Biology subjects

SUN, Y.

Publications and source records attributed to SUN, Y..

6 recordsLinked to original sources

bioRxiv2026

Systematic toxicological study of PFOS/PFOA co-exposure driving prostate cancer: Core target identification, TME immune remodeling, and combination drug prediction

BackgroundPer- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent organic pollutants ubiquitous in the environment. Epidemiological evidence has closely linked them to an elevated risk of prostate cancer (PCa). However, the precise molecular mechanisms by which combined PFOS/PFOA exposure promotes prostate cancer and their dynamic effects on the tumor microenvironment remain unclear. MethodsThis study constructed a multi-module analytical framework integrating network pharmacology and computational biology: (1) Through ADMET toxicity prediction, multi-database target collection (three-way Venn analysis), panoramic GO/KEGG enrichment, focused androgen receptor (AR) axis analysis, GWAS genetic association validation, protein-protein interaction (PPI) network construction, machine learning-based independent screening, and a relaxed intersection strategy, we systematically identified PFOS/PFOA-prostate cancer core targets. (2) Subsequently, a PFAS-PTS score weighted purely by Cox coefficients was employed to drive gene set variation analysis (GSVA)-based pathway enrichment, tumor microenvironment (TME) deconvolution, ordinary differential equation (ODE)-based kinetic modeling, and drug intervention prediction. ResultsTarget collection identified 100 shared PFOS/PFOA-prostate cancer targets, from which 18 core targets were determined after multi-module screening. These targets were significantly enriched in the AR signaling axis, the PI3K-AKT pathway, and cell cycle regulation. Molecular docking confirmed strong binding affinities of PFOS/PFOA with AR (-9.49/-8.56 kcal/mol), AKT1 (-7.56/-6.93 kcal/mol), and PTEN (-6.36/-6.08 kcal/mol). GSVA revealed that the G2M checkpoint and E2F target gene pathways were significantly upregulated in the high-risk group (padj < 0.001), whereas the androgen response pathway was downregulated (padj = 4.8e-4). TME deconvolution (GSE141445, NNLS) revealed a significantly increased proportion of tumor cells (PCa) (p = 2.4e-4) and markedly reduced CD8+ T cell infiltration (p = 5.7e-4) in the high-risk group, indicating immunosuppressive microenvironment remodeling. ODE-based kinetic modeling confirmed that PFAS promoted tumor cell proliferation and suppressed immune surveillance in a dose-dependent manner. Drug intervention simulation demonstrated that the combination of enzalutamide and Alpelisib achieved optimal tumor cell inhibition (33.9% predicted by the ODE model). ConclusionPFOS/PFOA promote prostate cancer progression primarily through multi-target synergy involving AR axis disruption, PI3K-AKT pathway activation, and cell cycle dysregulation, while reshaping an immunosuppressive tumor microenvironment. The integrative computational framework established in this study provides systematic computational evidence for risk assessment and therapeutic intervention in PFAS-associated prostate cancer.

pharmacology and toxicology↗

bioRxiv2025

A bibliometric analysis of research on the mitochondrial roles in prostate cancer and the virtual design of LONP1 - specific antibodies using the GeoBiologics platform

BackgroundProstate cancer remains one of the most prevalent malignancies among men globally, with its incidence showing an upward trend worldwide. Mitochondria, as central regulators of cellular energy metabolism, play crucial roles in prostate cancer initiation, progression, and drug resistance mechanisms. While mitochondria-targeted therapeutic strategies have emerged as a significant focus in cancer research in recent years, comprehensive bibliometric analyses mapping the evolving landscape of this field remain scarce. This study systematically investigates research trends in mitochondrial-prostate cancer interactions through bibliometric methods, identifying LONP1 as an emerging research focus in mitochondria-related prostate cancer therapy. Building on these findings, we employed artificial intelligence to virtually design a LONP1-specific antibody, proposing novel therapeutic targeting strategies for this field. MethodsUtilizing the Web of Science Core Collection database (2015-2023), we conducted visualization analyses through CiteSpace and VOSviewer to map network relationships among countries, institutions, journals, authors, and keywords. Building on this foundation, a humanized antibody targeting LONP1 was computationally designed and screened through the GeoBiologics platform. ResultsAnalysis of 452 included publications revealed the United States and China as leading contributors in this research domain. The field has progressively transitioned from fundamental mechanistic investigations to clinical applications, particularly focusing on drug resistance mechanisms, and combination therapy. LONP1 was identified as a critical mitochondrial regulator strongly associated with prostate cancer progression. Our AI-designed antibody (Antibody_82) demonstrated superior binding affinity and stability through effective targeting of LONP1s ATP-binding site. ConclusionThis bibliometric study delineates evolving research trends in mitochondrial involvement in prostate cancer. The developed LONP1-targeting antibody shows promising therapeutic potential for castration-resistant prostate cancer (CRPC) patients, potentially offering more effective treatment alternatives.

