Tathiane Maistro Malta

The paper develops a spatial-statistical framework to model cell-type interactions in glioblastoma using CosMx data, revealing patient-specific spatial patterns and their molecular correlates.

The paper shows cold acclimation increases n-3 HUFAs in the liver, reducing steatosis by altering lipid composition and metabolism.

This study integrates multi-omics and functional drug screening in patient-derived organoids to identify personalized therapeutic vulnerabilities in adult high-grade gliomas, finding distinct drug responses in IDH1 mutant and MYCN-amplified tumors.

The paper introduces two machine-learning models to assess stemness in gliomas using bulk gene expression data, revealing associations with prognosis and therapeutic resistance.

This study analyzes the epigenetic evolution of IDH1-mutant and IDH1-wildtype gliomas under treatment, showing IDHmut tumors undergo epigenomic changes resembling IDHwt tumors, with implications for treatment strategies.

The paper applies a one-class logistic regression model to predict stemness in single-cell and spatial omics datasets without requiring cell annotation.

TCGAbiolinksGUI provides a graphical interface for analyzing GDC cancer data, making the TCGAbiolinks package more accessible to non-R users.

The paper identifies an epigenetic shift from G-CIMP-high to G-CIMP-low in gliomas during recurrence, associated with genomic instability and stem cell-like features, and proposes biomarkers for predicting recurrence.