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Biology subjects

Yao, X.

Publications and source records attributed to Yao, X..

At least 55 records · Page 3Linked to original sources

Single-Cell and Spatial Multi-omics Reveal Interferon Signaling in the Pathogenesis of Perianal Fistulizing Crohn's Disease

Background & AimsPerianal fistulizing Crohns disease (PCD) is a common and debilitating complication with elusive pathophysiology. We examined mucosal cells from patients with PCD and related conditions using a multi-omics approach. MethodsWe recruited patients with PCD (n = 24), CD without perianal disease (NPCD, n = 10), and idiopathic perianal fistulas (IPF, n = 29). Biopsies were taken from fistula tracts, fistula opening, and rectal mucosa. Single-cell RNA-sequencing (scRNA-seq), mass cytometry (CyTOF), spatial transcriptomics (ST), immunohistochemistry, and integrated analysis were performed. ResultsScRNA-seq, CyTOF, and ST unraveled immune and non-immune cell compartments in PCD and IPF fistula tracts. PCD fistulas showed hyperactivated pathogenic pathways including interferon (IFN)G response and TNF signaling in myeloid and stromal cells. Intestinal cells from PCD patients also expressed greater levels of IFNG-responsive and EMT genes compared to NPCD patients. Furthermore, both fistula tracts and ileal mucosa from PCD patients harbored expanded IFNG+ pathogenic Th17 cells, which expressed elevated inflammatory mediators. CyTOF also identified skewed immune cell phenotypes in the fistula tracts, fistula opening, and rectum in PCD patients including expanded Th17 cells, increased pathogenic myeloid cells, and altered T cell exhaustion markers. Further analysis also revealed cellular modules associated with anti-TNF therapy in PCD patients. ConclusionMulti-omics analysis revealed immune, stromal, and epithelial cell landscapes of PCD, which highlight the pathogenic role of hyperactivated IFNG signaling in both fistula tracts and luminal mucosa. This study identified IFNG as a potential therapeutic target for PCD.

systems biology↗

Interpretable PROTAC degradation prediction with structure-informed deep ternary attention framework

Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional ligands that form ternary complexes with Protein Of Interests (POIs) and E3 ligases, exploiting the ubiquitin-proteasome system to degrade disease-associated proteins, promising to drug the undruggable. While PROTAC research primarily relies on costly and time-consuming wet experimental approaches, deep learning offers a promising avenue to accelerate development and reduce expenses. However, existing deep learning methods for PROTAC degradation prediction often overlook the significance of hierarchical molecular representation and protein structural information, hindering effective data modeling. Moreover, their black-box nature limits the interpretability of computational outcomes, failing to provide intuitive insights into substructure interactions within the PROTAC system. This study introduces PROTAC-STAN, a structure-informed deep ternary attention network (STAN) framework for interpretable PROTAC degradation prediction. PROTAC-STAN represents PROTAC molecules across atom, molecule, and property hierarchies and incorporates structure information for POIs and E3 ligases using a protein language model infused with structural data. Furthermore, it simulates interactions among three entities at the atom and amino acid levels via a novel ternary attention network tailored for the PROTAC system, providing unprecedented insights into the degradation mechanism. By integrating hierarchical PROTAC molecule representation, structural embedding of POI and E3 ligase, and ternary attention network modeling interactions, our approach substantially improves prediction accuracy by 10.95% while enabling significant model interpretability via atomic and residue level visualization of molecule and complex. Experiments on the refined public PROTAC dataset demonstrate that PROTAC-STAN outperforms state-of-the-art baselines in overall performance. The excellent performance of PROTAC-STAN is anticipated to establish it as a foundational tool in future research on PROTAC-related drugs, thereby accelerating the development of this field.

bioinformatics↗

Antigen-specific T cell immunotherapy by in vivo mRNA delivery

Immunotherapy has shown promise for treating patients with autoimmune diseases or cancer, yet treatment is associated with adverse effects associated with global activation or suppression of T cell immunity. Here, we developed antigen-presenting nanoparticles (APNs) to selectively engineer disease antigen (Ag)-specific T cells by in vivo mRNA delivery. APNs consist of a lipid nanoparticle core functionalized with peptide-major histocompatibility complexes (pMHCs), facilitating antigen-specific T cell transfection through cognate T cell receptor-mediated endocytosis. In mouse models of type 1 diabetes and multiple myeloma, APNs selectively deplete autoreactive T cells leading to durable control of glycemia, and engineer virus-specific T cells with anti-cancer chimeric antigen receptors (CARs), achieving comparable therapeutic outcome as virally transduced ex vivo CAR. Overall, our work supports the use of APNs to engineer disease-relevant T cells in vivo as Ag-specific immunotherapy for autoimmune disorders and cancer.

