Biology subjects

Gleave, M. E.

Publications and source records attributed to Gleave, M. E..

10 recordsLinked to original sources

bioRxiv2025

Longitudinal single-cell RNA sequencing of a neuroendocrine transdifferentiation model reveals transcriptional reprogramming in treatment-induced neuroendocrine prostate cancer

Neuroendocrine transdifferentiation (NEtD) of prostate adenocarcinoma (PRAD) leads to aggressive neuroendocrine prostate cancer (NEPC). The LTL331 patient-derived xenograft (PDX) model consistently progresses to NEPC following castration, mimicking clinical responses to androgen-deprivation therapy. Here we tracked NEtD using longitudinal single-cell RNA sequencing (scRNA-seq) across eight time points in LTL331 from pre- to post-castration. Castration led to the loss of AR-high PRAD cells, expansion of AR-low populations, and emergence of an AR- and NE-negative (AR-/NE-) intermediate state that transitioned into NEPC. We delineate a model in which pre-EMT cells enriched in ciliogenesis and cell-adhesion pathways differentiate into EMT-like populations before branching into distinct ASCL1+ and ASCL1- NEPC states. The EMT-enriched intermediate, marked by progenitor and neural crest stem-cell genes, acts as a transition bridge, suggesting EMT-associated stemness underlies lineage plasticity. A terminal ASCL1-NEPC state also suggests that ASCL1 is not essential for NEPC maintenance. Gene regulatory analysis highlighted key regulators driving NEtD, including MSX1 and ASCL1 in early EMT-like and NEPC states, respectively. These transcriptional states were validated in both patient-derived bulk and scRNA-seq data. Our findings offer insights into intervention strategies to delay or prevent NEtD with the potential of identifying novel prognostic and therapeutic targets.

cancer biology↗

bioRxiv2025

AR-V7 condensates drive androgen-independent transcription in castration resistant prostate cancer

Biomolecular condensates organize cellular environments and regulate key processes such as transcription. We previously showed that full-length androgen receptor (AR-FL), a major oncogenic driver in prostate cancer (PCa), forms nuclear condensates upon androgen stimulation in androgen-sensitive PCa cells. Disrupting these condensates impairs AR-FL transcriptional activity, highlighting their functional importance. However, resistance to androgen deprivation therapy often leads to castration-resistant prostate cancer (CRPC), driven by constitutively active splice variants like AR variant 7 (AR-V7). The mechanisms underlying AR-V7s role in CRPC remain unclear. In this study, we characterized the condensate-forming ability of AR-V7 and compared its phase behavior with AR-FL across a spectrum of PCa models and in vitro conditions. Our findings indicate that cellular context can influence AR-V7s condensate-forming capacity. Unlike AR-FL, AR-V7 spontaneously forms condensates in the absence of androgen stimulation and functions independently of AR-FL in CRPC models. However, AR-V7 requires a higher concentration to form condensates, both in cellular contexts and in vitro. We further reveal that AR-V7 drives transcription via both condensate-dependent and condensate-independent mechanisms. Using an AR-V7 mutant incapable of forming condensates, while retaining nuclear localization and DNA-binding ability, we reveal that the condensate-dependent regime activates part of the oncogenic KRAS pathway in CRPC models. Genes under this condensate-dependent regime were found to harbor significantly higher numbers of AR-binding sites and exhibited boosted expression in response to AR-V7. These findings uncover a previously unrecognized role of AR-V7 condensate formation in driving oncogenic transcriptional programs and shed light on its unique contribution to CRPC progression. HighlightsO_LIAR-V7 condensates form independently of both androgens and AR-FL in CRPC models. C_LIO_LIAR-V7 mediates condensate-dependent and independent transcription C_LIO_LICondensate-dependent transcription enables boosted expression of oncogenic KRAS genes C_LIO_LICondensate-dependent genes exhibit an exponential increase in expression, with a higher number of AR binding sites potentially playing a key role in their reliance on condensate formation. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/631986v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@16b50d1org.highwire.dtl.DTLVardef@86e3b6org.highwire.dtl.DTLVardef@1cfe7f3org.highwire.dtl.DTLVardef@8532a2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Deciphering the Transcription Factor Landscape in Neuroendocrine Prostate Cancer Progression: A Novel Approach to Understand NE Transdifferentiation

