Abstract S2-01: Theranostic multiparametric tests improve residual risk assessment in early luminal breast cancer

Abstract

Abstract Background: Despite rapidly expanding availability of multiparametric tests which inform residual risk following adjuvant therapy for early breast cancer current approaches provide minimal information on the appropriate targeted therapy to be selected for patients at high risk of recurrence. We hypothesised that inclusion of key signalling nodes from driver molecular pathways in early breast cancer in residual risk signatures would both improve risk stratification and identify candidate theranostic targets for the next generation of clinical trials. Methods: RNA was extracted from FFPE luminal breast cancers from the TEAM pathology study (Exemestane versus Tamoxifen-Exemestane). Gene expression analyses were performed for 29 genes mapped across key signalling nodes within the PIK3CA pathway. mRNA assessment for IHC4 (ER, PgR, HER2 and Ki67) was included in the model. Quantitative gene expression was performed using the Nanostring platform. Novel signatures were trained in a randomly selected sub-set of the TEAM pathology cohort (n=˜1700) and validated using the remaining 50% of patients (n=˜1700). Results presented represent those from the validation cohort. Results: The IHC4-protein and IHC4-mRNA risk scores were highly correlated (Rho=0.72, p=4.12x10-265), suggesting the mRNA abundance-based classifier is able to serve as a good substitute for the protein-based model. A gene signature including IHC4 markers assessed by mRNA performed significantly better (AUC 0.70 vs 0.66) than conventional IHC4. A gene signature including 4 signalling modules from the PIK3CA pathway significantly outperformed both IHC4 and the 4 gene (ER, PgR, HER2, Ki67) classifier (AUC 0.75; p = 3.23x10-7 vs IHC4 and 1.39x10-3 vs "IHC4mRNA"). Conclusions: Inclusion of PIK3CA signalling modules identified key genes/nodes which are linked to early relapse in luminal breast cancer and provided a significantly improvement in risk classification when compared to a currently validated multiparameter test. Citation Format: John MS Bartlett, Vicky S Sabine, Syed Haider, Camilla Drake, Cheryl Crozier, Cindy Q Yao, Cassandra L Brookes, Cornelis JH van de Velde, Annette Hasenburg, Dirk G Kieback, Christos Markopoulos, Luc Y Dirix, Caroline Seynaeve, Daniel W Rea, Paul C Boutros. Theranostic multiparametric tests improve residual risk assessment in early luminal breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S2-01.