Timing of treatment shapes the path to androgen receptor signaling inhibitor resistance in prostate cancer.

There is optimism that cancer drug resistance can be addressed through appropriate combination therapy, but success requires understanding the growing complexity of resistance mechanisms, including the evolution and population dynamics of drug-sensitive and drug-resistant clones over time. Using DNA barcoding to trace individual prostate tumor cells in vivo , we find that the evolutionary path to acquired resistance to androgen receptor signaling inhibition (ARSI) is dependent on the timing of treatment. In established tumors, resistance occurs through polyclonal adaptation of drug-sensitive clones, despite the presence of rare subclones with known, pre-existing ARSI resistance. Conversely, in an experimental setting designed to mimic minimal residual disease, resistance occurs through outgrowth of pre-existing resistant clones and not by adaptation. Despite these different evolutionary paths, the underlying mechanisms responsible for resistance are shared across the two evolutionary paths. Furthermore, mixing experiments reveal that the evolutionary path to adaptive resistance requires cooperativity between subclones. Thus, despite the presence of pre-existing ARSI-resistant subclones, acquired resistance in established tumors occurs primarily through cooperative, polyclonal adaptation of drug-sensitive cells. This tumor ecosystem model of resistance has new implications for developing effective combination therapy.

Defining the therapeutic selective dependencies for distinct subtypes of PI3K pathway-altered prostate cancers.

Previous studies have suggested that PTEN loss is associated with p110ß signaling dependency, leading to the clinical development of p110ß-selective inhibitors. Here we use a panel pre-clinical models to reveal that PI3K isoform dependency is not governed by loss of PTEN and is impacted by feedback inhibition and concurrent PIK3CA/PIK3CB alterations. Furthermore, while pan-PI3K inhibition in PTEN-deficient tumors is efficacious, upregulation of Insulin Like Growth Factor 1 Receptor (IGF1R) promotes resistance. Importantly, we show that this resistance can be overcome through targeting AKT and we find that AKT inhibitors are superior to pan-PI3K inhibition in the context of PTEN loss. However, in the presence of wild-type PTEN and PIK3CA-activating mutations, p110α-dependent signaling is dominant and selectively inhibiting p110α is therapeutically superior to AKT inhibition. These discoveries reveal a more nuanced understanding of PI3K isoform dependency and unveil novel strategies to selectively target PI3K signaling nodes in a context-specific manner.

Rapid interrogation of cancer cell of origin through CRISPR editing.

The increasing complexity of different cell types revealed by single-cell analysis of tissues presents challenges in efficiently elucidating their functions. Here we show, using prostate as a model tissue, that primary organoids and freshly isolated epithelial cells can be CRISPR edited ex vivo using Cas9-sgRNA (guide RNA) ribotnucleoprotein complex technology, then orthotopically transferred in vivo into immunocompetent or immunodeficient mice to generate cancer models with phenotypes resembling those seen in traditional genetically engineered mouse models. Large intrachromosomal (∼2 Mb) or multigenic deletions can be engineered efficiently without the need for selection, including in isolated subpopulations to address cell-of-origin questions.

Tumor Microenvironment-Derived NRG1 Promotes Antiandrogen Resistance in Prostate Cancer.

Despite the development of second-generation antiandrogens, acquired resistance to hormone therapy remains a major challenge in treating advanced prostate cancer. We find that cancer-associated fibroblasts (CAFs) can promote antiandrogen resistance in mouse models and in prostate organoid cultures. We identify neuregulin 1 (NRG1) in CAF supernatant, which promotes resistance in tumor cells through activation of HER3. Pharmacological blockade of the NRG1/HER3 axis using clinical-grade blocking antibodies re-sensitizes tumors to hormone deprivation in vitro and in vivo. Furthermore, patients with castration-resistant prostate cancer with increased tumor NRG1 activity have an inferior response to second-generation antiandrogen therapy. This work reveals a paracrine mechanism of antiandrogen resistance in prostate cancer amenable to clinical testing using available targeted therapies.

