Type

Journal Article

Authors

William M Gallagher
Donal J Brennan
Michael J Duffy
Goran Landberg
Sallyann L O'Brien
Darran P O'Connor
Karin Jirstrom
Elton Rexhepaj

Subjects

Microbiology

Topics
cytoplasm aged 80 and over sweden receptors progesterone estrogen receptor modulators inhibitor of apoptosis proteins image interpretation computer assisted predictive value of tests therapeutic use decision trees algorithms therapy adult humans tamoxifen kaplan meier estimate ki 67 antigen cell nucleus chi square distribution breast neoplasms receptor erbb 2 pattern recognition automated chemistry female risk assessment receptors estrogen treatment outcome tissue array analysis proportional hazards models erbb2 protein human aged birc5 protein human middle aged tumor markers biological mortality risk factors time factors microtubule associated proteins immunohistochemistry reproducibility of results

Validation of cytoplasmic-to-nuclear ratio of survivin as an indicator of improved prognosis in breast cancer. (2010)

Abstract Conflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients. Survin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression. Following optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018). Using the same threshold as our previous study, we have validated survivin CNR as a marker of good prognosis in breast cancer in a large independent cohort. These findings provide robust evidence of the importance of survivin CNR as a breast cancer biomarker, and its potential to predict outcome in tamoxifen-treated patients.
Collections Ireland -> University College Dublin -> PubMed

Full list of authors on original publication

William M Gallagher, Donal J Brennan, Michael J Duffy, Goran Landberg, Sallyann L O'Brien, Darran P O'Connor, Karin Jirstrom, Elton Rexhepaj

Experts in our system

1
William M Gallagher
University College Dublin
Total Publications: 148
 
2
Donal J Brennan
University College Dublin
 
3
Michael J Duffy
University College Dublin
 
4
Darran P O'Connor
Royal College of Surgeons in Ireland
Total Publications: 43
 
5
Karin Jirstrom
University College Dublin