bioengineering↗

Microbial strategies of environmental adaptation revealed by trait-environmental relationships

Microbial trait variation along environment gradients is crucial to understanding their ecological adaptation mechanisms. With the increasing availability of microbial genomes, making full use of the genome-based traits to decipher their adaptation strategies becomes promising and urgent. Here, we examined microbial communities in water and sediments of 20 East African lakes with pH values ranging from 7.2 to 10.1 through taxonomic-profiling and genome-centric metagenomics. We identified functional traits important for microbial adaptation to the stresses of alkalinity and salinity based on the significant trait-environment relationships (TERs), including those involved in cytoplasmic pH homeostasis, compatible solute accumulation, cell envelope modification and energy requisition. By integrating these significant-TER traits, we further developed an environmental adaptation index to quantify the species-level adaptive capacity for environmental stresses, such as high pH environments. The adaptation index of pH showed consistently significant positive relationships with species pH optima across regional and global genomic datasets from freshwater, marine and soda lake ecosystems. The generality of the index for quantifying environmental adaptation was demonstrated by showing significant relationships with the species niche optima for the gradients of soil temperature and seawater salinity. These results highlight the importance of trait-environment relationships in facilitating the inference of microbial genomic-based adaptation mechanisms, and expand our understanding of ecological adaptative strategies along environmental gradients.

ecology↗

Pipeline for Assessing Tumor Immune Status Using Superplex Immunostaining and Spatial Immune Interaction Analysis

The characteristics of the tumor microenvironment (TME) are closely linked to tumor progression and treatment response. The TME comprises various cell types, their spatial distribution, cell-cell interactions, and their organization into cellular niches or neighborhoods. To capture this complexity, several spatial profiling technologies have been developed. However, challenges such as low throughput, high costs, and complicated data analysis have limited their widespread use in immune research. In this study, we introduce the Cyclic-multiplex TSA (CmTSA) staining platform, a high-throughput superplex staining technology based on tyramide signal amplification (TSA) immunostaining combined with an efficient fluorophore recycling method. The CmTSA platform allows for the labeling of 30-60 antigens across multiple parallel formalin-fixed paraffin-embedded (FFPE) slides. Furthermore, the automated CmTSA workflow requires only standard histological equipment and conventional immunohistochemistry (IHC) primary antibodies (Abs), significantly reducing costs. While the superplex images produced contain extensive multidimensional information, extracting the spatial features of the TME from raw pixel data can be challenging. To address this, we present a computer vision-based analysis pipeline, which begins with deep learning-based algorithms to segment individual cells and identify cell types based on defined annotation rules. It then evaluates the spatial distribution tendencies of each cell type, the interaction intensity between paired cells, and the multicellular functional niches. This comprehensive approach enables researchers to visualize and quantify the types, states, and levels of immune activities within the TME effectively, advancing tumor immunology research and precision immune medicine.

cancer biology↗

MED26-enriched condensates drive erythropoiesis through modulating transcription pausing

The Mediator complex regulates various aspects of hematopoietic development, but whether composition of the Mediator complex undergoes dynamic changes for diversifying transcription and functional outputs is unknown. Here, we found that MED26, a subunit in the core Mediator complex, played a distinctive role in facilitating transcription pausing essential for erythroid development. While most Mediator subunits drastically decreased during this process, MED26 remained relatively abundant. Intriguingly, in the early stages, more than half of MED26 occupancy sites did not co-localize with MED1, a representative Mediator subunit, suggesting these subunits exert context-dependent gene regulation. We revealed that MED26-enriched loci were associated with RNA polymerase pausing. MED26 manifested a markedly preferential recruitment of pausing-related factors, leading to an increase in Pol pausing critical for genome-wide transcription repression during erythropoiesis. Moreover, MED26 exhibited pronounced condensate-forming capability, which was necessary for its function in promoting erythropoiesis and recruiting pausing-related factors. Collectively, this study provides mechanistic insights into the functional coordination of distinct Mediator subunits during development and highlights the switch of transcription condensates towards a MED26 enriched form, which modulates transcription pausing to facilitate transcription repression and erythroid development.

