In addition to these predictors usually available in daily clinical practice, there are many others that are still in the research phase: HER2DX, a supervised learning algorithm incorporating tumor size, nodal staging, and four gene expression signatures tracking immune infiltration, tumor cell proliferation, luminal differentiation, the expression of the HER2 amplicon, into a single score [32], the value of tumor-infiltrating lymphocytes (TILs) [35], the oncogene bcl-2 [36], HER2/CEN17 ratio [37], androgen receptor [38], and even Machine Learning with MRI Radiomics [39]. This evidence concerns the gene ERBB2 and neoplasm.