Biomedical subjects

Jiayi Wang

Publications and source records attributed to Jiayi Wang.

8 recordsLinked to original sources

PubMed2026

Exploring trop-2-directed ADCs monotherapy and combination therapy in pretreated mTNBC: a real-world study.

PURPOSE: Although Trop-2 antibody-drug conjugates (ADCs) have improved outcomes in pretreated metastatic triple-negative breast cancer (mTNBC), resistance remains common and the optimal combination strategy in routine practice is unclear. METHODS: In this retrospective real-world study, we identified patients with mTNBC from a health record-derived database who received sacituzumab govitecan or sacituzumab tirumotecan in the later-line setting between April 2020 and December 2025. Patients received at least two cycles of Trop-2 ADC therapy as monotherapy, plus a PD-1 inhibitor (dual-agent combination), or plus a PD-1 inhibitor and an antiangiogenic agent (triple-agent combination). RESULTS: Descriptively, the ORR was 57.1% in the triple-agent combination group, 38.5% in the dual-agent combination group, and 31.7% in the monotherapy group. Median follow-up was 15.2 months (95% CI, 8.7-20.6). Median progression-free survival (mPFS) was 15.4 months (95% CI, 5.3-NA) in the triple-agent combination group, 10.0 months (95% CI, 4.2-NA) in the dual-agent combination group, and 3.8 months (95% CI, 3.2-5.2) in the monotherapy group. Severe treatment-related toxicity was not increased in the combination groups. Exploratory analyses identified a genomic scoring system that may enable stratification of patients with a higher likelihood of benefiting from the triple-agent combination. CONCLUSION: To our knowledge, this study represents one of the earliest real-world evaluations of this triple-agent strategy in previously treated mTNBC, providing a basis for further prospective validation and biomarker-guided application.

Humans↗

PubMed2025

Decoding Arginine Dimethylation Isomers via pH-Tuned Reactivity with Methylglyoxal: A Chemical Approach for Functional Proteomics.

Arginine dimethylation, encompassing asymmetric and symmetric configurations, represents a fundamental post-translational modification. Despite sharing identical chemical formulas, the two arginine dimethylation isomers exhibit different or even opposite biological effects. Therefore, it is necessary to determine their specific structure before conducting a further biological investigation. However, current methods for arginine dimethylation analysis face great challenges in efficient isomer differentiation, preventing the functional investigation of arginine dimethylation. To overcome this obstacle, herein, we introduce a novel chemical strategy leveraging pH-tuned reactivity with methylglyoxal (MGO) to decode these dimethylation isomers. By utilizing molecular dynamics simulation analysis, we revealed the different chemical reactivities of asymmetrically and symmetrically dimethylated arginine when reacted with MGO at different pH conditions. This property enabled the development of a pH-tuned chemical strategy by combining the MGO reaction with boronate affinity enrichment to simultaneously enrich and differentiate the dimethylation isomers. This strategy can effectively distinguish dimethylated arginine isomers in complex cell samples, and the good feasibility of this strategy was verified by orthogonal validation with the neutral loss. Of the obtained data set, this strategy identified sDMA at R112 of SNRPN, which is confirmed to be modified by PRMT5. Further functional analysis reveals its crucial role in maintaining protein stability and in regulating spliceosome assembly. Overall, by transforming the inherent pH sensitivity of MGO reactions into a powerful analytical tool, our work establishes the first chemical platform for functional proteomic dissection of arginine dimethylation isomers, which paves the way for further regulating mechanism investigations of protein methylation.

Pyruvaldehyde↗

PubMed2025

Marine endophytes: biosynthetic engines for novel bioactive metabolites.

Marine endophytes are prolific sources of structurally diverse secondary metabolites with significant pharmaceutical potential, including anticancer, antimicrobial, and antioxidant agents. However, their commercial utilization is hindered by genomic instability in axenic cultures and inconsistent metabolite yields. While current studies focus on symbiotic interactions and compound discover, critical gaps persist in harnessing their biosynthetic capabilities. This review synthesizes knowledge on marine fungal metabolites and proposes a paradigm shift toward resource-driven research. It addresses strain improvement limitations and suggests strategies like mutagenesis, protoplast fusion, and metabolic engineering to bolster production stability and efficiency. The paper also discusses biological process optimization, including fermentation tuning, inducer and precursor addition, and adsorbent use, to enhance natural product synthesis. By identifying these research gaps and proposing a strategic roadmap, the review advances the stable and scalable production of bioactive metabolites, unlocking the commercial and therapeutic potential of marine endophytic fungi.

bioactive metabolites↗

PubMed2025

DNABERT-S: pioneering species differentiation with species-aware DNA embeddings.

