ArticleDiscover oncology2026
Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundOvarian cancer (OC) is a highly aggressive malignancy with poor prognosis and limited response to immunotherapy. Ribosomal stress, a cellular response to disrupted ribosome biogenesis, has been increasingly implicated in tumorigenesis and immune regulation, yet its contribution to OC remains unclear.
methodsWe integrated four GEO transcriptomic datasets and identified ribosomal stress related signature genes (RSRGs) through differential expression and functional enrichment analyses. To construct a robust diagnostic model, three machine learning algorithms: LASSO regression, support vector machine recursive feature elimination (SVM-RFE), and random forest were combined. Immune infiltration patterns were evaluated using CIBERSORT, and interpretability analysis was performed using SHAP to determine feature importance. Functional validation of BMP6 was performed in ovarian cancer cell lines by RT-qPCR, Western blot, CCK-8, colony formation, and Transwell assays to evaluate its effects on proliferation, migration, and invasion.
resultsA total of 117 differentially expressed RSRGs were identified, mainly enriched in cytoskeletal regulation, lipid metabolism, proteoglycan signaling, and IL-17 mediated inflammatory pathways. The integrated machine learning approach identified six feature genes (SPP1, MAPK13, LCN2, JUP, DSP, and BMP6). SHAP analysis revealed that SPP1 and DSP had the greatest contributions to the predictive model. Immune profiling revealed increased macrophage M0/M2 and decreased CD8 + T cell infiltration in high-risk samples, with SPP1, MAPK13, and DSP positively correlated with macrophage abundance. Functional assays demonstrated that BMP6 was downregulated in ovarian cancer cells and that its overexpression significantly inhibited proliferation, migration, and invasion.
conclusionsThis study identifies a six-gene ribosomal stress signature linking tumor intrinsic pathways and immune remodeling in OC. BMP6 exerts tumor-suppressive effects, supporting the potential of targeting ribosomal stress and its immune axis as a therapeutic strategy in ovarian cancer.
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