Abstract P6-07-10: DNA methylation signature predicting bevacizumab efficacy in metastatic breast cancer
Authors: SP Gampenrieder, G Rinnerthaler, W Pulverer, A Weinhäusel, C Hufnagl, H Hackl, C Hauser-Kronberger, B Mlineritsch, R Greil
Journal: Cancer Research (2017)

Abstract Background: Biomarkers predicting response to bevacizumab containing therapy in breast cancer are still missing. Since epigenetic modifications can contribute to an aberrant regulation of angiogenesis and to treatment resistance, we investigated the influence of DNA methylation on bevacizumab efficacy. Patients and methods: A genome-wide methylation profiling using the Illumina Infinium HumanMethylation450 BeadChip was performed in archival FFPE specimen of 36 patients with HER2-negative metastatic breast cancer treated with chemotherapy in combination with bevacizumab as first-line therapy (learning set). Based on objective response and progression-free survival (PFS) and considering ER expression, patients were divided in responders (R) and non-responders (NR). Differentially methylated gene loci (methylation variable position = MVP) and differentially methylated regions (DMR) between R and NR were identified. Only significant sites with a strong change in methylation levels (Δβ&amp;gt;0.15 or Δβ&amp;lt;-0.15), an area under the curve of at least 0.85 by logistic regression analysis, and/or sites in proximity to genes functionally involved in angiogenesis and carcinogenesis were selected and further validated. Validation was performed in 81 bevacizumab treated breast cancer patients (validation set) and in 15 patients treated with chemotherapy only (control set) using targeted bisulfite sequencing. Methylated gene loci were considered predictive if there was a significant association with outcome (PFS) in the validation set but not in the control set using Spearman rank correlation, Cox regression, and logrank test. Results: In the learning set 435 MVPs (p&amp;lt;0.001) and 144 DMRs (adjusted combined p&amp;lt;0.0001 with at least 3 significant MVPs p&amp;lt;0.05 in the same region) showed significantly different methylation between R and NR. In R 152 sites were hypermethylated with a median change of methylation (Δβ) of 0.13; 283 sites were hypomethylated with a median Δβ of -0.09. A methylation signature of 48 genes was specified allowing a good separation between responders and non-responders (odds ratio=101, p&amp;lt;0.0001; data presented at the 38th SABCS 2015, P3-07-43). At least one methylated cytosine in close proximity to 24 of these genes showed a significant association with PFS in the validation set but was not (or in the other direction) in the control set. Based on these data the methylation signature predicting long lasting response to bevacizumab could be reduced to 24 genes including several genes involved in angiogenesis and carcinogenesis, respectively (FLT1 also known as VEGFR-1, MLH1, GNAS, APC, DKK3, WNT2B and COL4A1). Conclusion: A 24-gene methylation signature can reproducible discriminate between responders and non-responders to a bevacizumab-based therapy in breast cancer and could help to identify patients deriving greater benefit from anti-VEGF agents. Citation Format: Gampenrieder SP, Rinnerthaler G, Pulverer W, Weinhäusel A, Hufnagl C, Hackl H, Hauser-Kronberger C, Mlineritsch B, Greil R. DNA methylation signature predicting bevacizumab efficacy in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-07-10.