Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions.

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

Chromatin context-dependent effects of epigenetic drugs on CRISPR-Cas9 editing.

The efficiency and outcome of CRISPR/Cas9 editing depends on the chromatin state at the cut site. It has been shown that changing the chromatin state can influence both the efficiency and repair outcome, and epigenetic drugs have been used to improve Cas9 editing. However, because the target proteins of these drugs are not homogeneously distributed across the genome, the efficacy of these drugs may be expected to vary from locus to locus. Here, we systematically analyzed this chromatin context-dependency for 160 epigenetic drugs. We used a human cell line with 19 stably integrated reporters to induce a double-stranded break in different chromatin environments. We then measured Cas9 editing efficiency and repair pathway usage by sequencing the mutational signatures. We identified 58 drugs that modulate Cas9 editing efficiency and/or repair outcome dependent on the local chromatin environment. For example, we find a subset of histone deacetylase inhibitors that improve Cas9 editing efficiency throughout all types of heterochromatin (e.g. PCI-24781), while others were only effective in euchromatin and H3K27me3-marked regions (e.g. apicidin). In summary, this study reveals that most epigenetic drugs alter CRISPR editing in a chromatin-dependent manner, and provides a resource to improve Cas9 editing more selectively at the desired location.

PAXIP1 and STAG2 converge to maintain 3D genome architecture and facilitate promoter/enhancer contacts to enable stress hormone-dependent transcription.

How steroid hormone receptors (SHRs) regulate transcriptional activity remains partly understood. Upon activation, SHRs bind the genome together with a co-regulator repertoire, crucial to induce gene expression. However, it remains unknown which components of the SHR-recruited co-regulator complex are essential to drive transcription following hormonal stimuli. Through a FACS-based genome-wide CRISPR screen, we functionally dissected the Glucocorticoid Receptor (GR) complex. We describe a functional cross-talk between PAXIP1 and the cohesin subunit STAG2, critical for regulation of gene expression by GR. Without altering the GR cistrome, PAXIP1 and STAG2 depletion alter the GR transcriptome, by impairing the recruitment of 3D-genome organization proteins to the GR complex. Importantly, we demonstrate that PAXIP1 is required for stability of cohesin on chromatin, its localization to GR-occupied sites, and maintenance of enhancer-promoter interactions. In lung cancer, where GR acts as tumor suppressor, PAXIP1/STAG2 loss enhances GR-mediated tumor suppressor activity by modifying local chromatin interactions. All together, we introduce PAXIP1 and STAG2 as novel co-regulators of GR, required to maintain 3D-genome architecture and drive the GR transcriptional programme following hormonal stimuli.

HDAC1 and PRC2 mediate combinatorial control in SPI1/PU.1-dependent gene repression in murine erythroleukaemia.

Although originally described as transcriptional activator, SPI1/PU.1, a major player in haematopoiesis whose alterations are associated with haematological malignancies, has the ability to repress transcription. Here, we investigated the mechanisms underlying gene repression in the erythroid lineage, in which SPI1 exerts an oncogenic function by blocking differentiation. We show that SPI1 represses genes by binding active enhancers that are located in intergenic or gene body regions. HDAC1 acts as a cooperative mediator of SPI1-induced transcriptional repression by deacetylating SPI1-bound enhancers in a subset of genes, including those involved in erythroid differentiation. Enhancer deacetylation impacts on promoter acetylation, chromatin accessibility and RNA pol II occupancy. In addition to the activities of HDAC1, polycomb repressive complex 2 (PRC2) reinforces gene repression by depositing H3K27me3 at promoter sequences when SPI1 is located at enhancer sequences. Moreover, our study identified a synergistic relationship between PRC2 and HDAC1 complexes in mediating the transcriptional repression activity of SPI1, ultimately inducing synergistic adverse effects on leukaemic cell survival. Our results highlight the importance of the mechanism underlying transcriptional repression in leukemic cells, involving complex functional connections between SPI1 and the epigenetic regulators PRC2 and HDAC1.

CHIPIN: ChIP-seq inter-sample normalization based on signal invariance across transcriptionally constant genes.

