AbstractAnaplastic large cell lymphomas (ALCLs) represent a relatively common group of T-cell non-Hodgkin lymphomas (T-NHLs) that are unified by similar pathologic features but demonstrate marked genetic heterogeneity. ALCLs are broadly classified as being anaplastic lymphoma kinase (ALK)+ or ALK−, based on the presence or absence of ALK rearrangements. Exome sequencing of 62 T-NHLs identified a previously unreported recurrent mutation in the musculin gene, MSCE116K, exclusively in ALK− ALCLs. Additional sequencing for a total of 238 T-NHLs confirmed the specificity of MSCE116K for ALK− ALCL and further demonstrated that 14 of 15 mutated cases (93%) had coexisting DUSP22 rearrangements. Musculin is a basic helix-loop-helix (bHLH) transcription factor that heterodimerizes with other bHLH proteins to regulate lymphocyte development. The E116K mutation localized to the DNA binding domain of musculin and permitted formation of musculin–bHLH heterodimers but prevented their binding to authentic target sequence. Functional analysis showed MSCE116K acted in a dominant-negative fashion, reversing wild-type musculin-induced repression of MYC and cell cycle inhibition. Chromatin immunoprecipitation–sequencing and transcriptome analysis identified the cell cycle regulatory gene E2F2 as a direct transcriptional target of musculin. MSCE116K reversed E2F2-induced cell cycle arrest and promoted expression of the CD30–IRF4–MYC axis, whereas its expression was reciprocally induced by binding of IRF4 to the MSC promoter. Finally, ALCL cells expressing MSCE116K were preferentially targeted by the BET inhibitor JQ1. These findings identify a novel recurrent MSC mutation as a key driver of the CD30–IRF4–MYC axis and cell cycle progression in a unique subset of ALCLs.
Genome Wide Approaches to Identify Protein-DNA Interactions
Current Medicinal Chemistry | May 31, 2018 | Volume: 26 | Issue: 42 | Pages: 7641-7654
Background: Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. Objective: This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. Conclusion: ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome- wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux.
Prevalent Homozygous Deletions of Type I Interferon and Defensin Genes in Human Cancers Associate with Immunotherapy Resistance
Clinical Cancer Research | April 4, 2018 | Volume: 24 | Issue: 14 | Pages: 3299-3308