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Xianping Shi

Publications and source records attributed to Xianping Shi.

2 recordsLinked to original sources

Super enhancer-driven transcriptional reprogramming promotes abiraterone resistance via neuroendocrine transition and ferroptosis evasion in castration-resistant prostate cancer.

Abiraterone resistance represents a major clinical challenge in the management of castration-resistant prostate cancer (CRPC), yet the epigenetic mechanisms that sustain this resistance remain poorly understood. In particular, how super enhancers (SEs) reprogram transcriptional networks to promote this therapy resistance has not been fully elucidated. Here, by integrating chromatin immunoprecipitation sequencing and transcriptome profiling, we identified aberrantly activated oncogenic SEs that drive the transcriptional upregulation of the transcription factors ELF3 and JUNB in abiraterone-resistance CRPC cells. Importantly, SE-driven activation of the ELF3/JUNB axis promotes abiraterone resistance by inducing WNT11-mediated neuroendocrine transition. In parallel, this transdifferentiated state is closely associated with ferroptosis resistance, as evidenced by the upregulation of key ferroptosis-protective genes, including FTH1 and GPX4. In contrast, disruption of the ELF3/JUNB-WNT11 axis markedly restored abiraterone sensitivity and triggered ferroptotic cell death in CRPC cells both in vitro and in vivo. Collectively, our findings highlight targeting SE-driven transcriptional programs as a promising strategy for overcoming abiraterone resistance in CRPC.

Male

CMAtlas: a comprehensive DNA methylation atlas for exploring epigenetic alterations in 34 human cancer types.

MOTIVATION: Aberrant DNA methylation is a fundamental epigenetic hallmark of cancer. However, existing resources often lack technological diversity and comprehensive cancer coverage. Furthermore, most platforms fail to achieve deep multi-omics integration and tend to ignore cancer-type-specific methylation features, limiting their utility in precision oncology and drug discovery. RESULTS: We developed Cancer Methylation Atlas (CMAtlas), a comprehensive platform integrating 13 753 samples across 34 cancer types. By applying technology-tailored pipelines to data from various profiling technologies, we identified 830 725 tumor-specific differentially methylated elements (DMEs) and 1 480 098 differentially methylated regions (DMRs), alongside 1 154 256 cancer-type-specific DMEs and 329 154 DMRs. The platform demonstrates high cross-platform consistency and strong concordance between tumor tissues and cell lines, ensuring the robustness of our findings. All DMEs and DMRs are annotated with multi-omics data (RNA expression, somatic mutations, and chromatin accessibility) and clinical relevance (survival associations and cell-free DNA profiling). We further demonstrate the utility of CMAtlas by identifying prognostic aberrant methylation in colorectal cancer driver genes. AVAILABILITY AND IMPLEMENTATION: CMAtlas is freely accessible at {{https://cmatlas.renlab.cn/}}. The platform offers an intuitive web interface supporting gene-centric and cancer-centric queries, alongside customizable analysis modules designed to facilitate user-specific research needs.

Humans