Unstructured peer-to-peer infrastructure has been widely employed to support large-scale distributed applications. Many of these applications, such as location-based services and multimedia content distribution, require the support of range selection queries. Under the widely adopted query shipping protocols, the cost of query processing is affected by the number of result copies or replicas in the system. Since range queries can return results that include poorly-replicated data items, the cost of these queries is usually dominated by the retrieval cost of these data items. In this work, we propose a popularity-aware prefetch-based approach that can effectively facilitate the caching of poorly-replicated data items that are potentially requested in subsequent range queries, resulting in substantial cost savings. We prove that the performance of retrieving poorly-replicated data items is guaranteed to improve under an increasing query load. Extensive experiments show that the overall range query processing cost decreases significantly under various query load settings.