Biology subjects

He, Z.

Publications and source records attributed to He, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Dynamic early recruitment of GAK-Hsc70 regulates coated pit maturation

Clathrin-mediated endocytosis (CME) is the process by which clathrin assembles on the plasma membrane to form clathrin-coated pits (CCPs), which then invaginate, accumulate cargo and are released by fission from the membrane to form clathrin-coated vesicles (CCVs). A transition of nascent CCPs from flat-to-curved has been observed by various methods. However, what drives this transition remains unknown and controversial. GAK and its chaperone protein, Hsc70, are well-known to mediate clathrin release from CCVs and several studies have observed a late burst of GAK recruitment as CCVs form. Other studies have proposed that early recruitment of GAK-Hsc70 could function to provide the necessary energy source to remodel nascent flat clathrin lattices, replacing hexagons with pentagons and enabling a gain of curvature and invagination of the growing CCP; however, direct functional evidence is lacking. Here we show that GAK knockdown inhibits CCP formation and invagination. Furthermore, mutations in the J domain of GAK that abolish Hsc70 recruitment to and activation at CCPs, lead to the accumulation of GAK at CCPs, hinder CCP stabilization and invagination and result in a striking increase in the proportion of short-lived, abortive CCPs. These findings support the hypothesis that GAK-Hsc70 promotes the turnover and remodeling of nascent clathrin assemblies required for curvature development during CME. Significance StatementGAK and its chaperone protein, Hsc70, are known to be recruited to clathrin-coated vesicles (CCVs) to mediate clathrin uncoating. Previous studies have proposed that early recruitment of GAK-Hsc70 to CCPs could function to remodel nascent flat clathrin lattices, replacing hexagons with pentagons and enabling a gain of curvature of the assembling polymeric coat. However, there are conflicting views, and direct functional evidence is lacking. Here we show that GAK knockdown inhibits CCP formation and invagination. A detailed domain-specific mutational analysis of GAK pinpointed the importance of J domain-Hsc70 interactions in regulating crucial early steps of CME including CCP stabilization and invagination. These findings support a hypothesis that GAK-Hsc70 promotes turnover of clathrin at nascent CCPs required for curvature development.

cell biology↗

bioRxiv2025

Information Shielding Through Neural Deactivation: A Fundamental Mechanism of Human Information Processing

Information processing is a core issue in cognitive neuroscience. The brain can either accept or shield information. However, information shielding has traditionally been regarded as a byproduct of other cognitive processes that prepare brain areas for activation, with the accompanying brain deactivation seen as merely supportive. Here, we offer an alternative perspective, demonstrating that people can directly perform information shielding without engaging other cognitive processes. Using information shielding as a novel investigative lens, we provide direct evidence that deactivation serves as a primary mechanism in its own right. We found that information shielding was characterized by a deactivation-dominant neural dynamic, with initial executive control region activation giving way to increased sensory region deactivation, especially after a 3-second boundary. Neural decoding results further confirmed this deactivation trend. This deactivation pattern was consistent across both auditory and visual modalities. Furthermore, non-invasive brain stimulation demonstrated a causal relationship between the deactivation pattern and information shielding, and we found that this deactivation mechanism extended to general unnecessary information processing, regardless of whether the necessity was determined objectively or subjectively. This challenges the conventional emphasis on activation as the primary mode of information processing and opens new fundamental avenues for understanding inhibitory cognitive processes.

neuroscience↗

bioRxiv2025

A comprehensive benchmark and guide for sequence-function interpretable deep learning models in genomics

The development of sequence-based deep learning methods has greatly increased our understanding of how sequence determines function. In parallel, numerous interpretable algorithms have been developed to address complex tasks, such as elucidating sequence regulatory syntax and analyzing non-coding variants from trained models. However, few studies have systematically compared and evaluated the performance and interpretability of these algorithms. Here, we introduce a comprehensive benchmark framework for evaluating sequence-to-function models. We systematically evaluated multiple models and DNA language foundation models using 369 ATAC-seq datasets, employing diverse training strategies and evaluation metrics to uncover their critical strengths and limitations. Our benchmark study highlights that different model architectures and interpretability methods are better suited to specific scenarios. Negative samples derived from naturally inactive regions outperform synthetic sequences, whereas single-cell tasks require specialized models. Additionally, we demonstrate that interpretable sequence-function models can complement traditional sequence alignment methods in studying cross-species enhancer regulatory logic. We also provide a pipeline to help researchers select the optimal sequence-function prediction and interpretability algorithms.