Regenerative potential of prostate luminal cells revealed by single-cell analysis.

Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1 + and Psca +) and a large population of differentiated cells (Nkx3.1 +, Pbsn +). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells.

Loss of CHD1 Promotes Heterogeneous Mechanisms of Resistance to AR-Targeted Therapy via Chromatin Dysregulation.

Metastatic prostate cancer is characterized by recurrent genomic copy number alterations that are presumed to contribute to resistance to hormone therapy. We identified CHD1 loss as a cause of antiandrogen resistance in an in vivo small hairpin RNA (shRNA) screen of 730 genes deleted in prostate cancer. ATAC-seq and RNA-seq analyses showed that CHD1 loss resulted in global changes in open and closed chromatin with associated transcriptomic changes. Integrative analysis of this data, together with CRISPR-based functional screening, identified four transcription factors (NR3C1, POU3F2, NR2F1, and TBX2) that contribute to antiandrogen resistance, with associated activation of non-luminal lineage programs. Thus, CHD1 loss results in chromatin dysregulation, thereby establishing a state of transcriptional plasticity that enables the emergence of antiandrogen resistance through heterogeneous mechanisms.

Oncogenic ERG Represses PI3K Signaling through Downregulation of IRS2.

Genomic rearrangements leading to the aberrant expression of ERG are the most common early events in prostate cancer and are significantly enriched for the concomitant loss of PTEN. Genetically engineered mouse models reveal that ERG overexpression alone is not sufficient to induce tumorigenesis, but combined loss of PTEN results in an aggressive invasive phenotype. Here, we show that oncogenic ERG repressed PI3K signaling through direct transcriptional suppression of IRS2, leading to reduced RTK levels and activity. In accordance with this finding, ERG-positive human prostate cancers had a repressed AKT gene signature and transcriptional downregulation of IRS2. Although overexpression of IRS2 activated PI3K signaling, promoting cell migration in a PI3K-dependent manner, this did not fully recapitulate the phenotype seen with loss of PTEN as PI3K signaling is not as robust as observed in the setting of loss of PTEN. Importantly, deletions of the PTEN locus, which promotes active PI3K signaling, were among the most significant copy-number alterations that co-occurred with ERG genomic rearrangements. This work provides insight on how initiating oncogenic events may directly influence the selection of secondary concomitant alterations to promote oncogenic signaling during tumor evolution. SIGNIFICANCE: This work provides insight on how initiating oncogenic events may directly influence the selection of secondary concomitant alterations to promote tumorigenesis.

Prostate Organoid Cultures as Tools to Translate Genotypes and Mutational Profiles to Pharmacological Responses.

Presented here is a protocol to study pharmacodynamics, stem cell potential, and cancer differentiation in prostate epithelial organoids. Prostate organoids are androgen responsive, three-dimensional (3D) cultures grown in a defined medium that resembles the prostatic epithelium. Prostate organoids can be established from wild-type and genetically engineered mouse models, benign human tissue, and advanced prostate cancer. Importantly, patient derived organoids closely resemble tumors in genetics and in vivo tumor biology. Moreover, organoids can be genetically manipulated using CRISPR/Cas9 and shRNA systems. These controlled genetics make the organoid culture attractive as a platform for rapidly testing the effects of genotypes and mutational profiles on pharmacological responses. However, experimental protocols must be specifically adapted to the 3D nature of organoid cultures to obtain reproducible results. Described here are detailed protocols for performing seeding assays to determine organoid formation capacity. Subsequently, this report shows how to perform drug treatments and analyze pharmacological response via viability measurements, protein isolation, and RNA isolation. Finally, the protocol describes how to prepare organoids for xenografting and subsequent in vivo growth assays using subcutaneous grafting. These protocols yield highly reproducible data and are widely applicable to 3D culture systems.

Aberrant Expression of ERG Promotes Resistance to Combined PI3K and AR Pathway Inhibition through Maintenance of AR Target Genes.

