Multi-omics analysis defines a cuproptosis-related prognostic model for ovarian cancer: Implication of WASF2 in cuproptosis resistance

Kunyu Wang; Yanan Zhang; Miao Ao; Haixia Luo; Wei Mao; Bin Li

doi:10.1016/j.lfs.2023.122081

Multi-omics analysis defines a cuproptosis-related prognostic model for ovarian cancer: Implication of WASF2 in cuproptosis resistance

Life Sci. 2023 Nov 1:332:122081. doi: 10.1016/j.lfs.2023.122081. Epub 2023 Sep 16.

Authors

Kunyu Wang¹, Yanan Zhang¹, Miao Ao¹, Haixia Luo¹, Wei Mao¹, Bin Li²

Affiliations

¹ Department of Gynecological Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
² Department of Gynecological Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. Electronic address: libin@cicams.ac.cn.

PMID: 37717621
DOI: 10.1016/j.lfs.2023.122081

Abstract

Background: Ovarian cancer (OVC) is one of the deadliest and most aggressive tumors in women, with an increasing incidence in recent years. Cuproptosis, a newly discovered type of programmed cell death, is caused by intracellular copper-mediated lipoylated protein aggregation and proteotoxic stress. However, the role of cuproptosis-related features in OVC remains elusive.

Methods: The single-cell sequencing data from GSE154600 and bulk transcriptome data of 378 OVC patients from TCGA database. The RNA-seq and clinical data of 379 OVC patients in GSE140082 and 173 OV patients in GSE53963. The PROGENy score was calculated to assess tumor-associated pathways. Based on gene set enrichment analysis (GSEA) of the cuproptosis pathway, the single cells were divided into the cuproptosis^high and cuproptosis^low groups. The differentially expressed genes (DEGs) between the two groups were screened, and 47 prognosis-related genes were identified based on univariate cox regression analysis. Randomforest was used to construct a prognostic model. Immuno-infiltration analysis was performed using ssGSEA and xCell algorithms. In vitro and in vivo experiments were used for functional verification.

Results: Six major cell populations was identified, including fibroblast, T cell, myeloid, epithelial cell, endothelial cell, and B cell populations. The PROGENy score which revealed significant activation of the PI3K pathway in T and B cells, and activation of the TGF-β pathway in endothelial cells and fibroblasts. TIMM8B, COX8A, SSR4, HIGD2A, WASF2, PRDX5 and CLDN4 were selected to construct a prognostic model from the identified 47 prognosis-related genes. Furthermore, the cuproptosis^high and cuproptosis^low groups showed significant differences in the expression levels of the model genes, immune cell infiltration, and sensitivity to six potential drug candidates. The functional experiments showed that WASF2 is associated with cuproptotic resistance and promotes cancer cell proliferation and resistance to platinum, and its high expression is associated with poor prognosis of OVC patients.

Conclusion: A clinically significant cuproptosis-related prognostic model was identified which can accurately predict the prognosis and immune characteristics of OVC patients. WASF2, one of the cuproptosis-related gene in the risk model, promotes the proliferation and platinum resistance of OVC cells, and leads poor prognosis.

Keywords: Cuproptosis; Ovarian cancer; Platinum resistance; Prognostic model; Single cell sequencing; WASF2.