Integrative multi-omics analysis reveals metabolic dysfunction signatures as critical determinants of prostate cancer prognosis and immunosuppressive microenvironments - PubMed
8 hours ago
- #immunosuppression
- #prostate-cancer
- #metabolic-dysfunction
- Metabolic dysfunction signature (MODS) developed via machine learning predicts prostate cancer (PCa) prognosis.
- MODS correlates with adverse outcomes, genomic instability, and therapeutic resistance in PCa.
- High-MODS tumors show increased immunosuppressive features, including M2 macrophage infiltration.
- Single-cell analysis links metabolically dysregulated epithelial cells to poor prognosis and immunosuppression.
- HPRT1 identified as an oncogenic driver in PCa, promoting cell proliferation and migration.
- HPRT1 is a potential biomarker and therapeutic target for PCa intervention and prognosis.