SUMMARY: We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e. DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 28 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. AVAILABILITY AND IMPLEMENTATION: Model, codes, and data are publically available at https://github.com/MAGICS-LAB/DNABERT_S.

Sequence Analysis, DNA↗

PubMed2025

Preoperative Patient Education on Opioid Use and Pain After Surgery: A Randomized Trial.

OBJECTIVE: To evaluate the impact of preoperative analgesic education on postoperative opioid consumption, pain scores, and patient satisfaction with analgesia. BACKGROUND: Effective postoperative pain management is crucial for patient recovery and satisfaction, yet opioid use poses risks of tolerance and addiction. Preoperative patient education offers a potential avenue to mitigate opioid reliance and improve pain management outcomes. METHODS: This single-center randomized trial was conducted at the Cleveland Clinic Main Campus between October 2021 and October 2023. Adult patients scheduled for hip arthroplasty or laparoscopic-assisted abdominal surgery with an ASA physical status of 1 to 4 were eligible. Patients with a history of prolonged opioid use, planned regional block or epidural analgesia, or limited English fluency were excluded. Participants were randomized 1:1 to receive either an analgesic educational video or a generic video about surgery and hospitalization. The primary outcome was opioid consumption during the initial 72 postoperative hours. Secondary outcomes included time-weighted average pain scores and patient satisfaction with analgesia. RESULTS: Among 957 analyzed patients, preoperative analgesic education did not significantly reduce opioid consumption (adjusted ratio of geometric means, 1.01; 95% CI, 0.86-1.18; P =0.890) or improve pain scores (adjusted mean difference, -0.1; 95% CI, -0.3 to 0.2; P =0.617). Patient satisfaction scores also did not differ significantly between groups (adjusted mean difference, -0.1; 95% CI, -0.3 to 0.2; P = 0.611). CONCLUSIONS: Preoperative analgesic education did not result in clinically meaningful reductions in opioid consumption or improvements in pain management outcomes. Further research may explore more intensive educational interventions to optimize postoperative pain management strategies.

Humans↗

PubMed2025

Repression of varicella zoster virus gene expression during quiescent infection in the absence of detectable histone deposition.

Varicella zoster virus (VZV) is a human-specific herpesvirus that establishes latency in peripheral neurons. The only transcripts detected in infected human trigeminal ganglia (TG) obtained shortly after death correspond to the VZV latency-associated transcript (VLT) and associated VLT-ORF63 splice variants. In vitro studies showed that VLT-ORF63 is translated into a protein (pVLT-ORF63) that induces VZV transcription. The mechanisms that lead to this restricted gene expression and the transition to lytic replication remain unknown, partly due to the difficulty of working with human neurons. In this study, we addressed whether the neuroblastoma-derived cell line SH-SY5Y could serve as a model to investigate the mechanisms that lead to repression of VZV gene expression followed by reactivation. VZV productively infected differentiated SH-SY5Y (dSH-SY5Y) whereas incubation with acyclovir (ACV) inhibited virus replication and induced a progressive repression of the virus. Upon removal of ACV there was production of viral particles in a subset of cells, while others contained non-replicating VZV genomes and VLT-containing transcripts for at least 20 days post-infection (dpi). Exogenous expression of VLT-ORF63 induced productive infection, suggesting that the non-replicating and repressed genomes remained functional. Interestingly, histone deposition was undetectable at VZV genomes in quiescently infected dSH-SY5Y cells, pointing to a potential novel mechanism leading to VZV repression in this neuronal setting.

Humans↗

PubMed2024

DNABERT-S: Pioneering Species Differentiation with Species-Aware DNA Embeddings.

We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e., DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 23 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. Model, codes, and data is publicly available at https://github.com/MAGlCS-LAB/DNABERT_S.

Journal Article↗

PubMed2024

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Humans↗