AUTHOR=Zhao Songyun , Zhang Xin , Gao Feng , Chi Hao , Zhang Jinhao , Xia Zhijia , Cheng Chao , Liu Jinhui 

TITLE=Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1145797

DOI=10.3389/fendo.2023.1145797

ISSN=1664-2392

ABSTRACT=Background:Ovarian cancer (OC) is one of the common and most malignant gynaecological malignancies in gynaecology. On the other hand, dysregulation of copper metabolism (CM) is closely associated with tumourigenesis and progression. Here, we investigated the impact of genes associated to copper metabolism (CMRGs) on the prognosis of OC, discovered various CM clusters, and built a risk model to evaluate patient prognosis, immunological features, and therapy response.
Methods: 15 CMRGs affecting the prognosis of OC patients were identified in The Cancer Genome Atlas (TCGA). Consensus Clustering was used to identify two CM clusters. lasso-cox methods were used to establish copper metabolism-related gene prognostic signatures (CMRGPS) based on differentially expressed genes in the two clusters. The GSE63885 cohort was used as an external validation cohort. Expression of CM riskscore-associated genes was verified by single-cell sequencing and quantitative real-time PCR (qRT-PCR). Nomograms were used to visually depict the clinical value of CMRGPS. Differences in clinical traits, immune cell infiltration, and tumour mutational load (TMB) between risk groups were also extensively examined. Tumour Immune Dysfunction and Rejection (TIDE) and Immune Phenotype Score (IPS) were used to validate whether CMRGPS could predict response to immunotherapy in OC patients.
Results:In the TCGA and GSE63885 cohorts, we identified two CM clusters that differed significantly in terms of overall survival (OS) and tumour microenvironment. We then created a CMRGPS containing 11 genes to predict overall survival and confirmed its reliable predictive power for OC patients. The expression of CM riskscore-related genes was validated by qRT-PCR. Patients with OC were divided into low-risk (LR) and high-risk (HR) groups based on the median CM risk score, with better survival in the LR group. The 5-year AUC value reached 0.74. Enrichment analysis showed that the LR group was associated with tumour immune-related pathways. The results of TIDE and IPS showed a better response to immunotherapy in the LR group.
Conclusion:Our study therefore provides a valuable tool to further guide the clinical management and tailor treatment of patients with OC, offering new insights into individualised treatment.