Publications by authors named "A Patino-Garcia"
Pediatric diffuse midline gliomas (DMG) with altered H3-K27M are aggressive brain tumors that arise during childhood. Despite advances in genomic knowledge and the significant number of clinical trials testing new targeted therapies, patient outcomes are still poor. Immune checkpoint blockades with small molecules, such as aptamers, are opening new therapeutic options that represent hope for this orphan disease.
View Article and Find Full Text PDFPancreatic ductal adenocarcinoma represents one of the solid tumors showing the worst prognosis worldwide, with a high recurrence rate after adjuvant or neoadjuvant therapy. Circulating tumor DNA analysis raised as a promising non-invasive tool to characterize tumor genomics and to assess treatment response. In this study, surgical tumor tissue and sequential blood samples were analyzed by next-generation sequencing and were correlated with clinical and pathological characteristics.
View Article and Find Full Text PDFArticle Synopsis
- Pediatric high-grade gliomas (pHGGs), particularly diffuse midline gliomas (DMGs), are highly aggressive tumors with low survival rates, yet the combination of Delta-24-RGD and ONC201 has shown potential for enhanced treatment efficacy.
- In laboratory and mouse model studies, the combination treatment did not alter virus replication but demonstrated a synergistic or additive cytotoxic effect, leading to increased DNA damage and metabolic disruptions in tumor cells.
- Additionally, the combination treatment improved survival rates in mice models and led to a shift in the tumor microenvironment towards a more proinflammatory state, indicating a stronger immune response against the tumors.
Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma.
EBioMedicine
April 2024
Article Synopsis
- Tobacco significantly increases the risk of lung cancer, but some heavy smokers either develop it early or remain illness-free for many years, indicating a variability in susceptibility to cancer.
- Researchers analyzed the genetic profiles of heavy smokers who either developed lung adenocarcinoma at a young age or did not develop it at an old age using Whole Exome Sequencing and Machine Learning to identify genetic variants linked to these extreme phenotypes.
- The study validated multiple genetic variants and found that the gene HLA-A had the most variants associated with lower lung cancer risk, achieving a notable prediction accuracy with machine learning models, suggesting potential pathways for further research into lung cancer prevention.