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2011至2020年乳腺癌干细胞Web of Science数据库的文献计量学与可视化分析 被引量:2

Bibliometric and visualization analysis of breast cancer stem cell literature from 2011 to 2020 based on Web of Science database
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摘要 背景:目前人们已认识到乳腺癌干细胞在乳腺癌的发生、发展、转移、复发和产生耐药性等一系列过程中的重要作用,但对乳腺癌干细胞在其中的作用机制仍不明确,因此对乳腺癌的治疗还有待进一步的改善。目的:探索2011年至2020年乳腺癌干细胞研究领域的研究现状和发展趋势。方法:从Web of Science数据库获取乳腺癌干细胞研究领域的相关文献数据,用Microsoft Excel 2019软件绘制相应数据的二维条形图,采用VOSviewer软件的共现分析功能绘制关键词共现分析图及其与时间的叠加图。结果与结论:①共纳入1 013篇文献,美国的发文数量、H指数及被引频数总计均为世界之首;肿瘤学方向的文献数量最多,中山大学是产出文献数量最多的机构;密歇根大学的WICHA MS是发表文献最多的作者,国家自然科学基金支持产出的文献数量最多,在《ONCOTARGET》杂志上刊登的文献数量最多;②肿瘤学研究方面,化疗与二甲双胍的联合治疗、抗血管生成剂的靶向治疗是重点研究内容;③在基因遗传学研究方面,转录因子X2(sox2)、表观遗传调控因子H2(ezH2基因)及胚胎干细胞转录因子(nanog)是重点研究基因;④在乳腺癌干细胞应用于乳腺癌的治疗研究方面,上皮-间充质转化是主要研究内容;⑤在分子生物学研究方面,分化抗体CD24、分化抗体CD44为重点生物标志物;⑥核转录因子κB通路和抗乳腺癌干细胞特性(stemness)是最近出现频率较高的关键词;⑦与核转录因子κB通路相关的重组人受体酪氨酸激酶HRG/ErbB3信号、紫檀芪和双硫仑是研究热点,与乳腺癌干细胞特性相关的上皮/间充质杂质基因、miR34a-NOTCH1(跨膜受体蛋白)轴、LINC00511/miR-185-3p/E2F1/Nanog轴是重点研究内容;⑧在国家合著分析方面,美国与其他各国的链接强度最高;⑨上述数据说明在乳腺癌干细胞研究领域中,美国处于绝对领先地位;乳腺癌干细胞应用于乳腺癌治疗的研究较为受人关注,而核转录因子κB通路和抗乳腺癌干细胞特性的研究是该领域目前的研究热点。 BACKGROUND:It has been recognized that breast cancer stem cells play an important role in the occurrence,development,metastasis,recurrence and drug resistance of breast cancer,but the action mechanism of breast cancer stem cells in it is still unclear,and the treatment of breast cancer needs further improvement.OBJECTIVE:To explore the research status and development trend in the field of breast cancer stem cells from 2011 to 2020.METHODS:The relevant literature data in the field of breast cancer stem cell research were obtained from the Web of Science database,and the twodimensional bar diagram of the corresponding data was drawn by Microsoft excel 2019.The co-occurrence analysis function of VOSviewer software was used to draw the co-occurrence analysis chart of keywords and its superposition with time.RESULTS AND CONCLUSION:(1)A total of 1013 papers were included in this study.The number of papers,the H index,and the number of citations from the United States were the first in the world.The number of the literature on oncology is the largest.Sun Yat-Sen University is the largest producer of literature.WICHA MS is the author with the largest number of publications.National Natural Science Foundation of China supports the largest number of outputs.The largest number of publications is published in the ONCOTARGET.(2)The combination of chemotherapy and metformin and targeted antiangiogenic therapy are the key research contents in oncology.(3)In gene genetics,sox2,ezh2,and nanog are the key genes.(4)In the treatment of breast cancer stem cells,epithelialmesenchymal transition is the main research content.(5)In molecular biology,cd24 and cd44 are the key biomarkers.(6)“Nuclear factor-κB”and“stemness”are the closest keywords to the present time.(7)Recombinant human receptor tyrosine kinase HRG/ErbB3 signals related to the nuclear factor-κB pathway,Pterostilbene and disulfiram are the research focus,and the epithelial/mesenchymal heterogeneity,miR34a-NOTCH1 axis and LINC00511/miR-185-3p/E2F1/Nanog axis related to the stemness of breast cancer stem cells are the key research contents.(8)The United States has the highest link intensity with other countries in co-country analysis.(9)It is concluded that in the field of breast cancer stem cells,the United States is the most powerful country.The research direction in this field is gradually tending to the application of breast cancer stem cells to the treatment of breast cancer.The research of nuclear factor-κB and stemness may be the current research hotspots in this field.
作者 陆宇云 黄梅 石新蕾 陈宝艳 Lu Yuyun;Huang Mei;Shi Xinlei;Chen Baoyan(Department of Mammary Gland,the First Affiliated Hospital of Guangzhou University of Chinese Medicine,Guangzhou 510405,Guangdong Province,China)
出处 《中国组织工程研究》 CAS 北大核心 2021年第25期4001-4008,共8页 Chinese Journal of Tissue Engineering Research
基金 国家自然科学基金资助项目(81603653),项目负责人:陈宝艳。
关键词 干细胞 乳腺癌 乳腺癌干细胞 核转录因子ΚB 生物标志物 文献计量学 可视化分析 stem cells breast cancer breast cancer stem cells nuclear factor kappa B biomarkers bibliometrics visualization analysis
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