We present Innate Immune Function (IIF) profiling metrics derived from whole exome sequencing (WES) of cancer genomes that can be used to improve the ability of oncologists to predict the efficacy of cancer treatment regimes. These include drugs (or drug combinations) designed for hormone therapy or targeted checkpoint immunotherapies. They include classes of drugs and proteins (monoclonal antibodies) that are specific for markers associated with different types of cancer. These all work by exploiting the immune system to treat cancer through several mechanisms. The genomic IIF profile is predicated upon our growing understanding of the relationship between the highly targeted and regulated nature of processes involving endogenous cytosine (C-site) and adenosine (A-site) deaminases (APOBEC/ADAR) that are crucial for Innate Immune system processes viz. the mutagenic targeting early in infections of the DNA and RNA genomes of pathogens. When such deamination activities are dysregulated, they often target host cell genomes leading to the accumulation of many unwanted mutations, and thus eventually to the potential for full blown cancer. We have found that abnormal variations in various C-site and A-site IIF profiling metrics associated with deaminase activity (i.e. outside of the calculated range intervals for ‘normals’, or ‘responders’), provide an excellent indicator of whether or not a particular patient will respond to immunotherapy. Using mutation data from several clinical trials, we provide IIF profile examples to predict patient response to: Pembrolizumab (Keytruda), PD-1 blockade, in non-small cell carcinoma of lung [1]; Atezolizumab (Tecentriq), PD-L1 blockade, for metastatic urothelial cancer [2]; Trastuzumab (Herceptin), HER2/neu, for HER2+ve breast cancer [3]; Asatinib, ErB family inhibitor for HER2+ve inflammatory breast cancer [4]; and, Ipilimumab (Yervoy), CTLA-4 blockade in metastatic melanoma [5]. We show that IIF profiling using WES data is effective at differentiating between Responders and Non-Responders for a particular treatment, and that the personal profile of a patient provides clinicians with additional information that can help to guide further care.