The concept that genetic/genomic alterations (either DNA sequence or subsequent expression) may function as surrogate biomarkers of disease response or normal tissue toxicity underpins the field of radiogenomics (Rosenstein 2017). Prior to the genomics era, and for over half a century, research aimed at predicting tumor and normal tissue response to radiation was dominated by in vitro culture of malignant and normal cells (Fertil and Malaise 1981; West et al. 1991; Burnet et al. 1992; Geara et al. 1993; Steel 1993; Johansen 202et al. 1994; Begg et al. 1999). Although beyond the scope of this chapter, these experiments provided the foundation upon which the linear quadratic model was derived, but the methods had a limited ability to adequately and reliably model the heterogeneous response of tumors and normal tissue to ionizing radiation. With advances in knowledge enabled in part through the human genome project, investigators identified more sophisticated ways of both describing and predicting radiotherapy responses. This advance, coupled with technological advances that allow for a more complete evaluation of DNA, RNA, protein, and cellular metabolism, has led to the development of “omics”-based approaches for prediction of radiotherapy outcomes (Torres-Roca et al. 2005; Weichselbaum et al. 2008; Eschrich et al. 2009, 2012; Servant et al. 2012; Speers et al. 2015; Yard et al. 2016; Zhao et al. 2016; Scott et al. 2017).