Nuclear receptor Nur77 and Yin-Yang 1 synergistically increase mitochondrial abundance and activity in macrophages.

Mitochondrial biogenesis requires precise regulation of both mitochondrial-encoded and nuclear-encoded genes. Nuclear receptor Nur77 is known to regulate mitochondrial metabolism in macrophages and skeletal muscle. Here, we compared genome-wide Nur77 binding site and target gene expression in these two cell types, which revealed conserved regulation of mitochondrial genes and enrichment of motifs for the transcription factor Yin-Yang 1 (YY1). We show that Nur77 and YY1 interact, that YY1 increases Nur77 activity, and that their binding sites are co-enriched at mitochondrial ribosomal protein gene loci in macrophages. Nur77 and YY1 co-expression synergistically increases Mrpl1 expression as well as mitochondrial abundance and activity in macrophages but not skeletal muscle. As such, we identify a macrophage-specific Nur77-YY1 interaction that enhances mitochondrial metabolism.

Cancer Core Europe: Leveraging Institutional Synergies to Advance Oncology Research and Care Globally.

Cancer Core Europe brings together the expertise, resources, and interests of seven leading cancer institutes committed to leveraging collective innovation and collaboration in precision oncology. Through targeted efforts addressing key medical challenges in cancer and partnerships with multiple stakeholders, the consortium seeks to advance cancer research and enhance equitable patient care.

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.

Agent-based modeling of the prostate tumor microenvironment uncovers spatial tumor growth constraints and immunomodulatory properties.

Inhibiting androgen receptor (AR) signaling through androgen deprivation therapy (ADT) reduces prostate cancer (PCa) growth in virtually all patients, but response may be temporary, in which case resistance develops, ultimately leading to lethal castration-resistant prostate cancer (CRPC). The tumor microenvironment (TME) plays an important role in the development and progression of PCa. In addition to tumor cells, TME-resident macrophages and fibroblasts express AR and are therefore also affected by ADT. However, the interplay of different TME cell types in the development of CRPC remains largely unexplored. To understand the complex stochastic nature of cell-cell interactions, we created a PCa-specific agent-based model (PCABM) based on in vitro cell proliferation data. PCa cells, fibroblasts, "pro-inflammatory" M1-like and "pro-tumor" M2-like polarized macrophages are modeled as agents from a simple set of validated base assumptions. PCABM allows us to simulate the effect of ADT on the interplay between various prostate TME cell types. The resulting in vitro growth patterns mimic human PCa. Our PCABM can effectively model hormonal perturbations by ADT, in which PCABM suggests that CRPC arises in clusters of resistant cells, as is observed in multifocal PCa. In addition, fibroblasts compete for cellular space in the TME while simultaneously creating niches for tumor cells to proliferate in. Finally, PCABM predicts that ADT has immunomodulatory effects on macrophages that may enhance tumor survival. Taken together, these results suggest that AR plays a critical role in the cellular interplay and stochastic interactions in the TME that influence tumor cell behavior and CRPC development.

It Takes Two to Tango: The Interplay between Prostate Cancer and Its Microenvironment from an Epigenetic Perspective.

Prostate cancer is the second most common cancer in men worldwide and is associated with high morbidity and mortality. Consequently, there is an urgent unmet need for novel treatment avenues. In addition to somatic genetic alterations, deviations in the epigenetic landscape of cancer cells and their tumor microenvironment (TME) are critical drivers of prostate cancer initiation and progression. Unlike genomic mutations, epigenetic modifications are potentially reversible. Therefore, the inhibition of aberrant epigenetic modifications represents an attractive and exciting novel treatment strategy for castration-resistant prostate cancer patients. Moreover, drugs targeting the epigenome also exhibit synergistic interactions with conventional therapeutics by directly enhancing their anti-tumorigenic properties by "priming" the tumor and tumor microenvironment to increase drug sensitivity. This review summarizes the major epigenetic alterations in prostate cancer and its TME, and their involvement in prostate tumorigenesis, and discusses the impact of epigenome-targeted therapies.

Proteomics on malignant pleural effusions reveals ERα loss in metastatic breast cancer associates with SGK1-NDRG1 deregulation.

