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Tekoglu, E.

Publications and source records attributed to Tekoglu, E..

7 recordsLinked to original sources

Motif-based model of transcription predicts effects of sequence variants in AR enhancers and reveals distinct functions for AR-associated transcription factors

Androgen receptor (AR)-mediated transcription plays a central role in prostate cancer development and progression, yet the contributions of individual transcription factors (TFs) to AR-dependent enhancer activity remain incompletely understood. Here we use a biophysically motivated, interpretable motif-based model to dissect these contributions from STARR-seq data in LNCaP cells. By fitting the model separately to androgen inducibility and to baseline enhancer activity, we resolve TFs into three functional classes: hormone-dependent drivers, constitutive activators, and dual-role factors that contribute to both. These patterns suggest that inducibility is associated not only with the presence of AR and co-activator motifs, but also with the relative absence of constitutive activators that may saturate enhancer output. We validate the model against an independent saturation-mutagenesis dataset spanning 40 AR enhancers, predicting mutational effects at single-base resolution (AUC = 0.76), and show that direct fitting to these data independently recovers known AR regulators. Finally, we apply the model to prostate cancer GWAS risk alleles in AR binding site regions, prioritizing four candidate variants predicted to reduce the DHT/EtOH enhancer activity ratio at these loci.

genomics↗

The Androgen Receptor and MYC synergise to modulate the synthesis of Siglec-7 ligands in prostate cancer

Glyco-immune checkpoints have recently been shown to be critical mediators of immunotherapy resistance across multiple cancer types. In clinical trials, immunotherapeutic treatments for prostate cancer have failed to elicit durable clinical responses. PCa progression is driven by transcriptional networks regulated by key transcription factors including the androgen receptor (AR) and the oncogene MYC. How this crossover between hormone and oncogene-driven signalling pathways regulates tumour glyco-immune checkpoints remains unclear. Here, we show that O-glycans are the major substrates for sialylation in prostate cancer and that sialyltransferases that have preferences for O-glycans are differentially regulated by androgens. We show that supraphysiological levels of androgens produce distinct glycopeptide profiles in prostate cancer cells compared with cells exposed to physiological androgens. Additionally, we identify a direct and coordinated role for AR and MYC in regulating ST3Gal1 and the synthesis of Siglec-7 ligands in prostate cancer. Both transcription factors converge to repress ST3GAL1, thereby limiting the generation of Siglec-7 ligands. These findings highlight a context-dependent, cooperative relationship between the AR and MYC in shaping the tumour sialome, linking hormonal signalling and oncogenic transcription to Siglec biology. Our study highlights how cell-type specific differences in transcriptional networks has important downstream effects for immune modulating glycans and has tumour specific clinical implications.

cancer biology↗

B7-H3 as a Dual Clinically Relevant Checkpoint and Antibody Drug Conjugate Target Expressed Across Adenocarcinoma and Neuroendocrine Prostate Cancers

Background and ObjectivesCD276 (B7-H3) has recently emerged as a promising presumptive immune checkpoint inhibitor (ICI) and a potential antibody-drug conjugate (ADC) target for prostate cancer (PCa). We evaluated B7-H3 and 15 other clinically relevant ADC and ICI targets for expression at the RNA and protein level across the PCa continuum--hormone-sensitive, castration-resistant, and neuroendocrine. MethodsCCLE data analysis and western blot experiments were performed for quantifying RNA and protein expression variability across PCa cell lines. Inter- and intratumoral heterogeneity was evaluated by integrating single-cell RNA sequencing data across 595k cells and 102 patients, spanning the disease continuum. AR and B7-H3 knockouts of PCa cell lines were developed and investigated using R1881 and Enzalutamide to elucidate the AR-CD276 signaling pathway through qRT-PCR and flow cytometry. Key FindingsB7-H3 showed high expression in tumor and myeloid cells (tumor microenvironment - TME), lowest heterogeneity across all ADC and ICI targets, and was negatively regulated by androgen signaling. LimitationsFurther validation of ADC and ICI target protein expression in human samples and more exhaustive exploration of the AR-CD276 signaling cascade is required. ConclusionB7-H3 demonstrates the least susceptibility to selective pressure due to its stable expression across PCa disease states. Clinical ImplicationsB7-H3 represents an important ADC target for PCa due to its potential to minimize drug resistance and likely ability to be a valid target across the prostate cancer continuum. Additionally, its expression in myeloid cells supports a dual role as an ICI, further enhancing its therapeutic relevance. Graphical AbstractDiscovery of optimal checkpoints and antibody drug conjugates (ADCs) in Prostate Cancer (PCa). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/632253v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@1af1115org.highwire.dtl.DTLVardef@8a9d70org.highwire.dtl.DTLVardef@6659aeorg.highwire.dtl.DTLVardef@189e200_HPS_FORMAT_FIGEXP M_FIG C_FIG Patient SummaryIn this study, we demonstrate that prostate cancer expresses high amounts of a cell surface protein called B7-H3 both when first diagnosed and throughout various stages of metastatic disease. Furthermore, we demonstrate a clear and yet to be fully resolved cross-talk between B7-H3 and the androgen signaling pathway central to prostate cancer development. We conclude that B7-H3 is therefore a highly promising therapeutic cell surface protein expressed by prostate cancer due to its stable expression potentially leading to low selective pressure and reduced drug resistance--thereby having significant implications for clinical trial design and patient inclusion considerations. Advancing PracticePCa is a highly heterogeneous disease with an increasingly wide treatment landscape, governed by various factors including clinical covariates, histopathological features, and molecular factors. B7-H3 has recently emerged as a promising clinical target for immunotherapy in the localized setting and antibody drug targeting in the metastatic setting. Despite the clinical significance, B7-H3 expression has not yet been thoroughly evaluated against other clinically relevant immune checkpoint and antibody drug targets, especially along the continuum of PCa treatment stages--hormone sensitive, castration resistant, and neuroendocrine. To our knowledge, this is the first study to characterize B7-H3 in this continuum using representative cell lines and the largest collection of PCa patient single cell sequencing data yet assembled in the literature, thus accounting for the substantial heterogeneity across PCa disease states as well as between datasets. Take Home MessageThis article explores the therapeutic relevance of clinical stage ADC targets and immune checkpoints for Prostate Cancer (PCa). We show that B7-H3 is a highly promising therapeutic candidate for PCa due to its stable expression across various disease states.

