WGCNA co-expression network analysis with less than 20 samples
It's hard to say without knowing how different the subtypes are. If you do a common WGCNA, you may find modules related to the differences between A and B as well as to drivers of expression variation in A and B (common and separate). Since A has fewer samples, the variation will have to be stronger to be reflected by WGCNA modules. 

You can run the WGCNA, find modules that vary the most in A samples (these may or may not also vary in B samples), then see whether LncRNAs belong to these modules and have a high kME (module membership).