Department of Pharmacy, First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Department of Obstetrics and Gynecology, Zhongshan Hospital, Fudan University, Shanghai, China.
Front Endocrinol (Lausanne). 2023 Jun 13;14:1193622. doi: 10.3389/fendo.2023.1193622. eCollection 2023.
Ovarian cancer (OC) is a highly lethal and aggressive gynecologic cancer, with an overall survival rate that has shown little improvement over the decades. Robust models are urgently needed to distinguish high-risk cases and predict reliable treatment options for OC. Although anoikis-related genes (ARGs) have been reported to contribute to tumor growth and metastasis, their prognostic value in OC remains unknown. The purpose of this study was to construct an ARG pair (ARGP)-based prognostic signature for patients with OC and elucidate the potential mechanism underlying the involvement of ARGs in OC progression.
The RNA-sequencing and clinical information data of OC patients were obtained from The Center Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A novel algorithm based on pairwise comparison was utilized to select ARGPs, followed by the Least Absolute Shrinkage and Selection Operator Cox analysis to construct a prognostic signature. The predictive ability of the model was validated using an external dataset, a receiver operating characteristic curve, and stratification analysis. The immune microenvironment and the proportion of immune cells were analyzed in high- and low-risk OC cases using seven algorithms. Gene set enrichment analysis and weighted gene co-expression network analysis were performed to investigate the potential mechanisms of ARGs in OC occurrence and prognosis.
The 19-ARGP signature was identified as an important prognostic predictor for 1-, 2-, and 3-year overall survival of patients with OC. Gene function enrichment analysis showed that the high-risk group was characterized by the infiltration of immunosuppressive cells and the enrichment of adherence-related signaling pathway, suggesting that ARGs were involved in OC progression by mediating immune escape and tumor metastasis.
We constructed a reliable ARGP prognostic signature of OC, and our findings suggested that ARGs exerted a vital interplay in OC immune microenvironment and therapeutic response. These insights provided valuable information regarding the molecular mechanisms underlying this disease and potential targeted therapies.
卵巢癌(OC)是一种高度致命和侵袭性的妇科癌症,几十年来其总体生存率几乎没有提高。目前迫切需要建立稳健的模型来区分高危病例,并预测 OC 的可靠治疗选择。尽管已有研究报道与细胞凋亡相关的基因(ARGs)有助于肿瘤生长和转移,但它们在 OC 中的预后价值尚不清楚。本研究旨在构建基于 ARG 对(ARGP)的 OC 患者预后标志,并阐明 ARGs 参与 OC 进展的潜在机制。
从 The Center Genome Atlas(TCGA)和 Gene Expression Omnibus(GEO)数据库中获取 OC 患者的 RNA-seq 测序和临床信息数据。使用基于成对比较的新算法选择 ARGPs,然后使用最小绝对收缩和选择算子 Cox 分析构建预后标志。使用外部数据集、接收者操作特征曲线和分层分析验证模型的预测能力。使用七种算法分析高风险和低风险 OC 病例的免疫微环境和免疫细胞比例。进行基因集富集分析和加权基因共表达网络分析,以研究 ARGs 在 OC 发生和预后中的潜在机制。
确定了 19-ARGp 标志作为 OC 患者 1、2 和 3 年总生存率的重要预后预测因子。基因功能富集分析表明,高危组的特点是免疫抑制细胞浸润和粘附相关信号通路富集,提示 ARGs 通过介导免疫逃逸和肿瘤转移参与 OC 进展。
我们构建了一个可靠的 OC ARGP 预后标志,我们的研究结果表明,ARGs 在 OC 免疫微环境和治疗反应中发挥着重要的相互作用。这些发现为该疾病的分子机制及其潜在的靶向治疗提供了有价值的信息。