Abstract P2-09-02: Blinded molecular subtyping analysis from RNA-Seq of FFPE samples in the GeparQuinto trial reveals predictive value of VEGFA metagene for bevacizumab treatment

Abstract

Abstract Background: RNA-Seq from total RNA in FFPE tissue can be more challenging due to limited capture of partially degraded RNA. Exome-capture based RNA-Seq may circumvent such problems and allow reproducible complete molecular characterization of low-quality RNA from small clinical samples. Methods: HER2 negative patients within the GeparQuinto trial were treated with neoadjuvant anthracycline-taxane-based chemotherapy +/- bevacizumab. Patients with bevacizumab therapy had a significantly higher pCR rate, especially within the triple negative subgroup. We performed exome-capture RNA-Seq on 5µm FFPE sections from pre-therapeutic cores of 400 HER2 negative samples from this trial. In a prospectively planned, blinded study we correlated molecular subtypes and metagenes for proliferation, stroma, MHC2, and VEGFA with clinical and histopathological data. Molecular subtypes were defined using the AIMS methods. Metagenes were calculated as mean values corresponding to previously described gene clusters after platform transfer (Rody et al. 2011 PMID 21978456, Hu et al. 2009 PMID 19291283) and then z-transformed. Results: 296 samples with RNA-Seq data were classified as either of high (n=226) or of limited quality (n=70). For 22 samples RNA yield was insufficient and 82 did not pass initial QC. 121 (41%), 63 (21%), 34 (11.5%), 46 (15.5%), and 32 (11%) samples were defined as basal-like, HER2-enriched, luminal A, luminal B, and normal-like, respectively. Subtyping was robust with regard to gene filtering, normalization, and sample quality. ER and PR status from local IHC strongly correlated with gene expression (overall correctness 84% and 80% for ER, and 85% and 74% for PR, in samples with high and limited quality, respectively) and luminal subtypes (95% ER positive). Proliferation metagene correlated with histological grade (median -0.73, -0.39, and 0.53 in G1, G2, and G3, respectively; P<0.001) and MHC2 metagene correlated strongly with TIL counts (Rho=0.53, P<0.001). Among the high quality samples response rates (49.3% pCR overall) differed significantly by subtype, with higher pCR rates in basal-like (68.9%) and HER2-enriched (45.5%) than in luminal B (35.7%), luminal A (17.9%), and normal-like (20.0%). MHC2- (OR 1.60, 95%CI 1.21-2.12, P=0.001), proliferation- (OR 2.88, 95%CI 2.00-4.16, P<0.001), and VEGFA-metagenes (OR 1.92, 95%CI 1.41-2.60, P<0.001) were significant predictors for pCR. In a multivariate logistic regression (adjusted for bevacizumab treatment and hormone receptor status) both VEGFA metagene (OR 2.59, 95%CI 1.40-4.77, P=0.002) and the interaction between the VEGFA-metagene and bevacizumab treatment arm (P=0.023) significantly predicted pCR. Conclusions: Exome-capture RNA-Seq allows robust genomic characterization of clinical samples with limited FFPE material from core biopsies, and molecular subtypes and immune metagenes are predictive for pCR. The VEGFA metagene is a specific predictor for response to neoadjuvant bevacizumab treatment. Citation Format: Karn T, Meissner T, Weber K, Sinn B, Denkert C, Budczies J, Nekljudova V, Fasching PA, Holtrich U, Schem C, Solbach C, Hartmann A, Röcken C, Untch M, Young BM, Willis S, Leyland-Jones B, von Minckwitz G, Loibl S. Blinded molecular subtyping analysis from RNA-Seq of FFPE samples in the GeparQuinto trial reveals predictive value of VEGFA metagene for bevacizumab treatment [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-09-02.