Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms.

A focused library of analogues of the dual PLK1 kinase/BRD4 bromodomain inhibitor BI-2536 was prepared and then analyzed for BRD4 and PLK1 inhibitory activities. Particularly, replacement of the cyclopentyl group with a 3-bromobenzyl moiety afforded the most potent BRD4 inhibitor of the series (39j) with a K i = 8.7 nM, which was equipotent against PLK1. The superior affinity of 39j over the parental compound to BRD4 possibly derives from improved interactions with the WPF shelf. Meanwhile, substitution of the pyrimidine NH with an oxygen atom reversed the PLK1/BRD4 selectivity to convert BI-2536 into a BRD4-selective inhibitor, likely owing to the loss of a critical hydrogen bond in PLK1. We believe further fine-tuning will furnish a BRD4 "magic bullet" or an even more potent PLK1/BRD4 dual inhibitor toward the expansion and improved efficacy of the chemotherapy arsenal.

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Multiple myeloma (MM) is a malignant neoplasm of plasma cells. Although new molecular targeting agents against MM have been developed based on the better understanding of the underlying pathogenesis, MM still remains an incurable disease. We previously demonstrated that β-catenin, a downstream effector in the Wnt pathway, is a potential target in MM using RNA interference in an in vivo experimental mouse model. In this study, we have screened a library of more than 100 000 small-molecule chemical compounds for novel Wnt/β-catenin signaling inhibitors using a high-throughput transcriptional screening technology. We identified AV-65, which diminished β-catenin protein levels and T-cell factor transcriptional activity. AV-65 then decreased c-myc, cyclin D1 and survivin expression, resulting in the inhibition of MM cell proliferation through the apoptotic pathway. AV-65 treatment prolonged the survival of MM-bearing mice. These findings indicate that this compound represents a novel and attractive therapeutic agent against MM. This study also illustrates the potential of high-throughput transcriptional screening to identify candidates for anticancer drug discovery.