cell biology↗

The molecular mechanism of temperature-dependent phase separation of Heat shock factor 1

Heat shock factor 1 (HSF1) is the critical orchestrator for a cell responding to heat shock, and its dysfunction is linked to cancers and neurodegenerative diseases. HSF1 undergoes phase separation upon heat shock, and its activity is regulated by various post-translational modifications (PTMs). Despite its importance, the molecular details underlying HSF1 phase separation, temperature sensing, and post-translational modifications (PTMs) regulation remain poorly understood. Here, we discovered that HSF1 exhibits temperature-dependent phase separation with a lower critical solution temperature (LCST) behavior due to entropy contribution from solvent molecules, providing a new conceptual mechanism accounting for HSF1 activation. We employed a synergistic approach combining coarse-grain simulation and nuclear magnetic resonance spectroscopy to reveal the residue-level molecular details of the interactions driving the phase separation of wild-type HSF1 and its distinct PTM patterns at various temperatures. The identified interaction sites were further validated with biochemistry assays and mapped interface accounts for HSF1 functions reported. Importantly, the amino acid substitution experiment reveals the molecular grammar for temperature-dependent HSF1 phase separation is species-specific and physiologically relevant. These findings delineate chemical code that integrates protein PTM patterns with accurate phase separation for body physiological temperature control in animals.

biochemistry↗

Bio-macromolecular assembly machine for human limb lengthening

Growth plate (GP) is the critical cartilaginous structure for longitudinal bone growth. Herein, employing high-resolution analytical techniques, we explore the intricate mechanisms that govern the polarized mineralization patterns within GP. The GP-epiphysis interface displays a sharp transition in tissue modulus, acting as a "protective shell" for the underlying GP, whereas the GP-metaphysis interface exhibits a gradual modulus increase, enabling efficient load redistribution to metaphysis. The unique mechanical environments at these two interfaces contribute to polarized CaP mineralization patterns, which are regulated by a complex protein-based molecular machinery. The mineralization inhibitors SPP1 and AHSG enriched at the GP-epiphysis interface could act as a line of defence against mineralization. When these two proteins coexisted with the mineralization-promoting ENPP1 and ALPL at the GP-metaphysis interface, a sequential event of precise nucleation and programmable assembly of CaP minerals occur, forming "mineralization waves" to guide bone elongation. By replicating such specific macromolecular environment at GP-metaphysis interface, a hypertable amorphous calcium phosphate (ACP) phase is well-retained in vitro, demonstrating the possibility for precise and gentle control of ACP-hydroxyapatite (HAp) transformation under physiological conditions. Our study defines a novel concept of "mineralization waves" that govern the velocity and amplitude of GP-guided mineralization process.

bioengineering↗

Memorize multiple phase pattern attractors in nonlinear coupled oscillators dynamic via heterogeneous connectivity strength

Whole brain neural oscillation activities exhibit multiple wave patterns and seem to be supported by the common circuit network structure. We proposed a Hebbian-like Kuramoto model based entirely on heterogeneous connectivity strength rather than phase delay, which encodes the multiple phase patterns as attractors. We systematically investigated how the model dynamic landscape influenced by attractors and their corresponding eigenvalues, as well as how to control the stability of equilibrium points and the occurrence of high dimension bifurcations. This framework enables us to reproduce the dominant wave activity components in human brain functional MRI signal, and provides a canonical model for the multi body physical system spatio-temporal pattern attractor dynamics.

neuroscience↗

A Tough Biointerface in Human Knee Empowered by Dynamic Phase-transforming Minerals in Collagenous Matrix

