Abstract

Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.

Details

Title
Identification of modules and key genes associated with breast cancer subtypes through network analysis
Author
Mares-Quiñones, María Daniela 1 ; Galán-Vásquez, Edgardo 2 ; Pérez-Rueda, Ernesto 3 ; Pérez-Ishiwara, D. Guillermo 1 ; Medel-Flores, María Olivia 1 ; Gómez-García, María del Consuelo 1 

 Escuela Nacional de Medicina y Homeopatía, Instituto Politécnico Nacional, Laboratorio de Biomedicina Molecular, Programa de Doctorado en Biotecnología, Ciudad de México, Mexico (GRID:grid.418275.d) (ISNI:0000 0001 2165 8782) 
 Universidad Nacional Autónoma de México, Departamento de Ingeniería de Sistemas Computacionales y Automatización, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Ciudad de México, Mexico (GRID:grid.9486.3) (ISNI:0000 0001 2159 0001) 
 Unidad Académica del Estado de Yucatán, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mérida, Mexico (GRID:grid.9486.3) (ISNI:0000 0001 2159 0001) 
Pages
12350
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3061557437
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.