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卵巢癌预后的 DNA 甲基化亚型。

DNA methylation subtypes for ovarian cancer prognosis.

机构信息

Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.

出版信息

FEBS Open Bio. 2021 Mar;11(3):851-865. doi: 10.1002/2211-5463.13056. Epub 2021 Feb 3.

Abstract

Ovarian cancer is one of three major malignancies of the female reproductive system. DNA methylation (MET) is closely related to ovarian cancer occurrence and development, and as such, elucidation of effective MET subtype markers may guide individualized treatment and improve ovarian cancer prognosis. To identify potential markers, we downloaded a total of 571 ovarian cancer MET samples from The Cancer Genome Atlas (TCGA), and established a Cox proportional hazards model using the MET spectrum and clinical pathological parameters. A total of 250 prognosis-related MET loci were obtained by Cox regression, and six molecular subtypes were screened by consensus clustering of CpG loci with a significant difference in both univariate and multivariate analyses. There was a remarkable MET difference between most subtypes. Cluster 2 had the highest MET level and demonstrated the best prognosis, while Clusters 4 and 5 had MET levels significantly lower than those of the other subtypes and demonstrated very poor prognosis. All Cluster 5 samples were at a high grade, while the percentage of stage IV samples in Cluster 4 was greater than in the other subtypes. We obtained five CpG loci using a coexpression network: cg27625732, cg00431050, cg22197830, cg03152385, and cg22809047. Our cluster analysis showed that prognosis in patients with hypomethylation was significantly worse than in patients with hypermethylation. These MET molecular subtypes can be used not only to evaluate ovarian cancer prognosis, but also to fully distinguish the tumor stage and histological grade in patients with ovarian cancer.

摘要

卵巢癌是女性生殖系统三大恶性肿瘤之一。DNA 甲基化(MET)与卵巢癌的发生发展密切相关,因此,阐明有效的 MET 亚型标志物可能有助于指导个体化治疗并改善卵巢癌的预后。为了鉴定潜在的标志物,我们从癌症基因组图谱(TCGA)下载了总共 571 例卵巢癌 MET 样本,利用 MET 谱和临床病理参数建立了 Cox 比例风险模型。通过 Cox 回归获得了总共 250 个与预后相关的 MET 位置,并通过 CpG 位置的一致性聚类筛选了六个分子亚型,该聚类在单因素和多因素分析中均具有显著差异。大多数亚型之间存在显著的 MET 差异。Cluster 2 的 MET 水平最高,预后最好,而 Cluster 4 和 Cluster 5 的 MET 水平明显低于其他亚型,预后非常差。Cluster 5 的所有样本均为高级别,而 Cluster 4 中 IV 期样本的比例大于其他亚型。我们使用共表达网络获得了五个 CpG 位置:cg27625732、cg00431050、cg22197830、cg03152385 和 cg22809047。我们的聚类分析表明,低甲基化患者的预后明显比高甲基化患者差。这些 MET 分子亚型不仅可以用于评估卵巢癌的预后,还可以充分区分卵巢癌患者的肿瘤分期和组织学分级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f37a/7931230/f3c25b167ebb/FEB4-11-851-g001.jpg

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