Interaction of the oncoprotein transcription factor MYC with its chromatin cofactor WDR5 is essential for tumor maintenance.

The oncoprotein transcription factor MYC is overexpressed in the majority of cancers. Key to its oncogenic activity is the ability of MYC to regulate gene expression patterns that drive and maintain the malignant state. MYC is also considered a validated anticancer target, but efforts to pharmacologically inhibit MYC have failed. The dependence of MYC on cofactors creates opportunities for therapeutic intervention, but for any cofactor this requires structural understanding of how the cofactor interacts with MYC, knowledge of the role it plays in MYC function, and demonstration that disrupting the cofactor interaction will cause existing cancers to regress. One cofactor for which structural information is available is WDR5, which interacts with MYC to facilitate its recruitment to chromatin. To explore whether disruption of the MYC-WDR5 interaction could potentially become a viable anticancer strategy, we developed a Burkitt\u27s lymphoma system that allows replacement of wild-type MYC for mutants that are defective for WDR5 binding or all known nuclear MYC functions. Using this system, we show that WDR5 recruits MYC to chromatin to control the expression of genes linked to biomass accumulation. We further show that disrupting the MYC-WDR5 interaction within the context of an existing cancer promotes rapid and comprehensive tumor regression in vivo. These observations connect WDR5 to a core tumorigenic function of MYC and establish that, if a therapeutic window can be established, MYC-WDR5 inhibitors could be developed as anticancer agents

MYC regulates ribosome biogenesis and mitochondrial gene expression programs through its interaction with host cell factor-1.

The oncoprotein transcription factor MYC is a major driver of malignancy and a highly validated but challenging target for the development of anticancer therapies. Novel strategies to inhibit MYC may come from understanding the co-factors it uses to drive pro-tumorigenic gene expression programs, providing their role in MYC activity is understood. Here we interrogate how one MYC co-factor, host cell factor (HCF)-1, contributes to MYC activity in a human Burkitt lymphoma setting. We identify genes connected to mitochondrial function and ribosome biogenesis as direct MYC/HCF-1 targets and demonstrate how modulation of the MYC-HCF-1 interaction influences cell growth, metabolite profiles, global gene expression patterns, and tumor growth in vivo. This work defines HCF-1 as a critical MYC co-factor, places the MYC-HCF-1 interaction in biological context, and highlights HCF-1 as a focal point for development of novel anti-MYC therapies

Inhibition of MYC by the SMARCB1 tumor suppressor.

SMARCB1 encodes the SNF5 subunit of the SWI/SNF chromatin remodeler. SNF5 also interacts with the oncoprotein transcription factor MYC and is proposed to stimulate MYC activity. The concept that SNF5 is a coactivator for MYC, however, is at odds with its role as a tumor-suppressor, and with observations that loss of SNF5 leads to activation of MYC target genes. Here, we reexamine the relationship between MYC and SNF5 using biochemical and genome-wide approaches. We show that SNF5 inhibits the DNA-binding ability of MYC and impedes target gene recognition by MYC in cells. We further show that MYC regulation by SNF5 is separable from its role in chromatin remodeling, and that reintroduction of SNF5 into SMARCB1-null cells mimics the primary transcriptional effects of MYC inhibition. These observations reveal that SNF5 antagonizes MYC and provide a mechanism to explain how loss of SNF5 can drive malignancy

Magnitude of B cell responses to inactivated HIV-1 inversely correlates with viral load.

<p>(<b>A</b>) Expression of CD86 on B cells after stimulation of PBMC with HIV-1 MN control (left column) or HIV-1 MN (right column). Shown are representative plots from one individual (subject 10071).. (<b>B</b>) PBMCs from 21 HIV-infected individuals (closed circles) and 7 HIV-negative control subjects (open circles) were incubated with inactivated HIV-1 MN, and changes in CD86 expression on B cells were measured. Change was calculated by subtracting the frequency of CD86 expression from stimulation with the HIV-1 MN control (containing no HIV proteins) from stimulation with HIV-1 MN. CD86 expression on B cells in response to HIV-antigen in HIV infected individuals is negatively correlated with viral load (r= -.6; p= .006). Correlation statistics are only applied to HIV-infected individuals and do not include data from uninfected subjects. </p

PD-1 blockade improves B cell responses to stimulation with inactivated HIV-1.

<p>PBMCs were cultured overnight with or without anti-PD-1 and stimulated with inactivated HIV-1 MN protein. Change in response to MN stimulation was calculated by subtracting stimulation with MN control protein from stimulation with HIV-1 MN protein (p= .003).</p

CD86+ B cells are more frequent in HIV+ than HIV- subjects and correlate with viremia.

<p>PBMCs from HIV- (open circles) or HIV+ (closed circles) subjects were incubated overnight without stimulation and evaluated for surface level CD86 expression on B cells. HIV+ subjects had a higher frequency of CD86+ B cells compared to HIV- subjects (unpaired t-test not shown on graph, p=0.03). The frequency of CD19+CD86+ B cells in HIV+ individuals correlates with the level of viremia (r=.63; p=.003). Correlation statistics shown are derived from HIV+ subject data only and do not include data from HIV- subjects. </p

Change in CD25 expression on B and CD4+ T cells negatively correlates with viral load.

<p>PBMCs were cultured overnight with or without anti-CD3 stimulation. Change in CD25 or CD86 expression was determined by subtracting the frequency of expression before stimulation from the frequency of expression after stimulation. (<b>A</b>) Representative plots of CD25 expression on CD4+ T cells and B cells with (bottom) and without (top) anti-CD3 stimulation. CD4+ T cell population shown is CD3+CD4+CD19- and B cell population shown is CD3-CD4-CD19+. (<b>B</b>-<b>D</b>) Change in expression of CD25 on CD4+ T cells (r= -.53; p= .056) (B), CD25 on B cells (r= -.63; p= .018) (C), and CD86 on B cells (r= -.44; p= .11) (D) correlates negatively with viral load. </p