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Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Differentially Expressed Genes Associated with the Development of Cervical Cancer
Diego Armando Alvarado-Camacho1, Ricardo Castillo-Velázquez2, Angelica Judith Granados-López1
1Laboratorio de microRNAs y Cáncer, Unidad Académica de Ciencias Biológicas, Universidad Autónoma de Zacatecas "Francisco García Salinas", Av. Preparatoria S/N, Zacatecas 98066, Mexico.
Abstract:
Cervical cancer remains a significant cause of cancer-related mortality among women, particularly in low- and middle-income countries. High-throughput technologies, such as microarrays, have facilitated the comprehensive analysis of gene expression profiles in cervical cancer, enabling the identification of key differentially expressed genes (DEGs) involved in its pathogenesis. The publicly available microarray datasets, including GSE39001, GSE9750, GSE7803, GSE6791, GSE63514, and GSE52903 in combination with bioinformatics database predictions, were used to identify differential expression genes, potential biomarkers, and therapeutic targets for cervical cancer; additionally, we undertook bioinformatic analysis to determine gene ontology and possible miRNA targets related to our DEGs. Our analysis revealed several DEGs significantly associated with cervical cancer progression, such as cell death, regulation of DNA replication, protein binding processes, and transcription factors. The most relevant transcription factors (TFs) identified were SP1, ELF3, E2F1, TP53, RELA, HDAC, and FOXM1. Importantly, the DEGs with more important changes were 11 coding genes that were upregulated (KIF4A, MCM5, RFC4, PLOD2, MMP12, PRC1, TOP2A, MCM2, RAD51AP1, KIF20A, AIM2) and 14 that were downregulated (CXCL14, KRT1, KRT13, MAL, SPINK5, EMP1, CRISP3, ALOX12, CRNN, SPRR3, PPP1R3C, IVL, CFD, CRCT1), which were associated with cervical cancer. Interestingly, hub proteins KIF4A, NUSAP1, BUB1B, CEP55, DLGAP5, NCAPG, CDK1, MELK, KIF11, and KIF20A were found to be potentially regulated by several miRNAs, including miR-107, miR-124-3p, miR-147a, miR-16-5p, miR-34a-5p, miR-34c-5p, miR-126-3p, miR-10b-5p, miR-23b-3p, miR-200b-3p, miR-138-5p, miR-203a-3p, miR-214-3p, and let-7b-5p. The relationship between these genes highlights their potential as candidate biomarkers for further research in treatment, diagnosis, and prognosis.
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