High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell–like diffuse large B-cell lymphoma cells

Lesley A. Mathews Griner(National Institutes of Health), Rajarshi Guha(National Institutes of Health), Paul Shinn(National Institutes of Health), Ryan M. Young(Center for Cancer Research), Jonathan M. Keller(National Institutes of Health), Dongbo Liu(National Institutes of Health), Ian S. Goldlust(National Institutes of Health), Adam Yasgar(National Institutes of Health), Crystal McKnight(National Institutes of Health), Matthew B. Boxer(National Institutes of Health), Damien Duveau(National Institutes of Health), Jian‐kang Jiang(National Institutes of Health), Sam Michael(National Institutes of Health), Tim Mierzwa(National Institutes of Health), Wenwei Huang(National Institutes of Health), Martin J. Walsh(National Institutes of Health), Bryan T. Mott(National Institutes of Health), Paresma Patel(National Institutes of Health), William Leister(National Institutes of Health), David J. Maloney(National Institutes of Health), Christopher A. LeClair(National Institutes of Health), Ganesha Rai(National Institutes of Health), Ajit Jadhav(National Institutes of Health), Brian D. Peyser(National Institutes of Health), Christopher P. Austin(National Institutes of Health), Scott E. Martin(National Institutes of Health), Anton Simeonov(National Institutes of Health), Marc Ferrer(National Institutes of Health), Louis M. Staudt(Center for Cancer Research), Craig J. Thomas(National Institutes of Health)
Proceedings of the National Academy of Sciences
January 27, 2014
Cited by 396Open Access
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Abstract

The clinical development of drug combinations is typically achieved through trial-and-error or via insight gained through a detailed molecular understanding of dysregulated signaling pathways in a specific cancer type. Unbiased small-molecule combination (matrix) screening represents a high-throughput means to explore hundreds and even thousands of drug-drug pairs for potential investigation and translation. Here, we describe a high-throughput screening platform capable of testing compounds in pairwise matrix blocks for the rapid and systematic identification of synergistic, additive, and antagonistic drug combinations. We use this platform to define potential therapeutic combinations for the activated B-cell-like subtype (ABC) of diffuse large B-cell lymphoma (DLBCL). We identify drugs with synergy, additivity, and antagonism with the Bruton's tyrosine kinase inhibitor ibrutinib, which targets the chronic active B-cell receptor signaling that characterizes ABC DLBCL. Ibrutinib interacted favorably with a wide range of compounds, including inhibitors of the PI3K-AKT-mammalian target of rapamycin signaling cascade, other B-cell receptor pathway inhibitors, Bcl-2 family inhibitors, and several components of chemotherapy that is the standard of care for DLBCL.


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