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Oncogene ; 43(18): 1369-1385, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38467851

RESUMEN

Breast cancer is the most prevalent type of cancer in women worldwide. Within breast tumors, the basal-like subtype has the worst prognosis, prompting the need for new tools to understand, detect, and treat these tumors. Certain germline-restricted genes show aberrant expression in tumors and are known as Cancer/Testis genes; their misexpression has diagnostic and therapeutic applications. Here we designed a new bioinformatic approach to examine Cancer/Testis gene misexpression in breast tumors. We identify several new markers in Luminal and HER-2 positive tumors, some of which predict response to chemotherapy. We then use machine learning to identify the two Cancer/Testis genes most associated with basal-like breast tumors: HORMAD1 and CT83. We show that these genes are expressed by tumor cells and not by the microenvironment, and that they are not expressed by normal breast progenitors; in other words, their activation occurs de novo. We find these genes are epigenetically repressed by DNA methylation, and that their activation upon DNA demethylation is irreversible, providing a memory of past epigenetic disturbances. Simultaneous expression of both genes in breast cells in vitro has a synergistic effect that increases stemness and activates a transcriptional profile also observed in double-positive tumors. Therefore, we reveal a functional cooperation between Cancer/Testis genes in basal breast tumors; these findings have consequences for the understanding, diagnosis, and therapy of the breast tumors with the worst outcomes.


Asunto(s)
Neoplasias de la Mama , Biología Computacional , Regulación Neoplásica de la Expresión Génica , Humanos , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Femenino , Biología Computacional/métodos , Metilación de ADN , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Línea Celular Tumoral , Masculino , Epigénesis Genética
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