Joining heterogeneous materials in engineered structures remains a daunting challenge because of stress concentration, often resulting in unexpected failures1,2. Studying the structures in organisms that evolved for centuries provides valuable insights that can be instrumental in addressing this mechanical challenge3-5. The human meniscus root-bone interface is a remarkable example known for its exceptional fatigue resistance, toughness and interfacial adhesion properties throughout its lifespan6-8. We studied the multiscale graded mineralization structure designs within the 30-micron soft-hard interface at the root-bone junction and examined its toughening mechanisms. This graded interface with interdigitated structures and exponential modulus increase exhibits a phase transition from amorphous calcium phosphate (ACP) to gradually matured hydroxyapatite (HAP) crystals, mediated by location-specific distributed biomolecules. In coordination with collagen fibril deformation and reorientation, ACP particles debond with collagen and slide to new positions which enable frictional energy dissipation, and HAP particles arrest cracks. The mineral in transforming phases work synergistically to provide interfacial toughening. The presented biointerface model exemplifies human musculoskeletal systems adaptations to mechanical requirements, offering a blueprint for developing tough interfaces in broad applications.

bioengineering↗

Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives in ME/CFS Gut Microbiome

Disruptions in microbial metabolite interactions due to gut microbiome dysbiosis and metabolomic shifts may contribute to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other immune-related conditions. The aryl hydrocarbon receptor (AhR), activated upon binding various tryptophan metabolites, modulates host immune responses. This study investigates whether the metabolic diversity--the concentration distribution--of bacterial indole pathway metabolites can differentiate bacterial strains and classify ME/CFS samples. A fast targeted liquid chromatography-parallel reaction monitoring method at a rate of 4 minutes per sample was developed for large-scale analysis. This method revealed significant metabolic differences in indole derivatives among B. uniformis strains cultured from human isolates. Principal component analysis identified two major components (PC1, 68.9%; PC2, 18.7%), accounting for 87.6% of the variance and distinguishing two distinct B. uniformis clusters. The metabolic difference between clusters was particularly evident in the relative contributions of indole-3-acrylate and indole-3-aldehyde. We further measured concentration distributions of indole derivatives in ME/CFS by analyzing fecal samples from 10 patients and 10 healthy controls using the fast targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success with a mean LOOCV accuracy of 0.65 (Control: precision of 0.67, recall of 0.60, F1-score of 0.63; ME/CFS: precision of 0.64, recall of 0.7000, F1-score of 0.67). These results suggest that the metabolic diversity of indole derivatives from tryptophan degradation, facilitated by the fast targeted metabolomics and machine learning, is a potential biomarker for differentiating bacterial strains and classifying ME/CFS samples. Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (ST002308, DOI: 10.21228/M8G13Q; ST003344, DOI: 10.21228/M8RJ9N; ST003346, DOI: 10.21228/M8RJ9N).

biochemistry↗

CIB2 as a Ca2+ Sensor for Auditory Mechano-Electrical Transduction and Linked to Genetic-Heterogeneity of TMC1 in Hearing Loss

Non-syndromic sensorineural hearing loss is characterized by genetic heterogeneity, leading to potential clinical misdiagnosis. TMC1, a unique causative gene associated with deafness, exhibits variants with autosomal dominant and recessive inheritance patterns. TMC1 codes for the transmembrane channel-like 1 (TMC1), a key component of the mechano-electrical transduction (MET) machinery for hearing. However, the molecular mechanism of Ca2+ regulation in MET, which is essential for sound perception, remains unclear. CIB2, another MET component associated with deafness, can bind with calcium and may play a role in MET gating. Our study reveals that the TMC1-CIB2 complex undergoes a Ca2+-induced conformational change, highlighting the crucial role of Ca2+ in MET. We identified a vertebrate-specific binding site on TMC1, named CR3, that interacts with apo CIB2, with the binding interface linked to hearing loss. Using an in-vivo animal model, we demonstrated that disruption of the calcium-sensing site of CIB2 perturbs the MET channel conductivity, confirming its role as a Ca2+ sensor for MET. Additionally, after systematically analyzing the hearing-loss variants, we observed that dominant mutations of TMC1 are often located near the ion pore or at the binding interfaces with the Ca2+ sensor CIB2. This provides a detailed mechanism of the genetic heterogeneity of TMC1 in hearing loss at an atomic level.

molecular biology↗

Sex-dependent gastrointestinal colonization resistance to MRSA is microbiome and Th17 dependent

