Related Experiment Video
Updated: Nov 5, 2025
Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Genomic profiling of advanced cervical cancer to predict response to programmed death-1 inhibitor combination
Xin Huang1,2, Minjun He1,2, Hongyu Peng1,2
1Gynecologic Oncololgy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Background:
The Camrelizumab Plus Apatinib in Patients with Advanced Cervical Cancer trial was a single-arm, phase II study that showed promising activity of the programmed death-1 (PD-1) inhibitor camrelizumab plus the vascular endothelial growth factor receptor-2 inhibitor apatinib in patients with advanced cervical cancer. However, the predictive biomarkers for treatment outcomes are unknown. In this study, we aimed to identify potential predictors of treatment response in PD-1 inhibitor combination therapy.
Methods:
Genomic profiling was performed on patients with available biopsy or surgical samples by targeted next-generation sequencing of 425 cancer-related genes in this preplanned, secondary analysis. Somatic alterations, including all non-synonymous mutations, and tumor mutational burden (TMB) were assessed for their predictive values in objective response rate, progression-free survival (PFS), and overall survival (OS).
Results:
A subset of 32 patients was included in this analysis. Top altered genes included PIK3CA (43.8%), STK11 (25%), FBXW7 (15.6%), and PTEN (15.6%). The PI3K/AKT pathway was among the most frequently dysregulated pathways, and its genetic alterations were identified in 68.8% of patients. PIK3CA (PFS HR 0.33, p=0.05; OS HR 0.23, p=0.04) and PTEN (PFS HR 3.71e-09, p=0.05; OS HR 3.64e-09, p=0.08) alterations were associated with improved outcomes. PI3K/AKT pathway genetic alterations showed improved predictive power compared with either PIK3CA or PTEN alterations alone (PFS HR 0.33, p=0.03; OS HR 0.25, p=0.02), while ERBB3 mutations (PFS HR 34.9, p<0.001; OS HR 19.8, p<0.001) correlated with poor survival. TMB-high (≥5 mut/Mb) was associated with prolonged PFS (HR 0.26, p<0.01) and OS (HR 0.31, p=0.05). Multivariate analysis showed ERBB3 mutations (PFS p=0.01, OS p<0.001), PD-L1 positive (PFS p=0.01, OS p=0.05), and high TMB (PFS p=0.01, OS p=0.05) remained significantly associated with survival.
Conclusions:
We uncovered that genetic alterations in PIK3CA, PTEN, ERBB3, and PI3K/AKT pathway, as well as TMB, could be novel predictive biomarkers in patients with cervical cancer treated with PD-1 inhibitor combination therapy.
Trial Registration Number:
NCT03816553.
Insights
Genetic alterations in PIK3CA, PTEN, ERBB3, and PI3K/AKT pathway, along with high tumor mutational burden (TMB), may predict treatment response in advanced cervical cancer patients receiving PD-1 inhibitor combination therapy.
Area of Science:
- Oncology
- Genomics
- Cancer Biomarkers
Background:
- The Camrelizumab Plus Apatinib trial showed promise for advanced cervical cancer.
- Predictive biomarkers for treatment response remain unknown.
- This study aimed to identify predictors for PD-1 inhibitor combination therapy outcomes.
Purpose of the Study:
- Identify potential predictive biomarkers for treatment response.
- Analyze genomic alterations and tumor mutational burden (TMB).
- Correlate genetic markers with objective response rate, progression-free survival (PFS), and overall survival (OS).
Main Methods:
- Genomic profiling using targeted next-generation sequencing of 425 cancer-related genes.
- Assessment of somatic alterations and TMB for predictive value.
- Analysis of a subset of 32 patients from the phase II study.
Main Results:
- PIK3CA, STK11, FBXW7, and PTEN were frequently altered genes.
- PI3K/AKT pathway alterations were found in 68.8% of patients.
- PIK3CA and PTEN alterations, PI3K/AKT pathway alterations, and high TMB were associated with improved survival outcomes.
- ERBB3 mutations correlated with poor survival.
- Multivariate analysis confirmed ERBB3 mutations, PD-L1 positivity, and high TMB as significant survival predictors.
Conclusions:
- Genetic alterations in PIK3CA, PTEN, ERBB3, and the PI3K/AKT pathway are potential predictive biomarkers.
- Tumor mutational burden (TMB) is also a significant predictive biomarker.
- These findings can guide personalized treatment strategies for cervical cancer.
Related Concept Videos
02:50Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
02:57Targeted Cancer Therapies
There are several types of targeted therapies against...