bioinformatics↗

bioRxiv2024

The Impact of Coiled-Coil Domains on the Phase Behavior of Biomolecular Condensates

Spatial organization is fundamental to biological systems, with biomolecular condensates as a key subset. Many studies show that folded domains play important roles in condensate formation by facilitating interactions. However, little is known about how the presence of large structured elements impacts condensate formation. Using coarse-grained simulations, we investigated a model system of two multivalent proteins, one containing a coiled-coil domain (CCD), which undergoes liquid-liquid phase separation (LLPS). We found that CCDs promote LLPS by preventing loop-closure defects, enabling protein networking. Replacing the CCD with a flexible linker abolishes LLPS due to formation of oligomeric clusters. There is a critical length of the CCD where the system rapidly changes from no LLPS to LLPS at low concentrations. This highlights their potential in regulating condensate formation and properties. This study provides insights into the phase behavior of biomolecular condensates and offers a framework for designing synthetic condensates with tunable phase behaviors.

biophysics↗

bioRxiv2024

Modest functional diversity decline and pronounced composition shifts of microbial communities in a uranium-contaminated aquifer

BackgroundMicrobial taxonomic diversity declines with increased environmental stress. Yet, few studies have explored whether phylogenetic and functional diversities track taxonomic diversity along the stress gradient. Here, we investigated bacterial communities within an aquifer in Oak Ridge, Tennessee, USA, which is characterized by a broad spectrum of stressors, including extremely high levels of nitrate, heavy metals like cadmium and chromium, radionuclides such as uranium, and extremely low pH (<3). ResultsBoth taxonomic and phylogenetic -diversities were reduced in the most impacted wells, while the decline in functional -diversity was modest and statistically insignificant, indicating a more robust buffering capacity to environmental stress. Differences in functional gene composition (i.e., functional {beta}-diversity) were pronounced in highly contaminated wells, while convergent functional gene composition was observed in uncontaminated wells. The relative abundances of most carbon degradation genes were decreased in contaminated wells, but genes associated with denitrification, adenylylsulfate reduction, and sulfite reduction were increased. Compared to taxonomic and phylogenetic compositions, environmental variables played a more significant role in shaping functional gene composition, suggesting that niche selection could be more closely related to microbial functionality than taxonomy. ConclusionsOverall, we demonstrated that despite a reduced taxonomic -diversity, microbial communities under stress maintained functionality underpinned by environmental selection.

microbiology↗

bioRxiv2024

Divergent Visuomotor Strategies in Teleosts: Neural Circuit Mechanisms in Zebrafish and Danionella cerebrum

