In typical coded caching scenarios, the content of a central library is assumed to be of interest to all receiving users. However, in a realistic scenario the users may have diverging interests which may intersect to various degrees. What happens for example if each file is of potential interest to, say, $40\,\%$ of the users and each user has potential interest in $40\,\%$ of the library? What if then each user caches selfishly only from content of potential interest? In this work, we formulate the symmetric selfish coded caching problem, where each user naturally makes requests from a subset of the library, which defines its own file demand set (FDS), and caches selfishly only contents from its own FDS. For the scenario where the different FDSs symmetrically overlap to some extent, we propose a novel information-theoretic converse that reveals, for such general setting of symmetric FDS structures, that selfish coded caching yields a load performance which is strictly worse than that in standard coded caching.