Browsing by Author "Pinto, Felipe"

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    Comprehensive in‑silico molecular analysis of early‑onset gastric cancer identifies novel genes implicated in disease characterization and progression (Review)
    (2025) Gómez‑Valenzuela, Fernán; Silva, Ian; Retamal, Ignacio N.; García‑Bloj, Benjamín; De Mayo Glasser, Tomás; Muñoz‑Medel, Matías; Gómez, Alex; San Martín, Cristopher; Sánchez, Carolina; Pinto, Felipe; Aravena, Paola; Sabioncello, Andrea C.; Garrido Villanueva, Marcelo; Sigler Chávez, Fernado; Corvalán, Ignacio; Barrios, Henry; Erpel, José M.; Manque, Patricio A.; Godoy, Juan A.; Garrido, Marcelo
    Gastric cancer, a prevalent and fatal form of cancer worldwide, is manifested at different age ranges during the lifespan. Approximately one‑third of newly diagnosed gastric cancer cases are early‑onset gastric cancer (EO‑GC), which affects individuals under the age of 50 years. EO‑GC tends to be more aggressive than late‑onset gastric cancer (L‑GC), with a faster and multifocal disease progression. Furthermore, EO‑GC is associated with early metastatic disease. Recent research has underscored the need for a deeper understanding of EO‑GC that promotes therapeutic approaches specific to EO‑GC. The present study determined the main transcrip‑tomic differences between EO‑GC and L‑GC. Transcriptomic expression data from The Cancer Genome Atlas‑Stomach Adenocarcinoma were explored to elucidate whether age is associated with a specific genomic expression pattern and is associated with gastric cancer. Subsequently, a differential gene expression analysis of the EO‑GC vs. L‑GC groups was performed, providing new insights into EO‑GC gene expression characteristics and their association with survival outcomes. Furthermore, the study focused on whether the influence of representative gene expression in EO‑GC cases (KLHL4, MAGEL2, CYP8B1, RNLS, CLDN6, MIOX, PNMA5 and ACTL8 genes) may be associated with its aggressive phenotype and methylation profiles of these patients. In this review, the necessity of incorporating age as a crucial element in understanding the disparities in outcomes for EO‑GC cases in public datasets was discussed. Furthermore, this insight may be useful for targeted early personalized clinical interventions to improve patient prognosis and survival rates in EO‑GC cases.

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