Development and validation of a risk model for effective immune and stromal related signature predicting prognosis of patients with ovarian cancer.

ABSTRACT: The tumor microenvironment (TME) plays a critical role in ovarian cancer (OC) progression, yet the relationship between immune and stromal scores within the TME and prognostic outcomes remains poorly understood. Immune and stromal cell scores were computed using the "estimate" R package, which enabled the assessment of immune and stromal components in OC samples. We then performed univariate and multivariate Cox regression analyses to identify prognostic factors associated with these scores using data from The Cancer Genome Atlas (TCGA). Additionally, LASSO Cox regression were employed to identify key prognostic genes linked to immune infiltration. Our analysis of OC expression data identified 1,667 differentially expressed genes (DEGs) associated with immune and stromal scores. From these

SUBMITTER: Yu Y 

PROVIDER: S-EPMC12075501 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature