Genomic landscape, immune characteristics, and a prognostic mutation signature of advanced cervical cancer in China (162)

Abstract

Objectives: This study aimed to analyze genomic alteration profiles and immune characteristics of a cohort of Chinese advanced cervical cancer patients to understand why certain patients benefited from molecular targeted therapies, immunotherapy, and their prognostic significance. Methods: PD-L1 expression and clinical-pathologic information from 98 cervical cancer samples were obtained. Cervical cancer data were obtained from The Cancer Genome Atlas (TCGA). Differences in PD-L1 expression and gene mutations between squamous cell carcinoma (SCC) and adenocarcinoma (AC) were analyzed using the Chi-square test or Fisher’s exact test. Differences in gene mutations between our cohort and TCGA cohort were tested by Fisher’s exact test. The relationship between gene mutation and TMB was analyzed by the Mann-Whitney U test. Logistic regression was used to analyze factors influencing TMB-high. Kaplan-Meier survival analyses were applied. Results: Positive PD-L1 expression was significantly higher in cervical SCC than in cervical AC (87% vs 39%, p < 0.001). Frequently mutated genes in cervical cancer included PIK3CA, KMT2D, and KMT2C genes, among others. PIK3CA gene mutation rates were significantly higher in SCC than in AC (p = 0.004). TERT gene mutation rate was significantly higher in our cohort than TCGA cohort (12% vs 1%, p < 0.001). SCC had a significantly higher TMB than AC (p < 0.001). The independent predictors of TMB-high were KMT2C and LRP1B gene mutations (p <0.05). In this study, the median progression-free survival (PFS) was 12.16 months in the PTEN mutant group versus 21.75 months in the wild-type group (p=0.0024). Conclusions: Cervical SCC and AC have different molecular profiling and immune characteristics, suggesting that targeted treatments for SCC and AC patients may improve clinical outcomes. KMT2C and LRP1B gene mutations are independent predictors of TMB-high status in cervical cancer. We have also proposed the prognostic value of PTEN mutation. Objectives: This study aimed to analyze genomic alteration profiles and immune characteristics of a cohort of Chinese advanced cervical cancer patients to understand why certain patients benefited from molecular targeted therapies, immunotherapy, and their prognostic significance. Methods: PD-L1 expression and clinical-pathologic information from 98 cervical cancer samples were obtained. Cervical cancer data were obtained from The Cancer Genome Atlas (TCGA). Differences in PD-L1 expression and gene mutations between squamous cell carcinoma (SCC) and adenocarcinoma (AC) were analyzed using the Chi-square test or Fisher’s exact test. Differences in gene mutations between our cohort and TCGA cohort were tested by Fisher’s exact test. The relationship between gene mutation and TMB was analyzed by the Mann-Whitney U test. Logistic regression was used to analyze factors influencing TMB-high. Kaplan-Meier survival analyses were applied. Results: Positive PD-L1 expression was significantly higher in cervical SCC than in cervical AC (87% vs 39%, p < 0.001). Frequently mutated genes in cervical cancer included PIK3CA, KMT2D, and KMT2C genes, among others. PIK3CA gene mutation rates were significantly higher in SCC than in AC (p = 0.004). TERT gene mutation rate was significantly higher in our cohort than TCGA cohort (12% vs 1%, p < 0.001). SCC had a significantly higher TMB than AC (p < 0.001). The independent predictors of TMB-high were KMT2C and LRP1B gene mutations (p <0.05). In this study, the median progression-free survival (PFS) was 12.16 months in the PTEN mutant group versus 21.75 months in the wild-type group (p=0.0024). Conclusions: Cervical SCC and AC have different molecular profiling and immune characteristics, suggesting that targeted treatments for SCC and AC patients may improve clinical outcomes. KMT2C and LRP1B gene mutations are independent predictors of TMB-high status in cervical cancer. We have also proposed the prognostic value of PTEN mutation.