Topoisomerase I (TOP1) enzymes are essential in higher eukaryotes, as they are required to relax DNA supercoiling generated by transcription, replication and chromatin remodelling. Topoisomerases are particularly vulnerable to topoisomerase I inhibitors during their cleavage reaction, which is referred to as the 'cleavage complex'. TOP1 can be trapped by anticancer drugs as it cleaves DNA. Moreover, TOP1 can be trapped by endogenous alterations to DNA (mismatches, abasic sites, nicks and adducts) and apoptotic alterations to chromatin. Camptothecin is a natural product of which TOP1 is the only cellular target. Two camptothecin derivatives have recently been approved by the US Food and Drug Administration: topotecan for ovarian and lung cancers and irinotecan for colorectal cancer. Various non-camptothecin inhibitors of TOP1 are in development, including indolocarbazole, phenanthridine and indenoisoquinoline derivatives. Non-camptothecins are expected to be active in cancers that are currently resistant to camptothecins, and to have a greater therapeutic index. Co-crystal structures of TOP1 inhibitors illustrate the interfacial inhibition paradigm by which a small drug molecule can trap conformational intermediates of macromolecular complexes (in the case of TOP1 inhibitors, the TOP1 enzyme and its cleaved DNA substrate). The cytotoxic activity of TOP1 inhibitors is related to the interference of trapped TOP1 cleavage complexes with DNA replication and transcription. Deficiencies in both the checkpoint and DNA-repair pathways determine cellular sensitivity to TOP1 inhibitors. Therefore, the identification of such deficiencies in tumours should guide the rational use of TOP1 inhibitors. Targeting checkpoint and repair pathways should also increase the selectivity of TOP1 inhibitors in tumours that have pre-existing deficiencies in relevant redundant pathways.

Small-molecule inhibitors of PARP are thought to mediate their antitumor effects as catalytic inhibitors that block repair of DNA single-strand breaks (SSB). However, the mechanism of action of PARP inhibitors with regard to their effects in cancer cells is not fully understood. In this study, we show that PARP inhibitors trap the PARP1 and PARP2 enzymes at damaged DNA. Trapped PARP–DNA complexes were more cytotoxic than unrepaired SSBs caused by PARP inactivation, arguing that PARP inhibitors act in part as poisons that trap PARP enzyme on DNA. Moreover, the potency in trapping PARP differed markedly among inhibitors with niraparib (MK-4827) > olaparib (AZD-2281) >> veliparib (ABT-888), a pattern not correlated with the catalytic inhibitory properties for each drug. We also analyzed repair pathways for PARP–DNA complexes using 30 genetically altered avian DT40 cell lines with preestablished deletions in specific DNA repair genes. This analysis revealed that, in addition to homologous recombination, postreplication repair, the Fanconi anemia pathway, polymerase β, and FEN1 are critical for repairing trapped PARP–DNA complexes. In summary, our study provides a new mechanistic foundation for the rational application of PARP inhibitors in cancer therapy. Cancer Res; 72(21); 5588–99. ©2012 AACR.

High-throughput and high-content databases are increasingly important resources in molecular medicine, systems biology, and pharmacology. However, the information usually resides in unwieldy databases, limiting ready data analysis and integration. One resource that offers substantial potential for improvement in this regard is the NCI-60 cell line database compiled by the U.S. National Cancer Institute, which has been extensively characterized across numerous genomic and pharmacologic response platforms. In this report, we introduce a CellMiner (http://discover.nci.nih.gov/cellminer/) web application designed to improve the use of this extensive database. CellMiner tools allowed rapid data retrieval of transcripts for 22,379 genes and 360 microRNAs along with activity reports for 20,503 chemical compounds including 102 drugs approved by the U.S. Food and Drug Administration. Converting these differential levels into quantitative patterns across the NCI-60 clarified data organization and cross-comparisons using a novel pattern match tool. Data queries for potential relationships among parameters can be conducted in an iterative manner specific to user interests and expertise. Examples of the in silico discovery process afforded by CellMiner were provided for multidrug resistance analyses and doxorubicin activity; identification of colon-specific genes, microRNAs, and drugs; microRNAs related to the miR-17-92 cluster; and drug identification patterns matched to erlotinib, gefitinib, afatinib, and lapatinib. CellMiner greatly broadens applications of the extensive NCI-60 database for discovery by creating web-based processes that are rapid, flexible, and readily applied by users without bioinformatics expertise. Cancer Res; 72(14); 3499–511. ©2012 AACR.