Many animals respond to sensory cues with species-specific coordinated movements to successfully navigate their environment. However, the neural mechanisms that support diverse sensorimotor transformations across species with distinct navigational strategies remain largely unexplored. By comparing related teleost species, zebrafish (Danio rerio, ZF) and Danionella cerebrum (DC), we investigated behavioral patterns and neural architectures during the visually guided optomotor response (OMR). Closed-loop behavioral tracking during visual stimulation revealed that larval ZF employ burst-and-glide locomotion, while larval DC display continuous, smooth swimming punctuated with sharp directional turns. Although DC achieve higher average speeds, they lack the direction-dependent velocity modulation observed in ZF. Whole-brain two-photon calcium imaging and tail tracking in head-fixed fish reveals that both species exhibit direction-selective motion encoding in homologous regions, including the retinorecipient pretectum, with DC exhibiting fewer binocular, direction-selective neurons overall. Kinematic analysis of head-fixed behavior reveals that DC sustain significantly longer directed swim events across all stimuli than ZF, highlighting the divergent visuomotor strategies, with ZF reducing tail movement duration in response to oblique, turn-inducing stimuli. Lateralized motor-associated neural activity in the medial and anterior hindbrain of both species suggests a shared circuit motif, with distinct neural circuits that independently control movement vigor and direction. These findings highlight the diversity in visuomotor strategies among teleost species, underscored by shared sensorimotor neural circuit motifs, and establish a robust framework for unraveling the neural mechanisms driving continuous and discrete visually guided locomotion, paving the way for deeper insights into vertebrate sensorimotor functions. Research HighlightsO_LILarval DC exhibit faster swimming than ZF, matching the direction of visual motion. C_LIO_LIDC execute OMR in smooth, curved swimming patterns, interspersed with sharp directional turns. C_LIO_LIZF and DC share similar visuomotor neural architecture, recruiting pretectal and hindbrain regions. C_LIO_LIZF and DC demonstrate lateralized encoding of turns, particularly in medial hindbrain neurons. C_LI In BriefLarval Danionella cerebrum respond to global visual motion cues in smooth, low-angle swimming patterns, interspersed with sharp directional turns, swimming consistently faster than zebrafish. Fouke et al. use behavioral tracking of freely moving and head fixed fish to reveal an evolutionarily conserved visuomotor neural architecture transforming visual motion cues into species-specific locomotor behaviors. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/624938v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@13076f4org.highwire.dtl.DTLVardef@d18dc8org.highwire.dtl.DTLVardef@1b35025org.highwire.dtl.DTLVardef@152d2f0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

neuroscience↗

bioRxiv2024

Accurate structure prediction of immune proteins using parameter-efficient transfer learning

Accurate prediction of immune protein structures is crucial for understanding the immune system and advancing immunotherapy development. While deep learning methods have significantly advanced protein structure prediction by extracting evolutionary constraints from homologous sequences of a target protein, they struggle with immune proteins due to the limited number of known structures and the lack of homologous sequences in hypervariable regions. To address this challenge, we propose ImmuneFold, a transfer learning approach that fine-tunes ESMFold specifically for immune proteins. We leverage low-rank adaption (LoRA), a parameter-efficient fine-tuning technique that requires considerably less memory and substantially fewer parameters. Evaluations on various immune proteins, including T-cell receptors, antibodies, and nanobodies, demonstrate that ImmuneFold outperforms existing methods in prediction accuracy. Furthermore, we apply ImmuneFold to develop a zero-shot protocol for TCR-epitope binding prediction. Unlike previous supervised methods suffering from severe overfitting due to limited experimental binding data, our approach first predicts TCR-epitope structure using ImmuneFold and then directly estimates the binding affinity by calculating Rosseta energy. Evaluations on experimental binding datasets suggest that our method is robust and accurate in predicting TCR-epitope binding. In summary, ImmuneFold demonstrates accurate predictions of immune protein structures and TCR-epitope binding, highlighting its potential to advance the development of immunotherapies.

bioinformatics↗

bioRxiv2024

Image-based DNA Sequencing Encoding for Detecting Low-Mosaicism Somatic Mobile Element Insertions

Active LINE-1 (L1), Alu, and SVA mobile elements in the human genome are capable of retrotransposition, resulting in novel mobile element insertions (MEIs) in both germline and somatic tissues. Detecting MEIs through DNA sequencing relies on supporting reads overlapping MEI junctions; however, artifacts from DNA amplification, sequencing, and alignment errors produce numerous false positives. Systematic detection of somatic MEIs, particularly those with low mosaicism, remains a significant challenge. Previous methods had required a high number of supporting reads which limits the detection sensitivity, or human inspections that are susceptible to biases. Here, we developed RetroNet, an algorithm that encodes MEI-supporting sequencing reads into images, and employs a deep neural network to identify somatic MEIs with as few as two reads. Trained on extensive and diverse datasets and benchmarked across various conditions, RetroNet surpasses previous methods and eliminates the need for extensive manual examinations. The RetroNet analysis on the Illumina sequencing of 161x or 195x of a cancer cell line achieved an average precision of 0.885 and recall of 0.579 for detecting somatic L1 insertions that are present in as few as 1.79% of the cells. Additionally, we demonstrated that RetroNet is effective for analyzing highly degraded DNA, such as circulating tumor DNA. RetroNet is applicable to the rapidly generated short-read sequencing data and has the potential to provide further insights into the functional and pathological implications of somatic retrotranspositions.

