(S043) RadiotypeDx: Validation of a Radiation Sensitivity Signature in Human Breast Cancer

Corey Speers, MD, PhD, O. Alejandro Balbin, PhD, Meilan Liu, MD, Prasanna Aluri, MD, PhD, Lori J. Pierce, MD, Felix Y. Feng, MD; Department of Radiation Oncology, Comprehensive Cancer Center, University of Michigan

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 < .05 and false discovery rate (FDR) of < 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 (n = 185 patients) 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 identified a range of radiation sensitivity in human BCC lines (SF 77%–17%) with no significant correlation (r value < .3) to the intrinsic BC subtype. Using Spearman’s correlation method, a total of 126 genes were identified as being associated with radiation sensitivity (72 positively correlated, 54 negatively correlated). Unsupervised hierarchical expression discriminated gene expression patterns in the RT-resistant and RT-sensitive cell lines and were 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 identified previously unreported radiation resistance genes, including TACC1 and RND3, with enhancement ratios of 1.25 and 1.37 in BCC lines, respectively. Application of this RS signature to an independent breast cancer dataset with clinical outcomes validated the signature and accurately identified patients with decreased rates of recurrence compared with patients with high expression of the radioresistant signature (P < .0001; misclassification error rate 0.31; 12/13 patients with locoregional recurrence accurately identified). This signature was then externally validated on another independent dataset of patients treated with adjuvant RT with locoregional recurrence data (P < .001; misclassification error rate 0.33; 26/28 patients with locoregional recurrence accurately identified).

Conclusion: In this study, we derived a human BC-specific RT sensitivity signature (RadiotypeDx) with biologic relevance from preclinical studies and validated this signature for prediction of recurrence in two independent clinical datasets. The signature is not correlated with 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.

Proceedings of the 96th Annual Meeting of the American Radium Society - americanradiumsociety.org