Biology subjects

Morova, T.

Publications and source records attributed to Morova, T..

10 recordsLinked to original sources

bioRxiv2025

Longitudinal single-cell analysis reveals RUNX1T1 as an early driver in treatment-induced neuroendocrine transdifferentiation

Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a lethal form of advanced prostate cancer that can emerge from adenocarcinoma under androgen receptor pathway inhibition, but the tumor-cell states and regulators underlying this transition remain incompletely defined. Here, we analyzed longitudinal single-cell RNA sequencing data from the LTL331/331R patient-derived xenograft model across seven disease stages, comprising 32,269 tumor-cell transcriptomes from treatment-naive adenocarcinoma, post-castration regression, and relapsed NEPC. We identified an AR-low/NE-low intermediate state that emerged after castration and before overt relapse, as well as two transcriptionally distinct terminal NEPC states marked by ASCL1high/FOXA2low and ASCL1low/FOXA2high programs. RUNX1T1 was induced in the intermediate state and remained elevated across both terminal states. RUNX1T1 enhanced NE-associated features and cell viability during enzalutamide treatment in adenocarcinoma cells, whereas its knockdown in NCI-H660 cells reduced NE-associated transcriptional programs, proliferation, and survival and shifted the transcriptome toward an intermediate-like state. Chromatin interactome analysis and co-immunoprecipitation linked RUNX1T1 to G9A/LASP1-containing chromatin repressor complexes. These findings define a temporal framework for treatment-induced NEPC progression and identify RUNX1T1 as an early-induced and sustained regulator of NE lineage transition and maintenance of established NEPC.

cancer biology↗

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↗

bioRxiv2024

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↗

bioRxiv2023

Breast cancer risk SNPs converge on estrogen receptor binding sites commonly shared between breast tumors to locally alter estrogen signalling output

Estrogen Receptor alpha (ER) is the main driver and prime drug target in luminal breast. ER 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 ER chromatin action, along with its biological implications. Here, we use a large set of ER ChIP-seq data from 70 ER+ breast cancers to explore inter-patient heterogeneity in ER DNA binding, to reveal a striking inter-tumor heterogeneity of ER action. Interestingly, commonly-shared ER sites showed the highest estrogen-driven enhancer activity and were most-engaged in long-range chromatin interactions. In addition, the most-commonly shared ER-occupied enhancers were enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ER 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 ER-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ER landscape, with the most-common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

genomics↗

bioRxiv2023

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↗

bioRxiv2022

Epigenetic-focused CRISPR/Cas9 screen identifies ASH2L as a regulator of glioblastoma cell survival

Glioblastoma is the most common and aggressive primary brain tumor with poor prognosis, highlighting an urgent need for novel treatment strategies. In this study, we investigated epigenetic regulators of glioblastoma cell survival through CRISPR/Cas9 based genetic ablation screens using a customized sgRNA library EpiDoKOL, which targets critical functional domains of chromatin modifiers. Screens conducted in multiple cell lines revealed ASH2L, a histone lysine methyltransferase complex subunit, as a major regulator of glioblastoma cell viability. ASH2L depletion led to cell cycle arrest and apoptosis. RNA sequencing and greenCUT&RUN together identified a set of cell cycle regulatory genes, such as TRA2B, BARD1, KIF20B, ARID4A and SMARCC1 that were downregulated upon ASH2L depletion. Mass spectrometry analysis revealed the interaction partners of ASH2L in glioblastoma cell lines as SET1/MLL family members including SETD1A, SETD1B, MLL1 and MLL2. We further showed that glioblastoma cells had a differential dependency on expression of SET1/MLL family members for survival. The growth of ASH2L-depleted glioblastoma cells was markedly slower than controls in orthotopic in vivo models. TCGA analysis showed high ASH2L expression in glioblastoma compared to low grade gliomas and immunohistochemical analysis revealed significant ASH2L expression in glioblastoma tissues, attesting to its clinical relevance. Therefore, high throughput, robust and affordable screens with focused libraries, such as EpiDoKOL, holds great promise to enable rapid discovery of novel epigenetic regulators of cancer cell survival, such as ASH2L. Together, we suggest that targeting ASH2L could serve as a new therapeutic opportunity for glioblastoma.

cancer biology↗

bioRxiv2022

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

The vast majority of disease-associated single nucleotide polymorphisms identified from genome-wide association study (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and number of variants tested per loci. Using this strategy, we interrogated 70 of 140 known prostate cancer (PCa) risk-associated loci and demonstrated that 26 (37%) of them harbor 36 SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

genetics↗

bioRxiv2021

EPIKOL, a chromatin-focused CRISPR/Cas9-based screening platform, to identify cancer-specific epigenetic vulnerabilities

Dysregulation of the epigenome due to alterations in chromatin modifier proteins commonly contribute to malignant transformation. To discover new drug targets for more targeted and personalized therapies, functional interrogation of epigenetic modifiers is essential. We therefore generated an epigenome-wide CRISPR-Cas9 knock-out library (EPIKOL) that targets a wide-range of epigenetic modifiers and their cofactors. We conducted eight screens in two different cancer types and showed that EPIKOL performs with high efficiency in terms of sgRNA distribution, depletion of essential genes and steady behaviors of non-targeting sgRNAs. From this, we discovered novel epigenetic modifiers besides previously known ones that regulate triple-negative breast cancer and prostate cancer cell fitness. With further validation assays, we confirmed the growth-regulatory function of individual candidates, including SS18L2 and members of the NSL complex (KANSL2, KANSL3, KAT8) in triple negative breast cancer cells. Overall, we show that EPIKOL, a focused sgRNA library targeting approximately 800 genes, can reveal epigenetic modifiers that are essential for cancer cell fitness and serve as a tool to offer novel anti-cancer targets. With its thoroughly generated epigenome-wide gene list, and the relatively high number of sgRNAs per gene, EPIKOL offers a great advantage to study functional roles of epigenetic modifiers in a wide variety of research applications, such as screens on primary cells, patient-derived xenografts as well as in vivo models.

cancer biology↗

bioRxiv2021

Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Methods that link genetic variation to steady-state gene expression levels, such as expression quantitative trait loci (eQTLs), are widely used to functionally annotate trait-associated variants, but they are limited in identifying context-dependent effects on transcription. To address this challenge, we developed the cistrome-wide association study (CWAS), a framework for nominating variants that impact traits through their effects on chromatin state. CWAS associates the genetic determinants of cistromes (e.g., the genome-wide profiles of transcription factor binding sites or histone modifications) with traits using summary statistics from genome-wide association studies (GWAS). We performed CWASs of prostate cancer and androgen-related traits, using a reference panel of 307 prostate cistromes from 165 individuals. CWAS nominated susceptibility regulatory elements or androgen receptor (AR) binding sites at 52 out of 98 known prostate cancer GWAS loci and implicated an additional 17 novel loci. We functionally validated a subset of our results using CRISPRi and in vitro reporter assays. At 28 of the 52 risk loci, CWAS identified regulatory mechanisms that are not observable via eQTLs, implicating genes with complex or context-specific regulation that are overlooked by current approaches that relying on steady-state transcript measurements. CWAS genes include transcription factors that govern prostate development such as NKX3-1, HOXB13, GATA2, and KLF5. Moreover, CWAS boosts discovery power in modestly sized GWAS, identifying novel genetic associations mediated through AR binding for androgen-related phenotypes, including resistance to prostate cancer therapy. CWAS is a powerful and biologically interpretable paradigm for studying variants that influence traits by affecting context-dependent transcriptional regulation.

genetics↗

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↗