A cuproptosis-related signature predicts prognosis and indicates cross-talk with immunocyte in ovarian cancer

Ovarian cancer (OC) is one of the most common malignant gynecological tumors, and its mortality rate remains high [1]. Because the disease is often asymptomatic and there is a lack of related biomarkers, a large proportion of patients are diagnosed at an advanced stage [2]. Despite the application of standard therapy such as debulking surgery and adjuvant chemotherapy, more than 70% of patients exhibit tumor recurrence due to chemotherapy resistance [3]. There has been tremendous research effort, and numerous treatment options, such as poly ADP-ribose polymerase (PARP) inhibitors and immunotherapy for ovarian cancer patients, have been tested [4, 5]. However, the molecular heterogeneity at the genomic level, prominent toxicity, and possible acquisition of drug resistance substantially decrease efficacy in the clinical applications of adjuvant chemotherapy and targeted therapies [6]. Therefore, in addition to the basic strategy of complete tumor resection, efficient therapeutic targets for sensitization and signatures of ovarian cancer related to the response to targeted therapy and immunotherapy should be explored to improve prognosis and survival.

Copper is an essential trace metal for living organisms (bacteria, animals, and humans) and plays an important role as a cofactor of copper-binding enzymes in many biological processes, including mitochondrial respiration, iron uptake, antioxidant activity, and detoxification [7]. Copper maintains dynamic equilibrium at low concentrations via evolutionarily conserved homeostatic mechanisms and participates in cell proliferation (cuproplasia), while abnormal accumulation of copper can cause cytotoxicity and induce cell death (cuproptosis) [8]. Copper ions induce abnormal oligomerization of lipoylated proteins by binding lipoylated components of the tricarboxylic acid (TCA) cycle, subsequently reducing iron-sulfur cluster protein levels and inducing a proteotoxic stress response, ultimately leading to cell death [9]. Significantly elevated copper levels in serum and tumor tissue have been found in patients with a variety of cancers, including breast cancer, thyroid cancer, pancreatic cancer, and bladder cancer [10‐13]. An increasing number of studies have demonstrated that an abnormal increase in copper stress is involved in the proliferation, invasion, and metastasis of cancers [14]. Léo Aubert found that the copper-exporter ATP7A is essential for neoplastic growth by regulating intracellular copper icon levels and further indicated that copper bioavailability is a KRAS-specific vulnerability in colorectal cancer[15]. Additionally, copper ions contributed to tumor angiogenesis by activating many angiogenic factors, such as vascular endothelial growth factor (VEGF), VEGF2, and fibroblast growth factor 1 (FGF1) [16‐18]. However, some studies showed that the prognosis of OC patients was correlated to the procuproptosis gene-lipoic acid synthase (LIAS), and patients with OC who have high expression of LIAS showed a better overall survival and post-progressive survival [19]. This demonstrated that promoting cuproptosis was beneficial to the prognosis of OC, but whether more CRGs had a positive effect on the prognosis of OC needed to be further explored.

In the present study, a scoring model based on cuproptosis-related differentially expressed genes was constructed, and this model may provide novel potential strategies to predict prognosis, immune infiltration, immunotherapy, and chemotherapy response. Furthermore, ligand–receptor pairs and RNA velocity in single-cell RNA-seq analysis were assessed based on this system, and these strategies supplement the current methods for evaluating novel connections between cancer cells and immunocytes. In general, the cuproptosis-related scoring model might assess aggressiveness and provide more efficient immunotherapeutic strategies for OC patients.

Copper is a valuable coenzyme in many physiological activities, such as the oxidative stress response, lipid metabolism, and mitochondrial respiration [33]. Cuproptosis, an unconventional mechanism of cell death, is playing an increasingly important role in promoting tumor progression, recurrence, TME, and chemotherapy response [34, 35]. The mechanisms of copper-induced tumor cell death include induction of reactive oxygen species production, decreasing the expression of signaling pathways, and overcoming chemoresistance, but its effects on OC remain poorly understood. In ovarian cancer, previous studies showed that CDKN2A, the mutations of which led to loss of growth control in ovarian cancer cells, is related to the cell cuproptosis sensitivity [9, 36], indicating that cuproptosis plays essential role in ovarian cancer.

