Genomic profiling of ovarian clear cell carcinoma in Chinese patients reveals potential prognostic biomarkers for survival

Introduction Ovarian clear cell carcinoma (OCCC) has distinct clinical and molecular features and heterogeneous prognosis. Insights into the somatic genomic abnormalities of OCCC provide the basis for deeper understanding and potential therapeutic avenues. Herein, we performed extensive genomic profiling in Chinese patients to illustrate the mutation landscape and genetic prognostic biomarkers of OCCC. Patients and methods We used targeted DNA sequencing on 61 OCCC cases with a panel of 520 cancer-related genes. Correlations between clinicopathological features and survival were evaluated. Nomogram-based models were constructed to predict progress-free survival (PFS). Results We detected 763 somatic mutations spanning 286 genes. The most frequent genetic alterations, ARID1A (49%) and PIK3CA (48%), were concurrently mutated. Comprehensive copy number alterations (CNAs) were identified in chromosomes 20q13.2 and 8q. Most (73.7%) patients harboured potentially targetable driver mutations. The mean and median tumour mutational burden were 7.0 and 3.0 mutations/Mb, respectively. Microsatellite instability (high) was identified in 8.2% of patients. Mutation of the base-excision repair pathway was significantly higher in patients of stage II/III/IV. ATM mutation was associated with platinum sensitivity (p < .05). Survival analysis identified chr8q CNAs in all patients, PIK3CA mutations in stage I patients and SWI/SNF complex (ARID1A and SMARCA4) mutations in stage II/III/IV patients as potential prognosticators (p < .05). Integration of genetic alterations (SWI/SNF complex mutations, ATM mutations and chr8q CNAs) improved the performance of a nomogram based on tumour stage and residual disease (concordance index 0.75 vs. 0.70, p < .05). Conclusions We described somatic genomic alterations in Chinese OCCC patients and observed different genomic alterations between stage I and stage II/III/IV tumours. Genetic factors may supplement clinical factors in nomogram modelling for PFS prediction. Key Messages We performed extensive genomic profiling in a well-annotated cohort of 61 Chinese ovarian clear cell carcinoma (OCCC) patients. PIK3CA mutations were associated with worse overall survival (OS) in stage I OCCC, and SWI/SNF gene mutations were associated with improved OS in stage II/III/IV disease. We propose an easy-to-use nomogram using clinical factors (tumour stage and residual disease) and genetic alterations (SWI/SNF complex mutations, ATM mutations and chr8q CNAs) to predict the progress-free survival (PFS) of OCCC.