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We trained and evaluated predictive models for loss-of-function (LOF) of 145 individual DNA damage response genes based on genome-wide mutational patterns, including structural variants, indels, and base-substitution signatures. We identified 24 genes whose deficiency could be predicted with good accuracy, including expected mutational patterns for\n                    <jats:italic>BRCA1\/2<\/jats:italic>\n                    ,\n                    <jats:italic>MSH3\/6<\/jats:italic>\n                    ,\n                    <jats:italic>TP53<\/jats:italic>\n                    , and\n                    <jats:italic>CDK12<\/jats:italic>\n                    LOF variants.\n                    <jats:italic>CDK12<\/jats:italic>\n                    is associated with tandem duplications, and we here demonstrate that this association can accurately predict gene deficiency in prostate cancers (area under the receiver operator characteristic curve = 0.97). Our novel associations include mono- or biallelic LOF variants of\n                    <jats:italic>ATRX<\/jats:italic>\n                    ,\n                    <jats:italic>IDH1<\/jats:italic>\n                    ,\n                    <jats:italic>HERC2<\/jats:italic>\n                    ,\n                    <jats:italic>CDKN2A<\/jats:italic>\n                    ,\n                    <jats:italic>PTEN<\/jats:italic>\n                    , and\n                    <jats:italic>SMARCA4<\/jats:italic>\n                    , and our systematic approach yielded a catalogue of predictive models, which may provide targets for further research and development of treatment, and potentially help guide therapy.\n                  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