Biology subjects

Bergman, A. M.

Publications and source records attributed to Bergman, A. M..

7 recordsLinked to original sources

bioRxiv2025

TRIM33 loss reduces Androgen Receptor transcriptional output and H2BK120 ubiquitination

The Androgen Receptor (AR) is a ligand-dependent transcription factor that drives prostate cancer development and progression. Although, a detailed effect on AR biology has been described for a number of interacting proteins, many AR coregulators remain to be characterized in relation to their distinct impact on AR function. Here, we describe TRIM33 as a conserved AR-interactor across multiple prostate cancer cell lines. We observed that TRIM33 and AR share overall chromatin interaction profiles, in which TRIM33 is involved in downstream responsive transcriptomic output. In contrast to prior reports, we show that TRIM33 does not impact AR protein stability, but instead propose a model in which TRIM33 facilitates maximal AR activity by interfering with H2BK120 ubiquitination levels.

molecular biology↗

bioRxiv2023

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 is temporary, and resistance inevitably 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.

systems biology↗

bioRxiv2023

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-{kappa}B 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-{kappa}B 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.

cancer biology↗

bioRxiv2023

Exploring the onset and progression of prostate cancer through a multicellular agent-based model

Over ten percent of men will be diagnosed with prostate cancer (PCa) during their lifetime. Arising from luminal cells of the prostatic acinus, PCa 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 PCa. In this study, we developed an agent-based model of a prostatic acinus including its microenvironment, to allow for in silico studying of PCa development. The model was based on prior reports and in-house data of tumor cells co-cultured with Cancer Associated Fibroblasts (CAFs) and pro-tumor and/or anti-tumor macrophages. Growth patterns depicted by the model were pathologically validated on H&E slide images of human PCa specimens. We identified that stochasticity of interactions between macrophages and tumor cells at early stages strongly affect tumor development. Additionally, 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 cancer patients 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.

systems biology↗

bioRxiv2020

Functional mapping of androgen receptor enhancer activity

Androgen receptor (AR) is critical to the initiation, growth and progression of almost all prostate cancers. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10-100x more binding sites than differentially expressed genes. It still remains unclear how individual sites contribute to AR-mediated transcription. While descriptive functional genomic approaches broadly correlate with enhancer activity, they do not provide the locus-specific resolution needed to delineate the underlying regulatory logic of AR-mediated transcription. Therefore, we functionally tested all commonly occuring clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq) to generate the first map of intrinsic AR enhancer activity. This approach is not significantly affected by endogenous chromatin modifications and measures the potential enhancer activity at each cis-regulatory element. Interestingly we found that only 7% of AR binding sites displayed increased enhancer activity upon hormonal stimulation. Instead, the vast majority of AR binding sites were either inactive (81%) or constitutively active enhancers (11%). These annotations strongly correlated with enhancer-associated features in both cell line and clinical prostate cancer. With these validated annotations we next investigated the effect of each enhancer class on transcription and found that AR-driven inducible enhancers frequently interacted with promoters, forming central chromosomal loops critical for gene transcription. We demonstrated that these inducible enhancers act as regulatory hubs that increase contacts with both other AR binding sites and gene promoters. This functional map was used to identify a somatic mutation that significantly reduces the expression of a commonly mutated AR-regulated tumour suppressor. Together, our data reveal a complex interplay between different AR binding sites that work in a highly coordinated manner to drive gene transcription.

cancer biology↗

bioRxiv2020

Human Prostate Cancer-Associated Macrophage Subtypes with Prognostic Potential Revealed by Single-cell Transcriptomics

Macrophages in the tumor microenvironment are causally linked with prostate cancer development and progression, yet little is known about their composition in neoplastic human tissue. By performing single cell transcriptomic analysis of human prostate cancer resident macrophages, three distinct populations were identified in the diseased prostate. Unexpectedly, macrophages isolated from the tumor-adjacent site of the prostatectomy specimen were identical to those from the tumorous site. Markers associated with canonical M1 and M2 macrophage phenotypes were identifiable, however these were not the main factors defining unique subtypes. The genes selectively associated with each macrophage cluster were used to develop a gene signature which was highly associated with both recurrence-free and metastasis-free survival. These results highlight the relevance of tissue-specific macrophage subtypes in the tumour microenvironment for prostate cancer progression and demonstrates the utility of profiling single-cell transcriptomics in human tumor samples as a strategy to design gene classifiers for patient prognostication.

immunology↗

bioRxiv2019

The genomic landscape of metastatic castration-resistant prostate cancers using whole genome sequencing reveals multiple distinct genotypes with potential clinical impact

Here we present whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 castration-resistant prostate cancer patients. Using hierarchical unsupervised clustering based on genomic aberrations only, we defined eight different clusters. We detected four distinct and potentially clinically relevant genotypes harboring unique genomic features, including: 1) Microsatellite Instability; 2) Homologous Recombination Deficiency (HRD) with enriched genomic deletions and BRCA2 aberrations; 3) tandem duplication phenotype associated with biallelic CDK12 mutations; and 4) a subgroup enriched for chromothripsis events. Our data suggest that classifying patients using WGS characteristics may improve classification of HRD patients. Moreover, we confirmed that important regulators of AR-mediated signaling are located in non-coding regions. Using ChIP sequencing data, we showed that the amplified AR and MYC promoter regions contain open chromatin and bind AR, suggesting a role in AR mediated biology. Thus, high-resolution WGS may be used to improve patient stratification.

cancer biology↗