Breast cancer (BCa) is a highly heterogeneous disease, with hormone receptor status being a key factor in patient prognostication and treatment decision-making. The majority of primary tumours are positive for oestrogen receptor alpha (ERα), which plays a key role in tumorigenesis and disease progression, and represents the major target for treatment of BCa. However, around one-third of patients with ERα-positive BCa relapse and progress into the metastatic stage, with 20% of metastatic cases characterised by loss of ERα expression after endocrine treatment, known as ERα-conversion. It remains unclear whether ERα-converted cancers are biologically similar to bona fide ERα-negative disease and which signalling cascades compensate for ERα loss and drive tumour progression. To better understand the biological changes that occur in metastatic BCa upon ERα loss, we performed (phospho)proteomics analysis of 47 malignant pleural effusions derived from 37 BCa patients, comparing ERα-positive, ERα-converted and ERα-negative cases. Our data revealed that the loss of ERα-dependency in this metastatic site leads to only a partial switch to an ERα-negative molecular phenotype, with preservation of a luminal-like proteomic landscape. Furthermore, we found evidence for decreased activity of several key kinases, including serum/glucocorticoid regulated kinase 1 (SGK1), in ERα-converted metastases. Loss of SGK1 substrate phosphorylation may compensate for the loss of ERα-dependency in advanced disease and exposes a potential therapeutic vulnerability that may be exploited in treating these patients.

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.

Luminal breast cancer identity is determined by loss of glucocorticoid receptor activity.

Glucocorticoid receptor (GR) is a transcription factor that plays a crucial role in cancer biology. In this study, we utilized an in silico-designed GR activity signature to demonstrate that GR relates to the proliferative capacity of numerous primary cancer types. In breast cancer, the GR activity status determines luminal subtype identity and has implications for patient outcomes. We reveal that GR engages with estrogen receptor (ER), leading to redistribution of ER on the chromatin. Notably, GR activation leads to upregulation of the ZBTB16 gene, encoding for a transcriptional repressor, which controls growth in ER-positive breast cancer and associates with prognosis in luminal A patients. In relation to ZBTB16's repressive nature, GR activation leads to epigenetic remodeling and loss of histone acetylation at sites proximal to cancer-driving genes. Based on these findings, epigenetic inhibitors reduce viability of ER-positive breast cancer cells that display absence of GR activity. Our findings provide insights into how GR controls ER-positive breast cancer growth and may have implications for patients' prognostication and provide novel therapeutic candidates for breast cancer treatment.

Compartmentalization of androgen receptors at endogenous genes in living cells.

A wide range of nuclear proteins are involved in the spatio-temporal organization of the genome through diverse biological processes such as gene transcription and DNA replication. Upon stimulation by testosterone and translocation to the nucleus, multiple androgen receptors (ARs) accumulate in microscopically discernable foci which are irregularly distributed in the nucleus. Here, we investigated the formation and physical nature of these foci, by combining novel fluorescent labeling techniques to visualize a defined chromatin locus of AR-regulated genes-PTPRN2 or BANP-simultaneously with either AR foci or individual AR molecules. Quantitative colocalization analysis showed evidence of AR foci formation induced by R1881 at both PTPRN2 and BANP loci. Furthermore, single-particle tracking (SPT) revealed three distinct subdiffusive fractional Brownian motion (fBm) states: immobilized ARs were observed near the labeled genes likely as a consequence of DNA-binding, while the intermediate confined state showed a similar spatial behavior but with larger displacements, suggesting compartmentalization by liquid-liquid phase separation (LLPS), while freely mobile ARs were diffusing in the nuclear environment. All together, we show for the first time in living cells the presence of AR-regulated genes in AR foci.

Perturbations in 3D genome organization can promote acquired drug resistance.

Acquired drug resistance is a major problem in the treatment of cancer. hTERT-immortalized, untransformed RPE-1 cells can acquire resistance to Taxol by derepressing the ABCB1 gene, encoding for the multidrug transporter P-gP. Here, we investigate how the ABCB1 gene is derepressed. ABCB1 activation is associated with reduced H3K9 trimethylation, increased H3K27 acetylation, and ABCB1 displacement from the nuclear lamina. While altering DNA methylation and H3K27 methylation had no major impact on ABCB1 expression, nor did it promote resistance, disrupting the nuclear lamina component Lamin B Receptor did promote the acquisition of a Taxol-resistant phenotype in a subset of cells. CRISPRa-mediated gene activation supported the notion that lamina dissociation influences ABCB1 derepression. We propose a model in which nuclear lamina dissociation of a repressed gene allows for its activation, implying that deregulation of the 3D genome topology could play an important role in tumor evolution and the acquisition of drug resistance.

