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Prevalence and prognostic value of PD-L1 expression and tumor mutational burden in persistent, recurrent, or metastatic cervical cancer

Min‐Hyun Baek, Lei Chen, Cumhur Tekin, Răzvan Cristescu, Xiao Yang Jin, Changxia Shao, Soo Yeon Ihm, Petar Jelinic, Jeong‐Yeol Park

2024Journal of Gynecologic Oncology16 citationsDOIOpen Access PDF

Abstract

OBJECTIVE: To evaluate the prevalence and prognostic role of programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB) in patients with non-immunotherapy-treated advanced cervical cancer. METHODS: Clinical data were retrospectively collected from medical records between January 1, 2008, and December 31, 2016, at Asan Medical Center (Korea); archived tumor samples were assessed for PD-L1 expression (combined positive score [CPS] ≥1) and TMB (≥175 mutations/exome). Overall survival (OS) was defined as time from advanced diagnosis or initiation of first-line or second-line systemic therapy until death/last follow-up. The association of OS with PD-L1 expression and TMB were analyzed using the log-rank test and Cox proportional hazards model adjusted for covariates. RESULTS: Of 267 patients, 76.0% had squamous cell carcinoma (SCC), 24.0% had adenocarcinoma (AC)/adenosquamous carcinoma (ASC), 64.4% had PD-L1 CPS ≥1, and 32.6% had TMB ≥175 mutations/exome. PD-L1 CPS ≥1 and TMB ≥175 mutations/exome were more prevalent in SCC than in AC/ASC (73.9% and 37.2% vs. 34.4% and 17.7%). There was no association between OS and PD-L1 expression (CPS ≥1 vs. <1: adjusted hazard ratio [HR]=1.14; 95% confidence interval [CI]=0.84-1.53 from advanced diagnosis); OS trended shorter for the subgroup with TMB ≥175 versus <175 mutations/exome (adjusted HR=1.29; 95% CI=0.95-1.75). CONCLUSION: Retrospective analysis of non-immunotherapy-treated patients with advanced cervical cancer demonstrated a higher prevalence of PD-L1 CPS ≥1 and TMB ≥175 mutations/exome in SCC versus AC/ASC. PD-L1 CPS ≥1 was not associated with OS; TMB ≥175 mutations/exome showed a trend toward shorter OS. Additional studies are needed to confirm these findings.

Topics & Concepts

MedicineCervical cancerOncologyInternal medicineValue (mathematics)Metastatic tumorCancerMetastasisMachine learningComputer scienceEndometrial and Cervical Cancer TreatmentsCervical Cancer and HPV ResearchCancer Immunotherapy and Biomarkers