On the basis of our previous work defining the molecular rationale for combined targeting of the PI3K and AR pathways in PTEN loss prostate cancer, the first clinical trial was recently reported demonstrating a significant benefit for combination therapy in patients with metastatic prostate cancer. In this phase II trial, loss of PTEN was a biomarker predictive of response to combined AKT and AR inhibition. Given that PTEN loss prostate cancers are significantly enriched for ERG genomic rearrangements, we evaluated how the aberrant expression of ERG may impact response to PI3K/AR-targeted therapy. Here, we show that overexpression of ERG in the setting of Pten loss promotes resistance to combined PI3K and AR pathway inhibition with associated maintenance of AR target gene expression. Importantly, following AR knockout in the setting of ERG overexpression, there is maintenance of a subset of AR lineage-specific target genes, making AR dispensable in this context. This has important clinical implications as even in the setting of the androgen-regulated TMPRSS2:ERG genomic rearrangement, ERG expression is never abolished following AR inhibition and may allow for cell survival following AR (lineage)-targeted therapies.

GREB1 amplifies androgen receptor output in human prostate cancer and contributes to antiandrogen resistance.

Genomic amplification of the androgen receptor (AR) is an established mechanism of antiandrogen resistance in prostate cancer. Here, we show that the magnitude of AR signaling output, independent of AR genomic alteration or expression level, also contributes to antiandrogen resistance, through upregulation of the coactivator GREB1. We demonstrate 100-fold heterogeneity in AR output within human prostate cancer cell lines and show that cells with high AR output have reduced sensitivity to enzalutamide. Through transcriptomic and shRNA knockdown studies, together with analysis of clinical datasets, we identify GREB1 as a gene responsible for high AR output. We show that GREB1 is an AR target gene that amplifies AR output by enhancing AR DNA binding and promoting EP300 recruitment. GREB1 knockdown in high AR output cells restores enzalutamide sensitivity in vivo. Thus, GREB1 is a candidate driver of enzalutamide resistance through a novel feed forward mechanism.

Crystal structure of the effector AvrLm4-7 of Leptosphaeria maculans reveals insights into its translocation into plant cells and recognition by resistance proteins.

The avirulence gene AvrLm4-7 of Leptosphaeria maculans, the causal agent of stem canker in Brassica napus (oilseed rape), confers a dual specificity of recognition by two resistance genes (Rlm4 and Rlm7) and is strongly involved in fungal fitness. In order to elucidate the biological function of AvrLm4-7 and understand the specificity of recognition by Rlm4 and Rlm7, the AvrLm4-7 protein was produced in Pichia pastoris and its crystal structure was determined. It revealed the presence of four disulfide bridges, but no close structural analogs could be identified. A short stretch of amino acids in the C terminus of the protein, (R/N)(Y/F)(R/S)E(F/W), was well-conserved among AvrLm4-7 homologs. Loss of recognition of AvrLm4-7 by Rlm4 is caused by the mutation of a single glycine to an arginine residue located in a loop of the protein. Loss of recognition by Rlm7 is governed by more complex mutational patterns, including gene loss or drastic modifications of the protein structure. Three point mutations altered residues in the well-conserved C-terminal motif or close to the glycine involved in Rlm4-mediated recognition, resulting in the loss of Rlm7-mediated recognition. Transient expression in Nicotiana benthamiana (tobacco) and particle bombardment experiments on leaves from oilseed rape suggested that AvrLm4-7 interacts with its cognate R proteins inside the plant cell, and can be translocated into plant cells in the absence of the pathogen. Translocation of AvrLm4-7 into oilseed rape leaves is likely to require the (R/N)(Y/F)(R/S)E(F/W) motif as well as an RAWG motif located in a nearby loop that together form a positively charged region.

CEBS--Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data.

