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胸腺瘤中预后因素及亚甲基四氢叶酸还原酶C667T基因多态性的研究

The Studies of Prognostic Factors and the Genetic Polymorphism of Methylenetetrahydrofolate Reductase C667T in Thymic Epithelial Tumors.

作者信息

Yan Miaolong, Wu Jiayuan, Xue Min, Mo Juanfen, Zheng Li, Zhang Jun, Gao Zhenzhen, Bao Yi

机构信息

The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.

The Key Laboratory, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.

出版信息

Front Oncol. 2022 Jun 6;12:847957. doi: 10.3389/fonc.2022.847957. eCollection 2022.

DOI:10.3389/fonc.2022.847957
PMID:35734597
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9207241/
Abstract

OBJECTIVE

To describe the clinical features of a cohort of patients with thymic epithelial tumors (TETs) and to analyze their prognostic factors. In particular, we investigated the correlation between the genetic polymorphism of methylenetetrahydrofolate reductase () C667T and the incidence of TETs.

METHODS

Pathological records were reviewed from the database of the Second Affiliated Hospital of Jiaxing University, from January 2010 to December 2020, and 84 patients with TETs were recruited for this study. Univariate and multivariate analyses were performed to determine the prognostic factors. The genetic polymorphism of  C667T was examined in the patients with TETs and in a group of healthy individuals. The correlation between transcriptional levels and methylation was analyzed using The Cancer Genome Atlas (TCGA) thymoma dataset from the cBioPortal platform.

RESULTS

Kaplan-Meier univariate survival analysis showed that sex, age, the maximum tumor diameter, surgery, chemotherapy, radiotherapy, WHO histological classification, Masaoka-Koga stage, and 8th UICC/AJCC TNM staging, were statistically significantly correlated with the prognosis of patients with TETs. The Masaoka-Koga stage and 8th UICC/AJCC TNM staging were strongly correlated with each other in this study (r=0.925, P<0.001). Cox multivariate survival analysis showed that the maximum tumor diameter, Masaoka-Koga stage, and 8th UICC/AJCC TNM staging were independent prognostic factors affecting the overall survival (OS) of patients with TETs (0.05). The C667T genotype ( 7.987, =0.018) and allele distribution ( 5.750, 0.016) were significantly different between the patients and healthy controls. CT heterozygous and TT homozygous genotypes at this polymorphism significantly increased the risk of TETs (odds ratio [OR] 4.721, 0.008). Kaplan-Meier univariate survival analysis showed that there was no correlation between different genotypes and the prognosis of TETs (CC versus CT + TT, 0.003, =0.959). Finally, a negative correlation between the transcriptional and methylation levels of was observed in the TCGA thymoma dataset (-0.24, 0.010).

CONCLUSIONS

The Masaoka-Koga stage, 8th UICC/AJCC TNM staging, and maximum tumor diameter were independent prognostic factors for TETs. Reduced methylation levels of and particular polymorphic variants may contribute to the susceptibility to developing TETs.

摘要

目的

描述一组胸腺上皮肿瘤(TETs)患者的临床特征,并分析其预后因素。特别是,我们研究了亚甲基四氢叶酸还原酶(MTHFR)C667T基因多态性与TETs发病率之间的相关性。

方法

回顾嘉兴学院附属第二医院2010年1月至2020年12月数据库中的病理记录,招募84例TETs患者进行本研究。进行单因素和多因素分析以确定预后因素。检测TETs患者和一组健康个体中MTHFR C667T的基因多态性。使用来自cBioPortal平台的癌症基因组图谱(TCGA)胸腺瘤数据集分析MTHFR转录水平与甲基化之间的相关性。

结果

Kaplan-Meier单因素生存分析显示,性别、年龄、肿瘤最大直径、手术、化疗、放疗、世界卫生组织(WHO)组织学分类、Masaoka-Koga分期和第8版国际抗癌联盟(UICC)/美国癌症联合委员会(AJCC)TNM分期与TETs患者的预后在统计学上显著相关。在本研究中,Masaoka-Koga分期和第8版UICC/AJCC TNM分期彼此高度相关(r = 0.925,P < 0.001)。Cox多因素生存分析显示,肿瘤最大直径、Masaoka-Koga分期和第8版UICC/AJCC TNM分期是影响TETs患者总生存(OS)的独立预后因素(P < 0.05)。患者与健康对照之间MTHFR C667T基因型(χ² = 7.987,P = 0.018)和等位基因分布(χ² = 5.750,P = 0.016)存在显著差异。该多态性的CT杂合子和TT纯合子基因型显著增加了TETs的发病风险(比值比[OR] 4.721,P = 0.008)。Kaplan-Meier单因素生存分析显示,不同基因型与TETs的预后无相关性(CC与CT + TT比较,χ² = 0.003,P = 0.959)。最后,在TCGA胸腺瘤数据集中观察到MTHFR转录水平与甲基化水平呈负相关(r = -0.24,P = 0.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/d6db427d36ca/fonc-12-847957-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/71460558f6fe/fonc-12-847957-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/4e4420e52049/fonc-12-847957-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/6d37cdf7fec9/fonc-12-847957-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/d6db427d36ca/fonc-12-847957-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/71460558f6fe/fonc-12-847957-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/4e4420e52049/fonc-12-847957-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/6d37cdf7fec9/fonc-12-847957-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618f/9207241/d6db427d36ca/fonc-12-847957-g004.jpg

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