Recently, there has been an increased interest in incorporating in database management systems rank-aware query operators, such as top-k queries, that allow users to retrieve only the most interesting data objects. In this paper, we propose a cache-based approach for efficiently supporting top-k queries in distributed database management systems. In large distributed systems, the query performance depends mainly on the network cost, measured as the number of tuples transmitted over the network. Ideally, only the k tuples that belong to the query result set should be transmitted. Nevertheless, a server cannot decide based only on its local data which tuples belong to the result set. Therefore, in this paper, we use caching of previous results to reduce the number of tuples that must be fetched over the network. To this end, our approach always delivers as many tuples as possible from cache and constructs a remainder query to fetch the remaining tuples. This is different from the existing distributed approaches that need to re-execute the entire top-k query when the cached entries are not sufficient to provide the result set. We demonstrate the feasibility and efficiency of our approach through implementation in a distributed database management system.