SINDY CABARCA ^1,2,3 Carmen G. Ili ² Carlos Vanegas ³ Laura Gil ³ Melba Vertel-Morrinson ^3,4* Priscilla Brebi ^2*

• ¹ University of La Frontera, Temuco, Chile
• ² Laboratorio de Biología Integrativa, Centro de Excelencia en Medicina Traslacional, Universidad de La Frontera, Temuco, Chile
• ³ University of Sucre, Sincelejo, Sucre, Colombia
• ⁴ University of Cordoba, Córdoba, Spain

Background: 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. Methods: 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. Results: 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. Conclusions: 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.