Transposable Elements Are Co-opted as Oncogenic Regulatory Elements by Lineage-Specific Transcription Factors in Prostate Cancer.

Transposable elements hold regulatory functions that impact cell fate determination by controlling gene expression. However, little is known about the transcriptional machinery engaged at transposable elements in pluripotent and mature versus oncogenic cell states. Through positional analysis over repetitive DNA sequences of H3K27ac chromatin immunoprecipitation sequencing data from 32 normal cell states, we report pluripotent/stem and mature cell state-specific "regulatory transposable elements." Pluripotent/stem elements are binding sites for pluripotency factors (e.g., NANOG, SOX2, OCT4). Mature cell elements are docking sites for lineage-specific transcription factors, including AR and FOXA1 in prostate epithelium. Expanding the analysis to prostate tumors, we identify a subset of regulatory transposable elements shared with pluripotent/stem cells, including Tigger3a. Using chromatin editing technology, we show how such elements promote prostate cancer growth by regulating AR transcriptional activity. Collectively, our results suggest that oncogenesis arises from lineage-specific transcription factors hijacking pluripotent/stem cell regulatory transposable elements. SIGNIFICANCE: We show that oncogenesis relies on co-opting transposable elements from pluripotent stem cells as regulatory elements altering the recruitment of lineage-specific transcription factors. We further discover how co-option is dependent on active chromatin states with important implications for developing treatment options against drivers of oncogenesis across the repetitive DNA. This article is featured in Selected Articles from This Issue, p. 2293.

TRIM25 targets p300 for degradation.

p300 is an important transcriptional co-factor. By stimulating the transfer of acetyl residues onto histones and several key transcription factors, p300 enhances transcriptional initiation and impacts cellular processes including cell proliferation and cell division. Despite its importance for cellular homeostasis, its regulation is poorly understood. We show that TRIM25, a member of the TRIM protein family, targets p300 for proteasomal degradation. However, despite TRIM25's RING domain and E3 activity, degradation of p300 by TRIM25 is independent of TRIM25-mediated p300 ubiquitination. Instead, TRIM25 promotes the interaction of p300 with dynein, which ensures a microtubule-dependent transport of p300 to cellular proteasomes. Through mediating p300 degradation, TRIM25 affects p300-dependent gene expression.

Crosstalk between glucocorticoid and mineralocorticoid receptors boosts glucocorticoid-induced killing of multiple myeloma cells.

The glucocorticoid receptor (GR) is a crucial drug target in multiple myeloma as its activation with glucocorticoids effectively triggers myeloma cell death. However, as high-dose glucocorticoids are also associated with deleterious side effects, novel approaches are urgently needed to improve GR action in myeloma. Here, we reveal a functional crosstalk between GR and the mineralocorticoid receptor (MR) that plays a role in improved myeloma cell killing. We show that the GR agonist dexamethasone (Dex) downregulates MR levels in a GR-dependent way in myeloma cells. Co-treatment of Dex with the MR antagonist spironolactone (Spi) enhances Dex-induced cell killing in primary, newly diagnosed GC-sensitive myeloma cells. In a relapsed GC-resistant setting, Spi alone induces distinct myeloma cell killing. On a mechanistic level, we find that a GR-MR crosstalk likely arises from an endogenous interaction between GR and MR in myeloma cells. Quantitative dimerization assays show that Spi reduces Dex-induced GR-MR heterodimerization and completely abolishes Dex-induced MR-MR homodimerization, while leaving GR-GR homodimerization intact. Unbiased transcriptomics analyses reveal that c-myc and many of its target genes are downregulated most by combined Dex-Spi treatment. Proteomics analyses further identify that several metabolic hallmarks are modulated most by this combination treatment. Finally, we identified a subset of Dex-Spi downregulated genes and proteins that may predict prognosis in the CoMMpass myeloma patient cohort. Our study demonstrates that GR-MR crosstalk is therapeutically relevant in myeloma as it provides novel strategies for glucocorticoid-based dose-reduction.

Exploring the Onset and Progression of Prostate Cancer through a Multicellular Agent-based Model.

