Cositecan

As part of continuing our research on diverse C-7 derivatives of camptothecin (CPT), 16 CPT derivatives bearing piperazinyl-thiourea chemical scaffold and different substituent groups have been designed, synthesized and evaluated in vitro for cytotoxicity against five tumor cell lines (A-549, MDA-MB-231, MCF-7, KB and KBvin). As a result, all the synthesized compounds showed promising in vitro cytotoxic activity against the five tumor cell lines tested, and were more potent than irinotecan. Importantly, compounds 13 g (IC₅₀ = 0.514 μM) and 13o (IC₅₀ = 0.275 μM) possessed similar or better antiproliferative activity against the multidrug-resistant (MDR) KBvin subline than that of topotecan (IC₅₀ = 0.511 μM) and merit further development as anticancer candidates for clinical trail. With these results in hand, we have a reason to conclude that incorporating piperazinyl-thiourea motifs into position-7 of camptothecin confers well cytotoxic activity against cancer cell lines, probably resulting in new anticancer drugs.

Repurposing of drugs to novel disease indications has promise for faster clinical translation. However, identifying the best drugs for a given pathological context is not trivial. We developed an integrated random walk-based network framework that combines functional biomolecular relationships and known drug–target interactions as a platform for contextual prioritization of drugs, genes and pathways. We show that the use of gene-centric or drug-centric data, such as gene expression data or a phenotypic drug screen, respectively, within this network platform can effectively prioritize drugs and pathways, respectively, to the studied biological context. We demonstrate that various genomic data can be used as contextual cues to effectively prioritize drugs to the studied context, while similarly, phenotypic drug screen data can be used to effectively prioritize genes and pathways to the studied phenotypic context. As a proof-of-principle, we showcase the use of our platform to identify known and novel drug indications against different subsets of breast cancers through contextual prioritization based on genome-wide gene expression, shRNA and drug screen and clinical survival data. The integrated network and associated methods are incorporated into the NetWalker suite for functional genomics analysis (http://netwalkersuite.org).