Biomedical subjects

Xiaoyang Zhang

Publications and source records attributed to Xiaoyang Zhang.

3 recordsLinked to original sources

PubMed2026

BRD9 Degraders Unleash GBAF Chromatin Remodeling Activity in Synovial Sarcoma.

UNLABELLED: Synovial sarcoma incorporates the SS18::SSX fusion oncoprotein into GLTSCR1-containing BRG1/BRM and associated factors (GBAF) complexes, which confers a dependency on the GBAF subunit BRD9. However, synovial sarcoma clinical trials with multiple BRD9 degraders failed to achieve clinically impactful remissions. In this study, we identified a mechanistic framework to explain these results. BRD9 depletion served to blunt proliferation in synovial sarcoma harboring minimal genomic alterations, rare in trial participants. In cultured cells, xenografts, and recombinant-purified complexes, BRD9 loss did not affect GBAF assembly. Although BRD9 degradation in synovial sarcoma reduced GBAF enrichment at target loci, BRD9-less complexes maintained or increased chromatin accessibility and associated gene transcription. Biochemical assays with purified recombinant GBAF demonstrated increased nucleosome sliding in the absence of BRD9. Together, these findings show that BRD9 restrains GBAF activity, with BRD9 degradation increasing enzymatic remodeling and target gene expression by fusion oncoprotein-distributed GBAFs in synovial sarcoma. This subtle epigenetic disturbance creates a low hurdle for synovial sarcoma to surpass, limiting the therapeutic efficacy of BRD9 degraders. SIGNIFICANCE: BRD9 represses the GBAF chromatin remodeling complex, which causes enhanced rather than disrupted SS18::SSX complex activity following BRD9 degradation and explains the lack of efficacy of pharmacological BRD9 degraders in synovial sarcoma.

Sarcoma, Synovial↗

PubMed2026

Exploring Endoplasmic Reticulum Stress-Related Genes in Cartilage Defects: Implications for Diagnosis and Therapy.

INTRODUCTION: Cartilage defects (CDs) are orthopedic conditions with limited regenerative potential. This study aimed to identify endoplasmic reticulum (ER) stress-related biomarkers and construct a diagnostic model to enhance the early detection of CD. METHODS: This study analyzed the transcriptomic dataset GSE129147 to identify ER stressrelated differentially expressed genes (ERSRDEGs) between CD and control tissues using the limma package (version 3.58.1). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were employed for functional enrichment. Immune infiltration was assessed using cell-type identification, which involved estimating the relative subsets of RNA transcripts and single-sample gene set enrichment analysis. Diagnostic models were constructed using logistic regression, support vector machine, and least absolute shrinkage and selection operator regression. RESULTS: Twenty ERSRDEGs were identified, with CYBB, ATP6V1A, and TNFRSF12A significantly upregulated in CD samples. GO and KEGG analyses highlighted oxidative stress response and extracellular matrix remodeling as key mechanisms in CD pathogenesis. Immune analysis revealed an increase in regulatory T cells and a reduction in CD8. T cells. TNFRSF12A showed strong immune associations and, together with TWIST1 and ATP6V1A, formed the final preliminary diagnostic model. The preliminary LASSO model achieved satisfactory predictive accuracy (AUC: 0.7-0.9). DISCUSSION: These findings suggest that ER stress and immune imbalance jointly contribute to cartilage degeneration. The identified genes, particularly TNFRSF12A, TWIST1, and ATP6V1A, not only serve as potential biomarkers but also provide preliminary evidence for new mechanistic insights into stress-immune crosstalk in CD. CONCLUSION: This study reveals the key roles of ER stress and immune dysregulation in CDs. Moreover, the ERSRDEG-based diagnostic model provides preliminary bioinformatics evidence and potential molecular indicators for targeted diagnostics and therapies.

Humans↗

PubMed2024

Cis-regulatory control of transcriptional timing and noise in response to estrogen.

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single-cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We found that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Humans↗