Infiltration of immune cells was validated to be associated with cancer cell proliferation, invasion, and metastasis in multiple cancers [37‐40]. Some immune cells were differentially infiltrated in the CuRS subgroups. While the high-risk group had more M0 macrophages, resting memory CD4 T cells, activated NK cells, and activated mast cells, the low-risk group had more CD8 T cells and M1 macrophages. The ssGSEA algorithm results also revealed that patients in the low-risk group had higher immune activity. Tumor-associated macrophages (TAMs) are the key regulatory agent of treatment responses in the TME [41]. M2 macrophages, as a major subtype of macrophages, are conducive to tumor cell growth, invasion, and angiogenesis, and these cells are associated with a poor prognosis in many cancers [42]. In contrast, a high level of M1 macrophages is related to antigen presentation and indicates antitumor activity in patients with ovarian cancer [43]. Many studies have shown that a high level of T-cell infiltration, particularly cytotoxic CD8 T cell infiltration, indicates a favorable prognosis, and our findings support these conclusions [44]. According to the ESTIMATE algorithm, a low-risk group had higher immune scores than a high-risk group. As previously reported, the higher TMB is associated with better prognosis in OC patients [45], which is consistent with the findings in this study. These results suggested that our model can accurately predict the prognosis and immune status of OC patients and develop personalized immunotherapeutic strategies.

As previously shown, no studies have revealed the cellular relationship between cuproptosis and the progression of OC or the immune landscape. By integrating bulk and single-cell RNA sequencing, we first systematically analyzed the heterogeneity of OC. Based on the cuproptosis genes, we classified 15 clusters and 8 subtypes of OC cells using the Seurat package and copy number variation (CNV) profile, and these clusters were visualized by using the UMAP algorithm. Pseudotime trajectory analysis via the Monocle 3 algorithm also illustrated the time-dependent evolution of OC cells among these clusters. In our study, we show that the differentiation and progression of OC cells is classified along with increasing CuRS, which demonstrates that the CuRS scoring model can be used to evaluate tumorigenesis.

The development of chemotherapy drug resistance is an important cause of recurrence and death in patients, but there is no effective treatment [46]. Copper transporters mediate resistance of OC cells to platinum-based drugs, and may predict platinum sensitivity and prognosis of OV patients. Prevent study showed that cisplatin chemotherapy resistance by glutathione-resistant copper-based nanomedicine via cuproptosis [47]. Based on the chemotherapy sensitivity analysis, it is possible that patients with high-CuRS are more responsive to platinum chemotherapy drugs. Consistently, increased drug responsiveness to olaparib and niraparib was identified in patients with high cuproptosis scores, suggesting that PARP inhibitors have potential value and providing a useful reference for combining PARP inhibitors and with cuproptosis-targeting agents to alleviate platinum resistance. Furthermore, our data show that OC patients with high cuproptosis scores had higher sensitivity to other targeted chemotherapy drugs, including VEGFR inhibitors, mTOR inhibitors, and PI3K signal inhibitors, than those with low cuproptosis scores. These results suggest that cuproptosis-related genes may predict or affect the response to chemotherapy in patients with OC.

In this study, we built a prognostic scoring model relying on cuproptosis-related DEGs in ovarian cancer samples. High CuAS samples show a more aggressive growth pattern and worse clinical outcomes than low CuRS samples. Tumor cells with different CuRS values communicate with immunocytes in a distinct manner, implying that cuproptosis activation may modulate immunocyte function. We assumed that targeting high CuRS samples may improve the patient’s prognosis, and novel potential compounds were predicted via a machine learning algorithm. The specific mechanisms underlying the function of these model genes and the correlation of prognostic and therapeutic gene signatures in ovarian cancer need further clarification. Nevertheless, our model can accurately predict the prognosis and immune status of OC patients and guide precision treatment. In summary, comprehensive bioinformatics analysis demonstrated that the CuRS model can be used to evaluate ovarian cancer aggressiveness and modulate crosstalk with immunocytes, offering a new option for chemotherapy combination treatments and response evaluation.