BACKGROUND: Multiple studies rely on ChIP-seq experiments to assess the effect of gene modulation and drug treatments on protein binding and chromatin structure. However, most methods commonly used for the normalization of ChIP-seq binding intensity signals across conditions, e.g., the normalization to the same number of reads, either assume a constant signal-to-noise ratio across conditions or base the estimates of correction factors on genomic regions with intrinsically different signals between conditions. Inaccurate normalization of ChIP-seq signal may, in turn, lead to erroneous biological conclusions. RESULTS: We developed a new R package, CHIPIN, that allows normalizing ChIP-seq signals across different conditions/samples when spike-in information is not available, but gene expression data are at hand. Our normalization technique is based on the assumption that, on average, no differences in ChIP-seq signals should be observed in the regulatory regions of genes whose expression levels are constant across samples/conditions. In addition to normalizing ChIP-seq signals, CHIPIN provides as output a number of graphs and calculates statistics allowing the user to assess the efficiency of the normalization and qualify the specificity of the antibody used. In addition to ChIP-seq, CHIPIN can be used without restriction on open chromatin ATAC-seq or DNase hypersensitivity data. We validated the CHIPIN method on several ChIP-seq data sets and documented its superior performance in comparison to several commonly used normalization techniques. CONCLUSIONS: The CHIPIN method provides a new way for ChIP-seq signal normalization across conditions when spike-in experiments are not available. The method is implemented in a user-friendly R package available on GitHub: https://github.com/BoevaLab/CHIPIN.

snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis.

Summary: Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses. Availability and implementation: Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

FANCA deficiency promotes leukaemic progression by allowing the emergence of cells carrying oncogenic driver mutations.

Leukaemia is caused by the clonal evolution of a cell that accumulates mutations/genomic rearrangements, allowing unrestrained cell growth. However, recent identification of leukaemic mutations in the blood cells of healthy individuals revealed that additional events are required to expand the mutated clones for overt leukaemia. Here, we assessed the functional consequences of deleting the Fanconi anaemia A (Fanca) gene, which encodes a DNA damage response protein, in Spi1 transgenic mice that develop preleukaemic syndrome. FANCA loss increases SPI1-associated disease penetrance and leukaemic progression without increasing the global mutation load of leukaemic clones. However, a high frequency of leukaemic FANCA-depleted cells display heterozygous activating mutations in known oncogenes, such as Kit or Nras, also identified but at low frequency in FANCA-WT mice with preleukaemic syndrome, indicating that FANCA counteracts the emergence of oncogene mutated leukaemic cells. A unique transcriptional signature is associated with the leukaemic status of FANCA-depleted cells, leading to activation of MDM4, NOTCH and Wnt/ß-catenin pathways. We show that NOTCH signalling improves the proliferation capacity of FANCA-deficient leukaemic cells. Collectively, our observations indicate that loss of the FANC pathway, known to control genetic instability, fosters the expansion of leukaemic cells carrying oncogenic mutations rather than mutation formation. FANCA loss may contribute to this leukaemogenic progression by reprogramming transcriptomic landscape of the cells.

Breast cancer risk SNPs converge on estrogen receptor binding sites commonly shared between breast tumors to locally alter estrogen signalling output.

Estrogen Receptor alpha (ERα) is the main driver and prime drug target in luminal breast. ERα chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ERα chromatin action, along with its biological implications. Here, we use a large set of ERα ChIP-seq data from 70 ERα+ breast cancers to explore inter-patient heterogeneity in ERα DNA binding, to reveal a striking inter-tumor heterogeneity of ERα action. Interestingly, commonly-shared ERα sites showed the highest estrogen-driven enhancer activity and were most-engaged in long-range chromatin interactions. In addition, the most-commonly shared ERα-occupied enhancers were enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ERα and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we could confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ERα-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ERα landscape, with the most-common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

A genome-wide CRISPR screen in human prostate cancer cells reveals drivers of macrophage-mediated cell killing and positions AR as a tumor-intrinsic immunomodulator.

The crosstalk between prostate cancer (PCa) cells and the tumor microenvironment plays a pivotal role in disease progression and metastasis and could provide novel opportunities for patient treatment. Macrophages are the most abundant immune cells in the prostate tumor microenvironment (TME) and are capable of killing tumor cells. To identify genes in the tumor cells that are critical for macrophage-mediated killing, we performed a genome-wide co-culture CRISPR screen and identified AR, PRKCD, and multiple components of the NF-κB pathway as hits, whose expression in the tumor cell are essential for being targeted and killed by macrophages. These data position AR signaling as an immunomodulator, and confirmed by androgen-deprivation experiments, that rendered hormone-deprived tumor cells resistant to macrophage-mediated killing. Proteomic analyses showed a downregulation of oxidative phosphorylation in the PRKCD- and IKBKG-KO cells compared to the control, suggesting impaired mitochondrial function, which was confirmed by electron microscopy analyses. Furthermore, phosphoproteomic analyses revealed that all hits impaired ferroptosis signaling, which was validated transcriptionally using samples from a neoadjuvant clinical trial with the AR-inhibitor enzalutamide. Collectively, our data demonstrate that AR functions together with the PRKCD and the NF-κB pathway to evade macrophage-mediated killing. As hormonal intervention represents the mainstay therapy for treatment of prostate cancer patients, our findings may have direct implications and provide a plausible explanation for the clinically observed persistence of tumor cells despite androgen deprivation therapy.