Cache-enabled wireless networks have gained increasing popularity in recent years for facilitating the delivery of content. Most existing works assumed that the network is static without the change of users and content, which is not the case in the real world. In this paper, we study the content delivery in cache-enabled wireless networks, where the network evolves in terms of users and content. We adopt the affiliation network model to reveal the network evolution process, where new users and content are added into the network randomly and connected with existing nodes via the preferential attachment. Users with strong social relations tend to request the same content objects, thus content popularity is sharply concentrated. Therefore, caching technique is more effective. To maximize the content delivery rate, we formulate the optimization problem of caching replication jointly with routing strategy. We show that network evolution can greatly improve the content delivery rate. In particular, when per-user cache capacity is in the order of $\Theta (1)$ , per-user delivery rate can achieve constant, i.e., the network can scale. Finally, theoretical results are validated based on a real-world data set from Facebook.