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鉴定卵巢癌中与铜代谢相关的亚型并建立预后模型。

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

机构信息

Wuxi Medical Center of Nanjing Medical University, Wuxi, China.

Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.

出版信息

Front Endocrinol (Lausanne). 2023 Mar 6;14:1145797. doi: 10.3389/fendo.2023.1145797. eCollection 2023.

Abstract

BACKGROUND

Ovarian cancer (OC) is one of the most common and most malignant gynecological malignancies in gynecology. On the other hand, dysregulation of copper metabolism (CM) is closely associated with tumourigenesis and progression. Here, we investigated the impact of genes associated with 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 the copper metabolism-related gene prognostic signature (CMRGPS) based on differentially expressed genes in the two clusters. The GSE63885 cohort was used as an external validation cohort. Expression of CM risk score-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 tumor 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 tumor 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 risk score-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 tumor 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 clinical management and tailor the treatment of patients with OC, offering new insights into individualized treatment.

摘要

背景

卵巢癌(OC)是妇科最常见和最恶性的妇科恶性肿瘤之一。另一方面,铜代谢失调(CM)与肿瘤发生和进展密切相关。在这里,我们研究了与铜代谢相关的基因(CMRGs)对 OC 预后的影响,发现了各种 CM 簇,并构建了一个风险模型来评估患者的预后、免疫特征和治疗反应。

方法

在癌症基因组图谱(TCGA)中鉴定了 15 个影响 OC 患者预后的 CMRGs。使用共识聚类法识别出两个 CM 簇。基于两个簇中差异表达的基因,使用lasso-cox 方法建立了铜代谢相关基因预后签名(CMRGPS)。使用 GSE63885 队列作为外部验证队列。通过单细胞测序和定量实时 PCR(qRT-PCR)验证 CM 风险评分相关基因的表达。使用列线图直观地描绘了 CMRGPS 的临床价值。还广泛研究了风险组之间的临床特征、免疫细胞浸润和肿瘤突变负荷(TMB)的差异。使用肿瘤免疫功能障碍和排斥(TIDE)和免疫表型评分(IPS)来验证 CMRGPS 是否可以预测 OC 患者对免疫治疗的反应。

结果

在 TCGA 和 GSE63885 队列中,我们鉴定了两个 CM 簇,它们在总生存(OS)和肿瘤微环境方面存在显著差异。然后,我们创建了一个包含 11 个基因的 CMRGPS 来预测总生存,并证实其对 OC 患者具有可靠的预测能力。通过 qRT-PCR 验证了 CM 风险评分相关基因的表达。根据 CM 风险评分的中位数,OC 患者被分为低风险(LR)和高风险(HR)组,LR 组的生存情况更好。5 年 AUC 值达到 0.74。富集分析表明,LR 组与肿瘤免疫相关途径有关。TIDE 和 IPS 的结果表明,LR 组对免疫治疗的反应更好。

结论

因此,我们的研究为进一步指导 OC 患者的临床管理和制定治疗方案提供了有价值的工具,为个体化治疗提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6718/10025496/54553e6a230c/fendo-14-1145797-g001.jpg

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