CEBS (Chemical Effects in Biological Systems) is an integrated public repository for toxicogenomics data, including the study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. CEBS contains data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. CEBS is designed to permit the user to query the data using the study conditions, the subject responses and then, having identified an appropriate set of subjects, to move to the microarray module of CEBS to carry out gene signature and pathway analysis. Scope of CEBS: CEBS currently holds 22 studies of rats, four studies of mice and one study of Caenorhabditis elegans. CEBS can also accommodate data from studies of human subjects. Toxicogenomics studies currently in CEBS comprise over 4000 microarray hybridizations, and 75 2D gel images annotated with protein identification performed by MALDI and MS/MS. CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Additionally, clinical chemistry and histopathology findings from over 1500 animals are included in CEBS. CEBS/BID: The BID (Biomedical Investigation Database) is another component of the CEBS system. BID is a relational database used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee (in preparation). BID has been shared with Health Canada and the US Environmental Protection Agency. CEBS is available at http://cebs.niehs.nih.gov. BID can be accessed via the user interface from https://dir-apps.niehs.nih.gov/arc/. Requests for a copy of BID and for depositing data into CEBS or BID are available at http://www.niehs.nih.gov/cebs-df/.

Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application.

MOTIVATION: The CEBS data repository is being developed to promote a systems biology approach to understand the biological effects of environmental stressors. CEBS will house data from multiple gene expression platforms (transcriptomics), protein expression and protein-protein interaction (proteomics), and changes in low molecular weight metabolite levels (metabolomics) aligned by their detailed toxicological context. The system will accommodate extensive complex querying in a user-friendly manner. CEBS will store toxicological contexts including the study design details, treatment protocols, animal characteristics and conventional toxicological endpoints such as histopathology findings and clinical chemistry measures. All of these data types can be integrated in a seamless fashion to enable data query and analysis in a biologically meaningful manner. RESULTS: An object model, the SysBio-OM (Xirasagar et al., 2004) has been designed to facilitate the integration of microarray gene expression, proteomics and metabolomics data in the CEBS database system. We now report SysTox-OM as an open source systems toxicology model designed to integrate toxicological context into gene expression experiments. The SysTox-OM model is comprehensive and leverages other open source efforts, namely, the Standard for Exchange of Nonclinical Data (http://www.cdisc.org/models/send/v2/index.html) which is a data standard for capturing toxicological information for animal studies and Clinical Data Interchange Standards Consortium (http://www.cdisc.org/models/sdtm/index.html) that serves as a standard for the exchange of clinical data. Such standardization increases the accuracy of data mining, interpretation and exchange. The open source SysTox-OM model, which can be implemented on various software platforms, is presented here. AVAILABILITY: A universal modeling language (UML) depiction of the entire SysTox-OM is available at http://cebs.niehs.nih.gov and the Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov CONTACT: xirasagars@saic.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chemical effects in biological systems--data dictionary (CEBS-DD): a compendium of terms for the capture and integration of biological study design description, conventional phenotypes, and 'omics data.

A critical component in the design of the Chemical Effects in Biological Systems (CEBS) Knowledgebase is a strategy to capture toxicogenomics study protocols and the toxicity endpoint data (clinical pathology and histopathology). A Study is generally an experiment carried out during a period of time for the purpose of obtaining data, and the Study Design Description captures the methods, timing, and organization of the Study. The CEBS Data Dictionary (CEBS-DD) has been designed to define and organize terms in an attempt to standardize nomenclature needed to describe a toxicogenomics Study in a structured yet intuitive format and provide a flexible means to describe a Study as conceptualized by the investigator. The CEBS-DD will organize and annotate information from a variety of sources, thereby facilitating the capture and display of toxicogenomics data in biological context in CEBS, i.e., associating molecular events detected in highly-parallel data with the toxicology/pathology phenotype as observed in the individual Study Subjects and linked to the experimental treatments. The CEBS-DD has been developed with a focus on acute toxicity studies, but with a design that will permit it to be extended to other areas of toxicology and biology with the addition of domain-specific terms. To illustrate the utility of the CEBS-DD, we present an example of integrating data from two proteomics and transcriptomics studies of the response to acute acetaminophen toxicity (A. N. Heinloth et al., 2004, Toxicol. Sci. 80, 193-202).