Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains

By Junwei Shi, E. Wang, Joseph P Milazzo, Zhihua Wang, Justin B. Kinney, C. Vakoc. Nature Biotechnology, 2015

706 citations recorded by the source corpus.

CRISPR-Cas9 genome editing technology holds great promise for discovering therapeutic targets in cancer and other diseases. Current screening strategies target CRISPR-Cas9–induced mutations to the 5′ exons of candidate genes, but this approach often produces in-frame variants that retain functionality, which can obscure even strong genetic dependencies. Here we overcome this limitation by targeting CRISPR-Cas9 mutagenesis to exons encoding functional protein domains. This generates a higher proportion of null mutations and substantially increases the potency of negative selection. We also show that the magnitude of negative selection can be used to infer the functional importance of individual protein domains of interest. A screen of 192 chromatin regulatory domains in murine acute myeloid leukemia cells identifies six known drug targets and 19 additional dependencies. A broader application of this approach may allow comprehensive identification of protein domains that sustain cancer cells and are suitable for drug targeting.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/33da68b60ba93e05833a748a1a78bd57b57a7cea

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Citations in the corpus

A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia (2016, background): “In fact, recent proof-of-principle studies have demonstrated the potential of this technology to identify cell-essential genes in mammalian cells (Koike-Yusa et al., 2014; Shalem et al., 2014; Shi et al., 2015; Wang et al., 2014).”
The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal and leukemia cells (2017, positive): “To further evaluate the role of METTL3 enzymatic activity in the context of murine leukemia, we utilized a CRISPR/Cas9 strategy that specifically targets functional protein domains within a gene and infers functional importance based on negative selection 13 .”