Bioinformatics analysis suggests that COL4A1 may play an important role in gastric carcinoma recurrence

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成果类型：

期刊论文

作者：

Li, De Feng;Wang, Nan Nan;Chang, Xin;Wang, Shu Ling;Wang, Li Sheng;...

通讯作者：

Li, Zhao Shen;Bai, Yu

作者机构：

[Yao, Jun; Li, De Feng; Wang, Li Sheng] Jinan Univ, Shenzhen Peoples Hosp, Clin Med Sch 2, Dept Gastroenterol, Shenzhen, Guangdong, Peoples R China.

[Li, De Feng] Jinan Univ, Integrated Chinese & Western Med Postdoctoral Res, Guangzhou, Guangdong, Peoples R China.

[Li, De Feng; Wang, Nan Nan] Univ South China, Affiliated Hosp 1, Dept Gastroenterol, Hengyang, Hunan, Peoples R China.

[Chang, Xin; Bai, Yu; Li, Zhao Shen; Bai, Y; Wang, Shu Ling] Second Mil Med Univ, Naval Med Univ, Changhai Hosp, Dept Gastroenterol, 168 Changhai Rd, Shanghai 200433, Peoples R China.

通讯机构：

[Li, ZS; Bai, Y] S

Second Mil Med Univ, Naval Med Univ, Changhai Hosp, Dept Gastroenterol, 168 Changhai Rd, Shanghai 200433, Peoples R China.

语种：

英文

关键词：

bioinformatics analysis;human COL4A1;recurrence;stomach neoplasms

期刊：

JOURNAL OF DIGESTIVE DISEASES

ISSN：

1751-2972

年：

2019

卷：

期：

页码：

391-400

DOI：

10.1111/1751-2980.12758

基金类别：

Technical Research and Development Project of Shenzhen, Grant/Award Number: No. JCYJ20150403101028164; Natural Science Foundation of Guangdong Province, Grant/Award Number: No. 2018A0303100024; Natural Science Foundation of Hunan Province, Grant/Award Number: No. 2017JJ3270, No. 2018JJ2355 and No.2018JJ2356; Three Engineering Training Funds in Shenzhen, Grant/Award Number: No. SYLY201718 and No. SYLY201801; National Key R&D Program of China, Grant/Award Number: No. 2017YFC1308800 and No. 2018YFC1313103; National Natural Science Foundation of China, Grant/Award Number: No. 81670473 and No. 81873546

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本校为其他机构

摘要：

Objective: Cancer recurrence is a complicated problem for clinicians that contributes to poor prognosis. This study aimed to use advanced gastric carcinoma genes profiles to predict increased risk of cancer recurrence in order to identify patients in need of adjuvant therapy for prognosis improvement. Methods: Differentially expressed genes were identified for advanced gastric carcinoma by analyzing the GSE2685 from the Gene Expression Omnibus database (GEO) using R package. The candidate genes were then obtained by gene ontology (GO), Kyoto En...

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Bioinformatics analysis suggests that COL4A1 may play an important role in gastric carcinoma recurrence

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