Abstract P6-06-05: RadiotypeDx: Identification and validation of a radiation sensitivity signature in human breast cancer
Authors: Speers C , Balbin OA , Liu M , Alluri P , Pierce L , Feng F 
Published: August 2014

Abstract
Purpose: An unmet clinical need in breast cancer (BC) management is the identification of which patients will respond to radiation therapy (RT). We hypothesized that the integration of post-RT clonogenic survival data with gene expression data across a large spectrum of BC cell lines would generate a BC-specific RT sensitivity signature predictive for RT response in BC patients and allow identification of patients with tumors refractive to conventional therapy.
Methods: Using clonogenic survival assays, we identified the range of surviving fraction (SF) after 2 Gy of RT across 21 BC cell lines. Using SF as a continuous variable, the RT sensitivity score (RSS) was correlated to gene expression using a Spearman correlation method on an individual gene basis. Genes were selected for the signature based on positive or negative correlation with a p-value &lt;0.05 and FDR of &lt;0.01. Unsupervised hierarchical clustering identified differences in gene expression across resistant and sensitive cell lines to generate a radiation sensitivity (RS) signature. This signature was trained and validated in a separate human breast tumor dataset (185 pts) containing early stage, node-negative patients treated with surgery and RT alone without adjuvant chemotherapy to assess the predictive effect of RS signature on recurrence risk after RT. Gene function and potentially actionable targets from the signature were validated using clongenic survival and DNA damage assays.
Results: Clonogenic survival identifies a range of radiation sensitivity in human BCC lines (SF 77%-17%) with no significant correlation (r value &lt;0.3) to the intrinsic BC subtype. Using Spearmans correlation method, a total of 126 genes were identified as being associated with radiation sensitivity (72 positively correlated, 54 negatively correlated). Unsupervised hierarchical expression discriminates gene expression patterns in the RT resistant and RT sensitive cell lines and is enriched for genes involved in cell cycle arrest and DNA damage response (enrichment p-value 5.0 E-22). Knockdown of genes associated with the radioresistance signature identifies previously unreported radiation resistance genes, including TACC1 and RND3 with enhancement ratios of 1.25 and 1.37 in BCC lines. Application of this RS signature to an independent breast cancer dataset with clinical outcomes validates the signature and accurately identifies patients with decreased rates of recurrence compared to patients with high expression of the radioresistant signature (p-value &lt;0.0001, misclassification error rate .31, 12/13 patients with locoregional recurrence accurately identified).
Conclusion: In this study, we derive a human BC-specific RT sensitivity signature (RadiotypeDx) with biologic relevance from preclinical studies and validate this signature for prediction of recurrence in an independent clinical dataset. The signature is not correlated to the intrinsic subtypes of human breast cancer and thus provides useful information beyond traditional breast cancer subtyping. By identifying patients with tumors refractory to standard RT, this signature has the potential to allow for personalization of radiotherapy, particularly in patients for whom treatment intensification is needed.
Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-06-05.