genomics↗

bioRxiv2024

Systemic inflammation and lymphocyte activation precede rheumatoid arthritis

Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a critical subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical at-risk state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified systemic inflammation, proinflammatory-skewed B cells, expanded Tfh17-like cells, epigenetic bias in naive T cells, TNF+IL1B+ monocytes resembling a synovial macrophage population, and CD4 T cell transcriptional features resembling those suppressed by abatacept (CTLA4-Ig) in RA patients. Our findings characterize pathogenesis prior to clinical diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity. We provide a suite of tools at https://apps.allenimmunology.org/aifi/insights/ra-progression/ to facilitate exploration and enhance accessibility of this extensive dataset. One Sentence SummaryACPA+ at-risk individuals show RA-like inflammation and multi-compartment immune dysregulation during transition to clinically active RA

immunology↗

bioRxiv2024

DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) advances RNA biology but is limited by relatively low basecalling accuracy, low throughput, yet high RNA input and costs. Here we introduce a novel DRS toolkit, DEMINERS, which integrates an RNA multiplexing experimental workflow, a machine-learning barcode classifier based on Random Forest and a novel basecaller built on an optimized convolutional neural network providing an additional species-specific training module. With the increased accuracy in barcode classification and basecalling, DEMINERS can demultiplex up to 24 samples and the required RNA input and running time are both substantially reduced. We demonstrated the applications of DEMINERS in clinical metagenomics, cancer transcriptomics and parallel comparison of transcriptomic features in different biological conditions, revealing altered airway microbial diversity in COVID-19 and a potential role of m6A in increasing transcriptomic diversity in glioma and the mature blood-stage of malaria parasites. Overall, DEMINERS is a simple, robust, high-throughput DRS method for accurately estimating transcript levels, poly(A) lengths, and mutation and RNA modification heterogeneity at single-read level, with minimal sequencing biases.

bioinformatics↗

bioRxiv2024

Multi-omics investigation of spontaneous T2DM macaque reveals gut microbiota promote T2DM by up-regulating the absorption of excess palmitic acid

Although gut microbiota and lipid metabolites have been suggested to be closely associated with type 2 diabetes mellitus (T2DM), the interactions between gut microbiota, lipid metabolites and the host in T2DM development remains unclear. Rhesus macaques may be the best animal model to investigate these relationships given their spontaneous development of T2DM. We identified eight spontaneous T2DM macaques and conducted a comprehensive study investigating the relationships using multi-omics sequencing technology. Our results from 16S rRNA, metagenome, metabolome and transcriptome analyses identified that gut microbiota imbalance, tryptophan metabolism and fatty acid {beta} oxidation disorders, long-chain fatty acid (LCFA) accumulation, and inflammation occurred in T2DM macaques. We verified the accumulation of palmitic acid (PA) and activation of inflammation in T2DM macaques. Importantly, mice transplanted with spontaneous T2DM macaque fecal microbiota and fed a high PA diet developed prediabetes within 120 days. We determined that gut microbiota mediated the absorption of excess PA in the ileum, resulting in the accumulation of PA in the serum consequently leading to T2DM in mice. In particular, we demonstrated that the specific microbiota composition was probably involved in the process. This study provides new insight into interactions between microbiota and metabolites and confirms causative effect of gut microbiota on T2DM development.

microbiology↗

bioRxiv2024

Global transcription factors analyses reveal hierarchy and synergism of regulatory networks and master virulence regulators in Pseudomonas aeruginosa