Gastrointestinal (GI) colonization by methicillin-resistant Staphylococcus aureus (MRSA) is associated with a high risk of transmission and invasive disease in vulnerable populations. The immune and microbial factors that permit GI colonization remain unknown. Male sex is correlated with enhanced Staphylococcus aureus nasal carriage, skin and soft tissue infections, and bacterial sepsis. Here, we established a mouse model of sexual dimorphism during GI colonization by MRSA. Our results show that in contrast to male mice that were susceptible to persistent colonization, female mice rapidly cleared MRSA from the GI tract following oral inoculation in a manner dependent on the gut microbiota. This colonization resistance displayed by female mice was mediated by an increase in IL-17A+ CD4+ T cells (Th17) and dependent on neutrophils. Ovariectomy of female mice increased MRSA burden, but gonadal female mice that have the Y chromosome retained enhanced Th17 responses and colonization resistance. Our study reveals a novel intersection between sex and gut microbiota underlying colonization resistance against a major widespread pathogen.

immunology↗

PIP-Seq identifies novel heterogeneous lung innate lymphocyte population activation after combustion product exposure

Innate lymphoid cells (ILCs) are a heterogeneous population that play diverse roles in airway inflammation after exposure to allergens and infections. However, how ILCs respond after exposure to environmental toxins is not well understood. Here we show a novel method for studying the heterogeneity of rare lung ILC populations by magnetic enrichment for lung ILCs followed by particle-templated instant partition sequencing (PIP-seq). Using this method, we were able to identify novel group 1 and group 2 ILC subsets that exist after exposure to both fungal allergen and burn pit-related constituents (BPC) that include dioxin, aromatic hydrocarbon, and particulate matter. Toxin exposure in combination with fungal allergen induced activation of specific ILC1/NK and ILC2 populations as well as promoted neutrophilic lung inflammation. Oxidative stress pathways and downregulation of specific ribosomal protein genes (Rpl41 and Rps19) implicated in anti-inflammatory responses were present after BPC exposure. Increased IFN{gamma} expression and other pro-neutrophilic mediator transcripts were increased in BPC-stimulated lung innate lymphoid cells. Further, the addition of BPC induced Hspa8 (encodes HSC70) and aryl hydrocarbon transcription factor activity across multiple lung ILC subsets. Overall, using an airway disease model that develops after occupational and environmental exposures, we demonstrate an effective method to better understand heterogenous ILC subset activation.

immunology↗

Multi-step engineered adeno-associated virus enables whole-brain mRNA delivery

Adeno-associated viruses (AAVs) are commonly used vectors for DNA delivery in gene therapy. Here we developed a system that enables the AAV shell to package mRNAs by multi-step introduction of RNA-packaging components and modification of AAV Rep proteins. The resultant mRNA-carrying AAVs (RAAVs) retained most properties of conventional AAVs, including capsid composition, virus morphology, and tissue tropism. These RAAVs could mediate mRNA transfer into target cells and tissues, leading to transient expression of the functional protein. Importantly, intravenously injected RAAVs efficiently crossed the blood-brain barrier (BBB) and infected the whole mouse brain. Thus, the DNA viral vector could be modified for RNA delivery, and our RAAV represents the first highly efficient BBB-crossing mRNA delivery system that could be used for therapeutic purposes via whole-brain infection.

bioengineering↗

scRNA-seq revealed the rules for CDR3 length pairing in TCR beta and alpha chains and BCR heavy and light chains in human and mice

