE breast cancer cell lines (x20 magnification). The T47D, MDA-MB-231 and Hs578T (i8) cell lines are specifically shown. Antibody positivity is indicated by the brown DAB staining. C: Representative cores of ANLN, PDZK1 and PBK protein expression from the TMAs graded on a scale from 0 to 3+ for protein staining intensity. Vertical red line represents the cut-off between low and high protein expression for each biomarker.
Figure 2
Figure 2
Prognostic role of ANLN, PBK and PDZK1 at the protein and mRNA level in breast cancer. A: Kaplan-Meier curves demonstrating high expression of PBK and ANLN protein and low expression of PDZK1 protein associated with reduced BCSS. B: Kaplan-Meier curves demonstrating high expression of PBK and ANLN protein and low expression of PDZK1 protein associated with reduced RFS. C: Meta-analysis of publicly available transcriptomic data demonstrating high expression of the ANLN and PBK mRNA and low expression of PDZK1 mRNA associated with reduced RFS. P-value represents log-rank test.
Figure 3
Figure 3
Transcriptomic screen identifies three markers as a prognostic panel in breast cancer. Our three-marker model is associated with RFS at mRNA level using a meta-analysis of 10 independent transcriptomic datasets.
Figure 4
Figure 4
Novel 3-protein panel as a prognostic model in breast cancer. Kaplan-Meier curves demonstrating that the three-protein panel is associated with reduced RFS and BCSS; A: Individual scores and BCSS, B: Dichotimised panel and BCSS, C: Individual scores and RFS, D: Dichotimised panel and RFS.

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