PD-1 and LAG-3 were optimal combination of immune checkpoints for predicting poor clinical outcomes of patients with ovarian cancer
Background
Although immune checkpoint blockade (ICB) therapy has transformed the therapeutic landscape for ovarian cancer (OC), the predictive utility of immune checkpoint (IC) expression signatures in stratifying clinical outcomes requires further systematic interrogation.
Methods
Transcriptomic profiles from 147 OC patients within The Cancer Genome Atlas (TCGA) cohort were interrogated to assess the prognostic significance of ICs. These genomic findings were subsequently validated through immunohistochemical analysis of an independent institutional cohort comprising 74 OC tissue specimens.
Results
Both TCGA and validation cohorts demonstrated that elevated expression of PD-1 and LAG-3 correlated with inferior overall survival (OS) in patients with OC. Importantly, among the ICs, PD-1/LAG-3 co-expression emerged as the optimal combinatorial biomarker, independently predicting adverse outcomes [hazard ratio (HR) = 1.74, 95% confidence interval (CI): 1.12-2.70, P < 0.001]. The derived nomogram model incorporating PD-1/LAG3 status, TNM stage, histologic grade, and age generated patient-tailored 1–5 year OS rate estimates. Notably, risk stratification using this model significantly enhanced prognostic precision versus conventional parameters (TNM stage or histologic grade) alone, especially in patients with serous cystadenocarcinoma.
Conclusion
Elevated IC expression correlated with poor OS in OC patients. Specifically, PD-1/LAG-3 co-expression emerged as the optimal prognostic biomarker pair, representing a promising therapeutic target for dual checkpoint blockade strategies in OC.