Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data.
Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data.
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利用生物信息学和现实世界数据鉴定WNT基因家族的2基因标记在UCEC中的预后价值。
DOI：
10.1186/s12935-021-02215-0
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发表时间：
2021-09-26
影响因子：
5.8
通讯作者：
Lin B
中科院分区：
文献类型：
--
作者：
Hu Y;Zheng M;Zhang D;Gou R;Liu O;Wang S;Lin B
WNT基因家族在恶性肿瘤的发生、发展中发挥着重要作用，但其在子宫体子宫内膜癌（UCEC）中的参与尚未系统分析。本研究旨在评估WNT基因家族在UCEC中的预后价值。下载UCSC Xena数据库的泛癌转录组数据和基因型组织表达（GTEx）正常组织数据，分析UCEC中19个WNT家族基因的表达和预后。来自癌症基因组图谱-子宫体子宫内膜癌 (TCGA-UCEC) 的队列用于分析 WNT 基因家族在不同免疫亚型和临床亚组中的表达。利用STRING数据库分析WNT基因家族的相互作用及其生物学功能。使用单变量Cox回归分析和Lasso cox分析来识别与显着预后相关的基因并构建多特征预后模型。使用免疫组织化学测定来验证模型的预测能力。使用风险评分和相关临床特征来构建列线图。 WNT2、WNT3、WNT3A、WNT5A、WNT7A和WNT10A的表达水平在不同免疫亚型之间存在显着差异，且与TP53突变相关。根据与UCEC预后相关的WNT家族基因，将UCEC分为两个亚型（C1、C2）。 C1亚型的预后明显好于C2亚型。构建了 2 基因特征（WNT2 和 WNT10A），并且可以根据中位风险评分划分两个显着预后组。这些结果使用真实世界数据进行了验证，并且使用临床特征和风险评分构建的列线图具有良好的预后能力。 WNT2和WNT10A等2个基因特征可用于预测UCEC患者的预后，这对于UCEC患者的临床决策和个体化治疗具有重要意义。
The WNT gene family plays an important role in the occurrence and development of malignant tumors, but its involvement has not been systematically analyzed in uterine corpus endometrial carcinoma (UCEC). This study aimed to evaluate the prognostic value of the WNT gene family in UCEC. Pan-cancer transcriptome data of the UCSC Xena database and Genotype-Tissue Expression (GTEx) normal tissue data were downloaded to analyze the expression and prognosis of 19 WNT family genes in UCEC. A cohort from The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) was used to analyze the expression of the WNT gene family in different immune subtypes and clinical subgroups. The STRING database was used to analyze the interaction of the WNT gene family and its biological function. Univariate Cox regression analysis and Lasso cox analysis were used to identify the genes associated with significant prognosis and to construct multi signature prognosis model. An immunohistochemical assay was used to verify the predictive ability of the model. Risk score and the related clinical features were used to construct a nomogram. The expression levels of WNT2, WNT3, WNT3A, WNT5A, WNT7A, and WNT10A were significantly different among different immune subtypes and correlated with TP53 mutation. According to the WNT family genes related to the prognosis of UCEC, UCEC was classified into two subtypes (C1, C2). The prognosis of subtype C1 was significantly better than that of subtype C2. A 2-gene signature (WNT2 and WNT10A) was constructed and the two significantly prognostic groups can be divided based on median Risk score. These results were verified using real-world data, and the nomogram constructed using clinical features and Risk score had good prognostic ability. The 2-gene signature including WNT2 and WNT10A can be used to predict the prognosis of patients with UCEC, which is important for clinical decision-making and individualized therapy for patients with UCEC.
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