The binding of T cell receptor (TCR)/B cell receptor (BCR) CDR3 with linear or conformational epitopes is a prerequisite for the adaptive immune response. The rules for CDR3 length pairing and the amino acid (AA) distributions in the prioritized rearrangement of the {beta} chain (or heavy chain) and subsequent rearrangement of the chain (or light chain) during the process of germline V(D)J gene rearrangement and self-tolerance selection to form the T- or B-cell CDR3 repertoire are currently unknown. Single-cell VDJ sequencing can provide abundant information on CDR3 sequences in paired chains. In this study, the paired-chain CDR3 sequences of central and peripheral T and B cells in humans and mice were analyzed according to single-cell VDJ sequencing data. This is the first study to find that T cells with {beta} chains longer than paired chains and B cells with heavy chains longer than paired light chains have absolute advantages. The proportion of T cells with length differences of three or more AAs between paired chains in CDR3 in humans was significantly higher than that in mice, and the proportion of B cells with length differences of six or more AAs between paired chains in CDR3 in humans was significantly higher than that in mice. The CDR3 length range of the {beta} chain was narrower than that of the chain, while the heavy chain had a much wider range than the light chain. The CDR3 length in human TCRs and BCRs was greater than that in mice. Extreme length differences were found between paired chains in both human and mouse T and B cells. There were significant differences in the range of pairing length, AA distribution, hydrophobicity, and polarity of the paired-chain CDR3 region in 5 chains ({beta}, , H, {kappa}, and {lambda}). Human TCR and BCR paired CDR3 sequences exhibited greater plasticity than those of mice. This study reveals new ideas about the molecular mechanisms of TCR and BCR responses to different antigenic epitopes. Our innovative findings offer novel perspectives and techniques for examining V(D)J rearrangement and selection mechanisms in T and B cells. These advancements enable us to analyze antigenic epitopes targeted by TCRs and BCRs, and further, to explore the genetic evolution of T and B cell responses across diverse animal species. Graphical AbstractscRNA-seq the TCR and BCR CDR3 repertoires of 35 samples from the central and peripheral tissues of humans and mice. It provides an opportunity to reveal the rules for CDR3 length pairing in TCR beta and alpha chains and BCR heavy and light chains. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=45 SRC="FIGDIR/small/596201v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@11982edorg.highwire.dtl.DTLVardef@1e2d1aaorg.highwire.dtl.DTLVardef@33200dorg.highwire.dtl.DTLVardef@7d61b1_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Development of a Two-Leaf Photosynthetic Model Sensitive to Chlorophyll and Its Coupling with a Wheat Growth Model

Crop growth models (CGMs) commonly simulates the response of photosynthetic rate to nitrogen (N) dynamic by calculating critical N concentration. However, critical N concentration makes it hard to describe the physiological effect of N dynamic on photosynthesis. Meanwhile, the effect of diffuse light on photosynthesis was limited in previous studies. In this study, we introduced a Two-leaf Photosynthetic Model Sensitive to Chlorophyll Content (TPMSCC) and coupled it with the crop growth model (WheatGrow) to enhance our understanding of how N dynamic and diffuse light affects photosynthesis. By coupling the Farquhar-von Caemmerer-Berry (FvCB) C3 photosynthesis model with a canopy radiative transfer model (PROSAIL), TPMSCC simulated the light interception of direct and diffuse light, and employed leaf chlorophyll content (LCC) to simulate the light absorption and electron transfer rate of leaves. Result showed that TPMSCC well simulated the light absorption of the wheat canopy and found the canopy photosynthetic rate benefited from the increase of diffuse radiation fraction (DRF) except for when the condition of a dense canopy at a high solar zenith angle was present. Research found the logarithmic and linear relationships of LCC to the initial light use efficiency ([a]) and the maximum photosynthetic rate (Amax), respectively, which followed the field measurements. Additionally, the optimized WheatGrow model outperforms its predecessor in describing the response of N application rate on photosynthesis.

biophysics↗

Androgen receptor-negative prostate cancer is vulnerable to SWI/SNF-targeting degrader molecules

Proteolysis targeting chimera (PROTAC) therapies degrading SWI/SNF ATPases offer a novel approach to interfere with androgen receptor (AR) signaling in AR-dependent castration-resistant prostate cancer (CRPC-AR). To explore the utility of SWI/SNF therapy beyond AR-sensitive CRPC, we investigated SWI/SNF-targeting agents in AR-negative CRPC. SWI/SNF targeting PROTAC treatment of cell lines and organoid models reduced the viability of not only CRPC-AR but also WNT-signaling dependent AR- negative CRPC (CRPC-WNT). The CRPC-WNT subgroup represents 11% of around 400,000 cases of CRPC worldwide who die yearly of CRPC. We discovered that SWI/SNF ATPase SMARCA4 depletion interfered with the master transcriptional regulator TCF7L2 (TCF4) in CRPC-WNT. Functionally, TCF7L2 maintains proliferation via the MAPK signaling axis in this subtype of CRPC. These data suggest a mechanistic rationale for interventions that perturb the DNA binding of the pro-proliferative TCF7L2 transcription factor (TF) and/or direct MAPK signaling inhibition in the CRPC-WNT subclass of advanced prostate cancer. Statement of significanceAndrogen receptor (AR)-negative prostate cancer (PCa) remains a clinical challenge due to the lack of targeted therapeutic options. Here, we identified a lineage-defining molecular axis in a subtype of AR- negative PCa, accounting for around 10% of castration-resistant PCa (CRPC) that can be interfered with by SWI/SNF-targeting agents.

cancer biology↗