Development and Validation of a Novel Radiosensitivity Signature in Human Breast Cancer

Abstract

Purpose: An unmet clinical need in breast cancer management is the accurate identification of patients who will benefit from adjuvant radiotherapy. We hypothesized that integration of postradiation clonogenic survival data with gene expression data across breast cancer cell (BCC) lines would generate a radiation sensitivity signature (RSS) and identify patients with tumors refractive to conventional therapy.Experimental Design: Using clonogenic survival assays, we identified the surviving fraction (SF-2Gy) after radiation across a range of BCC lines. Intrinsic radiosensitivity was correlated to gene expression using Spearman correlation. Functional analysis was performed in vitro, and enriched biologic concepts were identified. The RSS was generated using a Random Forest model and was refined, cross-validated, and independently validated in additional breast cancer datasets.Results: Clonogenic survival identifies a range of radiosensitivity in human BCC lines (SF-2Gy 77%-17%) with no significant correlation to the intrinsic breast cancer subtypes. One hundred forty-seven genes were correlated with radiosensitivity. Functional analysis of RSS genes identifies previously unreported radioresistance-associated genes. RSS was trained, cross-validated, and further refined to 51 genes that were enriched for concepts involving cell-cycle arrest and DNA damage response. RSS was validated in an independent dataset and was the most significant factor in predicting local recurrence on multivariate analysis, outperfoming all clinically used clinicopathologic features.Conclusions: We derive a human breast cancer-specific RSS with biologic relevance and validate this signature for prediction of locoregional recurrence. By identifying patients with tumors refractory to standard radiation this signature has the potential to allow for personalization of radiotherapy.

IQGAP3 Overexpression Correlates with Poor Prognosis and Radiation Therapy Resistance in Breast Cancer

“…Despite great progress in RT over recent years, locoregional recurrence and distant metastasis after RT remain key problems decreasing the survival of breast cancer patients [2]. Locoregional recurrence results from the presence or evolution of radioresistant tumor cells for which standard fractionated RT doses are sublethal[3]. Currently, there is a dearth of clinically available predictive biomarkers to indicate the optimal radiation dosing in breast cancer, which leads to suboptimal treatment of these patients[4].…”

Radiogenomics and radiotherapy response modeling

“…Ten-year receiver operating characteristic (ROC) curves (A) and Kaplan–Meier survival estimate (B) analysis in validation dataset of radiosensitivity in breast cancer using random forest machine learning (Speers et al , 2015). …”

Paradigm Shift From Halstedian Radical Mastectomy to Personalized Medicine

“…However, locoregional recurrence rate differs by molecular subtypes, and triple negative and HER2-enriched subtypes have a higher risk of loco-regional recurrence despite radiotherapy (33). While there is an absolute need for greater precision in prescribing radiotherapy in patients with breast cancer, Speers and his colleagues formulated a molecular signature of radiation response from in vitro studies, and they found that there was no relationship between radiosensitivity and molecular subtype (34). Radiotherapy needs to be tailorable to tumour biology ranging from no treatment to partial breast irradiation and loco-regional irradiation, even including the internal mammary chain (35).…”