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

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

doi:10.3390/ijms21031053

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

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

Alejandro Cabrera-Andrade

^1,2,3,*

Andrés López-Cortés

^3,4

Gabriela Jaramillo-Koupermann

⁵

César Paz-y-Miño

⁴

Yunierkis Pérez-Castillo

^1,6

Cristian R. Munteanu

^3,7,8

Humbert González-Díaz

^9,10

Alejandro Pazos

^3,7,8

and

Eduardo Tejera

^1,11,*

Grupo de Bio-Quimioinformática, Universidad de Las Américas, Quito 170125, Ecuador

Carrera de Enfermería, Facultad de Ciencias de la Salud, Universidad de Las Américas, Quito 170125, Ecuador

RNASA-IMEDIR, Computer Sciences Faculty, University of A Coruna, 15071 A Coruña, Spain

⁴

Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito 170129, Ecuador

⁵

Laboratorio de Biología Molecular, Subproceso de Anatomía Patológica, Hospital de Especialidades Eugenio Espejo, Quito 170403, Ecuador

⁶

Escuela de Ciencias Físicas y Matemáticas, Universidad de Las Américas, Quito 170125, Ecuador

⁷

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

⁹

Department of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940 Leioa, Spain

¹⁰

IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain

¹¹

Facultad de Ingeniería y Ciencias Agropecuarias, Universidad de Las Américas, Quito 170125, Ecuador

Show full affiliation list

Hide full affiliation list

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)

View Full-Text Download PDF

Browse Figures

Review Reports Citation Export

Abstract

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

▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary File 1:
ZIP-Document (ZIP, 150 KiB)

Share and Cite

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

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

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

Abstract

Supplementary Material

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI