文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

老年与中年食管鳞状细胞癌患者食管菌群宏基因组学的比较研究

[Comparative study on metagenomics of esophageal flora in elderly and middle-aged esophageal squamous cell carcinoma patients].

作者信息

Liu X B, Gao Z Y, Jin S, Gao B, Wang M S, Wu T, Li S B, Tong Q, Zhang J C

机构信息

Department of Gastroenterology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China Hubei Key Laboratory of Embryonic Stem Cell Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China.

Department of Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China.

出版信息

Zhonghua Yu Fang Yi Xue Za Zhi. 2021 Mar 6;55(3):371-378. doi: 10.3760/cma.j.cn112150-20200707-00984.


DOI:10.3760/cma.j.cn112150-20200707-00984
PMID:33730830
Abstract

To explore the flora characteristics and differences of esophageal tissues between elderly esophageal squamous cell carcinoma (ESCC) patients and young and middle-aged ESCC patients, so as to assist in studying the potential biomarkers of elderly ESCC patients. In this study, a retrospective study was adopted. 72 ESCC patients diagnosed in Taihe Hospital, Shiyan City, Hubei Province from July 2018 to July 2019 were selected, including 49 patients in the elderly group (≥ 60 years old, 40 males and 9 females), 23 patients in the young and middle-aged group (<60 years old, 21 males and 2 females). In the same period, 20 healthy persons without abnormal gastroscopy in endoscopy center were selected as the control group (aged 35-78 years old, median age 57 years old, 16 males and 4 females). The genomic DNA was extracted from the affected esophageal tissues of patients with ESCC and the middle esophageal samples of the control group. The V4 hypervariable region of bacterial 16SrRNA gene sequence was amplified. Illumina HiSeq sequencing technology was adopted. The flora characteristics of elderly, young and middle-aged ESCC patients was compared and analyzed. QIIME and Rstudio software were used to analyze the sequence data, and nonparametric Kruskal-Wallis test or Wilcoxon rank sum test were used for statistical methods. Shannon index [5.17 (4.53, 5.95) 4.79 (3.74, 5.97)], Simpson index [0.94 (0.91, 0.96) 0.92 (0.83, 0.96)] and Chao1 index [343.55 (259.76, 570.59) 329.16 (268.88, 648.00)] were similar in flora of two groups, and there was no significant difference (=-0.791, -1.057, -0.380, all >0.05). There was no significant difference in β-diversity between the elderly group and the young and middle-aged group (PC1=19.14%, PC2=6.95%, =0.67, =0.42). At the phyla level, the top 5 phyla in abundance were as follows: and in the young and middle-aged group, while the top 5 phyla in abundance were as follows: and in the elderly group; the significant difference between the two groups was (=0.596, 0.05). At the genus level, the top 5 genera in the young and middle-aged group in abundance were as follows: and In the elderly group, and were the top 5 in abundance, and there were significant difference in between the two groups (=0.938, 0.05). PICRUSt function prediction showed that the abundance of and in the elderly group were lower than those in the young and middle-aged group (all =0.734, 0.05). There is no significant difference in α-diversity and β-diversity between elderly ESCC patients and young and middle-aged patients, but the abundance of flora increased.

摘要

为探究老年食管鳞状细胞癌(ESCC)患者与中青年ESCC患者食管组织的菌群特征及差异,以辅助研究老年ESCC患者的潜在生物标志物。本研究采用回顾性研究方法。选取2018年7月至2019年7月在湖北省十堰市太和医院确诊的72例ESCC患者,其中老年组(≥60岁,40例男性,9例女性)49例,中青年组(<60岁,21例男性,2例女性)23例。同期,选取内镜中心20例胃镜检查无异常的健康人作为对照组(年龄35 - 78岁,中位年龄57岁,16例男性,4例女性)。提取ESCC患者病变食管组织及对照组食管中段样本的基因组DNA。扩增细菌16SrRNA基因序列的V4高变区。采用Illumina HiSeq测序技术。比较分析老年、中青年ESCC患者的菌群特征。使用QIIME和Rstudio软件分析序列数据,统计方法采用非参数Kruskal - Wallis检验或Wilcoxon秩和检验。两组菌群的香农指数[5.17(4.53, 5.95) 4.79(3.74, 5.97)]、辛普森指数[0.94(0.91, 0.96) 0.92(0.83, 0.96)]和Chao1指数[343.55(259.76, 570.59) 329.16(268.88, 648.00)]相似,差异无统计学意义(=-0.791, -1.057, -0.380,均>0.05)。老年组与中青年组之间的β多样性无显著差异(PC1 = 19.14%,PC2 = 6.95%,=0.67,=0.42)。在门水平上,丰度排名前5的门如下:中青年组为 和 ,而老年组为 和 ;两组间差异有统计学意义(=0.596,0.05)。在属水平上,中青年组丰度排名前5的属如下: 和 。老年组中, 和 丰度排名前5,两组间 差异有统计学意义(=0.938,0.05)。PICRUSt功能预测显示,老年组 和 的丰度低于中青年组(均=0.734,0.05)。老年ESCC患者与中青年患者之间的α多样性和β多样性无显著差异,但 菌群丰度增加。

相似文献

[1]
[Comparative study on metagenomics of esophageal flora in elderly and middle-aged esophageal squamous cell carcinoma patients].

Zhonghua Yu Fang Yi Xue Za Zhi. 2021-3-6

[2]
Characterization of Esophageal Microbiota in Patients With Esophagitis and Esophageal Squamous Cell Carcinoma.

Front Cell Infect Microbiol. 2021

[3]
Distribution of esophagus flora in esophageal squamous cell carcinoma and its correlation with clinicopathological characteristics.

Transl Cancer Res. 2020-6

[4]
Microbial characterization of esophageal squamous cell carcinoma and gastric cardia adenocarcinoma from a high-risk region of China.

Cancer. 2019-7-29

[5]
Combining fecal microbiome and metabolomics reveals diagnostic biomarkers for esophageal squamous cell carcinoma.

Microbiol Spectr. 2024-5-2

[6]
[Analysis of the dynamic changes in gut microbiota in patients with extremely severe burns by 16S ribosomal RNA high-throughput sequencing technology].

Zhonghua Shao Shang Za Zhi. 2020-12-20

[7]
Streptococcus and Prevotella are associated with the prognosis of oesophageal squamous cell carcinoma.

J Med Microbiol. 2018-6-20

[8]
Oral microbiota may predict the presence of esophageal squamous cell carcinoma.

J Cancer Res Clin Oncol. 2023-7

[9]
Characterization of the Esophageal Microbiota and Prediction of the Metabolic Pathways Involved in Esophageal Cancer.

Front Cell Infect Microbiol. 2020-6-26

[10]
[Correlation study between changes in intestinal microflora structure and immune indexes in newly treated patients with pulmonary tuberculosis].

Zhonghua Yu Fang Yi Xue Za Zhi. 2021-12-6

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索