cancer biology↗

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↗

Inference of Transcriptional Regulation From STARR-seq Data

One of the primary regulatory processes in cells is transcription, during which RNA polymerase II (Pol-II) transcribes DNA into RNA. The binding of Pol-II to its site is regulated through interactions with transcription factors (TFs) that bind to DNA at enhancer cis-regulatory elements. Measuring the enhancer activity of large libraries of distinct DNA sequences is now possible using Massively Parallel Reporter Assays (MPRAs), and computational methods have been developed to identify the dominant statistical patterns of TF binding within these large datasets. Such methods are global in their approach and may overlook important regulatory sites which function only within the local context. Here we introduce a method for inferring functional regulatory sites (their number, location and width) within an enhancer sequence based on measurements of its transcriptional activity from an MPRA method such as STARR-seq. The model is based on a mean-field thermodynamic description of Pol-II binding that includes interactions with bound TFs. Our method applied to simulated STARR-seq data for a variety of enhancer architectures shows how data quality impacts the inference and also how it can find local regulatory sites that may be missed in a global approach. We also apply the method to recently measured STARR-seq data on androgen receptor (AR) bound sequences, a TF that plays an important role in the regulation of prostate cancer. The method identifies key regulatory sites within these sequences which are found to overlap with binding sites of known co-regulators of AR. 1 Author SummaryWe present an inference method for identifying regulatory sites within a putative DNA enhancer sequence, given only the measured transcriptional output of a set of overlapping sequences using an assay like STARR-seq. It is based on a mean-field thermodynamic model that calculates the binding probability of Pol-II to its promoter and includes interactions with sites in the DNA sequence of interest. By maximizing the likelihood of the data given the model, we can infer the number of regulatory sites, their locations, and their widths. Since it is a local model, it can in principle find regulatory sites that are important within a local context that may get missed in a global fit. We test our method on simulated data of simple enhancer architectures and show that it is able to find only the functional sites. We also apply our method to experimental STARR-seq data from 36 androgen receptor bound DNA sequences from a prostate cancer cell line. The inferred regulatory sites overlap known important regulatory motifs and their ChIP-seq data in these regions. Our method shows potential at identifying locally important functional regulatory sites within an enhancer given only its measured transcriptional output.

genomics↗

HOXB13 alters chromatin accessibility in prostate cancer through interactions with the SWI/SNF complex

HOXB13 is a posterior homeobox protein that is associated with the initiation and growth of prostate cancer (PCa). While most research has focused on the role of HOXB13 on androgen receptor (AR) activity, we demonstrate that HOXB13 is essential to the proliferation of both AR-positive and -negative PCa. Strikingly, HOXB13 is remarkably selective and has almost no effect on non-prostatic tissues. Despite this common essentiality in PCa, HOXB13 activity is markedly different in AR-negative PCa, where interactions with the AP-1 change the HOXB13 cistrome in stem-cell like castration-resistant prostate cancer. We show that HOXB13 activity is commonly mediated by SMARCD2, a member of the mSWI/SNF chromatin remodeling complex. Despite the distinct transcription factor interactions in AR-positive and -negative PCa the HOXB13/SMARCD2 commonly alters chromatin accessibility at HOXB13 binding sites that causes increased proliferation in PCa. Overall, this work demonstrates a novel mechanism of action for HOXB13 and highlights its critical role in AR-negative castration-resistant prostate cancer.

cancer biology↗

Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins

NLR proteins are intracellular receptors constituting a conserved component of the innate immune system of multicellular organisms. In fungi, NLRs are characterized by high diversity of architectures and presence of amyloid signaling. Here, we explore the diverse world of effector and signaling domains of fungal NLRs using state-of-the-art bioinformatic methods including MMseqs2 for fast clustering, probabilistic context-free grammars for sequence analysis, and AlphaFold2 deep neural networks for structure prediction. In addition to substantially improving the overall annotation, especially in basidiomycetes, the study identifies novel domains and reveals the structural similarity of MLKL-related HeLo- and Goodbye-like domains forming the most abundant superfamily of fungal NLR effectors. Moreover, compared to previous studies, we found several times more amyloid motifs, including novel families, and validated aggregating and prion-forming properties of the most abundant of them in vitro and in vivo. Also, through an extensive in silico search, the NLR-associated amyloid signaling is for the first time identified in basidiomycetes. The emerging picture highlights similarities and differences in the NLR architectures and amyloid signaling in ascomycetes, basidiomycetes and other branches of life.

bioinformatics↗