Palmitoylation-related gene expression and its prognostic value in ovarian cancer: insights into immune infiltration and therapeutic potential.

Background: Palmitoylation, a key post-translational modification, plays a significant role in ovarian cancer (OV) progression. However, the impact of palmitoylation-related genes on genomic instability, immune infiltration, and therapeutic response in OV remains poorly understood. This study aimed to investigate these factors to facilitate risk stratification and therapeutic intervention, providing insights into personalized treatment strategies.

Methods: Data from TCGA and GEO were utilized to develop a prognostic model based on palmitoylation-related genes. Differential expression, functional enrichment, and immune infiltration analyses were performed. Immune cell composition and pathway activities in different risk groups were assessed using CIBERSORT and ssGSEA algorithms. Immunotherapy response was predicted using TIDE and SubMap, while drug sensitivity differences were evaluated using the GDSC database.

Results: Univariate, LASSO, and multivariate Cox regression analyses identified palmitoylation-related genes with significant prognostic value. The prognostic model effectively stratified patients into high- and low-risk groups, demonstrating significant survival differences. Immune infiltration analysis revealed distinct immune cell compositions and functions between risk groups. Low-risk patients exhibited higher immune scores and increased expression of immune checkpoints (PD-1, CD274, CTLA4), suggesting greater response to immunotherapy. Drug sensitivity analysis identified compounds with differential efficacy between risk groups, highlighting potential targeted treatment options.

Conclusion: Palmitoylation-related genomic features significantly influence OV progression and the immune landscape, offering potential for improved risk stratification and informing immunotherapy strategies to enhance patient outcomes.