Precision combination therapies from recurrent oncogenic co-alterations

Cancer cells rely on co-activation of oncogenic processes that are driven by co-occurring molecular aberrations. Combination therapies that target co-activated oncogenic processes can induce stronger and more durable responses compared to mono-therapies. Here, we developed REFLECT (REcurrent Features Leveraged for Combination Therapies) to match precision combination therapies to co-alteration signatures that are recurrent within patient cohorts. Using REFLECT, we generated a comprehensive resource mapping the actionable co-alteration signatures at DNA, mRNA and protein levels across more than 10,000 cancer patients and 199 cohorts. The patient cohorts are generated by stratifying the patient meta-cohort based on the existence of key oncogenic alterations. In the cohort of patients carrying potential immunotherapy markers, we identified distinct patient sub-cohorts that are enriched by actionable DNA repair aberrations, inflammation markers and B-cell presence. Through REFLECT analysis and validations in molecularly matched cell lines, we nominated HER2 and Aurora kinase inhibitors as effective in patients with mutations and HER2 activation. The analyses of DNA repair aberrations combined with validation experiments have identified recurrent molecular signatures that match effective combinations involving PARP, AKT, MET and other DNA repair pathway inhibitors. We expect REFLECT will facilitate the selection of effective combination therapies and benefiting patient cohorts matched to aberration signatures in preclinical and data-driven clinical trials.