Ye Wei, Fang Yuanyuan, Wei Zhaolian
Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China.
Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China.
J Cancer. 2024 Sep 23;15(18):5986-6001. doi: 10.7150/jca.100796. eCollection 2024.
Ovarian cancer (OV) is a prevalent malignancy among gynecological tumors. Numerous metabolic pathways play a significant role in various human diseases, including malignant tumors. Our study aimed to develop a prognostic signature for OV based on a comprehensive set of metabolism-related genes (MRGs). To achieve this, a bioinformatics analysis was performed on the expression profiles of 51 MRGs. The OV individuals were subsequently categorized into two molecular clusters based on the expression levels of MRGs. Following this, differentially expressed genes (DEGs) were identified among these clusters. The DEGs aided in the classification of two gene clusters, with a total of 390 DEGs being identified between them. A prognostic signature, constructed using the DEGs, enabled the calculation of risk scores for OV patients. This study revealed that patients classified as low-risk demonstrated a more favorable prognosis, increased immune cell infiltration, and superior response to chemotherapy in comparison to high-risk patients. Four signature genes, GDF6, KIF26A, P2RY14, and ALDH1A2, were identified as significant contributors to the prognostic signature. The expression levels of these signature genes were different between OV and normal ovary tissues through in vitro experiments. Additionally, P2RY14 protein was found to potentially influence the growth of OV cell lines. We have constructed a prognostic signature associated with MRGs that demonstrates exceptional efficacy in prognosis survival outcomes and therapeutic responses in patients diagnosed with OV. Downregulation of P2RY14 may contribute to an unfavorable prognosis in OV.
卵巢癌（OV）是妇科肿瘤中一种常见的恶性肿瘤。众多代谢途径在包括恶性肿瘤在内的各种人类疾病中发挥着重要作用。我们的研究旨在基于一组全面的代谢相关基因（MRGs）开发一种OV的预后特征。为实现这一目标，对51个MRGs的表达谱进行了生物信息学分析。随后，根据MRGs的表达水平将OV个体分为两个分子簇。在此之后，在这些簇中鉴定出差异表达基因（DEGs）。这些DEGs有助于两个基因簇的分类，它们之间共鉴定出390个DEGs。使用这些DEGs构建的预后特征能够计算OV患者的风险评分。本研究表明，与高风险患者相比，低风险患者的预后更有利，免疫细胞浸润增加，对化疗的反应更好。四个特征基因GDF6、KIF26A、P2RY14和ALDH1A2被确定为预后特征的重要贡献者。通过体外实验发现，这些特征基因在OV组织和正常卵巢组织中的表达水平不同。此外，发现P2RY14蛋白可能影响OV细胞系的生长。我们构建了一种与MRGs相关的预后特征，该特征在诊断为OV的患者的预后生存结果和治疗反应方面显示出卓越的效果。P2RY14的下调可能导致OV预后不良。