Background and ObjectiveProstate cancer (PCa) is a leading cause of cancer mortality in men, with neuroendocrine prostate cancer (NEPC) representing a particularly resistant subtype. The role of transcription factors (TFs) in the progression from prostatic adenocarcinoma (PRAD) to NEPC is poorly understood. This study aims to identify and analyze lineage-specific TF profiles in PRAD and NEPC and illustrate their dynamic shifts during NE transdifferentiation. MethodsA novel algorithmic approach was developed to evaluate the weighted expression of TFs within patient samples, enabling a nuanced understanding of TF landscapes in PCa progression and TF dynamic shifts during NE transdifferentiation. Resultsunveiled TF profiles for PRAD and NEPC, identifying 126 shared TFs, 46 adenocarcinoma-TFs, and 56 NEPC-TFs. Enrichment analysis across multiple clinical cohorts confirmed the lineage specificity and clinical relevance of these lineage-TFs signatures. Functional analysis revealed that lineage-TFs are implicated in pathways critical to cell development, differentiation, and lineage determination. Novel lineage-TF candidates were identified, offering potential targets for therapeutic intervention. Furthermore, our longitudinal study on NE transdifferentiation highlighted dynamic TF expression shifts and delineated a three-phase hypothesis for the process comprised of de-differentiation, dormancy, and re-differentiation. and proposing novel insights into the mechanisms of PCa progression. ConclusionThe lineage-specific TF profiles in PRAD and NEPC reveal a dynamic shift in the TF landscape during PCa progression, highlighting three distinct phases of NE transdifferentiation.

cancer biology↗

bioRxiv2023

ABI1 regulates transcriptional activity of Androgen Receptor by novel DNA and AR binding mechanism

Transcription regulates key functions of living organisms in normal and disease states, including cell growth and development, embryonic and adult tissue organization, and tumor progression. Here we identify a novel mechanism of transcriptional regulation by an actin regulatory and signaling protein, Abelson Interactor 1 (ABI1). Using prostate cancer models, we uncover a reciprocal regulation between ABI1 and the Androgen Receptor (AR). ABI1 is a direct, androgen-regulated target; in turn, ABI1 interacts with AR and its splice variant ARv7, and co-regulates a subset of specific transcriptional targets. ABI1 directs transcription through transient yet well-defined interaction of its intrinsically disordered region with DNA. Clinical evaluation shows that the ABI1-DNA binding (through Exon 4 splicing) and ABI1-AR interaction are regulated during androgen deprivation therapy and prostate cancer progression, thus controlling tumor plasticity through connecting actin cytoskeleton and cellular signaling to transcriptional regulation. We propose ABI1 as epigenetic regulator of transcriptional homeostasis in AR-driven cancers. Statement of importanceThis study describes fundamental discovery in prostate cancer identifying novel mechanism of transcription by unique DNA binding mechanism involving actin cytoskeleton regulatory protein ABI1. ABI1-DNA binding activity predicts survival of prostate cancer patients. Moreover, we discover ABI1-AR reciprocal regulation that has far reaching implications for tumor plasticity and androgen-sensitive pathogenesis.

cancer biology↗

bioRxiv2021

THEM6-mediated lipid remodelling sustains stress resistance in cancer

Despite the clinical benefit of androgen-deprivation therapy (ADT), the majority of patients with advanced prostate cancer (PCa) ultimately develop lethal castration-resistant prostate cancer (CRPC). In this study, we identified thioesterase superfamily member 6 (THEM6) as a marker of ADT resistance in PCa. In patients, THEM6 expression correlates with progressive disease and is associated with poor survival. THEM6 deletion reduces in vivo tumour growth and restores castration sensitivity in orthograft models of CRPC. Mechanistically, THEM6 is located at the endoplasmic reticulum (ER) membrane and controls lipid homeostasis by regulating intracellular levels of ether lipids. Consequently, THEM6 loss in CRPC cells significantly alters ER function, reducing de novo sterol biosynthesis and preventing lipid-mediated induction of ATF4. Finally, we show that THEM6 is required for the establishment of the MYC-induced stress response. Thus, similar to PCa, THEM6 loss significantly impairs tumorigenesis in the MYC-dependent subtype of triple negative breast cancer. Altogether, our results highlight THEM6 as a novel component of the treatment-induced stress response and a promising target for the treatment of CRPC and MYC-driven cancer.

cancer biology↗

bioRxiv2021

Dynamic phase separation of the androgen receptor and its coactivators to regulate gene expression.

