Objectives: The CLAP trial (NCT03816553) is a multicenter, single-arm, phase II study in patients with metastatic, recurrent, or persistent cervical cancer who were treated with PD-1 inhibitor camrelizumab plus a VEGFR2 inhibitor apatinib. In this study, we performed genomic profiling analysis to identify potential predictive biomarkers for this combination therapy. Methods: Genomic profiling was performed on 32 patients with available biopsy or surgical samples by targeted next-generation sequencing of 425 cancer-related genes. Somatic alterations and tumor mutational burden (TMB) were assessed for their predictive value on objective response rate (ORR), progression-free survival (PFS) and overall survival (OS). The Cancer Genome Atlas (TCGA) public dataset was used for validation. Results: Conclusions: In this study, we uncovered PIK3CA, PTEN, ERBB3, PI3K pathway genes mutations and TMB as novel predictive biomarkers in cervical cancer patients treated with PD-1 inhibitor combination therapy, which might be of great clinical relevance in patient stratification. The CLAP trial (NCT03816553) is a multicenter, single-arm, phase II study in patients with metastatic, recurrent, or persistent cervical cancer who were treated with PD-1 inhibitor camrelizumab plus a VEGFR2 inhibitor apatinib. In this study, we performed genomic profiling analysis to identify potential predictive biomarkers for this combination therapy. Genomic profiling was performed on 32 patients with available biopsy or surgical samples by targeted next-generation sequencing of 425 cancer-related genes. Somatic alterations and tumor mutational burden (TMB) were assessed for their predictive value on objective response rate (ORR), progression-free survival (PFS) and overall survival (OS). The Cancer Genome Atlas (TCGA) public dataset was used for validation. In this study, we uncovered PIK3CA, PTEN, ERBB3, PI3K pathway genes mutations and TMB as novel predictive biomarkers in cervical cancer patients treated with PD-1 inhibitor combination therapy, which might be of great clinical relevance in patient stratification.