CompGen-lnc: Identificación del papel de los lncRNAs en procesos de compensación de dosis génica mediados por miRNAs

Given the increasing number of diagnosed cancer patients and the presence of cases with diverse
backgrounds and growing complexity, it becomes imperative to explore solutions not only in terms of treatment
but also in the field of early disease detection, which is on the rise worldwide. Particularly, aneuploidy,
characterized by chromosomal imbalances, is associated with various types of cancer. Thus, this study focuses
on understanding how long non-coding RNAs (lncRNAs) interact with microRNAs (miRNAs) to influence gene
regulation in aneuploid cells, particularly in the context of gene dosage compensation of the MYC gene, pivotal
for tumor growth. In this context, the "CompGen-lnc" project aims to determine the role of lncRNAs in gene
dosage compensation processes mediated by miRNAs. The research stands out for creating a database of
miRNA-lncRNA interactions with structural information and developing a bioinformatics tool for analysis and
predictions of these interactions. This analysis holds the promise of advancing the understanding of gene
regulation in aneuploid cancer, potentially triggering novel therapeutic strategies and personalized medicine
approaches. Furthermore, the project aligns with the strategic axes of the ITCR, known as Industry and Health,
and contributes to the Sustainable Development Goals (SDG3 and SDG9). With this initiative, the Institute will
garner positive recognition within the international scientific community for its contributions to gene regulation
research.

Identificar potenciales lncRNAs involucrados en los procesos de compensación de dosis génica en cáncer aneuploide.

1. Matemática Aplicada: con esta línea se pretende abordar problemas relevantes y de actualidad de la
sociedad costarricense a través de herramientas y técnicas matemáticas que permitan una mejor
comprensión y análisis de los fenómenos involucrados, con el fin de aportar soluciones óptimas e
innovadoras. Así se trabaja en aplicaciones relacionadas con modelación, simulación, inteligencia
artificial, análisis de datos, analítica visual de datos, análisis numérico, probabilidad y estadística.