Ehsan Irajizad

This study identifies KRAS-driven metabolic reprogramming through MFSD2A-mediated lysophosphatidylcholine scavenging as a driver of PDAC progression and shows that targeting this pathway with edelfosine has anti-cancer effects.

The paper identifies a metabolic vulnerability in triple-negative breast cancer through sphingolipid metabolism, showing that targeting this pathway with eliglustat reduces tumor growth and improves survival.

This study introduces AUC-PR as a better metric for evaluating in silico perturbation models' ability to predict differentially expressed genes, showing it outperforms R2 in capturing biologically relevant outcomes.

This study identifies aberrant CD14 expression in breast tumor cells as a marker of poor clinical outcomes and aggressive disease.

The paper introduces SMAGS, a regression framework that maximizes sensitivity at a given specificity for binary classification, showing 14% improvement in sensitivity on a colorectal cancer dataset.