P4-09-12: Clinical Validation of Immunohistochemical Signature Predictive of Patients' 8 Year Outcome in Node Negative Breast Carcinomas.
Authors: Charpin C , Tavassoli F , Giusiano S , Secq V , Villeret J , Garcia S , Lavaut M-N , Bonnier P , Birnbaum D , Iovanna J 
Published: June 2012

Abstract
Background
Immunohistochemical (IHC) signatures predictive of prognosis can be a cost effective alternative to genomic signature suitable in clinical practice for patients’ management in early stages of breast carcinoma (BrCa) in clinical. IHC procedures are very easy to handle in pathology laboratories, since require very few amount of formalin fixed tissue samples since assessed on consecutive 4 μm thick sections of paraffin embedded tumors fragments validated by pathologists’ expertise. We recently reported (C Charpin et al Int J Cancer 2009) that standardized IHC assays using high throughput densitometry on digitized microscopic images allow to predict an adverse outcome of patients with BrCa, provided that identified the IHC predictive signatures can be validated in other patients’ cohorts. In this regard we have repeated our previously reported IHC procedures on 418 series of BrCa (Marseille University) on a second series including 303 BrCa diagnosed at Yale University.
Material and Methods: TMA(s) of two cohorts of patients with BrCa (418/Marseille University and 303 Yale University) were respectively investigated for immunohistochemical expression of 15 markers, including (i) those of the best signature predictive of patients outcome in N- patients in our previous studies and (ii) new markers reported in the literature as EMT cells and Stem cells. Monoclonal antibodies against HIFa, PI3, pAKT, pmTOR, moesin, P21, 4EBP-1, P27, Ker 5.6, pMAPKAPK-2, SHARP2, Claudin, ALDH, AF6, CD24, IHC was screened using standardized (Ventana Benchmark XT) on consecutive 4 μm thick sections of TMAs from both series, Quantitative measurements of immunoprecipitates were automatically assessed with TRIBVN device, and correlated to 8 year patients’ outcome. Logistic regression determined the best combination of markers to predict patients’ prognosis and results of the two cohorts were compared.
Results: In node negative BrCa the best predictive combination of markers signature was HIF-1a, PI3K, Claudin, AF6, pAKT independently of ER PR and HER-2 status. When results of logistic regression with these markers was compared very similar results were obtained with 92.34 % (333/418) of well classified patients in the first set (Marseille University series) and 89.8 % (158/176) in the second set from Yale University.
Discussion: The results suggest that the new optimal IHC signature predictive of prognosis identified in BrCa including HIF-1a, PI3K, Claudin, AF6 and pAKT is validated by this study with very similar results in two different cohorts of patients.
This validation also suggests (1) that IHC signatures investigated in individual patients can be considered as suitable in clinical practice offering a cost effective convenient mean to predict patients’ outcome at diagnostic time (2) and to select those patients with poor prognosis, particularly in N- BrCa subset, requiring more aggressive adjuvant therapies, and to avoid useless expensive therapies and their side effects in N- patients with favourable prognosis.
Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-09-12.