We propose a new centrality measure, graphlet degree centrality (GDC), to simultaneously measure the density and complexity of a node's extended neighborhood by counting the number of different graphlets that the node touches. We find that: (1) the enrichments in BC genes are much higher for GDC-central genes than for non-GDC-central genes; (2) the observed enrichments are statistically significant for GDC-central genes, while for non-GDC-central genes they are not; (3) BC genes that are GDCcentral have higher and statistically significant enrichments in known drug targets than BC genes that are non-GDC-central; and (4) GDC outperforms other centrality measures in the sense that it uncovers the largest number of BC genes among the most central genes and is thus the most discriminative centrality measure.