H. Noushmehr

This study analyzes longitudinal glioma data to identify recurrence-associated changes in genetics and microenvironment linked to therapy resistance.

This paper identifies and validates DNA methylation signatures that classify sporadic pituitary tumors based on clinicopathological features and adenohypophyseal cell lineages.

This study shows that glioma PDOX models accurately represent patient tumors and can predict treatment responses in personalized medicine.

This paper introduces CaCTS, an algorithm that identifies candidate master transcription factors (MTFs) across 34 cancer types using RNA-seq data, revealing novel MTFs and functional groupings.

This paper reviews the biological and clinical implications of G-CIMP subsets in gliomas, highlighting their role in prognosis and potential for personalized therapy.