In current study, we introduce a novel diffusion-based 3D molecular generative model, called as Diff-Shape, for shape-controlled 3D molecule generation. By directly incorporating a pre-trained unconditional 3D molecule generative model and a graph control module taking reference shape as input, the condition guided diffusion process of molecular generation can be achieved. In several tasks including the shape-conditioned generation of chemically diverse molecular structures and the reference guided ligand generation for structure-based drug design, our results demonstrate that the Diff-Shape model can efficiently generate drug-like molecular conformations which has not only high 3D similarity to the reference shape but also possess reasonable chemical novelty compared to the reference structure.