Numerous cancers, including prostate cancer (PCa), are addicted to transcription programs driven by superenhancers (SEs). The transcription of genes at SEs is enabled by the formation of phase-separated condensates by transcription factors and co-activators with intrinsically disordered regions. The androgen receptor (AR), main oncogenic driver in PCa, contains large disordered regions and is co-recruited with the co-activator MED1 to SEs to promote oncogenic programs. In this work, we show that dynamic AR-rich, liquid-like foci form in PCa models upon androgen stimulation and correlate with AR transcriptional activity. The co-activator MED1 plays an essential role in the formation of AR foci while AR antagonists hinder their formation. These results suggest that enhanced compartmentalization of AR and co-activators at SEs may play an important role in the activation of oncogenic transcription programs in PCa. A better understanding of the assembly and the regulation of these AR-rich compartments may provide novel therapeutic options.

cancer biology↗

bioRxiv2020

Schlafen family member 5 (SLFN5) regulates LAT1-mediated mTOR activation in castration-resistant prostate cancer

Androgen-deprivation therapy (ADT) is the standard of care for the treatment of non-resectable prostate cancer (PCa). Despite high treatment efficiency, most patients ultimately develop lethal castration-resistant prostate cancer (CRPC). In this study, we perform a comparative proteomic analysis of three in vivo, androgen receptor (AR)-driven, orthograft models of CRPC. Differential proteomic analysis reveals that distinct molecular mechanisms, including amino acid (AA) and fatty acid (FA) metabolism, are involved in the response to ADT between the different models. Despite this heterogeneity, we identify SLFN5 as an AR-regulated biomarker in CRPC. SLFN5 expression is high in CRPC tumours and correlates with poor patient outcome. In vivo, SLFN5 depletion strongly impairs tumour growth in castrated condition. Mechanistically, SLFN5 interacts with ATF4 and regulates the expression of LAT1, an essential AA transporter. Consequently, SLFN5 depletion in CRPC cells decreases intracellular levels of essential AA and impairs mTORC1 signalling in a LAT1-dependent manner.

cancer 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↗

bioRxiv2019

Deep Docking - a Deep Learning Approach for Virtual Screening of Big Chemical Datasets

Drug discovery is an extensive and rigorous process that requires up to 2 billion dollars of investments and more than ten years of research and development to bring a molecule "from bench to a bedside". While virtual screening can significantly enhance drug discovery workflow, it ultimately lags the current rate of expansion of chemical databases that already incorporate billions of purchasable compounds. This surge of available small molecules presents great opportunities for drug discovery but also demands for faster virtual screening methods and protocols. In order to address this challenge, we herein introduce Deep Docking (D2) - a novel deep learning-based approach which is suited for docking billions of molecular structures. The developed D2-platform utilizes quantitative structure-activity relationship (QSAR) based deep models trained on docking scores of subsets of a large chemical library (Big Base) to approximate the docking outcome for yet unprocessed molecular entries and to remove unfavorable structures in an iterative manner. We applied D2 to virtually screen 1.36 billion molecules form the ZINC15 library against 12 prominent target proteins, and demonstrated up to 100-fold chemical data reduction and 6,000-fold enrichment for top hits, without notable loss of well-docked entities. The developed D2 protocol can readily be used in conjunction with any docking program and was made publicly available.

bioinformatics↗

bioRxiv2018

BAP1 Loss Predicts Therapeutic Vulnerability in Malignant Peritoneal Mesothelioma

BackgroundMalignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM yet exist. In the search for novel therapeutic target candidates in PeM, we performed a comprehensive integrative multi-omics analysis of 19 treatment-naive PeM tumors.\n\nResultsThe analysis identified PeM tumors with BAP1 loss to form a distinct molecular subtype characterized by distinct expression patterns of genes involved in chromatin remodeling, DNA repair pathway, and immune checkpoint receptor activation. This PeM subtype could potentially benefit from immune checkpoint, PARP, or HDAC inhibition therapies.\n\nConclusionsOur findings uncover BAP1 as a trackable prognostic and predictive biomarker, and refine PeM disease classification. This integrated molecular characterization provides a comprehensive foundation for developing PeM precision medicine.

cancer biology↗