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Abstract
The identification of prognostic biomarkers is a priority for patients suffering from high-grade serous ovarian cancer (SOC), which accounts for >70% of ovarian cancer (OC) deaths. Meanwhile, borderline ovarian cancer (BOC) is a low malignancy tumor and usually patients undergo surgery with low probabilities of recurrence. However, SOC remains the most lethal neoplasm due to the lack of biomarkers for early diagnosis and prognosis. In this regard, BORIS (CTCFL), a CTCF paralog, is a promising cancer biomarker that is overexpressed and controls transcription in several cancer types, mainly in OC. Studies suggest that BORIS has an important function in OC by altering gene expression, but the effect and extent to which BORIS influences transcription in OC from a genome-wide perspective is unclear. Here, we sought to identify BORIS target genes in an OC cell line (OVCAR3) with potential biomarker use in OC tumor samples. To achieve this, we performed in vitro knockout and knockdown experiments of BORIS in OVCAR3 cell line followed by expression microarrays and bioinformatics network enrichment analysis to identify relevant BORIS target genes. In addition, ex vivo expression data analysis of 373 ovarian cancer patients were evaluated to identify the expression patterns of BORIS target genes. In vitro, we uncovered 130 differentially expressed genes and obtained the BORIS-associated regulatory network, in which the androgen receptor (AR) acts as a major transcription factor. Also, FN1, FAM129A, and CD97 genes, which are related to chemoresistance and metastases in OC, were identified. In SOC patients, we observed that malignancy is associated with high levels of BORIS expression while BOC patients show lower levels. Our study suggests that BORIS acts as a main regulator, and has the potential to be used as a prognostic biomarker and to yield novel drug targets among the genes BORIS controls in SOC patients.
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Details
; Thalía Estefanía Sánchez-Correa 5 ; Castro-Hernández, Clementina 2 ; Sánchez-Pérez, Yesennia 2 ; Aréchaga-Ocampo, Elena 3 ; García-Carrancá, Alejandro 2 ; Cantú de León, David 2 ; Herrera, Luis A 2 ; Baumbach, Jan 6 ; Soto-Reyes, Ernesto 3
1 Natural Sciences Department, Universidad Autónoma Metropolitana-Cuajimalpa (UAM-C), Mexico City, Mexico; Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany
2 Cancer Biomedical Research Unit, Instituto Nacional de Cancerología (INCan), Mexico City, Mexico
3 Natural Sciences Department, Universidad Autónoma Metropolitana-Cuajimalpa (UAM-C), Mexico City, Mexico
4 The Bioinformatics Centre Section for RNA and Computational Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
5 Instituto Nacional de Neurología y Neurocirugía “Manuel Velasco Suárez”, Mexico City, Mexico
6 Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany




