Cabarca Sindy, Ili Carmen, Vanegas Carlos, Gil Laura, Vertel-Morrinson Melba, Brebi Priscilla
Millennium Institute on Immunology and Immunotherapy. Laboratory of Integrative Biology (LIBi), Centro de Excelencia en Medicina Traslacional (CEMT), Scientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, Temuco, Chile.
Grupo de Investigación Estadística y Modelamiento Matemático Aplicado (GEMMA), Departamento de Matemáticas, Facultad de Educación y Ciencias, Universidad de Sucre, Sincelejo, Colombia.
Front Oncol. 2024 Nov 11;14:1450675. doi: 10.3389/fonc.2024.1450675. eCollection 2024.
Late diagnosis and patient relapse, mainly due to chemoresistance, are the key reasons for the high mortality rate of ovarian cancer patients. Hence, the search for biomarkers of high predictive value within the phenomenon of chemoresistance is vital. This study performs a bibliometric analysis of the scientific literature concerning biomarkers of drug resistance in ovarian cancer, considering the period from 2017 to 2022.
The terms "drug resistance biomarker" and "ovarian cancer" were linked by the Boolean operator "AND". The search was done in PubMed, selecting documents published over the last 5 years (2017-2022), which were analyzed with the open-source tool Bibliometrix developed in the R package. The language of the publications was restricted to English. Several types of papers such as case reports, clinical trials, comparative studies, and original articles were considered.
A total of 335 scientific articles were analyzed. The United States and China were the leading contributors and established the largest number of scientific collaborations. The Huazhong University of Science and Technology and the University of Texas MD Anderson Cancer Center were the most influential institutions. The Journal of Ovarian Research, International Journal of Molecular Science, and Scientific Reports are among the most relevant journals. The study identified high-profile, relevant thematic niches and important descriptors that indicate topics of interest, including studies on women, cell lines, solid tumors, and gene expression regulation. As well as studies involving middle-aged and adult participants, and those focusing on prognosis evaluation. Descriptors such as "drug resistance," "neoplasm," "genetics," "biomarker," "gene expression profile," and "drug therapy" would indicate new research trends. In addition, we propose that BCL-2, CHRF, SNAIL, miR-363, iASPP, ALDH1, Fzd7, and EZH2 are potential biomarkers of drug resistance.
This paper contributes to the global analysis of the scientific investigation related to drug resistance biomarkers in ovarian cancer to facilitate further studies and collaborative networks, which may lead to future improvements in therapy for this lethal disease.
晚期诊断和患者复发主要归因于化疗耐药性，是卵巢癌患者死亡率高的关键原因。因此，在化疗耐药现象中寻找具有高预测价值的生物标志物至关重要。本研究对2017年至2022年期间关于卵巢癌耐药生物标志物的科学文献进行了文献计量分析。
术语“耐药生物标志物”和“卵巢癌”通过布尔运算符“AND”进行关联。在PubMed中进行检索，选择过去5年（2017 - 2022年）发表的文献，使用R包中开发的开源工具Bibliometrix进行分析。出版物语言限制为英语。考虑了多种类型的论文，如病例报告、临床试验、比较研究和原创文章。
共分析了335篇科学文章。美国和中国是主要贡献者，并建立了最多的科学合作。华中科技大学和德克萨斯大学MD安德森癌症中心是最具影响力的机构。《卵巢研究杂志》《国际分子科学杂志》和《科学报告》是最相关的期刊之一。该研究确定了备受关注的相关主题领域和重要描述词，这些描述词表明了感兴趣的主题，包括对女性、细胞系、实体瘤和基因表达调控的研究。以及涉及中年和成年参与者的研究，还有专注于预后评估的研究。“耐药性”“肿瘤”“遗传学”“生物标志物”“基因表达谱”和“药物治疗”等描述词将表明新的研究趋势。此外，我们提出BCL - 2、CHRF、SNAIL、miR - 363、iASPP、ALDH1、Fzd7和EZH2是潜在的耐药生物标志物。
本文有助于对卵巢癌耐药生物标志物相关科学研究进行全球分析，以促进进一步的研究和合作网络，这可能会导致未来对这种致命疾病治疗的改进。
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