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Open AccessArticle

Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis

1
Grupo de Bio-Quimioinformática, Universidad de Las Américas, Quito 170125, Ecuador
2
Carrera de Enfermería, Facultad de Ciencias de la Salud, Universidad de Las Américas, Quito 170125, Ecuador
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RNASA-IMEDIR, Computer Sciences Faculty, University of A Coruna, 15071 A Coruña, Spain
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Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito 170129, Ecuador
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Laboratorio de Biología Molecular, Subproceso de Anatomía Patológica, Hospital de Especialidades Eugenio Espejo, Quito 170403, Ecuador
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Escuela de Ciencias Físicas y Matemáticas, Universidad de Las Américas, Quito 170125, Ecuador
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Biomedical Research Institute of A Coruña (INIBIC), University Hospital Complex of A Coruña (CHUAC), 15006 A Coruña, Spain
8
Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC), Campus de Elviña s/n, 15071 A Coruña, Spain
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Department of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940 Leioa, Spain
10
IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain
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Facultad de Ingeniería y Ciencias Agropecuarias, Universidad de Las Américas, Quito 170125, Ecuador
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(3), 1053; https://doi.org/10.3390/ijms21031053
Received: 10 December 2019 / Revised: 30 January 2020 / Accepted: 30 January 2020 / Published: 5 February 2020
(This article belongs to the Section Molecular Oncology)
Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein–protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as MMP2 and MMP9, and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored. View Full-Text
Keywords: gene prioritization; osteosarcoma; communality analysis; pathogenesis; early recognition gene prioritization; osteosarcoma; communality analysis; pathogenesis; early recognition
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MDPI and ACS Style

Cabrera-Andrade, A.; López-Cortés, A.; Jaramillo-Koupermann, G.; Paz-y-Miño, C.; Pérez-Castillo, Y.; Munteanu, C.R.; González-Díaz, H.; Pazos, A.; Tejera, E. Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis. Int. J. Mol. Sci. 2020, 21, 1053. https://doi.org/10.3390/ijms21031053

AMA Style

Cabrera-Andrade A, López-Cortés A, Jaramillo-Koupermann G, Paz-y-Miño C, Pérez-Castillo Y, Munteanu CR, González-Díaz H, Pazos A, Tejera E. Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis. International Journal of Molecular Sciences. 2020; 21(3):1053. https://doi.org/10.3390/ijms21031053

Chicago/Turabian Style

Cabrera-Andrade, Alejandro; López-Cortés, Andrés; Jaramillo-Koupermann, Gabriela; Paz-y-Miño, César; Pérez-Castillo, Yunierkis; Munteanu, Cristian R.; González-Díaz, Humbert; Pazos, Alejandro; Tejera, Eduardo. 2020. "Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis" Int. J. Mol. Sci. 21, no. 3: 1053. https://doi.org/10.3390/ijms21031053

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