Over 10% of men will be diagnosed with prostate cancer during their lifetime. Arising from luminal cells of the prostatic acinus, prostate cancer is influenced by multiple cells in its microenvironment. To expand our knowledge and explore means to prevent and treat the disease, it is important to understand what drives the onset and early stages of prostate cancer. In this study, we developed an agent-based model of a prostatic acinus including its microenvironment, to allow for in silico studying of prostate cancer development. The model was based on prior reports and in-house data of tumor cells cocultured with cancer-associated fibroblasts (CAF) and protumor and/or antitumor macrophages. Growth patterns depicted by the model were pathologically validated on hematoxylin and eosin slide images of human prostate cancer specimens. We identified that stochasticity of interactions between macrophages and tumor cells at early stages strongly affect tumor development. In addition, we discovered that more systematic deviations in tumor development result from a combinatorial effect of the probability of acquiring mutations and the tumor-promoting abilities of CAFs and macrophages. In silico modeled tumors were then compared with 494 patients with cancer with matching characteristics, showing strong association between predicted tumor load and patients' clinical outcome. Our findings suggest that the likelihood of tumor formation depends on a combination of stochastic events and systematic characteristics. While stochasticity cannot be controlled, information on systematic effects may aid the development of prevention strategies tailored to the molecular characteristics of an individual patient. Significance: We developed a computational model to study which factors of the tumor microenvironment drive prostate cancer development, with potential to aid the development of new prevention strategies.

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.

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.

Grade Group 1 Prostate Cancers Exhibit Tumor-defining Androgen Receptor-driven Programs.

Grade group 1 (GG1) primary prostate cancers with a pathologic Gleason score of 6 are considered indolent and generally not associated with fatal outcomes, so treatment is not indicated for most cases. These low-grade cancers have an overall negligible risk of locoregional progression and metastasis to distant organs, which is why there is an ongoing debate about whether these lesions should be reclassified as "noncancerous". However, the underlying molecular activity of key disease drivers, such as the androgen receptor (AR), have thus far not been thoroughly characterized in low-grade tumors. Therefore, we set out to delineate the AR chromatin-binding landscape in low-grade GG1 prostate cancers to gain insights into whether these AR-driven programs are actually tumor-specific or are normal prostate epithelium-like. These analyses showed that GG1 tumors do not harbor a distinct AR cistrome and, similar to higher-grade cancers, AR preferentially binds to tumor-defining cis-regulatory elements. Furthermore, the enhancer activity of these regions and the expression of their respective target genes were not significantly different in GG1 tumors. From an epigenetic perspective, this finding supports the cancer designation currently given to these low-grade tumors and clearly distinguishes them from noncancerous benign tissue. PATIENT SUMMARY: We characterized the molecular activity of the androgen receptor protein, which drives prostate cancer disease, in low-grade tumors. Our results show that these tumors are true cancers and are clearly separate from benign prostate tissue despite their low clinical aggressiveness.

Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer.

Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.g., biopsy), radiogenomics, combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which in turn can provide non-invasive advice on individualized treatment regimens. In this study, we carried out a parallel analysis on both imaging and transcriptomics data in order to identify features associated with clinically significant PCa (defined as an ISUP grade ≥ 3), subsequently evaluating the correlation between them. Textural imaging features were extracted from multi-parametric MRI sequences (T2W, DWI, and DCE) and combined with DCE-derived parametric pharmacokinetic maps obtained using magnetic resonance dispersion imaging (MRDI). A transcriptomic analysis was performed to derive functional features on transcription factors (TFs), and pathway activity from RNA sequencing data, here referred to as transcriptomic features. For both the imaging and transcriptomic features, different machine learning models were separately trained and optimized to classify tumors in either clinically insignificant or significant PCa. These models were validated in an independent cohort and model performance was used to isolate a subset of relevant imaging and transcriptomic features to be further investigated. A final set of 31 imaging features was correlated to 33 transcriptomic features obtained on the same tumors. Five significant correlations (p < 0.05) were found, of which, three had moderate strength (|r| ≥ 0.5). The strongest significant correlations were seen between a perfusion-based imaging feature-MRDI A median-and the activities of the TFs STAT6 (-0.64) and TFAP2A (-0.50). A higher-order T2W textural feature was also significantly correlated to the activity of the TF STAT6 (-0.58). STAT6 plays an important role in controlling cell proliferation and migration. Loss of the AP2alpha protein expression, quantified by TFAP2A, has been strongly associated with aggressiveness and progression in PCa. According to our findings, a combination of texture features extracted from T2W and DCE, as well as perfusion-based pharmacokinetic features, can be considered for the prediction of clinically significant PCa, with the pharmacokinetic MRDI A feature being the most correlated with the underlying transcriptomic information. These results highlight a link between quantitative imaging features and the underlying transcriptomic landscape of prostate tumors.

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.