The transcription factor (TF) regulatory network in Pseudomonas aeruginosa is complex and involves multiple regulators that respond to various environmental signals and physiological cues by regulating gene expression. However, the biological functions of at least half of its 373 putative TFs remain uncharacterised. Herein, chromatin immunoprecipitation sequencing (ChIP-seq) was used to investigate the binding sites of 172 TFs in the P. aeruginosa PAO1 strain. The results revealed 81,009 significant binding peaks in the genome, more than half of which were located in the promoter regions. To further decode the diverse regulatory relationships among TFs, a hierarchical network was assembled into three levels: top, middle, and bottom. Thirteen ternary regulatory motifs revealed flexible relationships among TFs in small hubs, and a comprehensive co-association atlas was established, showing the enrichment of seven core associated clusters. Twenty-four TFs were identified as the master regulators of virulence-related pathways. The pan-genome analysis revealed the conservation and evolution of TFs in P. aeruginosa complex and other species. A Web-based database combining existing and new data from ChIP-seq and the high-throughput systematic evolution of ligands by exponential enrichment was established for searching TF-binding sites. This study provides important insights into the pathogenic mechanisms of P. aeruginosa and related bacteria and is expected to contribute to the development of effective therapies for infectious diseases caused by this pathogen.

microbiology↗

bioRxiv2024

Continual integration of single-cell multimodal data with MIRACLE

Single-cell sequencing technologies have revolutionized our understanding of cellular heterogeneity and facilitated the construction of multi-omics cell atlases via data integration. However, updating these atlases with new data conventionally requires reintegration of all data and is computationally intensive, hindering timely updates and dynamic adjustments in biological and medical research. To address this challenge, we present Multimodal Integration with Continual Learning (MIRACLE), a novel online learning framework for the adaptive and efficient integration of single-cell multimodal data. MIRACLE employs dynamic architectures and data rehearsal strategies to support continual learning, allowing diverse data to be integrated while minimizing information loss over time. Our evaluations demonstrate that MIRACLE achieves accurate online integration with reduced computational requirements, effectively updating and expanding atlases with new cross-tissue and cross-modal data, and precisely identifying novel cell types and transferring labels across datasets. MIRACLE provides an efficient and flexible tool for single-cell community to integrate, share and explore biological knowledge from single-cell multimodal data.

bioinformatics↗

bioRxiv2024

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair for somatic benchmarks

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

genomics↗

bioRxiv2024

Genetic code expansion reveals site-specific lactylation in living cells reshapes protein function

Still in its infancy, the functions of lactylation remain elusive. To address this, we established a comprehensive workflow for lactylation studies that integrates the discovery of lactylation sites with proteomics, the expression of site-specifically lactylated proteins in living cells via genetic code expansion (GCE), and the evaluation of the resulting biological consequences. Specifically, we developed a wet-and-dry-lab combined proteomics strategy, and identified highly conserved lactylation at ALDOA-K147. Driven by its potential biological significance, we site-specifically expressed this lactylated ALDOA in mammalian cells and interrogated the biological changes. We discovered that it not only inhibited enzyme activity but also elicited gain-of-function effects----it dramatically reshaped the functionality of ALDOA by improving stability, enhancing nuclear translocation and affecting gene expression. Further, we demonstrated broad applicability of this workflow to study distinct histone lactylation sites. Together, we anticipate its wide uses in elucidating causative links between site-specific lactylation and target-centric or cell-wide changes.

molecular biology↗

bioRxiv2024

Complete Chloroplast Genome Sequence and Phylogenetic Analysis of Camellia sinensis sp. Baihaozao

