Abstract P4-07-03: MicroRNAs correlating with outcome in patients treated with first-line bevacizumab for metastatic breast cancer
Authors: Simon P Gampenrieder, Frank Hamacher, Gabriel Rinnerthaler, Clemens Hufnagl, Hubert Hackl, Franz Romeder, Claudia Muß, Cornelia Hauser-Kronbeger, Brigitte Mlineritsch, Richard Greil
Journal: Cancer Research (2015)

Abstract Background: Biomarkers predicting response to bevacizumab containing therapy in breast cancer are of urgent need. MiRNAs, small non-coding RNAs, can be involved in tumor evolution including regulation of angiogenesis and development of treatment resistance. Therefore, miRNAs can provide both prognostic and predictive information in different cancer entities. Patients and methods: A genome-wide miRNA profiling using high-throughput TaqMan® Array Human MicroRNA Cards enabling quantification of 754 unique human miRNAs was performed. Formalin-fixed paraffin-embedded specimens from 60 patients treated with bevacizumab as first-line therapy at our institution were analyzed. Based on the median overall progression-free survival (PFS) patients were divided into a responder (G1) and a non-responder group (G2). Differentially expressed miRNAs were selected considering a more than two-fold change and a false discovery rate (FDR) &amp;lt; 10% as significant. Further interesting miRNAs were selected by a multivariate logistic regression approach using LASSO (Least Absolute Selection and Shrinkage Operator) regularization. Results: Overall median PFS was 9.3 months with a median PFS of 17.5 and 5.0 months in G1 and G2, respectively. Eight miRNAs (miR-19b-3p, miR-21-5p, miR-9-5p, miR-590-5p, miR-106b-5p, miR-20a-5p) were significantly differentially expressed between these groups (FDR &amp;lt; 10%). Their expression levels were all negatively associated with G1. Additionally, four miRNAs (miR-210-3p, miR-224-5p, miR-155-5p, miR-28-5p) might be interesting predictive biomarkers as they were included in a logistic regression classification model providing an optimal separation between responder and non-responder group (evident from the area under curve [AUC] and 100 x 5-fold cross validation). Currently these data is being validated in a patient cohort not treated with bevacizumab in order to detect the predictive value of these miRNAs for a bevacizumab-based treatment. These validated results will be presented at the meeting. Conclusion: Twelve miRNAs in breast cancer tissue could be identified showing promising predictive value for bevacizumab-based therapy. Although these data need to be confirmed, differences in miRNA expression could help identifying patients with greater benefit from anti-VEGF agents. Citation Format: Simon P Gampenrieder, Frank Hamacher, Gabriel Rinnerthaler, Clemens Hufnagl, Hubert Hackl, Franz Romeder, Claudia Muß, Cornelia Hauser-Kronbeger, Brigitte Mlineritsch, Richard Greil. MicroRNAs correlating with outcome in patients treated with first-line bevacizumab for metastatic 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 P4-07-03.