Heterochromatic repetitive satellite RNAs are extensively transcribed in a variety of human cancers, including BRCA1 mutant breast cancer. Aberrant expression of satellite RNAs in cultured cells induces the DNA damage response, activates cell cycle checkpoints, and causes defects in chromosome segregation. However, the mechanism by which satellite RNA expression leads to genomic instability is not well understood. Here we provide evidence that increased levels of satellite RNAs in mammary glands induce tumor formation in mice. Using mass spectrometry, we further show that genomic instability induced by satellite RNAs occurs through interactions with BRCA1-associated protein networks required for the stabilization of DNA replication forks. Additionally, de-stabilized replication forks likely promote the formation of RNA-DNA hybrids in cells expressing satellite RNAs. These studies lay the foundation for developing novel therapeutic strategies that block the effects of non-coding satellite RNAs in cancer cells.

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Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics - that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFNγ) stimulation. We found that IRF1 responds to low concentration or short duration IFNγ stimulation, whereas CXCL10 and CXCL9 require longer or higher-concentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of non-responding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated simulations, as validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFNγ stimulus with very different response features and that upstream signal adaptation can contribute to shaping the features of heterogeneous gene expression.