Baihaozao (Camellia sinensis sp. Baihaozao) is esteemed in the domain of tea plant cultivation for its early harvest period, profusion of bud trichomes, and exceptional suitability for tea processing. Nevertheless, the intricate phylogenetic relationships among species within this genus remain ambiguous, primarily due to the limited availability of genomic data. This study endeavors to comprehensively investigate the genomic resources of Baihaozao by sequencing, assembling, and annotating its entire chloroplast (cp) genome. The sequencing results indicated that the total length of the Baihaozao cp genome is 157,052 base pairs (bp), with an overall guanine-cytosine (GC) content of 37.30%. The genome exhibits a typical quadripartite structure, consisting of a large single-copy region (LSC) of 86,586 bp, a small single-copy region (SSC) of 18,227 bp, and a pair of inverted repeats (IRs) totaling 52,162 bp. A total of 133 genes were identified within this genome, including 8 ribosomal RNA (rRNA) genes, 37 transfer RNA (tRNA) genes, 87 protein-coding genes, and 1 pseudogene. Furthermore, the study identified 157 simple sequence repeats (SSRs) and 90 long repeat sequences. Analysis of codon usage bias indicated that codons encoding leucine (Leu) were the most frequently utilized, whereas those encoding cysteine (Cys) were the least utilized. Examination of nucleotide diversity within the Baihaozao cp genome revealed five highly variable regions with elevated Pi values (rps19, rpl32, ndhF, rpl22, matK), suggesting their potential utility as molecular markers. Phylogenetic analysis of 20 cp genomes of the Theaceae family indicated a close evolutionary relationship between Baihaozao and Camellia sinensis OL450428.1. This study not only provides valuable data support for elucidating the maternal origin of cultivated Camellia species but also holds significant scientific implications for further exploring the phylogenetic relationships and germplasm resource utilization of Camellia plants.

genomics↗

bioRxiv2024

Different Roles of D1/D2 Medium Spiny Neurons in the Nucleus Accumbens in Pair Bond Formation of Male Mandarin Voles

The mesolimbic dopamine (DA) system has been implicated in pair bond formation. However, involvements of DA release, real time activities, and electrophysiological activities of D1/D2 medium spiny neurons (MSNs) in the nucleus accumbens (NAc) shell in pair bonding remain unclear. This work verified that male mandarin voles after pair bonding released higher levels of DA in the NAc shell and displayed higher levels of D1 MSNs activity and lower levels of D2 MSNs activity upon sniffing their partners compared to upon sniffing an unknown female. Moreover, pair bonding induced differential alterations in both synaptic plasticity and neuronal intrinsic excitability in both D1 MSNs and D2 MSNs. In addition, chemogenetic inhibition of ventral pallidum (VP) -projecting D2 MSNs in the NAc shell enhanced pair bond formation, while chemogenetic activation of VP-projecting D2 MSNs in the NAc shell inhibited pair bond formation. These findings suggest that different neuronal activity of NAc shell D1 MSNs / D2 MSNs regulated by increasing DA release after pair bonding may be a neurobiological mechanism underlying pair bond formation.

neuroscience↗

bioRxiv2024

Acute BRCAness Induction and AR Signaling Blockage through CDK12/7/9 Degradation Enhances PARP Inhibitor Sensitivity in Prostate Cancer

Current treatments for advanced prostate cancer (PCa) primarily target the androgen receptor (AR) pathway. However, the emergence of castration-resistant prostate cancer (CRPC) and resistance to AR pathway inhibitors (APSIs) remains ongoing challenges. Here, we present BSJ-5-63, a novel proteolysis-targeting chimera (PROTAC) targeting cyclin-dependent kinases (CDKs) CDK12, CDK7, and CDK9, offering a multi-pronged approach to CRPC therapy. BSJ-5-63 degrades CDK12, diminishing BRCA1 and BRCA2 expression and inducing a sustained "BRCAness" state. This sensitizes cancer cells to PARP inhibitors (PARPis) regardless of their homologous recombination repair (HRR) status. Furthermore, CDK7 and CDK9 degradation attenuates AR signaling, enhancing its therapeutic efficacy. Preclinical studies, including both in vitro and in vivo CRPC models, demonstrate that BSJ-5-63 exerts potent anti-tumor activity in both AR-positive and AR-negative setting. This study introduces BSJ-5-63 as a promising therapeutic agent that addresses both DNA repair and AR signaling mechanisms, with potential benefits for a board patient population.

cancer biology↗