cancer biology↗

bioRxiv2024

Dimorphic Neural Network Architecture Prioritizes Sexual-related Behaviors in Male C.elegans

Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on the neural network architectures of male and hermaphrodite C. elegans and the association with sexually dimorphic behaviors. We applied graph theory and computational neuroscience methods to systematically discern the features of these two neural networks. Our findings revealed that a small percentage of sexual-specific neurons exerted dominance throughout the entire male neural net-work, suggesting males prioritized sexual-related behavior outputs. Based on the structural and dynamical characteristics of two complete neural networks, sub-networks containing sex-specific neurons and their immediate neighbors, or sub-networks exclusively comprising sex-shared neurons, we predicted dimorphic behavioral outcomes for males and hermaphrodites. To verify the prediction, we performed behavioral and calcium imaging experiments and dissected a circuit that is specific for the increased spontaneous local search in males for mate-searching. Our research sheds light on the neural circuits that underlie sexually dimorphic behaviors in C. elegans, and provides significant insights into the inter-connected relationship between network architecture and functional outcomes at the whole-brain level.

neuroscience↗

bioRxiv2022

Mechanical regulation of Titin N2B-us conformation and its binding to FHL2

The 572 amino acids unique sequence on titin N2B element (N2B-us) is known to regulate the passive elasticity of muscle as an elastic spring. It also serves as a hub for cardiac hypertrophic signaling by interacting with multiple proteins such as FHL1(Sheikh et al, 2008), FHL2(Lange et al, 2002), and Erk2(Perkin et al, 2015). N2B-us is thought to be an intrinsically disordered region. In addition, N2B-us bears force; therefore, the functions of N2B-us are likely regulated by mechanical stretching. In the work, we investigated the conformation of N2B-us as well as its force-dependent interaction with FHL2 using a combination of AlphaFold2 predictions and single-molecule experimental validation. Surprisingly, a stable alpha/beta structural domain (~115 a.a.) was predicted and confirmed in N2B-us, which can be mechanically unfolded at forces greater than 5 pN. More than twenty FHL2 LIM domain binding sites were predicted to spread throughout N2B-us including the regions cryptic in the structural domain. Mechanosensitive binding of FHL2 to N2B-us is revealed in single-molecule manipulation experiments. Together, the results unveil several previously unknown aspects of the N2B-us conformations and its force-dependent interactions with FHL2, which provides new insights into the physiological functions of the force-bearing N2B-us region.

biophysics↗

bioRxiv2022

Genome Enrichment of Rare, Unknown Species from Complicated Microbiome by Nanopore Selective Sequencing

Rare species are vital members of a microbial community, but retrieving their genomes is difficult due to their low abundance. The ReadUntil (RU) approach allows nanopore devices to sequence specific DNA molecules selectively in real-time, which provides an opportunity for enriching rare species. However, there is still a gap in RU-based enriching of rare and unknown species in environmental samples whose community composition is unclear, and many species lack corresponding reference in public databases. Here we present metaRUpore to overcome this challenge. We applied metaRUpore to a thermophilic anaerobic digester (TAD) community, it successfully redirected the sequencing throughput from high-abundance populations to rare species while facilitating the recovery of 41 high-quality metagenome-assembled genomes (MAGs) at low sequencing effort. The simplicity and robustness of the approach make it accessible for labs with moderate computational resources and hold the potential to become the standard practice in future metagenomic sequencing of complicated microbiomes.

bioinformatics↗

bioRxiv2020

Snowball Earths, population bottlenecks, and the evolution of marine photosynthetic bacteria

Prochlorococcus are the most abundant photosynthetic organisms in the modern ocean. A massive DNA loss event occurred in their early evolutionary history, leading to highly reduced genomes in nearly all lineages, as well as enhanced efficiency in both nutrient uptake and light absorption. The environmental landscape that shaped this ancient genome reduction, however, remained unknown. Through careful molecular clock analyses, we established that this Prochlorococcus genome reduction occurred during the Neoproterozoic Snowball Earth climate catastrophe. The lethally low temperature and exceedingly dim light during the Snowball Earth event would have inhibited Prochlorococcus growth and proliferation and caused severe population bottlenecks. These bottlenecks are recorded as an excess of deleterious mutations that accumulated across genomic regions in the descendant lineages. Prochlorococcus adaptation to extreme environmental conditions during Snowball Earth intervals can be inferred by tracing the evolutionary paths of genes that encode key metabolic potential. This metabolic potential includes modified lipopolysaccharide structure, strengthened peptidoglycan biosynthesis, the replacement of a sophisticated circadian clock with an hourglass-like mechanism that resets daily for dim light adaption, and the adoption of ammonia diffusion as an efficient membrane transporter-independent mode of nitrogen acquisition. In this way, the Neoproterozoic Snowball Earth event altered the physiological characters of Prochlorococcus, shaping their ecologically vital role as the most abundant primary producers in the modern oceans.

microbiology↗