VIST - A Variant-Information Search Tool for Precision Oncology Diagnosis and treatment decisions in cancer increasingly depend on the analysis of the mutational status of a patient’s genome. Such analysis, involving sequencing a cancer gene panel or entire exomes, produces an (long) list of individual variants. Variants must be assessed and prioritized, using medical doctor personal experience and published evidences of the clinical relevance of the respective variant in the present cancer type. Evidences are typically gathered through web-based search engines like PubMed. The experts typically need to scan hundreds of abstracts and papers to identify those which are relevant in the particular case. This can easily take days in case of long variant lists or well-researched variants. We present Variant Information Search Tool (VIST), a search engine designed to speed-up this process by allowing a targeted search for clinically relevant publications given a list of genes or variants and a particular cancer entity. VIST indexes all PubMed abstracts, uses machine-learning based scores to judge the relevancy of documents, and applies advanced text mining to identify mentions of genes and variants. The server accepts as query (1) a (list of) gene names and / or variants in HGVS notation, (2) a cancer type (optional), and (3) result filter for journal names and range of publication years (optional). The server returns a list of PubMed abstracts ranked by clinical relevance of the abstract with respect to the query. A systematic evaluation with different queries involving several medical experts showed the superiority of this approach compared to less specialized search engines.